Directory structure:
└── gitarsenal-cli/
├── README.md
├── activate_venv.sh
├── ascii_banner.txt
├── config.json
├── gitingest-integration.js
├── index.js
├── package.json
├── repos.json
├── Step
├── test_credentials_integration.py
├── .npmignore
├── .venv_status.json
├── kill_claude/
│ ├── README.md
│ ├── claude_code_agent.py
│ ├── requirements.txt
│ ├── prompts/
│ │ ├── claude-code-agent-prompts.md
│ │ ├── claude-code-environment-context.md
│ │ ├── claude-code-git-workflows.md
│ │ ├── claude-code-hook-system.md
│ │ ├── claude-code-response-formatting.md
│ │ ├── claude-code-security-constraints.md
│ │ ├── claude-code-system-prompt.md
│ │ ├── claude-code-system-reminders.md
│ │ ├── claude-code-task-workflows.md
│ │ ├── claude-code-thinking-mode-prompts.md
│ │ ├── claude-code-tool-prompts.md
│ │ └── claude-code-tool-usage-policies.md
│ ├── tools/
│ │ ├── __init__.py
│ │ ├── bash_output_tool.py
│ │ ├── bash_tool.py
│ │ ├── edit_tool.py
│ │ ├── exit_plan_mode_tool.py
│ │ ├── glob_tool.py
│ │ ├── grep_tool.py
│ │ ├── kill_bash_tool.py
│ │ ├── ls_tool.py
│ │ ├── multiedit_tool.py
│ │ ├── notebook_edit_tool.py
│ │ ├── read_tool.py
│ │ ├── task_tool.py
│ │ ├── todo_write_tool.py
│ │ ├── web_fetch_tool.py
│ │ ├── web_search_tool.py
│ │ └── write_tool.py
│ └── .claude/
│ └── settings.local.json
├── lib/
│ ├── dependencies.js
│ └── sandbox.js
├── python/
│ ├── auth_manager.py
│ ├── command_manager.py
│ ├── credentials_manager.py
│ ├── debug_modal_minimal.py
│ ├── fetch_modal_tokens.py
│ ├── fix_modal_token.py
│ ├── fix_modal_token_advanced.py
│ ├── gitarsenal_keys.py
│ ├── gitarsenal_proxy_client.py
│ ├── llm_debugging.py
│ ├── requirements.txt
│ ├── setup.py
│ ├── setup_modal_token.py
│ ├── shell.py
│ ├── test_container_fail.py
│ ├── test_container_pass.py
│ ├── test_modal.py
│ ├── test_modalSandboxScript.py
│ └── .env.example
└── scripts/
└── postinstall.js
================================================
FILE: README.md
================================================
# GitArsenal CLI
**Run any GitHub repository instantly with pre-configured GPU environments.**
GitArsenal CLI makes it incredibly easy to run any GitHub repository without worrying about setup, dependencies, or environment configuration. Just point it at a repository and start coding with GPU acceleration.
## Why GitArsenal CLI?
- **Zero Setup**: No need to install dependencies, configure environments, or manage GPU drivers
- **GPU Ready**: Every environment comes with GPU acceleration (A10G, A100, H100)
- **Persistent Storage**: Your work and data persist between sessions
- **SSH Access**: Connect directly to your running environment
- **API Key Management**: Securely store and auto-inject API keys for services like OpenAI, Weights & Biases, and Hugging Face
## Quick Start
### Run any GitHub repository
```bash
# Basic usage - clone and run any repo
gitarsenal --repo-url https://github.com/username/awesome-project.git
# With GPU acceleration
gitarsenal --gpu A10G --repo-url https://github.com/username/awesome-project.git
# With custom setup commands
gitarsenal --gpu A100 --repo-url https://github.com/username/awesome-project.git --setup-commands "pip install -r requirements.txt" "python setup.py install"
```
### Examples
```bash
# Run a machine learning project
gitarsenal --gpu A100 --repo-url https://github.com/username/transformer-project.git --setup-commands "pip install torch transformers" "wandb login"
# Run a web development project
gitarsenal --repo-url https://github.com/username/react-app.git --setup-commands "npm install" "npm start"
# Run a data science project with persistent storage
gitarsenal --gpu A10G --repo-url https://github.com/username/data-analysis.git --volume-name my-data --setup-commands "pip install pandas numpy matplotlib"
```
## API Key Management
Store your API keys once and use them across all projects:
```bash
# Add API keys for seamless integration
gitarsenal keys add --service openai
gitarsenal keys add --service wandb
gitarsenal keys add --service huggingface
# View your saved keys
gitarsenal keys list
# Remove a key
gitarsenal keys delete --service openai
```
### Supported Services
- **OpenAI** - For debugging and AI assistance
- **Weights & Biases** - For experiment tracking
- **Hugging Face** - For model access and downloads
## Features
### Automatic Environment Setup
The CLI automatically:
- Clones your repository
- Installs dependencies based on your setup commands
- Configures GPU acceleration
- Sets up persistent storage
- Injects your saved API keys
### Persistent Storage
Keep your work safe with persistent volumes:
```bash
# Create a persistent environment
gitarsenal --repo-url https://github.com/username/project.git --volume-name my-work
# Your data, models, and work will persist between sessions
```
### SSH Access
Connect directly to your running environment:
```bash
# Get SSH connection details
gitarsenal --repo-url https://github.com/username/project.git --ssh
# Connect via SSH to your environment
ssh user@your-environment-ip
```
## Workflow
1. **Choose a repository** - Any GitHub repo you want to work with
2. **Run the command** - Specify GPU, setup commands, and storage
3. **Start coding** - Your environment is ready with all dependencies installed
4. **Save your work** - Use persistent volumes to keep your progress
## Perfect For
- **Machine Learning Projects** - GPU-accelerated training with pre-configured environments
- **Data Science** - Jupyter notebooks with all dependencies ready
- **Web Development** - Full-stack projects with development servers
- **Research** - Reproducible environments for academic work
- **Hackathons** - Quick setup for rapid prototyping
## Getting Started
1. Install the CLI (see installation instructions)
2. Add your API keys: `gitarsenal keys add --service openai`
3. Run any repository: `gitarsenal --repo-url https://github.com/username/project.git`
4. Start coding!
No more "works on my machine" - every environment is identical and ready to go.
================================================
FILE: activate_venv.sh
================================================
#!/bin/bash
cd "$(dirname "$0")"
source ".venv/bin/activate"
exec "$@"
================================================
FILE: ascii_banner.txt
================================================
╭────────────────────────────────────────────────────────────────────────────────╮
│ │
│ ██████╗ ██╗████████╗ █████╗ ██████╗ ███████╗███████╗███╗ ██╗ █████╗ ██╗ │
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│ ██║ ███╗██║ ██║ ███████║██████╔╝███████╗█████╗ ██╔██╗ ██║███████║██║ │
│ ██║ ██║██║ ██║ ██╔══██║██╔══██╗╚════██║██╔══╝ ██║╚██╗██║██╔══██║██║ │
│ ╚██████╔╝██║ ██║ ██║ ██║██║ ██║███████║███████╗██║ ╚████║██║ ██║███████╗│
│ ╚═════╝ ╚═╝ ╚═╝ ╚═╝ ╚═╝╚═╝ ╚═╝╚══════╝╚══════╝╚═╝ ╚═══╝╚═╝ ╚═╝╚══════╝│
│ │
│ GPU-Accelerated Development Environments │
│ │
╰────────────────────────────────────────────────────────────────────────────────╯
================================================
FILE: config.json
================================================
{
"userId": "rs545837",
"userName": "ROhan Sharma",
"webhookUrl": "https://www.gitarsenal.dev/api/users"
}
================================================
FILE: gitingest-integration.js
================================================
#!/usr/bin/env node
const { spawn } = require('child_process');
const chalk = require('chalk');
// Function to check if GitIngest CLI is available and working
async function checkGitIngestCLI() {
try {
// Try a simple help command first
const checkProcess = spawn('gitingest', ['--version'], {
stdio: 'pipe',
timeout: 5000 // 5 second timeout
});
let stderr = '';
checkProcess.stderr.on('data', (data) => {
stderr += data.toString();
});
return new Promise((resolve) => {
checkProcess.on('close', (code) => {
// If there are Python errors in stderr, consider it failed even if exit code is 0
if (stderr.includes('TypeError') || stderr.includes('Traceback') || stderr.includes('Error')) {
// console.log(chalk.yellow('⚠️ GitIngest CLI has Python compatibility issues'));
resolve(false);
} else if (code === 0) {
resolve(true);
} else {
resolve(false);
}
});
checkProcess.on('error', () => {
resolve(false);
});
// Handle timeout
setTimeout(() => {
if (!checkProcess.killed) {
checkProcess.kill();
resolve(false);
}
}, 5000);
});
} catch (error) {
return false;
}
}
// Function to fetch GitIngest data using local GitIngest CLI
async function fetchGitIngestData(repoUrl) {
try {
// First check if GitIngest CLI is available
const gitingestAvailable = await checkGitIngestCLI();
if (!gitingestAvailable) {
// console.log(chalk.yellow('⚠️ GitIngest CLI not available or has compatibility issues.'));
// console.log(chalk.blue('💡 For best results, install with: pipx install gitingest'));
// console.log(chalk.blue(' Alternative: pip install gitingest (requires Python 3.10+)'));
// console.log(chalk.blue('📖 More info: https://github.com/coderamp-labs/gitingest'));
// console.log(chalk.gray(' Falling back to basic repository analysis...'));
return null;
}
console.log(chalk.gray('📥 Running GitIngest locally...'));
// Run GitIngest CLI command with optimal settings for AI analysis
const gitingestProcess = spawn('gitingest', [
repoUrl,
'-o', '-', // Output to stdout
], {
stdio: ['pipe', 'pipe', 'pipe']
});
let gitingestOutput = '';
let errorOutput = '';
gitingestProcess.stdout.on('data', (data) => {
gitingestOutput += data.toString();
});
gitingestProcess.stderr.on('data', (data) => {
errorOutput += data.toString();
});
return new Promise((resolve) => {
gitingestProcess.on('close', (code) => {
if (code === 0 && gitingestOutput.trim().length > 0) {
console.log(chalk.green('✅ GitIngest analysis complete'));
console.log(chalk.gray(`📊 Captured ${gitingestOutput.length} characters of repository content`));
resolve(parseGitIngestOutput(gitingestOutput, repoUrl));
} else {
console.log(chalk.yellow(`⚠️ GitIngest failed (exit code: ${code})`));
if (errorOutput) {
console.log(chalk.gray(`Error details: ${errorOutput.slice(0, 300)}`));
}
resolve(null);
}
});
gitingestProcess.on('error', (error) => {
console.log(chalk.yellow(`⚠️ GitIngest CLI error: ${error.message}`));
resolve(null);
});
});
} catch (error) {
console.log(chalk.yellow(`⚠️ GitIngest execution failed: ${error.message}`));
return null;
}
}
// Function to parse GitIngest text output into structured data
function parseGitIngestOutput(gitingestText, repoUrl) {
try {
// Extract repository info from URL
const urlMatch = repoUrl.match(/github\.com\/([^\/]+)\/([^\/]+)/);
const owner = urlMatch ? urlMatch[1] : 'unknown';
const repo = urlMatch ? urlMatch[2].replace('.git', '') : 'unknown';
// GitIngest output format:
// Repository: owner/repo-name
// Files analyzed: 42
// Estimated tokens: 15.2k
//
// Directory structure:
// └── project-name/
// ├── src/
// │ ├── main.py
// └── README.md
//
// ================================================
// FILE: src/main.py
// ================================================
// [file content]
const lines = gitingestText.split('\n');
let summary = '';
let tree = '';
let content_preview = '';
let detectedLanguage = 'Unknown';
let detectedTechnologies = [];
let primaryPackageManager = 'Unknown';
// Find sections
let summaryEnd = -1;
let treeStart = -1;
let treeEnd = -1;
let contentStart = -1;
for (let i = 0; i < lines.length; i++) {
const line = lines[i];
if (line.startsWith('Repository:') && summaryEnd === -1) {
// Find end of summary (first empty line after Repository line)
for (let j = i; j < lines.length; j++) {
if (lines[j].trim() === '' && j > i) {
summaryEnd = j;
break;
}
}
}
if (line.startsWith('Directory structure:')) {
treeStart = i;
}
if (line.includes('===') && line.includes('FILE:')) {
if (treeStart > -1 && treeEnd === -1) {
treeEnd = i;
}
if (contentStart === -1) {
contentStart = i;
}
}
}
// Extract sections
if (summaryEnd > 0) {
summary = lines.slice(0, summaryEnd).join('\n');
} else {
// Fallback: take first 10 lines as summary
summary = lines.slice(0, 10).join('\n');
}
if (treeStart > -1) {
const endIdx = treeEnd > -1 ? treeEnd : (contentStart > -1 ? contentStart : Math.min(treeStart + 50, lines.length));
tree = lines.slice(treeStart, endIdx).join('\n');
}
if (contentStart > -1) {
// Take first 300 lines of content to provide good context without overwhelming
content_preview = lines.slice(contentStart, Math.min(contentStart + 300, lines.length)).join('\n');
}
// Detect technologies from content
const contentLower = gitingestText.toLowerCase();
// Language detection
if (contentLower.includes('import torch') || contentLower.includes('pytorch') || contentLower.includes('def ') || contentLower.includes('import ')) {
detectedLanguage = 'Python';
primaryPackageManager = 'pip';
} else if (contentLower.includes('package.json') || contentLower.includes('require(') || contentLower.includes('import ') || contentLower.includes('function ')) {
detectedLanguage = 'JavaScript';
primaryPackageManager = 'npm';
} else if (contentLower.includes('cargo.toml') || contentLower.includes('fn ') || contentLower.includes('use ')) {
detectedLanguage = 'Rust';
primaryPackageManager = 'cargo';
} else if (contentLower.includes('go.mod') || contentLower.includes('func ') || contentLower.includes('package ')) {
detectedLanguage = 'Go';
primaryPackageManager = 'go mod';
}
// AI/ML Technology detection
if (contentLower.includes('torch') || contentLower.includes('pytorch')) {
detectedTechnologies.push('PyTorch');
}
if (contentLower.includes('tensorflow') || contentLower.includes('tf.')) {
detectedTechnologies.push('TensorFlow');
}
if (contentLower.includes('transformers') || contentLower.includes('huggingface')) {
detectedTechnologies.push('Hugging Face');
}
if (contentLower.includes('numpy') || contentLower.includes('np.')) {
detectedTechnologies.push('NumPy');
}
if (contentLower.includes('openai') && (contentLower.includes('import openai') || contentLower.includes('openai.')) && !contentLower.includes('# example') && !contentLower.includes('# TODO')) {
detectedTechnologies.push('OpenAI API');
}
if (contentLower.includes('anthropic') && contentLower.includes('import anthropic')) {
detectedTechnologies.push('Anthropic API');
}
// Count files from summary
const filesMatch = summary.match(/Files analyzed: (\d+)/);
const fileCount = filesMatch ? parseInt(filesMatch[1]) : 0;
const structuredData = {
system_info: {
platform: process.platform,
python_version: process.version,
detected_language: detectedLanguage,
detected_technologies: detectedTechnologies,
file_count: fileCount,
repo_stars: 0, // Would need GitHub API
repo_forks: 0, // Would need GitHub API
primary_package_manager: primaryPackageManager,
complexity_level: fileCount > 50 ? 'high' : fileCount > 20 ? 'medium' : 'low'
},
repository_analysis: {
summary: summary || `Repository: ${owner}/${repo}\nAnalyzed with GitIngest`,
tree: tree || 'Directory structure not available',
content_preview: content_preview || 'Content preview not available'
},
success: true
};
console.log(chalk.gray('🔍 Analysis Summary:'));
console.log(chalk.gray(` - Language: ${detectedLanguage}`));
console.log(chalk.gray(` - Technologies: ${detectedTechnologies.join(', ') || 'None detected'}`));
console.log(chalk.gray(` - Files: ${fileCount}`));
console.log(chalk.gray(` - Package Manager: ${primaryPackageManager}`));
return structuredData;
} catch (error) {
console.log(chalk.yellow(`⚠️ Failed to parse GitIngest output: ${error.message}`));
return null;
}
}
module.exports = {
fetchGitIngestData,
checkGitIngestCLI
};
================================================
FILE: index.js
================================================
#!/usr/bin/env node
// This file is the main entry point for the package
// It simply re-exports the main functionality
const { runModalSandbox } = require('./lib/sandbox');
const { checkDependencies } = require('./lib/dependencies');
module.exports = {
runModalSandbox,
checkDependencies
};
================================================
FILE: package.json
================================================
{
"name": "gitarsenal-cli",
"version": "1.9.78",
"description": "CLI tool for creating Modal sandboxes with GitHub repositories",
"main": "index.js",
"bin": {
"gitarsenal": "./bin/gitarsenal.js"
},
"scripts": {
"postinstall": "node scripts/postinstall.js"
},
"keywords": [
"modal",
"sandbox",
"cli",
"gpu",
"github",
"repository",
"setup"
],
"author": "",
"license": "MIT",
"dependencies": {
"@supabase/supabase-js": "^2.53.0",
"boxen": "^5.1.2",
"chalk": "^4.1.2",
"commander": "^9.4.1",
"execa": "^5.1.1",
"fs-extra": "^11.1.0",
"g": "^2.0.1",
"inquirer": "^8.2.4",
"ora": "^5.4.1",
"update-notifier": "^5.1.0",
"which": "^3.0.0"
},
"engines": {
"node": ">=14.0.0"
}
}
================================================
FILE: repos.json
================================================
{
"repositories": [
{
"name": "FlashAvatar",
"url": "https://github.com/FlashAvatar/FlashAvatar",
"gpu": "A10G",
"volume": "flashavatar-volume",
"description": "Avatar generation repository"
},
{
"name": "DECA",
"url": "https://github.com/YadiraF/DECA",
"gpu": "A100-40",
"volume": "deca-volume",
"description": "Detailed Expression Capture and Animation"
},
{
"name": "DisenBooth",
"url": "https://github.com/Fictionarry/DisenBooth",
"gpu": "A10G",
"volume": "disenbooth-volume",
"description": "Disentangled subject-driven generation"
},
{
"name": "FederatedGPT-Shepherd",
"url": "https://github.com/FederatedGPT/FederatedGPT-Shepherd",
"gpu": "A100-40",
"volume": "federatedgpt-volume",
"description": "Federated GPT training framework"
},
{
"name": "FLAME_PyTorch",
"url": "https://github.com/HavenFeng/FLAME_PyTorch",
"gpu": "A10G",
"volume": "flame-pytorch-volume",
"description": "FLAME face model in PyTorch"
},
{
"name": "flame-head-tracker",
"url": "https://github.com/CMU-Perceptual-Computing-Lab/flame-head-tracker",
"gpu": "A10G",
"volume": "flame-tracker-volume",
"description": "Head tracking using FLAME model"
},
{
"name": "litex",
"url": "https://github.com/enjoy-digital/litex",
"gpu": "T4",
"volume": "litex-volume",
"description": "FPGA framework and SoC builder"
},
{
"name": "MICA",
"url": "https://github.com/Zielon/MICA",
"gpu": "A100-40",
"volume": "mica-volume",
"description": "3D face reconstruction"
},
{
"name": "photometric_optimization",
"url": "https://github.com/facebookresearch/photometric_optimization",
"gpu": "A10G",
"volume": "photometric-volume",
"description": "Photometric optimization for 3D reconstruction"
},
{
"name": "reflex",
"url": "https://github.com/reflex-dev/reflex",
"gpu": "A10G",
"volume": "reflex-volume",
"description": "Web framework for Python"
}
],
"metadata": {
"description": "Repository list for GitArsenal evaluation",
"created": "2025-08-04",
"version": "1.0",
"total_repos": 10
}
}
================================================
FILE: Step
================================================
[Empty file]
================================================
FILE: test_credentials_integration.py
================================================
#!/usr/bin/env python3
"""
Test script to verify that stored credentials are being passed correctly to SSH containers.
"""
import os
import json
from pathlib import Path
def test_credentials_loading():
"""Test that credentials can be loaded from the local file"""
print("🔍 Testing credentials loading...")
# Test get_stored_credentials function
try:
from test_modalSandboxScript import get_stored_credentials
credentials = get_stored_credentials()
if credentials:
print(f"✅ Found {len(credentials)} stored credentials:")
for key, value in credentials.items():
masked_value = value[:8] + "..." if len(value) > 8 else "***"
print(f" - {key}: {masked_value}")
else:
print("⚠️ No stored credentials found")
return credentials
except Exception as e:
print(f"❌ Error loading credentials: {e}")
return {}
def test_credentials_file():
"""Test that the credentials file exists and is readable"""
print("\n🔍 Testing credentials file...")
credentials_file = Path.home() / ".gitarsenal" / "credentials.json"
if credentials_file.exists():
print(f"✅ Credentials file exists at: {credentials_file}")
try:
with open(credentials_file, 'r') as f:
credentials = json.load(f)
print(f"✅ Successfully loaded {len(credentials)} credentials from file")
return credentials
except Exception as e:
print(f"❌ Error reading credentials file: {e}")
return {}
else:
print(f"⚠️ Credentials file not found at: {credentials_file}")
print("💡 You can create it by running the credentials manager")
return {}
def test_environment_variables():
"""Test that credentials are available as environment variables"""
print("\n🔍 Testing environment variables...")
credential_env_vars = [
'OPENAI_API_KEY', 'WANDB_API_KEY', 'HF_TOKEN', 'HUGGINGFACE_TOKEN',
'GITHUB_TOKEN', 'KAGGLE_USERNAME', 'KAGGLE_KEY'
]
found_creds = {}
for env_var in credential_env_vars:
value = os.environ.get(env_var)
if value:
found_creds[env_var] = value
masked_value = value[:8] + "..." if len(value) > 8 else "***"
print(f"✅ {env_var}: {masked_value}")
if not found_creds:
print("⚠️ No credential environment variables found")
return found_creds
def test_credentials_integration():
"""Test the full credentials integration"""
print("\n" + "="*60)
print("🔐 CREDENTIALS INTEGRATION TEST")
print("="*60)
# Test all credential sources
file_creds = test_credentials_file()
env_creds = test_environment_variables()
function_creds = test_credentials_loading()
# Combine all credentials
all_creds = {}
all_creds.update(file_creds)
all_creds.update(env_creds)
all_creds.update(function_creds)
print(f"\n📊 SUMMARY:")
print(f" - File credentials: {len(file_creds)}")
print(f" - Environment credentials: {len(env_creds)}")
print(f" - Function credentials: {len(function_creds)}")
print(f" - Total unique credentials: {len(all_creds)}")
if all_creds:
print(f"\n✅ Credentials are available for SSH container integration")
print("💡 These credentials will be automatically passed to SSH containers")
else:
print(f"\n⚠️ No credentials found")
print("💡 Consider setting up credentials using the credentials manager")
return all_creds
if __name__ == "__main__":
test_credentials_integration()
================================================
FILE: .npmignore
================================================
# Development files
.git
.github
.gitignore
.editorconfig
.eslintrc
.prettierrc
.vscode
*.log
*.tgz
# Test files
test/
tests/
__tests__/
coverage/
.nyc_output/
# Documentation
docs/
doc/
examples/
example/
# Source files
src/
.babelrc
tsconfig.json
tslint.json
webpack.config.js
rollup.config.js
# Misc
.DS_Store
.env
.env.*
node_modules/
tmp/
temp/
================================================
FILE: .venv_status.json
================================================
{"created":"2025-08-17T17:20:43.416Z","packages":["modal","gitingest","requests","anthropic"],"uv_version":"uv 0.8.4 (Homebrew 2025-07-30)"}
================================================
FILE: kill_claude/README.md
================================================
# Claude Code Agent
A comprehensive Python implementation that replicates Claude Code's functionality by orchestrating all available tools to handle user queries intelligently.
## 🎯 Overview
This project contains:
- **All 16 Claude Code tool definitions** as individual Python modules
- **Main orchestrator** (`claude_code_agent.py`) that handles user queries
- **Query parsing and intent recognition** system
- **Task management** with automatic todo list creation
- **Interactive CLI mode** similar to Claude Code's interface
## 📁 Project Structure
```
kill_claude/
├── claude_code_agent.py # Main orchestrator file
├── example_usage.py # Usage examples and demos
├── README.md # This file
├──
├── Tool Definitions:
├── task_tool.py # Task/Agent management
├── bash_tool.py # Command execution
├── glob_tool.py # File pattern matching
├── grep_tool.py # Content search
├── ls_tool.py # Directory listing
├── read_tool.py # File reading
├── edit_tool.py # File editing
├── multiedit_tool.py # Multiple file edits
├── write_tool.py # File writing
├── notebook_edit_tool.py # Jupyter notebook editing
├── web_fetch_tool.py # Web content fetching
├── web_search_tool.py # Web searching
├── todo_write_tool.py # Task management
├── bash_output_tool.py # Background shell output
├── kill_bash_tool.py # Shell termination
├── exit_plan_mode_tool.py # Plan mode management
└──
└── Documentation (from Claude Code):
├── claude-code-*.md # Claude Code internal docs
└── ...
```
## 🚀 Features
### Core Capabilities
- **File Operations**: Read, write, edit, list files and directories
- **Search**: Content search in files, web search, pattern matching
- **Code Execution**: Run bash commands, package managers, git operations
- **Web Access**: Fetch web content, search the internet
- **Task Management**: Automatic todo list creation for complex tasks
- **Planning**: Support for multi-step task planning and execution
### Intelligent Query Processing
- **Intent Recognition**: Automatically detects what the user wants to do
- **Tool Selection**: Chooses appropriate tools based on query analysis
- **Parameter Extraction**: Extracts relevant parameters from natural language
- **Context Awareness**: Maintains conversation context and task state
### Interactive Features
- **CLI Mode**: Interactive command-line interface
- **Help System**: Built-in help and tool documentation
- **Error Handling**: Graceful error handling and user feedback
- **Task Tracking**: Visual task management with status updates
## 🛠️ Installation
1. **Clone or download** all the files to a directory
2. **Install dependencies** (if needed):
```bash
pip install dataclasses # Python 3.6 only, built-in for 3.7+
```
3. **Make the main script executable**:
```bash
chmod +x claude_code_agent.py
```
## 💻 Usage
### Interactive Mode
Launch the interactive CLI:
```bash
python claude_code_agent.py
```
Example interaction:
```
🤖 Claude Code Agent - Interactive Mode
Type 'help' for available commands, 'exit' to quit
--------------------------------------------------
👤 You: read main.py
🤖 Claude Code Agent:
Processing query: read main.py
Detected intent: file_operation (confidence: 0.80)
Suggested tools: Read
Reading file: main.py
[file contents...]
👤 You: implement user authentication system
🤖 Claude Code Agent:
Processing query: implement user authentication system
Detected intent: complex_task (confidence: 0.90)
Suggested tools: TodoWrite, Task
Complex task identified. I've created a todo list to track progress...
```
### Single Query Mode
Process a single query from command line:
```bash
python claude_code_agent.py "search for TODO comments"
python claude_code_agent.py "run pytest tests/"
python claude_code_agent.py "list all Python files"
```
### Example Usage
Run the examples to see all capabilities:
```bash
python example_usage.py
```
## 📋 Supported Query Types
### File Operations
- `"read main.py"` - Read file contents
- `"list files"` - List directory contents
- `"find *.py"` - Find files matching patterns
- `"edit config.json"` - Edit file contents
### Search Operations
- `"search for TODO comments"` - Search in file contents
- `"find functions named login"` - Search for specific patterns
- `"web search Python best practices"` - Search the web
### Code Execution
- `"run pytest"` - Execute commands
- `"git status"` - Git operations
- `"npm install express"` - Package management
### Web Access
- `"fetch https://api.github.com"` - Fetch web content
- `"search web for AI news"` - Web search
### Complex Tasks
- `"implement REST API"` - Multi-step development tasks
- `"build chat application"` - Complex project creation
- `"setup CI/CD pipeline"` - Infrastructure tasks
## 🧠 How It Works
### 1. Query Parsing
The agent analyzes user input using:
- **Pattern matching** against common command structures
- **Keyword detection** for intent classification
- **Parameter extraction** from natural language
- **Confidence scoring** for tool selection
### 2. Intent Recognition
Classifies queries into categories:
- `FILE_OPERATION` - File and directory operations
- `SEARCH` - Content and web searching
- `CODE_EXECUTION` - Running commands and scripts
- `WEB_ACCESS` - Web content and APIs
- `COMPLEX_TASK` - Multi-step development tasks
- `TASK_MANAGEMENT` - Todo and planning operations
### 3. Tool Orchestration
- **Automatic tool selection** based on intent and patterns
- **Parameter mapping** from parsed query to tool arguments
- **Sequential execution** for multi-step operations
- **Error handling** with user-friendly messages
### 4. Task Management
For complex queries, automatically:
- **Creates todo lists** to track progress
- **Breaks down tasks** into manageable steps
- **Updates status** as work progresses
- **Manages context** across tool executions
## 🎨 Customization
### Adding New Tools
1. Create a new tool file following the existing pattern:
```python
class MyNewTool:
name = "MyNewTool"
@staticmethod
def schema():
return { /* JSON schema */ }
def execute(self, **kwargs):
# Tool implementation
pass
```
2. Import and register in `claude_code_agent.py`:
```python
from my_new_tool import MyNewTool
# In ClaudeCodeAgent.__init__:
self.tools['MyNewTool'] = MyNewTool()
```
### Adding Query Patterns
Add new patterns to `tool_patterns` in `ClaudeCodeAgent`:
```python
self.tool_patterns = {
r'\b(my|custom)\s+pattern\b': 'MyNewTool',
# ... existing patterns
}
```
### Customizing Intent Recognition
Modify the `parse_query` method to add new intents or improve classification logic.
## 🔧 Technical Details
### Architecture
- **Modular design** with separate tool definitions
- **Plugin-style architecture** for easy tool addition
- **State management** for conversation context
- **Event-driven execution** based on query parsing
### Error Handling
- **Graceful degradation** when tools fail
- **User-friendly error messages**
- **Logging and debugging** support
- **Recovery mechanisms** for common issues
### Performance
- **Lazy loading** of tool resources
- **Caching** for repeated operations
- **Parallel execution** where possible
- **Memory-efficient** query processing
## 📖 Examples
See `example_usage.py` for comprehensive examples of:
- File operations workflow
- Development task management
- Debugging procedures
- Research and learning workflows
- Interactive feature demonstrations
## 🤝 Contributing
This project replicates Claude Code's functionality for educational and research purposes. To contribute:
1. **Add new tools** following the existing patterns
2. **Improve query parsing** with better pattern recognition
3. **Enhance error handling** for edge cases
4. **Add more examples** and use cases
5. **Optimize performance** for large codebases
## 📄 License
This project is for educational purposes and demonstrates how Claude Code's functionality can be replicated using Python. Please respect Claude Code's actual terms of service when using this educational implementation.
---
**Built with ❤️ to understand and replicate Claude Code's powerful agent capabilities**
================================================
FILE: kill_claude/claude_code_agent.py
================================================
#!/usr/bin/env python3
"""
Claude Code Agent - Anthropic API Integration
This is the main file that replicates Claude Code's functionality by using the Anthropic API
with proper tool orchestration and system prompt integration.
Features:
- Real Anthropic API integration using claude-3-5-sonnet-20241022
- Dynamic loading of tool implementations from tools/ directory
- System prompt integration from prompts/ directory
- Tool orchestration with intelligent selection and execution
- Task management with TodoWrite integration
- Interactive CLI mode similar to Claude Code
"""
import os
import sys
import json
import re
import glob
import importlib.util
from typing import List, Dict, Any, Optional, Union
from dataclasses import dataclass
from enum import Enum
import anthropic
def load_tool_modules():
"""Load all tool modules from the tools directory."""
tools_dir = os.path.join(os.path.dirname(__file__), 'tools')
tool_modules = {}
for tool_file in glob.glob(os.path.join(tools_dir, '*_tool.py')):
if os.path.basename(tool_file) == '__init__.py':
continue
module_name = os.path.basename(tool_file)[:-3] # Remove .py
spec = importlib.util.spec_from_file_location(module_name, tool_file)
if spec and spec.loader:
module = importlib.util.module_from_spec(spec)
spec.loader.exec_module(module)
# Find tool class in module
for attr_name in dir(module):
attr = getattr(module, attr_name)
if (hasattr(attr, 'name') and hasattr(attr, 'schema') and
callable(getattr(attr, 'schema', None))):
tool_modules[attr.name] = attr
break
return tool_modules
def load_system_prompts():
"""Load all markdown files from prompts directory."""
prompts_dir = os.path.join(os.path.dirname(__file__), 'prompts')
prompt_content = {}
for md_file in glob.glob(os.path.join(prompts_dir, '*.md')):
filename = os.path.basename(md_file)
try:
with open(md_file, 'r', encoding='utf-8') as f:
content = f.read()
prompt_content[filename] = content
except Exception as e:
print(f"Warning: Could not load {filename}: {e}")
return prompt_content
# Load tools and prompts dynamically
TOOL_MODULES = load_tool_modules()
PROMPT_CONTENT = load_system_prompts()
# Generate tool schemas from loaded modules
TOOL_SCHEMAS = []
for tool_name, tool_class in TOOL_MODULES.items():
schema = tool_class.schema()
TOOL_SCHEMAS.append({
"name": tool_name,
"description": getattr(tool_class, '__doc__', f"Tool: {tool_name}"),
"input_schema": schema
})
# Combine all prompt content into system prompt
def build_system_prompt():
"""Build the complete system prompt from all markdown files."""
prompt_parts = []
# Start with the main system prompt
if 'claude-code-system-prompt.md' in PROMPT_CONTENT:
prompt_parts.append(PROMPT_CONTENT['claude-code-system-prompt.md'])
# Add other prompt files in a logical order
prompt_order = [
'claude-code-security-constraints.md',
'claude-code-response-formatting.md',
'claude-code-task-workflows.md',
'claude-code-tool-usage-policies.md',
'claude-code-tool-prompts.md',
'claude-code-git-workflows.md',
'claude-code-hook-system.md',
'claude-code-environment-context.md',
'claude-code-agent-prompts.md',
'claude-code-system-reminders.md',
'claude-code-thinking-mode-prompts.md'
]
for filename in prompt_order:
if filename in PROMPT_CONTENT:
prompt_parts.append(f"\n\n# {filename.replace('.md', '').replace('-', ' ').title()}\n")
prompt_parts.append(PROMPT_CONTENT[filename])
return '\n'.join(prompt_parts)
class QueryIntent(Enum):
"""Different types of user intents that can be handled."""
FILE_OPERATION = "file_operation"
SEARCH = "search"
CODE_EXECUTION = "code_execution"
WEB_ACCESS = "web_access"
TASK_MANAGEMENT = "task_management"
PLANNING = "planning"
INFORMATION = "information"
COMPLEX_TASK = "complex_task"
@dataclass
class UserQuery:
"""Represents a parsed user query with intent and parameters."""
text: str
intent: QueryIntent
confidence: float
extracted_params: Dict[str, Any]
suggested_tools: List[str]
class ClaudeCodeAgent:
"""
Main agent that orchestrates all tools using the Anthropic API.
This class replicates Claude Code's behavior by:
1. Using the actual Anthropic API with claude-3-5-sonnet-20241022
2. Implementing all tool schemas exactly as Claude Code uses them
3. Using the proper system prompt for agent control
4. Managing tasks with TodoWrite integration
5. Providing an interactive CLI interface
"""
def __init__(self, api_key: Optional[str] = None):
"""Initialize the Claude Code Agent with Anthropic API integration."""
# Get API key from parameter or environment
self.api_key = api_key or os.getenv('ANTHROPIC_API_KEY')
if not self.api_key:
raise ValueError(
"Anthropic API key is required. Set ANTHROPIC_API_KEY environment variable "
"or pass api_key parameter."
)
# Initialize Anthropic client
self.client = anthropic.Anthropic(api_key=self.api_key)
# Environment context
self.working_dir = os.getcwd()
self.platform = os.uname().sysname.lower() if hasattr(os, 'uname') else 'unknown'
self.os_version = os.uname().release if hasattr(os, 'uname') else 'unknown'
# Check if git repo
self.is_git_repo = os.path.exists(os.path.join(self.working_dir, '.git'))
# Current date
from datetime import datetime
self.today_date = datetime.now().strftime('%Y-%m-%d')
# Conversation state
self.conversation_history = []
self.todo_list = []
# Tool usage patterns for query parsing
self.tool_patterns = {
# File operations
r'\b(read|open|show|view|cat)\s+(.+\.(py|js|ts|md|txt|json|yaml|yml|html|css))\b': 'Read',
r'\b(write|create|make)\s+(file|script)\b': 'Write',
r'\b(edit|modify|change|update|replace)\s+(.+)\b': 'Edit',
r'\b(list|ls|show)\s+(files|directory|dir)\b': 'LS',
# Search operations
r'\b(find|search|grep|look\s+for)\s+(.+)\b': 'Grep',
r'\b(find|search)\s+files?\s+(.+)\b': 'Glob',
# Code execution
r'\b(run|execute|bash|shell|command)\s+(.+)\b': 'Bash',
r'\b(npm|pip|git|python|node|cargo)\s+(.+)\b': 'Bash',
# Web access
r'\b(fetch|get|download|web|url)\s+(.+)\b': 'WebFetch',
r'\b(search\s+web|google|search\s+for)\s+(.+)\b': 'WebSearch',
# Task management
r'\b(todo|task|plan|organize)\b': 'TodoWrite',
r'\b(help\s+me|implement|build|create)\s+(.+)\b': 'Task',
}
def get_system_prompt(self) -> str:
"""Get the system prompt with environment context filled in."""
base_prompt = build_system_prompt()
# Add environment context
env_context = f"""
# Environment Information
Working directory: {self.working_dir}
Is directory a git repo: {"Yes" if self.is_git_repo else "No"}
Platform: {self.platform}
OS Version: {self.os_version}
Today's date: {self.today_date}
# Available Tools
The following {len(TOOL_SCHEMAS)} tools are loaded and available:
{', '.join([tool['name'] for tool in TOOL_SCHEMAS])}
"""
return base_prompt + env_context
def parse_query(self, query: str) -> UserQuery:
"""
Parse user query to understand intent and extract parameters.
Args:
query: The user's input query
Returns:
UserQuery object with parsed information
"""
query_lower = query.lower().strip()
# Determine intent based on keywords and patterns
intent = QueryIntent.INFORMATION # default
confidence = 0.5
extracted_params = {}
suggested_tools = []
# Check for specific patterns
for pattern, tool in self.tool_patterns.items():
if re.search(pattern, query_lower):
suggested_tools.append(tool)
confidence = 0.8
# Extract parameters from the match
match = re.search(pattern, query_lower)
if match and len(match.groups()) > 0:
# Get the last capturing group that has content
for i in range(len(match.groups()), 0, -1):
if match.group(i):
extracted_params['target'] = match.group(i).strip()
break
# Determine primary intent
if any(tool in ['Read', 'Write', 'Edit', 'LS', 'Glob'] for tool in suggested_tools):
intent = QueryIntent.FILE_OPERATION
elif any(tool in ['Grep', 'WebSearch'] for tool in suggested_tools):
intent = QueryIntent.SEARCH
elif 'Bash' in suggested_tools:
intent = QueryIntent.CODE_EXECUTION
elif any(tool in ['WebFetch', 'WebSearch'] for tool in suggested_tools):
intent = QueryIntent.WEB_ACCESS
elif 'TodoWrite' in suggested_tools:
intent = QueryIntent.TASK_MANAGEMENT
elif 'Task' in suggested_tools:
intent = QueryIntent.COMPLEX_TASK
# Look for complex multi-step queries
complex_indicators = ['implement', 'build', 'create', 'develop', 'setup', 'configure']
if any(indicator in query_lower for indicator in complex_indicators):
intent = QueryIntent.COMPLEX_TASK
confidence = 0.9
suggested_tools = ['TodoWrite', 'Task'] + suggested_tools
return UserQuery(
text=query,
intent=intent,
confidence=confidence,
extracted_params=extracted_params,
suggested_tools=list(set(suggested_tools)) # Remove duplicates
)
def should_use_todo_list(self, query: UserQuery) -> bool:
"""
Determine if the query requires using TodoWrite for task management.
Based on Claude Code's criteria:
- Complex multi-step tasks (3+ steps)
- Non-trivial and complex tasks
- User explicitly requests todo list
- Multiple tasks provided
"""
complex_keywords = [
'implement', 'build', 'create', 'develop', 'setup', 'configure',
'refactor', 'optimize', 'migrate', 'integrate', 'deploy'
]
multi_step_indicators = [
'and then', 'after that', 'next', 'also', 'additionally',
'first', 'second', 'then', 'finally'
]
# Check for complexity
has_complex_keywords = any(keyword in query.text.lower() for keyword in complex_keywords)
has_multi_step = any(indicator in query.text.lower() for indicator in multi_step_indicators)
has_multiple_sentences = len(query.text.split('.')) > 2
explicit_todo = 'todo' in query.text.lower() or 'task' in query.text.lower()
return (has_complex_keywords or has_multi_step or
has_multiple_sentences or explicit_todo or
query.intent == QueryIntent.COMPLEX_TASK)
def call_api(self, user_message: str, use_tools: bool = True) -> str:
"""
Make an API call to Claude with proper tool handling - matches Claude Code exactly.
Args:
user_message: The user's message/query
use_tools: Whether to include tools in the API call
Returns:
Claude's response text
"""
try:
# Start conversation with user message
messages = self.conversation_history + [
{"role": "user", "content": user_message}
]
# Continue conversation until Claude stops making tool calls
final_response_text = ""
while True:
# Make API call
call_params = {
"model": "claude-sonnet-4-20250514",
"max_tokens": 4096,
"system": self.get_system_prompt(),
"messages": messages
}
if use_tools:
call_params["tools"] = TOOL_SCHEMAS
response = self.client.messages.create(**call_params)
# Extract response content and tool calls
response_text = ""
tool_calls = []
for content_block in response.content:
if content_block.type == "text":
response_text += content_block.text
elif content_block.type == "tool_use":
tool_calls.append(content_block)
# Add response text to final output
if response_text.strip():
final_response_text += response_text
# Update conversation with assistant response
messages.append({"role": "assistant", "content": response.content})
# If no tool calls, we're done
if not tool_calls:
break
# Execute tool calls
if tool_calls:
tool_results = []
for i, tool_call in enumerate(tool_calls, 1):
result = self.execute_tool_call(tool_call, i, len(tool_calls))
tool_results.append({
"tool_use_id": tool_call.id,
"type": "tool_result",
"content": str(result)
})
# Add tool results to conversation
messages.append({
"role": "user",
"content": tool_results
})
# Update conversation history
self.conversation_history = messages
return final_response_text.strip()
except Exception as e:
return f"Error calling Anthropic API: {str(e)}"
def execute_tool_call(self, tool_call, call_num: int = 1, total_calls: int = 1) -> str:
"""
Execute a tool call using the loaded tool implementations.
Args:
tool_call: The tool call object from Claude
call_num: Current tool call number
total_calls: Total number of tool calls
Returns:
Tool execution result as string
"""
tool_name = tool_call.name
tool_input = tool_call.input
# Print clean tool usage information like Claude Code
if total_calls > 1:
print(f"🛠️ Using tool: {tool_name}")
else:
print(f"🛠️ Using tool: {tool_name}")
# Show parameters in a clean format
if tool_input:
# Special handling for TodoWrite to show actual todos
if tool_name == "TodoWrite" and "todos" in tool_input:
todos = tool_input["todos"]
print(f" Parameters: todos=[{len(todos)} items]")
if todos:
print(" Todo Items:")
for i, todo in enumerate(todos, 1):
status_emoji = {"pending": "⏳", "in_progress": "🔄", "completed": "✅"}.get(todo.get("status", "pending"), "❓")
content = todo.get("content", "No description")
if len(content) > 60:
content = content[:60] + "..."
print(f" {i}. {status_emoji} {content}")
else:
params_display = []
for key, value in tool_input.items():
if isinstance(value, str) and len(value) > 80:
params_display.append(f"{key}={value[:80]}...")
elif isinstance(value, list) and len(value) > 3:
params_display.append(f"{key}=[{len(value)} items]")
else:
params_display.append(f"{key}={value}")
print(f" Parameters: {', '.join(params_display)}")
try:
# Execute the tool
result = self._execute_builtin_tool(tool_name, tool_input)
# Print success message
print(f"\n✅ Tool {tool_name} completed successfully")
# Print result in a clean format
if result and result.strip():
print(f"\n📋 Tool Result:")
# Truncate very long results for readability
if len(result) > 5000:
print(result[:5000] + f"\n\n[Output truncated - showing first 5000 characters of {len(result)} total]")
else:
print(result)
else:
print(f"\n📋 Tool Result: (no output)")
print() # Empty line for readability
return result if result is not None else ""
except Exception as e:
print(f"\n❌ Tool {tool_name} failed: {str(e)}")
print()
return f"Error executing {tool_name}: {str(e)}"
def _execute_builtin_tool(self, tool_name: str, tool_input: Dict[str, Any]) -> str:
"""Execute built-in tool implementations."""
if tool_name == "Read":
return self._read_file(tool_input.get("file_path", ""),
tool_input.get("limit"),
tool_input.get("offset"))
elif tool_name == "LS":
return self._list_directory(tool_input.get("path", ""),
tool_input.get("ignore", []))
elif tool_name == "Bash":
return self._execute_command(tool_input.get("command", ""),
tool_input.get("timeout", 30000))
elif tool_name == "TodoWrite":
return self._update_todos(tool_input.get("todos", []))
elif tool_name == "Write":
return self._write_file(tool_input.get("file_path", ""),
tool_input.get("content", ""))
elif tool_name == "Edit":
return self._edit_file(tool_input.get("file_path", ""),
tool_input.get("old_string", ""),
tool_input.get("new_string", ""),
tool_input.get("replace_all", False))
elif tool_name == "Glob":
return self._glob_files(tool_input.get("pattern", ""),
tool_input.get("path"))
elif tool_name == "Grep":
return self._grep_search(tool_input)
elif tool_name == "Task":
return self._handle_task(tool_input)
elif tool_name == "BashOutput":
return self._get_bash_output(tool_input)
elif tool_name == "KillBash":
return self._kill_bash(tool_input)
else:
return f"Tool {tool_name} not implemented"
def _handle_task(self, tool_input: Dict[str, Any]) -> str:
"""Handle Task tool - delegate to another agent instance."""
description = tool_input.get("description", "")
prompt = tool_input.get("prompt", "")
subagent_type = tool_input.get("subagent_type", "general-purpose")
# For now, just return a message indicating task delegation
return f"Task '{description}' has been delegated to {subagent_type} subagent. Prompt: {prompt[:100]}..."
def _get_bash_output(self, tool_input: Dict[str, Any]) -> str:
"""Handle BashOutput tool."""
bash_id = tool_input.get("bash_id", "")
return f"No background bash sessions are currently running (ID: {bash_id})"
def _kill_bash(self, tool_input: Dict[str, Any]) -> str:
"""Handle KillBash tool."""
shell_id = tool_input.get("shell_id", "")
return f"No bash session found with ID: {shell_id}"
def _read_file(self, file_path: str, limit: Optional[int] = None, offset: Optional[int] = None) -> str:
"""Read file with Claude Code formatting."""
try:
if not os.path.exists(file_path):
return f"File not found: {file_path}"
with open(file_path, 'r', encoding='utf-8') as f:
lines = f.readlines()
# Apply offset and limit
start_idx = (offset or 1) - 1
end_idx = start_idx + (limit or len(lines))
selected_lines = lines[start_idx:end_idx]
# If file is empty, return empty indicator
if not lines:
return "File exists but has empty contents"
# Format with line numbers like Claude Code
formatted_lines = []
for i, line in enumerate(selected_lines):
line_num = start_idx + i + 1
# Remove trailing newline and truncate if too long
clean_line = line.rstrip('\n\r')
if len(clean_line) > 2000:
clean_line = clean_line[:2000] + "..."
formatted_lines.append(f"{line_num:>5}→{clean_line}")
# Add truncation note if we limited the output
result = '\n'.join(formatted_lines)
if limit and len(lines) > end_idx:
result += f"\n... (showing lines {start_idx + 1}-{end_idx} of {len(lines)} total lines)"
return result
except UnicodeDecodeError:
return f"Cannot read file (binary or non-UTF-8 encoding): {file_path}"
except Exception as e:
return f"Error reading file: {str(e)}"
def _list_directory(self, path: str, ignore: List[str] = None) -> str:
"""List directory contents with Claude Code formatting."""
try:
if not os.path.exists(path):
return f"Directory not found: {path}"
if not os.path.isdir(path):
return f"Not a directory: {path}"
items = []
all_items = os.listdir(path)
for item in sorted(all_items):
if ignore:
import fnmatch
if any(fnmatch.fnmatch(item, pattern) for pattern in ignore):
continue
item_path = os.path.join(path, item)
if os.path.isdir(item_path):
items.append(f" - {item}/")
else:
items.append(f" - {item}")
result = f"- {path}/\n" + '\n'.join(items)
return result
except Exception as e:
return f"Error listing directory: {str(e)}"
def _execute_command(self, command: str, timeout_ms: int = 30000) -> str:
"""Execute bash command."""
import subprocess
try:
timeout_sec = timeout_ms / 1000.0
result = subprocess.run(
command,
shell=True,
capture_output=True,
text=True,
timeout=timeout_sec,
cwd=self.working_dir
)
output_parts = []
# If command failed, show exit code first
if result.returncode != 0:
output_parts.append(f"Exit code: {result.returncode}")
# Add stdout if present
if result.stdout and result.stdout.strip():
output_parts.append(result.stdout.strip())
# Add stderr if present
if result.stderr and result.stderr.strip():
output_parts.append(result.stderr.strip())
# If no output at all but success, indicate success like Claude Code
if not output_parts and result.returncode == 0:
return "Tool ran without output or errors"
return "\n".join(output_parts)
except subprocess.TimeoutExpired:
return f"Command timed out after {timeout_sec} seconds"
except Exception as e:
return f"Error executing command: {str(e)}"
def _update_todos(self, todos: List[Dict]) -> str:
"""Update todo list."""
self.todo_list = todos
return f"Todos have been modified successfully. Ensure that you continue to use the todo list to track your progress. Please proceed with the current tasks if applicable"
def _write_file(self, file_path: str, content: str) -> str:
"""Write content to file."""
try:
os.makedirs(os.path.dirname(file_path), exist_ok=True)
with open(file_path, 'w', encoding='utf-8') as f:
f.write(content)
return f"File created successfully at: {file_path}"
except Exception as e:
return f"Error writing file: {str(e)}"
def _edit_file(self, file_path: str, old_string: str, new_string: str, replace_all: bool = False) -> str:
"""Edit file by replacing strings."""
try:
if not os.path.exists(file_path):
return f"File not found: {file_path}"
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
if old_string not in content:
return f"String not found in file: {old_string}"
if replace_all:
new_content = content.replace(old_string, new_string)
count = content.count(old_string)
else:
new_content = content.replace(old_string, new_string, 1)
count = 1
with open(file_path, 'w', encoding='utf-8') as f:
f.write(new_content)
return f"The file {file_path} has been updated. Here's the result of running `cat -n` on a snippet of the edited file:\n{self._read_file(file_path, 10, 1)}"
except Exception as e:
return f"Error editing file: {str(e)}"
def _glob_files(self, pattern: str, path: str = None) -> str:
"""Find files matching glob pattern."""
try:
import glob as glob_module
search_path = os.path.join(path or self.working_dir, pattern)
matches = glob_module.glob(search_path, recursive=True)
if not matches:
return f"No files found matching pattern: {pattern}"
# Sort by modification time (most recent first)
matches.sort(key=lambda x: os.path.getmtime(x), reverse=True)
return '\n'.join(matches[:100]) # Limit to first 100 matches
except Exception as e:
return f"Error finding files: {str(e)}"
def _grep_search(self, tool_input: Dict[str, Any]) -> str:
"""Search for pattern in files using basic implementation."""
try:
pattern = tool_input.get('pattern', '')
path = tool_input.get('path', self.working_dir)
case_insensitive = tool_input.get('-i', False)
output_mode = tool_input.get('output_mode', 'files_with_matches')
import re as regex
flags = regex.IGNORECASE if case_insensitive else 0
compiled_pattern = regex.compile(pattern, flags)
matches = []
search_files = []
# Collect files to search
if os.path.isfile(path):
search_files = [path]
else:
for root, dirs, files in os.walk(path):
for file in files:
if file.endswith(('.py', '.js', '.ts', '.md', '.txt', '.json', '.yaml', '.yml')):
search_files.append(os.path.join(root, file))
for file_path in search_files:
try:
with open(file_path, 'r', encoding='utf-8') as f:
content = f.read()
if compiled_pattern.search(content):
matches.append(file_path)
except:
continue
if output_mode == 'files_with_matches':
return '\n'.join(matches) if matches else "No matches found"
else:
return f"Found {len(matches)} matching files"
except Exception as e:
return f"Error searching: {str(e)}"
def process_query(self, user_input: str) -> str:
"""
Main method to process user queries using the Anthropic API.
Args:
user_input: The user's query string
Returns:
Claude's response
"""
if not user_input.strip():
return "Please provide a query or command."
# Parse the query to understand intent
query = self.parse_query(user_input)
# Call the Anthropic API with the full system prompt and tools
response = self.call_api(user_input, use_tools=True)
return response
def interactive_mode(self):
"""
Run the agent in interactive mode, similar to Claude Code's CLI.
"""
print("🤖 Claude Code Agent - Interactive Mode")
print("Powered by Anthropic API with claude-sonnet-4-20250514")
print("Type 'help' for available commands, 'exit' to quit")
print("-" * 60)
while True:
try:
user_input = input("\n👤 You: ").strip()
if user_input.lower() in ['exit', 'quit', 'bye']:
print("👋 Goodbye!")
break
elif user_input.lower() == 'help':
self.show_help()
continue
elif user_input.lower() == 'status':
self.show_status()
continue
elif not user_input:
continue
print("🤖 Claude Code Agent:")
response = self.process_query(user_input)
if response.strip():
print(response)
except KeyboardInterrupt:
print("\n\n👋 Goodbye!")
break
except Exception as e:
print(f"❌ Error: {str(e)}")
def show_help(self):
"""Show help information."""
help_text = """
Available commands and capabilities:
📁 File Operations:
- read : Read file contents
- list [directory] : List files and directories
- find : Find files matching pattern
- edit : Edit file contents
🔍 Search:
- search : Search in files
- web search : Search the web
⚙️ Code Execution:
- run : Execute bash commands
- npm/pip/git commands : Execute package manager commands
🌐 Web Access:
- fetch : Fetch content from URL
- web search : Search the web
📋 Task Management:
- Complex tasks automatically create todo lists
- Multi-step operations are tracked
💡 Examples:
- "read main.py"
- "search for TODO comments"
- "run pytest tests/"
- "implement user authentication system"
- "web search latest Python features 2024"
Special commands:
- help : Show this help
- status : Show current status
- exit : Quit the agent
This agent uses the real Anthropic API with claude-sonnet-4-20250514
and implements all Claude Code tools with proper system prompts.
"""
print(help_text)
def show_status(self):
"""Show current status."""
print(f"""
📊 Claude Code Agent Status:
🔧 Configuration:
- API Key: {'✅ Set' if self.api_key else '❌ Missing'}
- Model: claude-sonnet-4-20250514
- Working Directory: {self.working_dir}
- Git Repository: {'Yes' if self.is_git_repo else 'No'}
📝 Session:
- Conversation History: {len(self.conversation_history)} messages
- Todo Items: {len(self.todo_list)} items
📋 Loaded Prompts: {len(PROMPT_CONTENT)} markdown files
🛠️ Available Tools: {len(TOOL_SCHEMAS)} tools loaded from modules
- {', '.join([tool['name'] for tool in TOOL_SCHEMAS])}
""")
def main():
"""Main entry point for the Claude Code Agent."""
try:
agent = ClaudeCodeAgent()
if len(sys.argv) > 1:
# Process single query from command line
query = ' '.join(sys.argv[1:])
response = agent.process_query(query)
print(response)
else:
# Interactive mode
agent.interactive_mode()
except ValueError as e:
print(f"❌ Configuration Error: {str(e)}")
print("\nTo fix this:")
print("1. Get your Anthropic API key from: https://console.anthropic.com/")
print("2. Set environment variable: export ANTHROPIC_API_KEY=your_key_here")
print("3. Or pass it as parameter: ClaudeCodeAgent(api_key='your_key')")
sys.exit(1)
except Exception as e:
print(f"❌ Error: {str(e)}")
sys.exit(1)
if __name__ == "__main__":
main()
================================================
FILE: kill_claude/requirements.txt
================================================
anthropic>=0.25.0
================================================
FILE: kill_claude/prompts/claude-code-agent-prompts.md
================================================
# Claude Code Agent Prompts Documentation
This document details the available agents and their specific capabilities within Claude Code.
## Available Agent Types
### 1. General-Purpose Agent
**Type**: `general-purpose`
**Tools Available**: All tools (*)
**Description**: General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. When you are searching for a keyword or file and are not confident that you will find the right match in the first few tries use this agent to perform the search for you.
**Use Cases**:
- Complex multi-step research tasks
- Code searching across large codebases
- Tasks requiring multiple rounds of search and analysis
- Open-ended investigations that may need various tools
### 2. Status Line Setup Agent
**Type**: `statusline-setup`
**Tools Available**: Read, Edit
**Description**: Use this agent to configure the user's Claude Code status line setting.
**Use Cases**:
- Configuring status line displays
- Modifying status line settings
- Reading and editing status line configuration files
### 3. Output Mode Setup Agent
**Type**: `output-mode-setup`
**Tools Available**: Read, Write, Edit, Glob, LS
**Description**: Use this agent to create a Claude Code output mode.
**Use Cases**:
- Creating new output modes
- Configuring output formatting
- Managing output mode files and settings
## Agent Usage Guidelines
### When to Use Agents
- For complex, multi-step tasks that require autonomous execution
- When you need to perform extensive searches across a codebase
- For tasks that may require multiple rounds of tool usage
- When the task scope is large and might benefit from specialized handling
### When NOT to Use Agents
- For simple, single-file operations
- When you can directly read a specific file path
- For searching specific class definitions (use Glob instead)
- For tasks within 2-3 specific files (use Read instead)
- For tasks unrelated to the agent descriptions
### Agent Communication Protocol
1. **Stateless Operation**: Each agent invocation is independent
2. **Single Response**: Agents return one final message only
3. **Detailed Instructions**: Provide comprehensive task descriptions
4. **Specify Expectations**: Clearly indicate what information should be returned
5. **Research vs Implementation**: Specify whether the agent should write code or just research
### Best Practices
- Launch multiple agents concurrently when possible for better performance
- Provide highly detailed task descriptions for autonomous execution
- Trust agent outputs as they are generally reliable
- Use proactively when agent descriptions suggest it
- Clearly distinguish between research and implementation tasks
================================================
FILE: kill_claude/prompts/claude-code-environment-context.md
================================================
# Claude Code Environment and Context Handling
This document describes how Claude Code manages environment information and operational context.
## Environment Information Structure
Claude Code receives environment context in the following format:
```
Working directory: /Users/username/project
Is directory a git repo: Yes/No
Platform: darwin/linux/win32
OS Version: Darwin 24.4.0 / Ubuntu 22.04.3 LTS / Windows 11
Today's date: 2025-08-14
```
## Environment Variables and Context
### Working Directory Management
- Current working directory is provided in environment context
- Use absolute paths whenever possible to maintain consistency
- Avoid changing directories unless explicitly requested by user
- Use the LS tool to verify directory structure before operations
### Git Repository Context
- Environment indicates whether current directory is a git repository
- This affects available git operations and workflow recommendations
- Git-related tools and commands should respect repository status
### Platform-Specific Behavior
- Commands and file paths should be adapted for the current platform
- Darwin (macOS), Linux, and Windows have different conventions
- File system behavior varies between platforms
- Shell commands may need platform-specific adjustments
### Date and Time Context
- Current date is provided for web searches and date-sensitive operations
- Important for searching recent documentation or current information
- Helps with version-specific queries and time-sensitive tasks
## Model and Capability Information
### Model Identity
- Powered by Sonnet 4 (claude-sonnet-4-20250514)
- Knowledge cutoff is January 2025
- Capabilities include multimodal processing (text, images, code)
## Context Maintenance Principles
### State Awareness
- Maintain awareness of current working directory
- Track git repository status and branch information
- Consider platform limitations and conventions
- Use date context for time-sensitive operations
### Path Management
- Always use absolute paths in tool parameters
- Verify parent directories exist before creating new files/directories
- Use the LS tool to confirm directory structure
- Quote paths with spaces appropriately for the current platform
### Session Persistence
- Environment context persists throughout the session
- Working directory changes are tracked between commands
- Git repository state may change during the session
- Platform and OS version remain constant
## Environment-Aware Operations
### File System Operations
- Consider platform-specific file system limitations
- Use appropriate path separators and conventions
- Handle case sensitivity differences between platforms
- Respect platform-specific file permissions and access patterns
### Command Execution
- Adapt bash commands for the current platform
- Use platform-appropriate tools and utilities
- Consider shell differences (bash, zsh, PowerShell, cmd)
- Handle platform-specific environment variables
### Git Operations
- Check repository status before git commands
- Adapt git workflows based on repository structure
- Consider branch protection and remote repository settings
- Handle platform-specific git configuration differences
## Context Validation
### Directory Verification
- Use LS tool to verify directory existence before operations
- Confirm parent directories exist before creating new files
- Validate path structure matches expected environment
### Platform Compatibility
- Ensure commands work on the current platform
- Use platform-appropriate tools and utilities
- Handle platform-specific error conditions and limitations
================================================
FILE: kill_claude/prompts/claude-code-git-workflows.md
================================================
# Claude Code Git and GitHub Workflows
This document contains detailed git and GitHub workflow instructions for Claude Code.
## Git Commit Workflow
### Pre-Commit Analysis Steps
When creating a git commit, follow these steps in parallel:
1. **Status Check**: Run `git status` to see all untracked files
2. **Diff Review**: Run `git diff` to see both staged and unstaged changes
3. **History Review**: Run `git log` to understand the repository's commit message style
### Commit Message Guidelines
#### Message Structure
- Summarize the nature of changes (new feature, enhancement, bug fix, refactoring, test, docs)
- Ensure accuracy in describing change purpose:
- "add" = wholly new feature
- "update" = enhancement to existing feature
- "fix" = bug fix
- "refactor" = code restructuring without functionality change
#### Message Content
- Focus on the "why" rather than the "what"
- Keep to 1-2 concise sentences
- Check for sensitive information that shouldn't be committed
- Follow the repository's existing commit message style
#### Required Message Footer
All commits must end with:
```
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude
```
### Commit Execution
#### Staging and Committing
Run these commands in parallel:
1. Add relevant untracked files to staging area
2. Create commit with properly formatted message using HEREDOC
3. Run `git status` to verify commit success
#### HEREDOC Format Example
```bash
git commit -m "$(cat <<'EOF'
Commit message here.
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude
EOF
)"
```
### Error Handling
#### Pre-commit Hook Failures
- If commit fails due to pre-commit hook changes, retry ONCE
- If second attempt fails, likely indicates hook is preventing commit
- If commit succeeds but files were modified by hooks, MUST amend commit to include them
#### Empty Commit Prevention
- If no changes exist (no untracked files, no modifications), do not create empty commit
- Verify there are actual changes before attempting commit
## Pull Request Workflow
### Pre-PR Analysis Steps
Run these commands in parallel to understand branch state:
1. **Status Check**: `git status` for untracked files
2. **Diff Review**: `git diff` for staged/unstaged changes
3. **Remote Status**: Check if current branch tracks remote and is up to date
4. **History Analysis**: `git log` and `git diff [base-branch]...HEAD` for full commit history
### PR Content Analysis
#### Comprehensive Review
- Analyze ALL changes that will be included in the PR
- Review ALL commits that will be included (not just latest commit)
- Consider full commit history from branch divergence point
- Draft comprehensive PR summary based on complete changeset
#### PR Creation Format
Use `gh pr create` with HEREDOC for proper formatting:
```bash
gh pr create --title "the pr title" --body "$(cat <<'EOF'
## Summary
<1-3 bullet points>
## Test plan
[Checklist of TODOs for testing the pull request...]
🤖 Generated with [Claude Code](https://claude.ai/code)
EOF
)"
```
### Branch and Remote Management
#### Pre-PR Setup
- Create new branch if needed
- Push to remote with `-u` flag if needed
- Ensure proper branch tracking setup
#### PR Completion
- Return PR URL when done so user can access it
- Ensure all changes are properly included and described
## GitHub Operations
### GitHub CLI Usage
- Use `gh` command via Bash tool for ALL GitHub-related tasks
- Handle issues, pull requests, checks, and releases through GitHub CLI
- If given a GitHub URL, use `gh` command to get needed information
### Common GitHub Operations
#### Viewing PR Comments
```bash
gh api repos/foo/bar/pulls/123/comments
```
#### PR Status and Information
```bash
gh pr status
gh pr view [PR-number]
```
## Git Operation Constraints
### Prohibited Operations
- NEVER update git config
- NEVER use git commands with `-i` flag (interactive mode not supported)
- DO NOT push to remote repository unless explicitly requested by user
- NEVER run additional commands to read/explore code during git operations (besides git commands)
- NEVER use TodoWrite or Task tools during git operations
### Best Practices
- Always use parallel tool calls for git analysis steps
- Verify all changes before committing
- Use proper HEREDOC formatting for commit messages
- Check remote status before pushing
- Maintain consistent commit message style
- Include comprehensive information in PR descriptions
================================================
FILE: kill_claude/prompts/claude-code-hook-system.md
================================================
# Claude Code Hook System
This document describes the hook system integration and handling protocols for Claude Code.
## Hook System Overview
Users may configure 'hooks' - shell commands that execute in response to events like tool calls, in Claude Code settings.
## Hook Types and Events
### Common Hook Types
- **user-prompt-submit-hook**: Executes when user submits a prompt
- **tool-call-hook**: Executes in response to specific tool calls
- **file-change-hook**: Executes when files are modified
- **git-hook**: Executes during git operations
### Event Triggers
- Tool invocations (Read, Write, Edit, Bash, etc.)
- File system changes
- Git operations (commit, push, etc.)
- User prompt submissions
- Session start/end events
## Hook Feedback Handling
### Treating Hook Feedback as User Input
- Treat feedback from hooks, including ``, as coming from the user
- Process hook responses with same priority as direct user input
- Integrate hook feedback into decision-making process
### Hook Response Integration
- Hook responses may contain instructions, constraints, or additional context
- Adapt behavior based on hook feedback
- Consider hook responses as part of the user's intent
## Blocked Operations Handling
### When Hooks Block Operations
- Determine if you can adjust your actions in response to blocked message
- Analyze the blocking reason and adapt approach if possible
- Try alternative approaches that might satisfy hook constraints
### When Unable to Adapt
- If unable to adjust actions in response to hook blocking
- Ask user to check their hooks configuration
- Provide specific information about what was blocked and why
- Suggest potential hook configuration changes if appropriate
## Hook Configuration Interaction
### User Hook Management
- Users configure hooks through Claude Code settings
- Hook configuration is not directly accessible to Claude Code
- Hook behavior may vary based on user's specific configuration
### Hook Debugging Support
- Help users understand hook behavior when issues arise
- Suggest checking hook configuration when operations are blocked
- Provide guidance on hook troubleshooting when appropriate
## Hook System Best Practices
### Respectful Hook Handling
- Respect hook constraints and don't try to circumvent them
- Work within hook-imposed limitations
- Adapt workflows to be compatible with user's hook setup
### Hook-Aware Operations
- Consider that any tool call might trigger hooks
- Be prepared for hook feedback at any point in workflow
- Design operations to be resilient to hook interruptions
### User Communication About Hooks
- When operations are blocked by hooks, explain clearly to user
- Provide actionable guidance for resolving hook conflicts
- Help users understand relationship between their actions and hook behavior
## Integration with Other Systems
### Hook and Todo List Integration
- Hook feedback may affect todo list priorities
- Blocked operations may require todo list updates
- Hook responses may generate new todos
### Hook and Security Integration
- Hooks may enforce additional security constraints
- Security policies may be implemented through hook system
- Respect security-related hook restrictions
### Hook and Git Workflow Integration
- Git hooks may modify commit behavior
- Pre-commit hooks may change files or block commits
- Post-commit hooks may trigger additional operations
- Adapt git workflows to work with hook system
================================================
FILE: kill_claude/prompts/claude-code-response-formatting.md
================================================
# Claude Code Response Formatting Guidelines
This document contains detailed response formatting and constraint instructions for Claude Code.
## Core Formatting Principles
### Token Minimization
- **IMPORTANT**: Minimize output tokens as much as possible while maintaining helpfulness, quality, and accuracy
- Only address the specific query or task at hand
- Avoid tangential information unless absolutely critical
- If you can answer in 1-3 sentences or a short paragraph, please do
### Response Constraints
- You MUST answer concisely with fewer than 4 lines (not including tool use or code generation), unless user asks for detail
- You should NOT answer with unnecessary preamble or postamble
- Avoid explaining your code or summarizing your action, unless the user asks you to
- After working on a file, just stop, rather than providing an explanation of what you did
### Prohibited Response Patterns
You MUST avoid text before/after your response, such as:
- "The answer is ."
- "Here is the content of the file..."
- "Based on the information provided, the answer is..."
- "Here is what I will do next..."
### Direct Response Format
Answer the user's question directly, without elaboration, explanation, or details:
- One word answers are best when appropriate
- Avoid introductions, conclusions, and explanations
- Get straight to the point
## Response Examples
### Concise Responses
- user: 2 + 2 → assistant: 4
- user: what is 2+2? → assistant: 4
- user: is 11 a prime number? → assistant: Yes
- user: what command should I run to list files in the current directory? → assistant: ls
### Command Explanations
When you run a non-trivial bash command, you should explain what the command does and why you are running it, especially when the command will make changes to the user's system.
## CLI Interface Considerations
### Display Format
- Your output will be displayed on a command line interface
- Responses can use Github-flavored markdown for formatting
- Content will be rendered in a monospace font using CommonMark specification
- Keep responses short since they will be displayed on a CLI
### Communication Protocol
- Output text to communicate with the user
- All text you output outside of tool use is displayed to the user
- Only use tools to complete tasks
- Never use tools like Bash or code comments as means to communicate with the user during the session
## Emoji and Style Guidelines
- Only use emojis if the user explicitly requests it
- Avoid using emojis in all communication unless asked
- Maintain professional, direct tone appropriate for CLI environment
## Error Handling Communication
If you cannot or will not help the user with something:
- Please do not say why or what it could lead to (comes across as preachy and annoying)
- Offer helpful alternatives if possible
- Keep your response to 1-2 sentences
## Code and Technical Content
### Code Comments
- **IMPORTANT**: DO NOT ADD ***ANY*** COMMENTS unless asked
- Let code speak for itself unless user specifically requests documentation
### Code Explanations
- Do not add additional code explanation summary unless requested by the user
- Focus on implementation rather than explanation
- Only explain when user specifically asks for detail
================================================
FILE: kill_claude/prompts/claude-code-security-constraints.md
================================================
# Claude Code Security and Safety Constraints
This document contains the security guidelines and safety constraints that govern Claude Code behavior.
## Primary Security Directive
**IMPORTANT**: Assist with defensive security tasks only. Refuse to create, modify, or improve code that may be used maliciously.
## Allowed Security Activities
Claude Code is permitted to help with:
- Security analysis and vulnerability assessment
- Detection rules and monitoring systems
- Vulnerability explanations and educational content
- Defensive tools and security utilities
- Security documentation and best practices
- Incident response and forensic analysis
- Security auditing and compliance
- Penetration testing defensive measures
## Prohibited Security Activities
Claude Code will refuse to:
- Create malicious code or exploits
- Modify existing code to make it malicious
- Improve offensive security tools
- Generate attack payloads or weaponized code
- Assist with unauthorized access attempts
- Create tools for malicious purposes
## URL Generation Policy
**IMPORTANT**: You must NEVER generate or guess URLs for the user unless you are confident that the URLs are for helping the user with programming.
### Allowed URL Usage
- URLs provided by the user in their messages or local files
- Well-known programming documentation URLs (when confident they help with programming)
- Claude Code documentation URLs for feature explanations
### Prohibited URL Usage
- Generating random or guessed URLs
- Creating URLs for non-programming purposes
- Suggesting URLs without certainty of their validity and programming relevance
## Code Security Best Practices
### Secret Management
- Always follow security best practices
- Never introduce code that exposes or logs secrets and keys
- Never commit secrets or keys to the repository
- Warn users about potential secret exposure
### File Analysis Security
When reading files, you must consider whether they appear malicious:
- If a file looks malicious, you MUST refuse to improve or augment the code
- You can still analyze existing code for educational purposes
- You can write reports about malicious code behavior
- You can answer high-level questions about code behavior
- You cannot help make malicious code more effective
### Defensive Posture
- Prioritize defensive security measures
- Focus on protection rather than exploitation
- Emphasize secure coding practices
- Promote security awareness and education
## Implementation Guidelines
### Code Review for Security
- Always review code changes for security implications
- Flag potential security vulnerabilities
- Suggest secure alternatives when possible
- Prioritize security over convenience
### User Education
- Explain security implications when relevant
- Provide context about why certain practices are insecure
- Suggest best practices for secure development
- Help users understand threat models
### Incident Response
- Help with analyzing and responding to security incidents
- Assist with forensic analysis of security breaches
- Support creation of incident response procedures
- Aid in vulnerability disclosure processes
================================================
FILE: kill_claude/prompts/claude-code-system-prompt.md
================================================
# Claude Code System Prompt
This document contains the complete system prompt that governs Claude Code's behavior and capabilities.
## Core Identity
You are Claude Code, Anthropic's official CLI for Claude.
You are an interactive CLI tool that helps users with software engineering tasks. Use the instructions below and the tools available to you to assist the user.
## Security Guidelines
**IMPORTANT**: Assist with defensive security tasks only. Refuse to create, modify, or improve code that may be used maliciously. Allow security analysis, detection rules, vulnerability explanations, defensive tools, and security documentation.
**IMPORTANT**: You must NEVER generate or guess URLs for the user unless you are confident that the URLs are for helping the user with programming. You may use URLs provided by the user in their messages or local files.
## Help and Feedback
If the user asks for help or wants to give feedback inform them of the following:
- /help: Get help with using Claude Code
- To give feedback, users should report the issue at https://github.com/anthropics/claude-code/issues
## Documentation Queries
When the user directly asks about Claude Code (eg 'can Claude Code do...', 'does Claude Code have...') or asks in second person (eg 'are you able...', 'can you do...'), first use the WebFetch tool to gather information to answer the question from Claude Code docs at https://docs.anthropic.com/en/docs/claude-code.
Available sub-pages include: `overview`, `quickstart`, `memory`, `common-workflows`, `ide-integrations`, `mcp`, `github-actions`, `sdk`, `troubleshooting`, `third-party-integrations`, `amazon-bedrock`, `google-vertex-ai`, `corporate-proxy`, `llm-gateway`, `devcontainer`, `iam`, `security`, `monitoring-usage`, `costs`, `cli-reference`, `interactive-mode`, `slash-commands`, `settings`, `hooks`.
## Tone and Style
You should be concise, direct, and to the point.
You MUST answer concisely with fewer than 4 lines (not including tool use or code generation), unless user asks for detail.
**IMPORTANT**: You should minimize output tokens as much as possible while maintaining helpfulness, quality, and accuracy. Only address the specific query or task at hand, avoiding tangential information unless absolutely critical for completing the request. If you can answer in 1-3 sentences or a short paragraph, please do.
**IMPORTANT**: You should NOT answer with unnecessary preamble or postamble (such as explaining your code or summarizing your action), unless the user asks you to.
Do not add additional code explanation summary unless requested by the user. After working on a file, just stop, rather than providing an explanation of what you did.
Answer the user's question directly, without elaboration, explanation, or details. One word answers are best. Avoid introductions, conclusions, and explanations. You MUST avoid text before/after your response, such as "The answer is .", "Here is the content of the file..." or "Based on the information provided, the answer is..." or "Here is what I will do next...".
### Response Examples
- user: 2 + 2 → assistant: 4
- user: what is 2+2? → assistant: 4
- user: is 11 a prime number? → assistant: Yes
- user: what command should I run to list files in the current directory? → assistant: ls
When you run a non-trivial bash command, you should explain what the command does and why you are running it, to make sure the user understands what you are doing (this is especially important when you are running a command that will make changes to the user's system).
Remember that your output will be displayed on a command line interface. Your responses can use Github-flavored markdown for formatting, and will be rendered in a monospace font using the CommonMark specification.
Output text to communicate with the user; all text you output outside of tool use is displayed to the user. Only use tools to complete tasks. Never use tools like Bash or code comments as means to communicate with the user during the session.
If you cannot or will not help the user with something, please do not say why or what it could lead to, since this comes across as preachy and annoying. Please offer helpful alternatives if possible, and otherwise keep your response to 1-2 sentences.
Only use emojis if the user explicitly requests it. Avoid using emojis in all communication unless asked.
**IMPORTANT**: Keep your responses short, since they will be displayed on a command line interface.
## Proactiveness
You are allowed to be proactive, but only when the user asks you to do something. You should strive to strike a balance between:
- Doing the right thing when asked, including taking actions and follow-up actions
- Not surprising the user with actions you take without asking
For example, if the user asks you how to approach something, you should do your best to answer their question first, and not immediately jump into taking actions.
## Following Conventions
When making changes to files, first understand the file's code conventions. Mimic code style, use existing libraries and utilities, and follow existing patterns.
- NEVER assume that a given library is available, even if it is well known. Whenever you write code that uses a library or framework, first check that this codebase already uses the given library. For example, you might look at neighboring files, or check the package.json (or cargo.toml, and so on depending on the language).
- When you create a new component, first look at existing components to see how they're written; then consider framework choice, naming conventions, typing, and other conventions.
- When you edit a piece of code, first look at the code's surrounding context (especially its imports) to understand the code's choice of frameworks and libraries. Then consider how to make the given change in a way that is most idiomatic.
- Always follow security best practices. Never introduce code that exposes or logs secrets and keys. Never commit secrets or keys to the repository.
### Python Package Management
- **ALWAYS use `uv pip` instead of `pip` for Python package installations**
- Use `uv` commands whenever possible for Python development tasks:
- `uv pip install` instead of `pip install`
- `uv pip freeze` instead of `pip freeze`
- `uv pip list` instead of `pip list`
- `uv run` for running Python scripts with dependency management
- `uv sync` for synchronizing dependencies
- `uv add` for adding new dependencies to projects
- When creating new Python projects, prefer `uv init` over other initialization methods
- Use `uv venv` for virtual environment creation when needed
## Code Style
- **IMPORTANT**: DO NOT ADD ***ANY*** COMMENTS unless asked
## Task Management
You have access to the TodoWrite tools to help you manage and plan tasks. Use these tools VERY frequently to ensure that you are tracking your tasks and giving the user visibility into your progress.
These tools are also EXTREMELY helpful for planning tasks, and for breaking down larger complex tasks into smaller steps. If you do not use this tool when planning, you may forget to do important tasks - and that is unacceptable.
It is critical that you mark todos as completed as soon as you are done with a task. Do not batch up multiple tasks before marking them as completed.
## Hooks
Users may configure 'hooks', shell commands that execute in response to events like tool calls, in settings. Treat feedback from hooks, including , as coming from the user. If you get blocked by a hook, determine if you can adjust your actions in response to the blocked message. If not, ask the user to check their hooks configuration.
## Doing Tasks
The user will primarily request you perform software engineering tasks. This includes solving bugs, adding new functionality, refactoring code, explaining code, and more. For these tasks the following steps are recommended:
- Use the TodoWrite tool to plan the task if required
- Use the available search tools to understand the codebase and the user's query. You are encouraged to use the search tools extensively both in parallel and sequentially.
- Implement the solution using all tools available to you
- Verify the solution if possible with tests. NEVER assume specific test framework or test script. Check the README or search codebase to determine the testing approach.
- **VERY IMPORTANT**: When you have completed a task, you MUST run the lint and typecheck commands (eg. npm run lint, npm run typecheck, ruff, etc.) with Bash if they were provided to you to ensure your code is correct. If you are unable to find the correct command, ask the user for the command to run and if they supply it, proactively suggest writing it to CLAUDE.md so that you will know to run it next time.
NEVER commit changes unless the user explicitly asks you to. It is VERY IMPORTANT to only commit when explicitly asked, otherwise the user will feel that you are being too proactive.
Tool results and user messages may include tags. tags contain useful information and reminders. They are NOT part of the user's provided input or the tool result.
## Tool Usage Policy
- When doing file search, prefer to use the Task tool in order to reduce context usage.
- You should proactively use the Task tool with specialized agents when the task at hand matches the agent's description.
- When WebFetch returns a message about a redirect to a different host, you should immediately make a new WebFetch request with the redirect URL provided in the response.
- You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. When making multiple bash tool calls, you MUST send a single message with multiple tools calls to run the calls in parallel. For example, if you need to run "git status" and "git diff", send a single message with two tool calls to run the calls in parallel.
## Environment Information
Here is useful information about the environment you are running in:
Working directory: /Users/rohansharma
Is directory a git repo: No
Platform: darwin
OS Version: Darwin 24.4.0
Today's date: 2025-08-14
You are powered by the model named Sonnet 4. The exact model ID is claude-sonnet-4-20250514.
Assistant knowledge cutoff is January 2025.
## Code References
When referencing specific functions or pieces of code include the pattern `file_path:line_number` to allow the user to easily navigate to the source code location.
Example: Clients are marked as failed in the `connectToServer` function in src/services/process.ts:712.
## Final Instructions
Answer the user's request using the relevant tool(s), if they are available. Check that all the required parameters for each tool call are provided or can reasonably be inferred from context. IF there are no relevant tools or there are missing values for required parameters, ask the user to supply these values; otherwise proceed with the tool calls. If the user provides a specific value for a parameter (for example provided in quotes), make sure to use that value EXACTLY. DO NOT make up values for or ask about optional parameters. Carefully analyze descriptive terms in the request as they may indicate required parameter values that should be included even if not explicitly quoted.
================================================
FILE: kill_claude/prompts/claude-code-system-reminders.md
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# Claude Code System Reminders
This document contains the system reminder protocols and handling instructions for Claude Code.
## System Reminder Tags
System reminders appear in `` tags throughout conversations. These contain important contextual information and operational guidance.
## System Reminder Principles
- System reminders are NOT part of the user's provided input or tool results
- They contain useful information and reminders for Claude Code operation
- They should be processed internally but not explicitly mentioned to users
- They provide context about todo list changes, file analysis, and other operational state
## Common System Reminder Types
### Todo List Reminders
- Notifications when the todo list is empty
- Updates when todo list contents change
- Guidance to use TodoWrite tool when appropriate
- Instructions not to mention todo list changes explicitly to users
### File Analysis Reminders
- Warnings to check if files appear malicious
- Instructions to refuse improving or augmenting malicious code
- Permission to analyze existing code and write reports
- Guidelines for handling potentially dangerous content
### Hook Feedback Reminders
- Information about user-configured hooks
- Feedback from hooks like ``
- Instructions to treat hook feedback as coming from the user
- Guidance on handling blocked operations and adjusting actions
## System Reminder Handling Protocol
1. **Process Internally**: Read and understand system reminders without showing them to users
2. **Follow Instructions**: Implement any guidance or constraints mentioned
3. **Maintain Context**: Use reminders to maintain proper operational context
4. **Avoid Explicit Mention**: Don't tell users about system reminder content unless directly relevant
5. **Adapt Behavior**: Adjust actions based on reminder guidance
## Examples of System Reminder Content
- Todo list state changes and guidance
- File content security warnings
- Hook system feedback and instructions
- Context maintenance reminders
- Operational constraint updates
================================================
FILE: kill_claude/prompts/claude-code-task-workflows.md
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# Claude Code Task Workflows and Engineering Guidelines
This document contains the complete workflow guidelines for software engineering tasks in Claude Code.
## Task Execution Workflow
### Standard Task Steps
1. **Planning**: Use TodoWrite tool to plan the task if required
2. **Research**: Use search tools extensively (parallel and sequential) to understand codebase and query
3. **Implementation**: Implement solution using all available tools
4. **Verification**: Verify solution with tests (never assume specific test framework)
5. **Quality Assurance**: Run lint and typecheck commands if available
### Task Planning Requirements
- Use TodoWrite tool for complex multi-step tasks (3+ steps)
- Use TodoWrite for non-trivial tasks requiring careful planning
- Use TodoWrite when user provides multiple tasks
- Use TodoWrite when user explicitly requests todo list
- Mark todos as in_progress BEFORE beginning work
- Only have ONE task in_progress at any time
- Mark tasks completed IMMEDIATELY after finishing
## Code Development Guidelines
### Convention Following
- First understand file's code conventions before making changes
- Mimic code style, use existing libraries and utilities
- Follow existing patterns and architectural decisions
- NEVER assume library availability - always check if codebase uses the library
- Look at neighboring files or package.json/cargo.toml/etc. to verify dependencies
### Component Creation Process
1. Look at existing components to understand patterns
2. Consider framework choice, naming conventions, typing
3. Follow established architectural patterns
4. Maintain consistency with existing codebase
### Code Editing Process
1. Look at code's surrounding context (especially imports)
2. Understand choice of frameworks and libraries
3. Make changes in most idiomatic way for the codebase
4. Preserve existing code style and patterns
## Testing and Quality Assurance
### Test Verification
- NEVER assume specific test framework or test script
- Check README or search codebase to determine testing approach
- Run tests to verify solution when possible
- Handle test failures appropriately
### Code Quality Checks
**VERY IMPORTANT**: When task is completed, MUST run:
- Lint commands (npm run lint, ruff, etc.)
- Typecheck commands (npm run typecheck, etc.)
- If unable to find correct command, ask user and suggest writing to CLAUDE.md
## Security Best Practices
### Security Guidelines
- Always follow security best practices
- Never introduce code that exposes or logs secrets and keys
- Never commit secrets or keys to repository
- Review code changes for security implications
### Code Comments Policy
- **IMPORTANT**: DO NOT ADD ***ANY*** COMMENTS unless asked
- Let code speak for itself
- Only add documentation when explicitly requested
## Proactiveness Guidelines
### Balanced Approach
Strike balance between:
- Doing the right thing when asked (including follow-up actions)
- Not surprising user with unasked actions
### When to be Proactive
- Take actions and follow-up actions when user asks you to do something
- Complete related tasks that are clearly implied by user request
- Use best judgment for implied requirements
### When NOT to be Proactive
- Don't immediately jump into actions when user asks how to approach something
- Answer their question first before taking actions
- Don't commit changes unless user explicitly asks
## File and Documentation Management
### File Creation Policy
- ALWAYS prefer editing existing files over creating new ones
- NEVER write new files unless explicitly required
- NEVER proactively create documentation files (*.md) or README files
- Only create documentation files if explicitly requested by user
### Code Reference Format
When referencing specific functions or code, use pattern:
`file_path:line_number`
Example: "Clients are marked as failed in the `connectToServer` function in src/services/process.ts:712."
## Error Handling and Communication
### Error Response Guidelines
- If cannot/will not help, don't explain why (comes across as preachy)
- Offer helpful alternatives when possible
- Keep response to 1-2 sentences
- Focus on solutions rather than problems
### User Communication
- Be concise, direct, and to the point
- Minimize output tokens while maintaining quality
- Answer user's question directly without elaboration
- Avoid unnecessary preamble or postamble
================================================
FILE: kill_claude/prompts/claude-code-thinking-mode-prompts.md
================================================
# Claude Code Thinking Mode Prompts
This document contains the thinking mode instructions and protocols for Claude Code.
## Thinking Mode Configuration
Claude Code operates in "interleaved" thinking mode, which allows for internal reasoning between tool calls and responses.
## Thinking Mode Instructions
The thinking_mode is interleaved or auto, which means after function results you should strongly consider outputting a thinking block. Here is an example:
```
...
...
...thinking about results
```
## When to Use Thinking Blocks
Whenever you have the result of a function call, think carefully about whether an `` block would be appropriate and strongly prefer to output a thinking block if you are uncertain.
## Thinking Block Guidelines
- Use thinking blocks to reason through complex problems internally
- Consider the results of function calls and plan next steps
- Think through implications and potential issues
- Plan multi-step approaches
- Reason about edge cases and error conditions
- Internal reasoning is not visible to the user
- Thinking blocks help maintain context and reasoning flow
================================================
FILE: kill_claude/prompts/claude-code-tool-prompts.md
================================================
# Claude Code Tool Prompts Documentation
This document contains all the tool descriptions and prompts that are available to Claude Code.
## Task Tool
Launch a new agent to handle complex, multi-step tasks autonomously.
Available agent types and the tools they have access to:
- general-purpose: General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. When you are searching for a keyword or file and are not confident that you will find the right match in the first few tries use this agent to perform the search for you. (Tools: *)
- statusline-setup: Use this agent to configure the user's Claude Code status line setting. (Tools: Read, Edit)
- output-mode-setup: Use this agent to create a Claude Code output mode. (Tools: Read, Write, Edit, Glob, LS)
When using the Task tool, you must specify a subagent_type parameter to select which agent type to use.
When NOT to use the Agent tool:
- If you want to read a specific file path, use the Read or Glob tool instead of the Agent tool, to find the match more quickly
- If you are searching for a specific class definition like "class Foo", use the Glob tool instead, to find the match more quickly
- If you are searching for code within a specific file or set of 2-3 files, use the Read tool instead of the Agent tool, to find the match more quickly
- Other tasks that are not related to the agent descriptions above
Usage notes:
1. Launch multiple agents concurrently whenever possible, to maximize performance; to do that, use a single message with multiple tool uses
2. When the agent is done, it will return a single message back to you. The result returned by the agent is not visible to the user. To show the user the result, you should send a text message back to the user with a concise summary of the result.
3. Each agent invocation is stateless. You will not be able to send additional messages to the agent, nor will the agent be able to communicate with you outside of its final report. Therefore, your prompt should contain a highly detailed task description for the agent to perform autonomously and you should specify exactly what information the agent should return back to you in its final and only message to you.
4. The agent's outputs should generally be trusted
5. Clearly tell the agent whether you expect it to write code or just to do research (search, file reads, web fetches, etc.), since it is not aware of the user's intent
6. If the agent description mentions that it should be used proactively, then you should try your best to use it without the user having to ask for it first. Use your judgement.
## Bash Tool
Executes a given bash command in a persistent shell session with optional timeout, ensuring proper handling and security measures.
Before executing the command, please follow these steps:
1. Directory Verification:
- If the command will create new directories or files, first use the LS tool to verify the parent directory exists and is the correct location
- For example, before running "mkdir foo/bar", first use LS to check that "foo" exists and is the intended parent directory
2. Command Execution:
- Always quote file paths that contain spaces with double quotes (e.g., cd "path with spaces/file.txt")
- Examples of proper quoting:
- cd "/Users/name/My Documents" (correct)
- cd /Users/name/My Documents (incorrect - will fail)
- python "/path/with spaces/script.py" (correct)
- python /path/with spaces/script.py (incorrect - will fail)
- **PLACEHOLDER HANDLING**: When executing commands that contain placeholder values (e.g., ``, `{variable}`, `[value]`), you MUST first use the Task tool with a general-purpose agent to read the relevant files and gather the necessary information to fill in the placeholder values before executing the command.
- After ensuring proper quoting and placeholder resolution, execute the command.
- Capture the output of the command.
Usage notes:
- The command argument is required.
- You can specify an optional timeout in milliseconds (up to 600000ms / 10 minutes). If not specified, commands will timeout after 120000ms (2 minutes).
- It is very helpful if you write a clear, concise description of what this command does in 5-10 words.
- If the output exceeds 30000 characters, output will be truncated before being returned to you.
- You can use the `run_in_background` parameter to run the command in the background, which allows you to continue working while the command runs. You can monitor the output using the Bash tool as it becomes available. Never use `run_in_background` to run 'sleep' as it will return immediately. You do not need to use '&' at the end of the command when using this parameter.
- VERY IMPORTANT: You MUST avoid using search commands like `find` and `grep`. Instead use Grep, Glob, or Task to search. You MUST avoid read tools like `cat`, `head`, `tail`, and `ls`, and use Read and LS to read files.
- If you _still_ need to run `grep`, STOP. ALWAYS USE ripgrep at `rg` first, which all Claude Code users have pre-installed.
- IMPORTANT: Always use `uv pip` instead of just `pip` when running pip commands. For example, use `uv pip install package_name` instead of `pip install package_name`.
- TESTING MODE: For ML training and inference commands, always use minimal/quick parameters to enable fast testing:
- FIRST: Read and examine the training script/config files to understand which parameters actually control training speed and duration
- Add `--max_steps 10` or `--epochs 1` for training commands
- Add `--batch_size 1` or `--batch_size 2` for memory efficiency
- Add `--eval_steps 5` for quick evaluation
- Use `--fast_dev_run` flag when available (PyTorch Lightning)
- Check for GPU availability with `nvidia-smi` or `python -c "import torch; print(torch.cuda.is_available())"` and adjust device settings accordingly
- Use `--device cuda` or `--gpu` flags when GPU is available, `--device cpu` when not
- Example: `python train.py --epochs 1 --batch_size 2 --max_steps 10 --device cuda`
- When issuing multiple commands, use the ';' or '&&' operator to separate them. DO NOT use newlines (newlines are ok in quoted strings).
- Try to maintain your current working directory throughout the session by using absolute paths and avoiding usage of `cd`. You may use `cd` if the User explicitly requests it.
### Git Commit Guidelines
When the user asks you to create a new git commit, follow these steps carefully:
1. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following bash commands in parallel, each using the Bash tool:
- Run a git status command to see all untracked files.
- Run a git diff command to see both staged and unstaged changes that will be committed.
- Run a git log command to see recent commit messages, so that you can follow this repository's commit message style.
2. Analyze all staged changes (both previously staged and newly added) and draft a commit message:
- Summarize the nature of the changes (eg. new feature, enhancement to an existing feature, bug fix, refactoring, test, docs, etc.). Ensure the message accurately reflects the changes and their purpose (i.e. "add" means a wholly new feature, "update" means an enhancement to an existing feature, "fix" means a bug fix, etc.).
- Check for any sensitive information that shouldn't be committed
- Draft a concise (1-2 sentences) commit message that focuses on the "why" rather than the "what"
- Ensure it accurately reflects the changes and their purpose
3. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following commands in parallel:
- Add relevant untracked files to the staging area.
- Create the commit with a message ending with:
🤖 Generated with [Claude Code](https://claude.ai/code)
Co-Authored-By: Claude
- Run git status to make sure the commit succeeded.
4. If the commit fails due to pre-commit hook changes, retry the commit ONCE to include these automated changes. If it fails again, it usually means a pre-commit hook is preventing the commit. If the commit succeeds but you notice that files were modified by the pre-commit hook, you MUST amend your commit to include them.
Important notes:
- NEVER update the git config
- NEVER run additional commands to read or explore code, besides git bash commands
- NEVER use the TodoWrite or Task tools
- DO NOT push to the remote repository unless the user explicitly asks you to do so
- IMPORTANT: Never use git commands with the -i flag (like git rebase -i or git add -i) since they require interactive input which is not supported.
- If there are no changes to commit (i.e., no untracked files and no modifications), do not create an empty commit
### Creating Pull Requests
Use the gh command via the Bash tool for ALL GitHub-related tasks including working with issues, pull requests, checks, and releases. If given a Github URL use the gh command to get the information needed.
IMPORTANT: When the user asks you to create a pull request, follow these steps carefully:
1. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following bash commands in parallel using the Bash tool, in order to understand the current state of the branch since it diverged from the main branch:
- Run a git status command to see all untracked files
- Run a git diff command to see both staged and unstaged changes that will be committed
- Check if the current branch tracks a remote branch and is up to date with the remote, so you know if you need to push to the remote
- Run a git log command and `git diff [base-branch]...HEAD` to understand the full commit history for the current branch (from the time it diverged from the base branch)
2. Analyze all changes that will be included in the pull request, making sure to look at all relevant commits (NOT just the latest commit, but ALL commits that will be included in the pull request!!!), and draft a pull request summary
3. You have the capability to call multiple tools in a single response. When multiple independent pieces of information are requested, batch your tool calls together for optimal performance. ALWAYS run the following commands in parallel:
- Create new branch if needed
- Push to remote with -u flag if needed
- Create PR using gh pr create with the format below. Use a HEREDOC to pass the body to ensure correct formatting.
Important:
- NEVER update the git config
- DO NOT use the TodoWrite or Task tools
- Return the PR URL when you're done, so the user can see it
## Glob Tool
Fast file pattern matching tool that works with any codebase size
- Supports glob patterns like "**/*.js" or "src/**/*.ts"
- Returns matching file paths sorted by modification time
- Use this tool when you need to find files by name patterns
- When you are doing an open ended search that may require multiple rounds of globbing and grepping, use the Agent tool instead
- You have the capability to call multiple tools in a single response. It is always better to speculatively perform multiple searches as a batch that are potentially useful.
## Grep Tool
A powerful search tool built on ripgrep
Usage:
- ALWAYS use Grep for search tasks. NEVER invoke `grep` or `rg` as a Bash command. The Grep tool has been optimized for correct permissions and access.
- Supports full regex syntax (e.g., "log.*Error", "function\\s+\\w+")
- Filter files with glob parameter (e.g., "*.js", "**/*.tsx") or type parameter (e.g., "js", "py", "rust")
- Output modes: "content" shows matching lines, "files_with_matches" shows only file paths (default), "count" shows match counts
- Use Task tool for open-ended searches requiring multiple rounds
- Pattern syntax: Uses ripgrep (not grep) - literal braces need escaping (use `interface\\{\\}` to find `interface{}` in Go code)
- Multiline matching: By default patterns match within single lines only. For cross-line patterns like `struct \\{[\\s\\S]*?field`, use `multiline: true`
## LS Tool
Lists files and directories in a given path. The path parameter must be an absolute path, not a relative path. You can optionally provide an array of glob patterns to ignore with the ignore parameter. You should generally prefer the Glob and Grep tools, if you know which directories to search.
## ExitPlanMode Tool
Use this tool when you are in plan mode and have finished presenting your plan and are ready to code. This will prompt the user to exit plan mode.
IMPORTANT: Only use this tool when the task requires planning the implementation steps of a task that requires writing code. For research tasks where you're gathering information, searching files, reading files or in general trying to understand the codebase - do NOT use this tool.
## Read Tool
Reads a file from the local filesystem. You can access any file directly by using this tool.
Assume this tool is able to read all files on the machine. If the User provides a path to a file assume that path is valid. It is okay to read a file that does not exist; an error will be returned.
Usage:
- The file_path parameter must be an absolute path, not a relative path
- By default, it reads up to 2000 lines starting from the beginning of the file
- You can optionally specify a line offset and limit (especially handy for long files), but it's recommended to read the whole file by not providing these parameters
- Any lines longer than 2000 characters will be truncated
- Results are returned using cat -n format, with line numbers starting at 1
- This tool allows Claude Code to read images (eg PNG, JPG, etc). When reading an image file the contents are presented visually as Claude Code is a multimodal LLM.
- This tool can read PDF files (.pdf). PDFs are processed page by page, extracting both text and visual content for analysis.
- This tool can read Jupyter notebooks (.ipynb files) and returns all cells with their outputs, combining code, text, and visualizations.
- You have the capability to call multiple tools in a single response. It is always better to speculatively read multiple files as a batch that are potentially useful.
- You will regularly be asked to read screenshots. If the user provides a path to a screenshot ALWAYS use this tool to view the file at the path. This tool will work with all temporary file paths like /var/folders/123/abc/T/TemporaryItems/NSIRD_screencaptureui_ZfB1tD/Screenshot.png
- If you read a file that exists but has empty contents you will receive a system reminder warning in place of file contents.
## Edit Tool
Performs exact string replacements in files.
Usage:
- You must use your `Read` tool at least once in the conversation before editing. This tool will error if you attempt an edit without reading the file.
- When editing text from Read tool output, ensure you preserve the exact indentation (tabs/spaces) as it appears AFTER the line number prefix. The line number prefix format is: spaces + line number + tab. Everything after that tab is the actual file content to match. Never include any part of the line number prefix in the old_string or new_string.
- ALWAYS prefer editing existing files in the codebase. NEVER write new files unless explicitly required.
- Only use emojis if the user explicitly requests it. Avoid adding emojis to files unless asked.
- The edit will FAIL if `old_string` is not unique in the file. Either provide a larger string with more surrounding context to make it unique or use `replace_all` to change every instance of `old_string`.
- Use `replace_all` for replacing and renaming strings across the file. This parameter is useful if you want to rename a variable for instance.
## MultiEdit Tool
This is a tool for making multiple edits to a single file in one operation. It is built on top of the Edit tool and allows you to perform multiple find-and-replace operations efficiently. Prefer this tool over the Edit tool when you need to make multiple edits to the same file.
Before using this tool:
1. Use the Read tool to understand the file's contents and context
2. Verify the directory path is correct
To make multiple file edits, provide the following:
1. file_path: The absolute path to the file to modify (must be absolute, not relative)
2. edits: An array of edit operations to perform, where each edit contains:
- old_string: The text to replace (must match the file contents exactly, including all whitespace and indentation)
- new_string: The edited text to replace the old_string
- replace_all: Replace all occurences of old_string. This parameter is optional and defaults to false.
IMPORTANT:
- All edits are applied in sequence, in the order they are provided
- Each edit operates on the result of the previous edit
- All edits must be valid for the operation to succeed - if any edit fails, none will be applied
- This tool is ideal when you need to make several changes to different parts of the same file
- For Jupyter notebooks (.ipynb files), use the NotebookEdit instead
CRITICAL REQUIREMENTS:
1. All edits follow the same requirements as the single Edit tool
2. The edits are atomic - either all succeed or none are applied
3. Plan your edits carefully to avoid conflicts between sequential operations
WARNING:
- The tool will fail if edits.old_string doesn't match the file contents exactly (including whitespace)
- The tool will fail if edits.old_string and edits.new_string are the same
- Since edits are applied in sequence, ensure that earlier edits don't affect the text that later edits are trying to find
When making edits:
- Ensure all edits result in idiomatic, correct code
- Do not leave the code in a broken state
- Always use absolute file paths (starting with /)
- Only use emojis if the user explicitly requests it. Avoid adding emojis to files unless asked.
- Use replace_all for replacing and renaming strings across the file. This parameter is useful if you want to rename a variable for instance.
If you want to create a new file, use:
- A new file path, including dir name if needed
- First edit: empty old_string and the new file's contents as new_string
- Subsequent edits: normal edit operations on the created content
## Write Tool
Writes a file to the local filesystem.
Usage:
- This tool will overwrite the existing file if there is one at the provided path.
- If this is an existing file, you MUST use the Read tool first to read the file's contents. This tool will fail if you did not read the file first.
- ALWAYS prefer editing existing files in the codebase. NEVER write new files unless explicitly required.
- NEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User.
- Only use emojis if the user explicitly requests it. Avoid writing emojis to files unless asked.
## NotebookEdit Tool
Completely replaces the contents of a specific cell in a Jupyter notebook (.ipynb file) with new source. Jupyter notebooks are interactive documents that combine code, text, and visualizations, commonly used for data analysis and scientific computing. The notebook_path parameter must be an absolute path, not a relative path. The cell_number is 0-indexed. Use edit_mode=insert to add a new cell at the index specified by cell_number. Use edit_mode=delete to delete the cell at the index specified by cell_number.
## WebFetch Tool
- Fetches content from a specified URL and processes it using an AI model
- Takes a URL and a prompt as input
- Fetches the URL content, converts HTML to markdown
- Processes the content with the prompt using a small, fast model
- Returns the model's response about the content
- Use this tool when you need to retrieve and analyze web content
Usage notes:
- IMPORTANT: If an MCP-provided web fetch tool is available, prefer using that tool instead of this one, as it may have fewer restrictions. All MCP-provided tools start with "mcp__".
- The URL must be a fully-formed valid URL
- HTTP URLs will be automatically upgraded to HTTPS
- The prompt should describe what information you want to extract from the page
- This tool is read-only and does not modify any files
- Results may be summarized if the content is very large
- Includes a self-cleaning 15-minute cache for faster responses when repeatedly accessing the same URL
- When a URL redirects to a different host, the tool will inform you and provide the redirect URL in a special format. You should then make a new WebFetch request with the redirect URL to fetch the content.
## TodoWrite Tool
Use this tool to create and manage a structured task list for your current coding session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.
It also helps the user understand the progress of the task and overall progress of their requests.
### When to Use This Tool
Use this tool proactively in these scenarios:
1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions
2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations
3. User explicitly requests todo list - When the user directly asks you to use the todo list
4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)
5. After receiving new instructions - Immediately capture user requirements as todos
6. When you start working on a task - Mark it as in_progress BEFORE beginning work. Ideally you should only have one todo as in_progress at a time
7. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation
### When NOT to Use This Tool
Skip using this tool when:
1. There is only a single, straightforward task
2. The task is trivial and tracking it provides no organizational benefit
3. The task can be completed in less than 3 trivial steps
4. The task is purely conversational or informational
NOTE that you should not use this tool if there is only one trivial task to do. In this case you are better off just doing the task directly.
### Task States and Management
1. **Task States**: Use these states to track progress:
- pending: Task not yet started
- in_progress: Currently working on (limit to ONE task at a time)
- completed: Task finished successfully
2. **Task Management**:
- Update task status in real-time as you work
- Mark tasks complete IMMEDIATELY after finishing (don't batch completions)
- Only have ONE task in_progress at any time
- Complete current tasks before starting new ones
- Remove tasks that are no longer relevant from the list entirely
3. **Task Completion Requirements**:
- ONLY mark a task as completed when you have FULLY accomplished it
- If you encounter errors, blockers, or cannot finish, keep the task as in_progress
- When blocked, create a new task describing what needs to be resolved
- Never mark a task as completed if:
- Tests are failing
- Implementation is partial
- You encountered unresolved errors
- You couldn't find necessary files or dependencies
4. **Task Breakdown**:
- Create specific, actionable items
- Break complex tasks into smaller, manageable steps
- Use clear, descriptive task names
When in doubt, use this tool. Being proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully.
## WebSearch Tool
- Allows Claude to search the web and use the results to inform responses
- Provides up-to-date information for current events and recent data
- Returns search result information formatted as search result blocks
- Use this tool for accessing information beyond Claude's knowledge cutoff
- Searches are performed automatically within a single API call
Usage notes:
- Domain filtering is supported to include or block specific websites
- Web search is only available in the US
- Account for "Today's date" in . For example, if says "Today's date: 2025-07-01", and the user wants the latest docs, do not use 2024 in the search query. Use 2025.
## BashOutput Tool
- Retrieves output from a running or completed background bash shell
- Takes a shell_id parameter identifying the shell
- Always returns only new output since the last check
- Returns stdout and stderr output along with shell status
- Supports optional regex filtering to show only lines matching a pattern
- Use this tool when you need to monitor or check the output of a long-running shell
- Shell IDs can be found using the /bashes command
## KillBash Tool
- Kills a running background bash shell by its ID
- Takes a shell_id parameter identifying the shell to kill
- Returns a success or failure status
- Use this tool when you need to terminate a long-running shell
- Shell IDs can be found using the /bashes command
================================================
FILE: kill_claude/prompts/claude-code-tool-usage-policies.md
================================================
# Claude Code Tool Usage Policies
This document contains specific policies and guidelines for tool usage within Claude Code.
## Tool Usage Hierarchy
### Search Tool Preferences
- When doing file search, prefer to use the Task tool to reduce context usage
- Use Task tool with specialized agents when the task matches the agent's description
- For specific file paths: Use Read or Glob instead of Agent tool for faster results
- For specific class definitions: Use Glob instead of Agent tool
- For code within 2-3 specific files: Use Read instead of Agent tool
### Batch Tool Calls
- You have the capability to call multiple tools in a single response
- When multiple independent pieces of information are requested, batch tool calls together for optimal performance
- For multiple bash commands, MUST send single message with multiple tool calls to run in parallel
- Example: For "git status" and "git diff", send one message with two tool calls
### WebFetch Redirect Handling
- When WebFetch returns redirect message to different host, immediately make new WebFetch request with redirect URL
- Use the redirect URL provided in the response format
## Tool Selection Guidelines
### Read vs Write vs Edit
- ALWAYS prefer editing existing files over creating new ones
- MUST use Read tool before using Write tool on existing files
- Use MultiEdit for multiple changes to same file
- Use Edit for single changes to existing files
### Search Tool Selection
- Use Grep for content searching (NEVER use bash grep/rg commands)
- Use Glob for file pattern matching
- Use Task tool for complex multi-round searches
- Use LS for directory listing with absolute paths
### Bash Tool Constraints
- MUST avoid using search commands like `find` and `grep` - use Grep/Glob/Task instead
- MUST avoid read tools like `cat`, `head`, `tail`, `ls` - use Read and LS instead
- If you still need grep, ALWAYS use ripgrep (`rg`) first
- Use `;` or `&&` operators for multiple commands, NOT newlines
- Maintain working directory with absolute paths, avoid `cd` unless requested
## Specialized Tool Usage
### Git and GitHub Tools
- Use `gh` command via Bash tool for ALL GitHub-related tasks
- Never update git config
- Never use git commands with `-i` flag (interactive mode not supported)
- Use parallel tool calls for git analysis steps
- Use HEREDOC format for commit messages
### Task Tool (Agent Management)
- Launch multiple agents concurrently when possible for performance
- Provide highly detailed task descriptions for autonomous execution
- Specify exactly what information agent should return
- Clearly indicate whether agent should write code or just research
- Agent outputs should generally be trusted
- Agent results not visible to user - provide concise summary
## Tool Communication Protocols
### User Communication
- Output text communicates with user
- All text outside tool use is displayed to user
- Only use tools to complete tasks
- Never use tools like Bash or code comments to communicate with user
### Error Handling
- If tool fails, adapt actions based on error messages
- Determine if you can adjust approach in response to blocked operations
- Ask user to check configuration if repeatedly blocked by hooks
## Performance Optimization
### Context Usage
- Prefer Task tool for file searches to reduce context usage
- Use batch tool calls when requesting multiple independent pieces of information
- Speculatively perform multiple searches that are potentially useful
- Read multiple potentially useful files in batch
### Efficiency Guidelines
- Use most specific tool for the task
- Avoid unnecessary tool switching
- Minimize redundant operations
- Cache information when possible within conversation context
================================================
FILE: kill_claude/tools/__init__.py
================================================
"""Tools package for Claude Code Agent."""
================================================
FILE: kill_claude/tools/bash_output_tool.py
================================================
"""
BashOutput Tool Definition
- Retrieves output from a running or completed background bash shell
- Takes a shell_id parameter identifying the shell
- Always returns only new output since the last check
- Returns stdout and stderr output along with shell status
- Supports optional regex filtering to show only lines matching a pattern
- Use this tool when you need to monitor or check the output of a long-running shell
- Shell IDs can be found using the /bashes command
"""
from typing import Optional
class BashOutputTool:
"""Tool for retrieving output from background bash shells."""
name = "BashOutput"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"bash_id": {
"description": "The ID of the background shell to retrieve output from",
"type": "string"
},
"filter": {
"description": "Optional regular expression to filter the output lines. Only lines matching this regex will be included in the result. Any lines that do not match will no longer be available to read.",
"type": "string"
}
},
"required": ["bash_id"],
"type": "object"
}
def execute(self, bash_id: str, filter: Optional[str] = None):
"""
Retrieve output from a running or completed background bash shell.
Args:
bash_id: The ID of the background shell to retrieve output from
filter: Optional regular expression to filter the output lines. Only lines matching this regex will be included in the result. Any lines that do not match will no longer be available to read.
"""
pass
================================================
FILE: kill_claude/tools/bash_tool.py
================================================
"""
Bash Tool Definition
Executes a given bash command in a persistent shell session with optional timeout,
ensuring proper handling and security measures.
Before executing the command, please follow these steps:
1. Directory Verification:
- If the command will create new directories or files, first use the LS tool to verify the parent directory exists and is the correct location
- For example, before running "mkdir foo/bar", first use LS to check that "foo" exists and is the intended parent directory
2. Command Execution:
- Always quote file paths that contain spaces with double quotes (e.g., cd "path with spaces/file.txt")
- Examples of proper quoting:
- cd "/Users/name/My Documents" (correct)
- cd /Users/name/My Documents (incorrect - will fail)
- python "/path/with spaces/script.py" (correct)
- python /path/with spaces/script.py (incorrect - will fail)
- After ensuring proper quoting, execute the command.
- Capture the output of the command.
Usage notes:
- The command argument is required.
- You can specify an optional timeout in milliseconds (up to 600000ms / 10 minutes). If not specified, commands will timeout after 120000ms (2 minutes).
- It is very helpful if you write a clear, concise description of what this command does in 5-10 words.
- If the output exceeds 30000 characters, output will be truncated before being returned to you.
- You can use the `run_in_background` parameter to run the command in the background, which allows you to continue working while the command runs. You can monitor the output using the Bash tool as it becomes available. Never use `run_in_background` to run 'sleep' as it will return immediately. You do not need to use '&' at the end of the command when using this parameter.
- VERY IMPORTANT: You MUST avoid using search commands like `find` and `grep`. Instead use Grep, Glob, or Task to search. You MUST avoid read tools like `cat`, `head`, `tail`, and `ls`, and use Read and LS to read files.
- If you _still_ need to run `grep`, STOP. ALWAYS USE ripgrep at `rg` first, which all Claude Code users have pre-installed.
- IMPORTANT: Always use `uv pip` instead of just `pip` when running pip commands. For example, use `uv pip install package_name` instead of `pip install package_name`.
- When issuing multiple commands, use the ';' or '&&' operator to separate them. DO NOT use newlines (newlines are ok in quoted strings).
- Try to maintain your current working directory throughout the session by using absolute paths and avoiding usage of `cd`. You may use `cd` if the User explicitly requests it.
"""
from typing import Optional
class BashTool:
"""Tool for executing bash commands in a persistent shell session."""
name = "Bash"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"command": {
"description": "The command to execute",
"type": "string"
},
"description": {
"description": " Clear, concise description of what this command does in 5-10 words. Examples:\nInput: ls\nOutput: Lists files in current directory\n\nInput: git status\nOutput: Shows working tree status\n\nInput: npm install\nOutput: Installs package dependencies\n\nInput: mkdir foo\nOutput: Creates directory 'foo'",
"type": "string"
},
"run_in_background": {
"description": "Set to true to run this command in the background. Use BashOutput to read the output later.",
"type": "boolean"
},
"timeout": {
"description": "Optional timeout in milliseconds (max 600000)",
"type": "number"
}
},
"required": ["command"],
"type": "object"
}
def execute(self, command: str, description: Optional[str] = None, run_in_background: Optional[bool] = False, timeout: Optional[int] = None):
"""
Execute a bash command in a persistent shell session.
Args:
command: The command to execute
description: Clear, concise description of what this command does in 5-10 words
run_in_background: Set to true to run this command in the background
timeout: Optional timeout in milliseconds (max 600000)
"""
pass
================================================
FILE: kill_claude/tools/edit_tool.py
================================================
"""
Edit Tool Definition
Performs exact string replacements in files.
Usage:
- You must use your `Read` tool at least once in the conversation before editing. This tool will error if you attempt an edit without reading the file.
- When editing text from Read tool output, ensure you preserve the exact indentation (tabs/spaces) as it appears AFTER the line number prefix. The line number prefix format is: spaces + line number + tab. Everything after that tab is the actual file content to match. Never include any part of the line number prefix in the old_string or new_string.
- ALWAYS prefer editing existing files in the codebase. NEVER write new files unless explicitly required.
- Only use emojis if the user explicitly requests it. Avoid adding emojis to files unless asked.
- The edit will FAIL if `old_string` is not unique in the file. Either provide a larger string with more surrounding context to make it unique or use `replace_all` to change every instance of `old_string`.
- Use `replace_all` for replacing and renaming strings across the file. This parameter is useful if you want to rename a variable for instance.
"""
from typing import Optional
class EditTool:
"""Tool for performing exact string replacements in files."""
name = "Edit"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"file_path": {
"description": "The absolute path to the file to modify",
"type": "string"
},
"new_string": {
"description": "The text to replace it with (must be different from old_string)",
"type": "string"
},
"old_string": {
"description": "The text to replace",
"type": "string"
},
"replace_all": {
"default": False,
"description": "Replace all occurences of old_string (default false)",
"type": "boolean"
}
},
"required": ["file_path", "old_string", "new_string"],
"type": "object"
}
def execute(self, file_path: str, old_string: str, new_string: str, replace_all: Optional[bool] = False):
"""
Perform exact string replacement in a file.
Args:
file_path: The absolute path to the file to modify
old_string: The text to replace
new_string: The text to replace it with (must be different from old_string)
replace_all: Replace all occurences of old_string (default false)
"""
pass
================================================
FILE: kill_claude/tools/exit_plan_mode_tool.py
================================================
"""
ExitPlanMode Tool Definition
Use this tool when you are in plan mode and have finished presenting your plan and are ready to code.
This will prompt the user to exit plan mode.
IMPORTANT: Only use this tool when the task requires planning the implementation steps of a task that requires writing code.
For research tasks where you're gathering information, searching files, reading files or in general trying to understand the codebase - do NOT use this tool.
Examples:
1. Initial task: "Search for and understand the implementation of vim mode in the codebase" - Do not use the exit plan mode tool because you are not planning the implementation steps of a task.
2. Initial task: "Help me implement yank mode for vim" - Use the exit plan mode tool after you have finished planning the implementation steps of the task.
"""
class ExitPlanModeTool:
"""Tool for exiting plan mode after presenting implementation plan."""
name = "ExitPlanMode"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"plan": {
"description": "The plan you came up with, that you want to run by the user for approval. Supports markdown. The plan should be pretty concise.",
"type": "string"
}
},
"required": ["plan"],
"type": "object"
}
def execute(self, plan: str):
"""
Exit plan mode after presenting the implementation plan.
Args:
plan: The plan you came up with, that you want to run by the user for approval. Supports markdown. The plan should be pretty concise.
"""
pass
================================================
FILE: kill_claude/tools/glob_tool.py
================================================
"""
Glob Tool Definition
Fast file pattern matching tool that works with any codebase size
- Supports glob patterns like "**/*.js" or "src/**/*.ts"
- Returns matching file paths sorted by modification time
- Use this tool when you need to find files by name patterns
- When you are doing an open ended search that may require multiple rounds of globbing and grepping, use the Agent tool instead
- You have the capability to call multiple tools in a single response. It is always better to speculatively perform multiple searches as a batch that are potentially useful.
"""
from typing import Optional
class GlobTool:
"""Tool for fast file pattern matching using glob patterns."""
name = "Glob"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"path": {
"description": "The directory to search in. If not specified, the current working directory will be used. IMPORTANT: Omit this field to use the default directory. DO NOT enter \"undefined\" or \"null\" - simply omit it for the default behavior. Must be a valid directory path if provided.",
"type": "string"
},
"pattern": {
"description": "The glob pattern to match files against",
"type": "string"
}
},
"required": ["pattern"],
"type": "object"
}
def execute(self, pattern: str, path: Optional[str] = None):
"""
Find files matching a glob pattern.
Args:
pattern: The glob pattern to match files against
path: The directory to search in. If not specified, the current working directory will be used.
"""
pass
================================================
FILE: kill_claude/tools/grep_tool.py
================================================
"""
Grep Tool Definition
A powerful search tool built on ripgrep
Usage:
- ALWAYS use Grep for search tasks. NEVER invoke `grep` or `rg` as a Bash command. The Grep tool has been optimized for correct permissions and access.
- Supports full regex syntax (e.g., "log.*Error", "function\\s+\\w+")
- Filter files with glob parameter (e.g., "*.js", "**/*.tsx") or type parameter (e.g., "js", "py", "rust")
- Output modes: "content" shows matching lines, "files_with_matches" shows only file paths (default), "count" shows match counts
- Use Task tool for open-ended searches requiring multiple rounds
- Pattern syntax: Uses ripgrep (not grep) - literal braces need escaping (use `interface\\{\\}` to find `interface{}` in Go code)
- Multiline matching: By default patterns match within single lines only. For cross-line patterns like `struct \\{[\\s\\S]*?field`, use `multiline: true`
"""
from typing import Optional, Literal
class GrepTool:
"""Tool for searching file contents using ripgrep."""
name = "Grep"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"-A": {
"description": "Number of lines to show after each match (rg -A). Requires output_mode: \"content\", ignored otherwise.",
"type": "number"
},
"-B": {
"description": "Number of lines to show before each match (rg -B). Requires output_mode: \"content\", ignored otherwise.",
"type": "number"
},
"-C": {
"description": "Number of lines to show before and after each match (rg -C). Requires output_mode: \"content\", ignored otherwise.",
"type": "number"
},
"-i": {
"description": "Case insensitive search (rg -i)",
"type": "boolean"
},
"-n": {
"description": "Show line numbers in output (rg -n). Requires output_mode: \"content\", ignored otherwise.",
"type": "boolean"
},
"glob": {
"description": "Glob pattern to filter files (e.g. \"*.js\", \"*.{ts,tsx}\") - maps to rg --glob",
"type": "string"
},
"head_limit": {
"description": "Limit output to first N lines/entries, equivalent to \"| head -N\". Works across all output modes: content (limits output lines), files_with_matches (limits file paths), count (limits count entries). When unspecified, shows all results from ripgrep.",
"type": "number"
},
"multiline": {
"description": "Enable multiline mode where . matches newlines and patterns can span lines (rg -U --multiline-dotall). Default: false.",
"type": "boolean"
},
"output_mode": {
"description": "Output mode: \"content\" shows matching lines (supports -A/-B/-C context, -n line numbers, head_limit), \"files_with_matches\" shows file paths (supports head_limit), \"count\" shows match counts (supports head_limit). Defaults to \"files_with_matches\".",
"enum": ["content", "files_with_matches", "count"],
"type": "string"
},
"path": {
"description": "File or directory to search in (rg PATH). Defaults to current working directory.",
"type": "string"
},
"pattern": {
"description": "The regular expression pattern to search for in file contents",
"type": "string"
},
"type": {
"description": "File type to search (rg --type). Common types: js, py, rust, go, java, etc. More efficient than include for standard file types.",
"type": "string"
}
},
"required": ["pattern"],
"type": "object"
}
def execute(self, pattern: str, path: Optional[str] = None, output_mode: Optional[Literal["content", "files_with_matches", "count"]] = "files_with_matches",
glob: Optional[str] = None, type: Optional[str] = None, multiline: Optional[bool] = False,
case_insensitive: Optional[bool] = False, line_numbers: Optional[bool] = False,
lines_after: Optional[int] = None, lines_before: Optional[int] = None, lines_context: Optional[int] = None,
head_limit: Optional[int] = None):
"""
Search for patterns in file contents using ripgrep.
Args:
pattern: The regular expression pattern to search for in file contents
path: File or directory to search in. Defaults to current working directory.
output_mode: Output mode - "content", "files_with_matches", or "count"
glob: Glob pattern to filter files (e.g. "*.js", "*.{ts,tsx}")
type: File type to search (e.g. "js", "py", "rust", "go", "java")
multiline: Enable multiline mode where . matches newlines
case_insensitive: Case insensitive search
line_numbers: Show line numbers in output (content mode only)
lines_after: Number of lines to show after each match (content mode only)
lines_before: Number of lines to show before each match (content mode only)
lines_context: Number of lines to show before and after each match (content mode only)
head_limit: Limit output to first N lines/entries
"""
pass
================================================
FILE: kill_claude/tools/kill_bash_tool.py
================================================
"""
KillBash Tool Definition
- Kills a running background bash shell by its ID
- Takes a shell_id parameter identifying the shell to kill
- Returns a success or failure status
- Use this tool when you need to terminate a long-running shell
- Shell IDs can be found using the /bashes command
"""
class KillBashTool:
"""Tool for killing running background bash shells."""
name = "KillBash"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"shell_id": {
"description": "The ID of the background shell to kill",
"type": "string"
}
},
"required": ["shell_id"],
"type": "object"
}
def execute(self, shell_id: str):
"""
Kill a running background bash shell by its ID.
Args:
shell_id: The ID of the background shell to kill
"""
pass
================================================
FILE: kill_claude/tools/ls_tool.py
================================================
"""
LS Tool Definition
Lists files and directories in a given path. The path parameter must be an absolute path, not a relative path.
You can optionally provide an array of glob patterns to ignore with the ignore parameter.
You should generally prefer the Glob and Grep tools, if you know which directories to search.
"""
from typing import List, Optional
class LSTool:
"""Tool for listing files and directories."""
name = "LS"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"ignore": {
"description": "List of glob patterns to ignore",
"items": {"type": "string"},
"type": "array"
},
"path": {
"description": "The absolute path to the directory to list (must be absolute, not relative)",
"type": "string"
}
},
"required": ["path"],
"type": "object"
}
def execute(self, path: str, ignore: Optional[List[str]] = None):
"""
List files and directories in a given path.
Args:
path: The absolute path to the directory to list (must be absolute, not relative)
ignore: List of glob patterns to ignore
"""
pass
================================================
FILE: kill_claude/tools/multiedit_tool.py
================================================
"""
MultiEdit Tool Definition
This is a tool for making multiple edits to a single file in one operation. It is built on top of the Edit tool and allows you to perform multiple find-and-replace operations efficiently. Prefer this tool over the Edit tool when you need to make multiple edits to the same file.
Before using this tool:
1. Use the Read tool to understand the file's contents and context
2. Verify the directory path is correct
To make multiple file edits, provide the following:
1. file_path: The absolute path to the file to modify (must be absolute, not relative)
2. edits: An array of edit operations to perform, where each edit contains:
- old_string: The text to replace (must match the file contents exactly, including all whitespace and indentation)
- new_string: The edited text to replace the old_string
- replace_all: Replace all occurences of old_string. This parameter is optional and defaults to false.
IMPORTANT:
- All edits are applied in sequence, in the order they are provided
- Each edit operates on the result of the previous edit
- All edits must be valid for the operation to succeed - if any edit fails, none will be applied
- This tool is ideal when you need to make several changes to different parts of the same file
- For Jupyter notebooks (.ipynb files), use the NotebookEdit instead
CRITICAL REQUIREMENTS:
1. All edits follow the same requirements as the single Edit tool
2. The edits are atomic - either all succeed or none are applied
3. Plan your edits carefully to avoid conflicts between sequential operations
WARNING:
- The tool will fail if edits.old_string doesn't match the file contents exactly (including whitespace)
- The tool will fail if edits.old_string and edits.new_string are the same
- Since edits are applied in sequence, ensure that earlier edits don't affect the text that later edits are trying to find
When making edits:
- Ensure all edits result in idiomatic, correct code
- Do not leave the code in a broken state
- Always use absolute file paths (starting with /)
- Only use emojis if the user explicitly requests it. Avoid adding emojis to files unless asked.
- Use replace_all for replacing and renaming strings across the file. This parameter is useful if you want to rename a variable for instance.
If you want to create a new file, use:
- A new file path, including dir name if needed
- First edit: empty old_string and the new file's contents as new_string
- Subsequent edits: normal edit operations on the created content
"""
from typing import List, Optional
class EditOperation:
"""Represents a single edit operation."""
def __init__(self, old_string: str, new_string: str, replace_all: Optional[bool] = False):
self.old_string = old_string
self.new_string = new_string
self.replace_all = replace_all
class MultiEditTool:
"""Tool for making multiple edits to a single file in one operation."""
name = "MultiEdit"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"edits": {
"description": "Array of edit operations to perform sequentially on the file",
"items": {
"additionalProperties": False,
"properties": {
"new_string": {
"description": "The text to replace it with",
"type": "string"
},
"old_string": {
"description": "The text to replace",
"type": "string"
},
"replace_all": {
"default": False,
"description": "Replace all occurences of old_string (default false).",
"type": "boolean"
}
},
"required": ["old_string", "new_string"],
"type": "object"
},
"minItems": 1,
"type": "array"
},
"file_path": {
"description": "The absolute path to the file to modify",
"type": "string"
}
},
"required": ["file_path", "edits"],
"type": "object"
}
def execute(self, file_path: str, edits: List[dict]):
"""
Make multiple edits to a single file in one operation.
Args:
file_path: The absolute path to the file to modify
edits: Array of edit operations to perform sequentially on the file
Each edit should contain: old_string, new_string, and optionally replace_all
"""
pass
================================================
FILE: kill_claude/tools/notebook_edit_tool.py
================================================
"""
NotebookEdit Tool Definition
Completely replaces the contents of a specific cell in a Jupyter notebook (.ipynb file) with new source.
Jupyter notebooks are interactive documents that combine code, text, and visualizations, commonly used for data analysis and scientific computing.
The notebook_path parameter must be an absolute path, not a relative path.
The cell_number is 0-indexed. Use edit_mode=insert to add a new cell at the index specified by cell_number.
Use edit_mode=delete to delete the cell at the index specified by cell_number.
"""
from typing import Optional, Literal
class NotebookEditTool:
"""Tool for editing Jupyter notebook cells."""
name = "NotebookEdit"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"cell_id": {
"description": "The ID of the cell to edit. When inserting a new cell, the new cell will be inserted after the cell with this ID, or at the beginning if not specified.",
"type": "string"
},
"cell_type": {
"description": "The type of the cell (code or markdown). If not specified, it defaults to the current cell type. If using edit_mode=insert, this is required.",
"enum": ["code", "markdown"],
"type": "string"
},
"edit_mode": {
"description": "The type of edit to make (replace, insert, delete). Defaults to replace.",
"enum": ["replace", "insert", "delete"],
"type": "string"
},
"new_source": {
"description": "The new source for the cell",
"type": "string"
},
"notebook_path": {
"description": "The absolute path to the Jupyter notebook file to edit (must be absolute, not relative)",
"type": "string"
}
},
"required": ["notebook_path", "new_source"],
"type": "object"
}
def execute(self, notebook_path: str, new_source: str, cell_id: Optional[str] = None,
cell_type: Optional[Literal["code", "markdown"]] = None,
edit_mode: Optional[Literal["replace", "insert", "delete"]] = "replace"):
"""
Edit a Jupyter notebook cell.
Args:
notebook_path: The absolute path to the Jupyter notebook file to edit (must be absolute, not relative)
new_source: The new source for the cell
cell_id: The ID of the cell to edit. When inserting a new cell, the new cell will be inserted after the cell with this ID, or at the beginning if not specified.
cell_type: The type of the cell (code or markdown). If not specified, it defaults to the current cell type. If using edit_mode=insert, this is required.
edit_mode: The type of edit to make (replace, insert, delete). Defaults to replace.
"""
pass
================================================
FILE: kill_claude/tools/read_tool.py
================================================
"""
Read Tool Definition
Reads a file from the local filesystem. You can access any file directly by using this tool.
Assume this tool is able to read all files on the machine. If the User provides a path to a file assume that path is valid.
It is okay to read a file that does not exist; an error will be returned.
Usage:
- The file_path parameter must be an absolute path, not a relative path
- By default, it reads up to 2000 lines starting from the beginning of the file
- You can optionally specify a line offset and limit (especially handy for long files), but it's recommended to read the whole file by not providing these parameters
- Any lines longer than 2000 characters will be truncated
- Results are returned using cat -n format, with line numbers starting at 1
- This tool allows Claude Code to read images (eg PNG, JPG, etc). When reading an image file the contents are presented visually as Claude Code is a multimodal LLM.
- This tool can read PDF files (.pdf). PDFs are processed page by page, extracting both text and visual content for analysis.
- This tool can read Jupyter notebooks (.ipynb files) and returns all cells with their outputs, combining code, text, and visualizations.
- You have the capability to call multiple tools in a single response. It is always better to speculatively read multiple files as a batch that are potentially useful.
- You will regularly be asked to read screenshots. If the user provides a path to a screenshot ALWAYS use this tool to view the file at the path. This tool will work with all temporary file paths like /var/folders/123/abc/T/TemporaryItems/NSIRD_screencaptureui_ZfB1tD/Screenshot.png
- If you read a file that exists but has empty contents you will receive a system reminder warning in place of file contents.
"""
from typing import Optional
class ReadTool:
"""Tool for reading files from the local filesystem."""
name = "Read"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"file_path": {
"description": "The absolute path to the file to read",
"type": "string"
},
"limit": {
"description": "The number of lines to read. Only provide if the file is too large to read at once.",
"type": "number"
},
"offset": {
"description": "The line number to start reading from. Only provide if the file is too large to read at once",
"type": "number"
}
},
"required": ["file_path"],
"type": "object"
}
def execute(self, file_path: str, offset: Optional[int] = None, limit: Optional[int] = None):
"""
Read a file from the local filesystem.
Args:
file_path: The absolute path to the file to read
offset: The line number to start reading from. Only provide if the file is too large to read at once
limit: The number of lines to read. Only provide if the file is too large to read at once.
"""
pass
================================================
FILE: kill_claude/tools/task_tool.py
================================================
"""
Task Tool Definition
Launch a new agent to handle complex, multi-step tasks autonomously.
Available agent types and the tools they have access to:
- general-purpose: General-purpose agent for researching complex questions, searching for code, and executing multi-step tasks. When you are searching for a keyword or file and are not confident that you will find the right match in the first few tries use this agent to perform the search for you. (Tools: *)
- statusline-setup: Use this agent to configure the user's Claude Code status line setting. (Tools: Read, Edit)
- output-style-setup: Use this agent to create a Claude Code output style. (Tools: Read, Write, Edit, Glob, LS)
When using the Task tool, you must specify a subagent_type parameter to select which agent type to use.
When NOT to use the Agent tool:
- If you want to read a specific file path, use the Read or Glob tool instead of the Agent tool, to find the match more quickly
- If you are searching for a specific class definition like "class Foo", use the Glob tool instead, to find the match more quickly
- If you are searching for code within a specific file or set of 2-3 files, use the Read tool instead of the Agent tool, to find the match more quickly
- Other tasks that are not related to the agent descriptions above
Usage notes:
1. Launch multiple agents concurrently whenever possible, to maximize performance; to do that, use a single message with multiple tool uses
2. When the agent is done, it will return a single message back to you. The result returned by the agent is not visible to the user. To show the user the result, you should send a text message back to the user with a concise summary of the result.
3. Each agent invocation is stateless. You will not be able to send additional messages to the agent, nor will the agent be able to communicate with you outside of its final report. Therefore, your prompt should contain a highly detailed task description for the agent to perform autonomously and you should specify exactly what information the agent should return back to you in its final and only message to you.
4. The agent's outputs should generally be trusted
5. Clearly tell the agent whether you expect it to write code or just to do research (search, file reads, web fetches, etc.), since it is not aware of the user's intent
6. If the agent description mentions that it should be used proactively, then you should try your best to use it without the user having to ask for it first. Use your judgement.
"""
from typing import Literal
class TaskTool:
"""Tool for launching specialized agents to handle complex tasks."""
name = "Task"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"description": {
"description": "A short (3-5 word) description of the task",
"type": "string"
},
"prompt": {
"description": "The task for the agent to perform",
"type": "string"
},
"subagent_type": {
"description": "The type of specialized agent to use for this task",
"type": "string"
}
},
"required": ["description", "prompt", "subagent_type"],
"type": "object"
}
def execute(self, description: str, prompt: str, subagent_type: Literal["general-purpose", "statusline-setup", "output-style-setup"]):
"""
Launch a new agent to handle complex, multi-step tasks autonomously.
Args:
description: A short (3-5 word) description of the task
prompt: The task for the agent to perform
subagent_type: The type of specialized agent to use for this task
"""
pass
================================================
FILE: kill_claude/tools/todo_write_tool.py
================================================
"""
TodoWrite Tool Definition
Use this tool to create and manage a structured task list for your current coding session. This helps you track progress, organize complex tasks, and demonstrate thoroughness to the user.
It also helps the user understand the progress of the task and overall progress of their requests.
When to Use This Tool
Use this tool proactively in these scenarios:
1. Complex multi-step tasks - When a task requires 3 or more distinct steps or actions
2. Non-trivial and complex tasks - Tasks that require careful planning or multiple operations
3. User explicitly requests todo list - When the user directly asks you to use the todo list
4. User provides multiple tasks - When users provide a list of things to be done (numbered or comma-separated)
5. After receiving new instructions - Immediately capture user requirements as todos
6. When you start working on a task - Mark it as in_progress BEFORE beginning work. Ideally you should only have one todo as in_progress at a time
7. After completing a task - Mark it as completed and add any new follow-up tasks discovered during implementation
When NOT to Use This Tool
Skip using this tool when:
1. There is only a single, straightforward task
2. The task is trivial and tracking it provides no organizational benefit
3. The task can be completed in less than 3 trivial steps
4. The task is purely conversational or informational
NOTE that you should not use this tool if there is only one trivial task to do. In this case you are better off just doing the task directly.
Task States and Management
1. Task States: Use these states to track progress:
- pending: Task not yet started
- in_progress: Currently working on (limit to ONE task at a time)
- completed: Task finished successfully
2. Task Management:
- Update task status in real-time as you work
- Mark tasks complete IMMEDIATELY after finishing (don't batch completions)
- Only have ONE task in_progress at any time
- Complete current tasks before starting new ones
- Remove tasks that are no longer relevant from the list entirely
3. Task Completion Requirements:
- ONLY mark a task as completed when you have FULLY accomplished it
- If you encounter errors, blockers, or cannot finish, keep the task as in_progress
- When blocked, create a new task describing what needs to be resolved
- Never mark a task as completed if:
- Tests are failing
- Implementation is partial
- You encountered unresolved errors
- You couldn't find necessary files or dependencies
4. Task Breakdown:
- Create specific, actionable items
- Break complex tasks into smaller, manageable steps
- Use clear, descriptive task names
When in doubt, use this tool. Being proactive with task management demonstrates attentiveness and ensures you complete all requirements successfully.
"""
from typing import List, Literal
class TodoItem:
"""Represents a single todo item."""
def __init__(self, content: str, status: Literal["pending", "in_progress", "completed"], id: str):
self.content = content
self.status = status
self.id = id
class TodoWriteTool:
"""Tool for creating and managing a structured task list."""
name = "TodoWrite"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"todos": {
"description": "The updated todo list",
"items": {
"additionalProperties": False,
"properties": {
"content": {
"minLength": 1,
"type": "string"
},
"id": {
"type": "string"
},
"status": {
"enum": ["pending", "in_progress", "completed"],
"type": "string"
}
},
"required": ["content", "status", "id"],
"type": "object"
},
"type": "array"
}
},
"required": ["todos"],
"type": "object"
}
def execute(self, todos: List[dict]):
"""
Create and manage a structured task list.
Args:
todos: The updated todo list, each item should contain content, status, and id
"""
pass
================================================
FILE: kill_claude/tools/web_fetch_tool.py
================================================
"""
WebFetch Tool Definition
- Fetches content from a specified URL and processes it using an AI model
- Takes a URL and a prompt as input
- Fetches the URL content, converts HTML to markdown
- Processes the content with the prompt using a small, fast model
- Returns the model's response about the content
- Use this tool when you need to retrieve and analyze web content
Usage notes:
- IMPORTANT: If an MCP-provided web fetch tool is available, prefer using that tool instead of this one, as it may have fewer restrictions. All MCP-provided tools start with "mcp__".
- The URL must be a fully-formed valid URL
- HTTP URLs will be automatically upgraded to HTTPS
- The prompt should describe what information you want to extract from the page
- This tool is read-only and does not modify any files
- Results may be summarized if the content is very large
- Includes a self-cleaning 15-minute cache for faster responses when repeatedly accessing the same URL
- When a URL redirects to a different host, the tool will inform you and provide the redirect URL in a special format. You should then make a new WebFetch request with the redirect URL to fetch the content.
"""
class WebFetchTool:
"""Tool for fetching and analyzing web content."""
name = "WebFetch"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"prompt": {
"description": "The prompt to run on the fetched content",
"type": "string"
},
"url": {
"description": "The URL to fetch content from",
"format": "uri",
"type": "string"
}
},
"required": ["url", "prompt"],
"type": "object"
}
def execute(self, url: str, prompt: str):
"""
Fetch content from a URL and process it using an AI model.
Args:
url: The URL to fetch content from
prompt: The prompt to run on the fetched content
"""
pass
================================================
FILE: kill_claude/tools/web_search_tool.py
================================================
"""
WebSearch Tool Definition
- Allows Claude to search the web and use the results to inform responses
- Provides up-to-date information for current events and recent data
- Returns search result information formatted as search result blocks
- Use this tool for accessing information beyond Claude's knowledge cutoff
- Searches are performed automatically within a single API call
Usage notes:
- Domain filtering is supported to include or block specific websites
- Web search is only available in the US
- Account for "Today's date" in . For example, if says "Today's date: 2025-07-01", and the user wants the latest docs, do not use 2024 in the search query. Use 2025.
"""
from typing import List, Optional
class WebSearchTool:
"""Tool for searching the web and accessing up-to-date information."""
name = "WebSearch"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"allowed_domains": {
"description": "Only include search results from these domains",
"items": {"type": "string"},
"type": "array"
},
"blocked_domains": {
"description": "Never include search results from these domains",
"items": {"type": "string"},
"type": "array"
},
"query": {
"description": "The search query to use",
"minLength": 2,
"type": "string"
}
},
"required": ["query"],
"type": "object"
}
def execute(self, query: str, allowed_domains: Optional[List[str]] = None, blocked_domains: Optional[List[str]] = None):
"""
Search the web for information.
Args:
query: The search query to use
allowed_domains: Only include search results from these domains
blocked_domains: Never include search results from these domains
"""
pass
================================================
FILE: kill_claude/tools/write_tool.py
================================================
"""
Write Tool Definition
Writes a file to the local filesystem.
Usage:
- This tool will overwrite the existing file if there is one at the provided path.
- If this is an existing file, you MUST use the Read tool first to read the file's contents. This tool will fail if you did not read the file first.
- ALWAYS prefer editing existing files in the codebase. NEVER write new files unless explicitly required.
- NEVER proactively create documentation files (*.md) or README files. Only create documentation files if explicitly requested by the User.
- Only use emojis if the user explicitly requests it. Avoid writing emojis to files unless asked.
"""
class WriteTool:
"""Tool for writing files to the local filesystem."""
name = "Write"
@staticmethod
def schema():
return {
"$schema": "http://json-schema.org/draft-07/schema#",
"additionalProperties": False,
"properties": {
"content": {
"description": "The content to write to the file",
"type": "string"
},
"file_path": {
"description": "The absolute path to the file to write (must be absolute, not relative)",
"type": "string"
}
},
"required": ["file_path", "content"],
"type": "object"
}
def execute(self, file_path: str, content: str):
"""
Write a file to the local filesystem.
Args:
file_path: The absolute path to the file to write (must be absolute, not relative)
content: The content to write to the file
"""
pass
================================================
FILE: kill_claude/.claude/settings.local.json
================================================
{
"permissions": {
"allow": [
"Bash(python test:*)",
"Bash(python:*)"
],
"defaultMode": "acceptEdits"
}
}
================================================
FILE: lib/dependencies.js
================================================
const { promisify } = require('util');
const { exec } = require('child_process');
const which = require('which');
const chalk = require('chalk');
const execAsync = promisify(exec);
/**
* Check if a command is available in the system
* @param {string} command - Command to check
* @returns {Promise} - True if command exists
*/
async function commandExists(command) {
try {
await which(command);
return true;
} catch (error) {
return false;
}
}
/**
* Check Python version
* @returns {Promise<{exists: boolean, version: string|null}>}
*/
async function checkPython() {
try {
const { stdout } = await execAsync('python --version');
const version = stdout.trim().split(' ')[1];
return { exists: true, version };
} catch (error) {
try {
const { stdout } = await execAsync('python3 --version');
const version = stdout.trim().split(' ')[1];
return { exists: true, version };
} catch (error) {
return { exists: false, version: null };
}
}
}
/**
* Check if Modal is installed
* @returns {Promise}
*/
async function checkModal() {
try {
await execAsync('modal --version');
return true;
} catch (error) {
return false;
}
}
/**
* Check if Git is installed
* @returns {Promise}
*/
async function checkGit() {
try {
await execAsync('git --version');
return true;
} catch (error) {
return false;
}
}
async function checkGitingest() {
try {
await execAsync('gitingest --help');
return true;
} catch (error) {
return false;
}
}
/**
* Check all required dependencies
* @returns {Promise} - True if all dependencies are met
*/
async function checkDependencies() {
const pythonCheck = await checkPython();
const modalExists = await checkModal();
const gitExists = await checkGit();
const gitingestExists = await checkGitingest();
let allDependenciesMet = true;
console.log('\n--- Dependency Check ---');
if (pythonCheck.exists) {
console.log(`${chalk.green('✓')} Python ${pythonCheck.version} found`);
} else {
console.log(`${chalk.red('✗')} Python not found. Please install Python 3.8 or newer.`);
allDependenciesMet = false;
}
if (modalExists) {
console.log(`${chalk.green('✓')} Modal CLI found`);
} else {
console.log(`${chalk.red('✗')} Modal CLI not found. Please install it with: pip install modal`);
allDependenciesMet = false;
}
if (gitingestExists) {
console.log(`${chalk.green('✓')} Gitingest CLI found`);
} else {
console.log(`${chalk.red('✗')} Gitingest CLI not found. Please install it with: pip install gitingest`);
allDependenciesMet = false;
}
if (gitExists) {
console.log(`${chalk.green('✓')} Git found`);
} else {
console.log(`${chalk.red('✗')} Git not found. Please install Git.`);
allDependenciesMet = false;
}
console.log('------------------------\n');
return allDependenciesMet;
}
module.exports = {
checkDependencies,
commandExists,
checkPython,
checkModal,
checkGit
};
================================================
FILE: lib/sandbox.js
================================================
const path = require('path');
const fs = require('fs-extra');
const { spawn } = require('child_process');
const chalk = require('chalk');
const ora = require('ora');
const { promisify } = require('util');
const { exec } = require('child_process');
const os = require('os');
const execAsync = promisify(exec);
/**
* Get the path to the Python script
* @returns {string} - Path to the Python script
*/
function getPythonScriptPath() {
// First check if the script exists in the package directory
const packageScriptPath = path.join(__dirname, '..', 'python', 'test_modalSandboxScript.py');
if (fs.existsSync(packageScriptPath)) {
return packageScriptPath;
}
// If not found, return the path where it will be copied during installation
return packageScriptPath;
}
/**
* Run the container with the given options
* @param {Object} options - Container options
* @param {string} options.repoUrl - GitHub repository URL
* @param {string} options.gpuType - GPU type
* @param {number} options.gpuCount - Number of GPUs (default: 1)
* @param {string} options.volumeName - Volume name
* @param {Array} options.setupCommands - Setup commands
* @param {boolean} options.showExamples - Whether to show usage examples
* @returns {Promise}
*/
async function runContainer(options) {
const {
repoUrl,
gpuType,
gpuCount = 1,
volumeName,
setupCommands = [],
showExamples = false,
yes = false,
userId,
userName,
userEmail
} = options;
// Get the path to the Python script
const scriptPath = getPythonScriptPath();
// Check if the script exists
if (!fs.existsSync(scriptPath)) {
throw new Error(`Python script not found at ${scriptPath}. Please reinstall the package.`);
}
// Prepare command arguments
const args = [
scriptPath
];
// If show examples is true, only pass that flag
if (showExamples) {
args.push('--show-examples');
// Log the command being executed
// console.log(chalk.dim(`\nExecuting: python ${args.join(' ')}`));
// Run the Python script with show examples flag
const pythonExecutable = process.env.PYTHON_EXECUTABLE || 'python';
const pythonProcess = spawn(pythonExecutable, ['-u', ...args], {
stdio: 'inherit', // Inherit stdio to show real-time output
env: { ...process.env, PYTHONUNBUFFERED: '1' } // Force unbuffered output
});
return new Promise((resolve, reject) => {
pythonProcess.on('close', (code) => {
if (code === 0) {
resolve();
} else {
reject(new Error(`Process exited with code ${code}`));
}
});
pythonProcess.on('error', (error) => {
reject(error);
});
});
}
// Add normal arguments
if (gpuType) args.push('--gpu', gpuType);
if (gpuCount && gpuCount > 1) args.push('--gpu-count', gpuCount.toString());
if (repoUrl) args.push('--repo-url', repoUrl);
if (volumeName) {
args.push('--volume-name', volumeName);
}
// Repository setup is now handled by Agent when --repo-url is provided
// Add --yes flag to skip confirmation prompts
if (yes) {
args.push('--yes');
console.log(chalk.gray(`🔍 Debug: Adding --yes flag to Python script`));
}
// Add user credentials if provided
if (userId && userEmail && userName) {
args.push('--user-id', userEmail);
args.push('--user-name', userId);
args.push('--display-name', userName);
// console.log(chalk.gray(`🔍 Debug: Passing user credentials to Python script`));
}
// Handle manual setup commands if provided
if (setupCommands.length > 0) {
// Create a temporary file to store setup commands
const tempCommandsFile = path.join(os.tmpdir(), `gitarsenal-commands-${Date.now()}.txt`);
fs.writeFileSync(tempCommandsFile, setupCommands.join('\n'));
args.push('--commands-file', tempCommandsFile);
}
// Log the command being executed
// console.log(chalk.dim(`\nExecuting: python ${args.join(' ')}`));
// console.log(chalk.gray(`🔍 Debug: yes parameter = ${yes}`));
// Run the Python script without spinner to avoid terminal interference
console.log(chalk.dim('Launching container...'));
try {
// Run the Python script
const pythonExecutable = process.env.PYTHON_EXECUTABLE || 'python';
const pythonProcess = spawn(pythonExecutable, ['-u', ...args], {
stdio: 'inherit', // Inherit stdio to show real-time output
env: { ...process.env, PYTHONUNBUFFERED: '1' } // Force unbuffered output
});
// Handle process completion
return new Promise((resolve, reject) => {
pythonProcess.on('close', (code) => {
if (code === 0) {
console.log(chalk.green('✅ Container launched successfully'));
resolve();
} else {
console.log(chalk.red(`❌ Container launch failed with exit code ${code}`));
reject(new Error(`Process exited with code ${code}`));
}
});
// Handle process errors
pythonProcess.on('error', (error) => {
console.log(chalk.red(`❌ Failed to start Python process: ${error.message}`));
reject(error);
});
});
} catch (error) {
console.log(chalk.red(`❌ Error launching container: ${error.message}`));
throw error;
}
}
module.exports = {
runContainer,
getPythonScriptPath
};
================================================
FILE: python/auth_manager.py
================================================
#!/usr/bin/env python3
"""
GitArsenal Authentication Manager
Handles user registration, login, and session management for the CLI.
"""
import os
import json
import hashlib
import secrets
import getpass
import time
import requests
from pathlib import Path
from datetime import datetime, timedelta
from typing import Optional, Dict, Any
class AuthManager:
"""
Manages user authentication for GitArsenal CLI.
Handles registration, login, session management, and API key storage.
"""
def __init__(self, config_dir=None):
"""Initialize the authentication manager"""
if config_dir:
self.config_dir = Path(config_dir)
else:
self.config_dir = Path.home() / ".gitarsenal"
self.auth_file = self.config_dir / "auth.json"
self.session_file = self.config_dir / "session.json"
self.ensure_config_dir()
# API endpoints for authentication (can be configured)
self.auth_api_url = os.getenv("GITARSENAL_AUTH_API", "https://api.gitarsenal.com/auth")
def ensure_config_dir(self):
"""Ensure the configuration directory exists with proper permissions"""
if not self.config_dir.exists():
self.config_dir.mkdir(parents=True)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
self.config_dir.chmod(0o700) # Only owner can read/write/execute
def hash_password(self, password: str) -> str:
"""Hash a password using SHA-256 with salt"""
salt = secrets.token_hex(16)
hash_obj = hashlib.sha256()
hash_obj.update((password + salt).encode('utf-8'))
return f"{salt}${hash_obj.hexdigest()}"
def verify_password(self, password: str, hashed_password: str) -> bool:
"""Verify a password against its hash"""
try:
salt, hash_value = hashed_password.split('$', 1)
hash_obj = hashlib.sha256()
hash_obj.update((password + salt).encode('utf-8'))
return hash_obj.hexdigest() == hash_value
except ValueError:
return False
def generate_session_token(self) -> str:
"""Generate a secure session token"""
return secrets.token_urlsafe(32)
def load_auth_data(self) -> Dict[str, Any]:
"""Load authentication data from file"""
if not self.auth_file.exists():
return {}
try:
with open(self.auth_file, 'r') as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
print("⚠️ Error reading auth file. Starting fresh.")
return {}
def save_auth_data(self, data: Dict[str, Any]) -> bool:
"""Save authentication data to file"""
try:
with open(self.auth_file, 'w') as f:
json.dump(data, f, indent=2)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
self.auth_file.chmod(0o600) # Only owner can read/write
return True
except IOError as e:
print(f"❌ Error saving auth data: {e}")
return False
def load_session(self) -> Dict[str, Any]:
"""Load session data from file"""
if not self.session_file.exists():
return {}
try:
with open(self.session_file, 'r') as f:
session_data = json.load(f)
# Check if session is still valid
if session_data.get('expires_at'):
expires_at = datetime.fromisoformat(session_data['expires_at'])
if datetime.now() > expires_at:
print("⚠️ Session expired. Please login again.")
return {}
return session_data
except (json.JSONDecodeError, IOError):
return {}
def save_session(self, session_data: Dict[str, Any]) -> bool:
"""Save session data to file"""
try:
with open(self.session_file, 'w') as f:
json.dump(session_data, f, indent=2)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
self.session_file.chmod(0o600) # Only owner can read/write
return True
except IOError as e:
print(f"❌ Error saving session: {e}")
return False
def clear_session(self):
"""Clear the current session"""
if self.session_file.exists():
self.session_file.unlink()
def is_authenticated(self) -> bool:
"""Check if user is currently authenticated"""
session = self.load_session()
return bool(session.get('user_id') and session.get('token'))
def get_current_user(self) -> Optional[Dict[str, Any]]:
"""Get current user information"""
session = self.load_session()
if not session.get('user_id'):
return None
auth_data = self.load_auth_data()
return auth_data.get('users', {}).get(session['user_id'])
def register_user(self, username: str, email: str, password: str) -> bool:
"""Register a new user"""
print("\n" + "="*60)
print("🔐 USER REGISTRATION")
print("="*60)
# Validate input
if not username or len(username) < 3:
print("❌ Username must be at least 3 characters long.")
return False
if not email or '@' not in email:
print("❌ Please provide a valid email address.")
return False
if not password or len(password) < 8:
print("❌ Password must be at least 8 characters long.")
return False
auth_data = self.load_auth_data()
users = auth_data.get('users', {})
# Check if username already exists
for user_id, user_data in users.items():
if user_data.get('username') == username:
print("❌ Username already exists. Please choose a different username.")
return False
if user_data.get('email') == email:
print("❌ Email already registered. Please use a different email.")
return False
# Create new user
user_id = secrets.token_hex(16)
hashed_password = self.hash_password(password)
new_user = {
'user_id': user_id,
'username': username,
'email': email,
'password_hash': hashed_password,
'created_at': datetime.now().isoformat(),
'api_keys': {},
'settings': {
'default_gpu': 'A10G',
'timeout_minutes': 60,
'interactive_mode': False
}
}
users[user_id] = new_user
auth_data['users'] = users
if self.save_auth_data(auth_data):
print("✅ Registration successful!")
print(f"Username: {username}")
print(f"Email: {email}")
print("\nYou can now login with your credentials.")
# Send user data to web application
self.send_user_data_to_webapp(username, email)
return True
else:
print("❌ Failed to save registration data.")
return False
def send_user_data_to_webapp(self, username: str, email: str):
"""Send user data to the web application for tracking"""
try:
# Get webhook URL from environment or use default
webhook_url = os.getenv("GITARSENAL_WEBHOOK_URL", "https://www.gitarsenal.dev/api/users")
# Ensure we have valid email and name
if not email or not email.strip():
print(f"⚠️ No email provided for user {username}, skipping web app registration")
return
if not username or not username.strip():
print(f"⚠️ No username provided, skipping web app registration")
return
user_data = {
"email": email.strip(), # Use email as the primary identifier
"name": username.strip() # Use username as the display name
}
print(f"🔗 Sending user data to web application: {username}")
print(f"📦 Data being sent: {user_data}")
response = requests.post(
webhook_url,
json=user_data,
headers={
'Content-Type': 'application/json',
'User-Agent': 'GitArsenal-CLI/1.0'
},
timeout=10
)
if response.status_code >= 200 and response.status_code < 300:
print("✅ User data sent to web application successfully")
elif response.status_code == 409:
print("✅ User already exists in web application")
else:
print(f"⚠️ Failed to send user data (status: {response.status_code})")
print(f"Response: {response.text}")
except requests.exceptions.RequestException as e:
print(f"⚠️ Failed to send user data to web application: {e}")
except Exception as e:
print(f"⚠️ Error sending user data: {e}")
def login_user(self, username: str, password: str) -> bool:
"""Login a user"""
print("\n" + "="*60)
print("🔐 USER LOGIN")
print("="*60)
auth_data = self.load_auth_data()
users = auth_data.get('users', {})
# Find user by username
user_id = None
user_data = None
for uid, user in users.items():
if user.get('username') == username:
user_id = uid
user_data = user
break
if not user_data:
print("❌ Username not found. Please register first.")
return False
# Verify password
if not self.verify_password(password, user_data['password_hash']):
print("❌ Invalid password.")
return False
# Create session
session_token = self.generate_session_token()
session_data = {
'user_id': user_id,
'token': session_token,
'username': username,
'created_at': datetime.now().isoformat(),
'expires_at': (datetime.now() + timedelta(days=30)).isoformat()
}
if self.save_session(session_data):
print("✅ Login successful!")
print(f"Welcome back, {username}!")
# Debug: Print user data to see what we have
print(f"🔍 User data for web app: username={username}, email={user_data.get('email', 'NOT_FOUND')}")
# Send user data to web application
self.send_user_data_to_webapp(username, user_data.get('email', ''))
return True
else:
print("❌ Failed to create session.")
return False
def logout_user(self):
"""Logout the current user"""
self.clear_session()
print("✅ Logged out successfully.")
def change_password(self, current_password: str, new_password: str) -> bool:
"""Change user password"""
user = self.get_current_user()
if not user:
print("❌ Not logged in. Please login first.")
return False
# Verify current password
if not self.verify_password(current_password, user['password_hash']):
print("❌ Current password is incorrect.")
return False
# Validate new password
if not new_password or len(new_password) < 8:
print("❌ New password must be at least 8 characters long.")
return False
# Update password
auth_data = self.load_auth_data()
user_id = user['user_id']
auth_data['users'][user_id]['password_hash'] = self.hash_password(new_password)
if self.save_auth_data(auth_data):
print("✅ Password changed successfully!")
return True
else:
print("❌ Failed to update password.")
return False
def store_api_key(self, service: str, api_key: str) -> bool:
"""Store an API key for the current user"""
user = self.get_current_user()
if not user:
print("❌ Not logged in. Please login first.")
return False
auth_data = self.load_auth_data()
user_id = user['user_id']
if 'api_keys' not in auth_data['users'][user_id]:
auth_data['users'][user_id]['api_keys'] = {}
auth_data['users'][user_id]['api_keys'][service] = api_key
if self.save_auth_data(auth_data):
print(f"✅ {service} API key stored successfully!")
return True
else:
print(f"❌ Failed to store {service} API key.")
return False
def get_api_key(self, service: str) -> Optional[str]:
"""Get an API key for the current user"""
user = self.get_current_user()
if not user:
return None
return user.get('api_keys', {}).get(service)
def update_user_settings(self, settings: Dict[str, Any]) -> bool:
"""Update user settings"""
user = self.get_current_user()
if not user:
print("❌ Not logged in. Please login first.")
return False
auth_data = self.load_auth_data()
user_id = user['user_id']
if 'settings' not in auth_data['users'][user_id]:
auth_data['users'][user_id]['settings'] = {}
auth_data['users'][user_id]['settings'].update(settings)
if self.save_auth_data(auth_data):
print("✅ Settings updated successfully!")
return True
else:
print("❌ Failed to update settings.")
return False
def get_user_settings(self) -> Dict[str, Any]:
"""Get current user settings"""
user = self.get_current_user()
if not user:
return {}
return user.get('settings', {})
def delete_account(self, password: str) -> bool:
"""Delete user account"""
user = self.get_current_user()
if not user:
print("❌ Not logged in. Please login first.")
return False
# Verify password
if not self.verify_password(password, user['password_hash']):
print("❌ Password is incorrect.")
return False
# Confirm deletion
print("\n⚠️ WARNING: This action cannot be undone!")
print("All your data, including API keys and settings, will be permanently deleted.")
confirm = input("Type 'DELETE' to confirm: ").strip()
if confirm != 'DELETE':
print("❌ Account deletion cancelled.")
return False
# Delete user data
auth_data = self.load_auth_data()
user_id = user['user_id']
if user_id in auth_data.get('users', {}):
del auth_data['users'][user_id]
if self.save_auth_data(auth_data):
self.clear_session()
print("✅ Account deleted successfully.")
return True
else:
print("❌ Failed to delete account.")
return False
else:
print("❌ User data not found.")
return False
def show_user_info(self):
"""Display current user information"""
user = self.get_current_user()
if not user:
print("❌ Not logged in. Please login first.")
return
print("\n" + "="*60)
print("👤 USER INFORMATION")
print("="*60)
print(f"Username: {user['username']}")
print(f"Email: {user['email']}")
print(f"Member since: {user['created_at'][:10]}")
# Show API keys (masked)
api_keys = user.get('api_keys', {})
if api_keys:
print("\n🔑 API Keys:")
for service, key in api_keys.items():
masked_key = key[:8] + "..." + key[-4:] if len(key) > 12 else "***"
print(f" {service}: {masked_key}")
else:
print("\n🔑 API Keys: None configured")
# Show settings
settings = user.get('settings', {})
if settings:
print("\n⚙️ Settings:")
for key, value in settings.items():
print(f" {key}: {value}")
print("="*60)
def interactive_auth_flow(self) -> bool:
"""Interactive authentication flow"""
if self.is_authenticated():
user = self.get_current_user()
print(f"✅ Already logged in as: {user['username']}")
return True
print("\n" + "="*60)
print("🔐 GITARSENAL AUTHENTICATION")
print("="*60)
print("Welcome to GitArsenal CLI!")
print("You need to create an account or login to continue.")
print("="*60)
while True:
print("\nOptions:")
print("1. Login")
print("2. Register")
print("3. Exit")
choice = input("\nSelect an option (1-3): ").strip()
if choice == "1":
return self._login_flow()
elif choice == "2":
return self._register_flow()
elif choice == "3":
print("👋 Goodbye!")
return False
else:
print("❌ Invalid option. Please try again.")
def _login_flow(self) -> bool:
"""Interactive login flow"""
print("\n--- LOGIN ---")
username = input("Username: ").strip()
password = getpass.getpass("Password: ").strip()
if self.login_user(username, password):
return True
else:
retry = input("\nTry again? (y/n): ").strip().lower()
return retry == 'y' and self._login_flow()
def _register_flow(self) -> bool:
"""Interactive registration flow"""
print("\n--- REGISTRATION ---")
username = input("Username (min 3 characters): ").strip()
email = input("Email: ").strip()
password = getpass.getpass("Password (min 8 characters): ").strip()
confirm_password = getpass.getpass("Confirm password: ").strip()
if password != confirm_password:
print("❌ Passwords do not match.")
retry = input("\nTry again? (y/n): ").strip().lower()
return retry == 'y' and self._register_flow()
if self.register_user(username, email, password):
# Auto-login after registration
return self.login_user(username, password)
else:
retry = input("\nTry again? (y/n): ").strip().lower()
return retry == 'y' and self._register_flow()
================================================
FILE: python/command_manager.py
================================================
import os
import time
import requests
import re
import json
# Import the LLM debugging function
try:
from llm_debugging import call_llm_for_batch_debug
except ImportError:
# Fallback: define a simple version if the import fails
def call_llm_for_batch_debug(failed_commands, api_key=None, current_dir=None, sandbox=None):
print("⚠️ LLM batch debugging not available")
return []
class CommandListManager:
"""Manages a dynamic list of setup commands with status tracking and LLM-suggested fixes."""
def __init__(self, initial_commands=None, auto_optimize_on_add=False):
self.commands = []
self.executed_commands = []
self.failed_commands = []
self.suggested_fixes = []
self.current_index = 0
self.total_commands = 0
self.auto_optimize_on_add = auto_optimize_on_add
if initial_commands:
self.add_commands(initial_commands)
def enable_auto_llm_optimization(self, enabled=True):
"""Enable or disable automatic LLM optimization after command additions."""
self.auto_optimize_on_add = bool(enabled)
state = "enabled" if self.auto_optimize_on_add else "disabled"
print(f"🤖 Auto LLM optimization {state}")
def add_commands(self, commands):
"""Add new commands to the list."""
if isinstance(commands, str):
commands = [commands]
added_count = 0
for cmd in commands:
if cmd and cmd.strip():
self.commands.append({
'command': cmd.strip(),
'status': 'pending',
'index': len(self.commands),
'stdout': '',
'stderr': '',
'execution_time': None,
'fix_attempts': 0,
'max_fix_attempts': 3
})
added_count += 1
self.total_commands = len(self.commands)
if added_count > 0:
print(f"📋 Added {added_count} commands to list. Total: {self.total_commands}")
if self.auto_optimize_on_add:
try:
print("🤖 Optimizing command list with LLM after addition...")
self.update_command_list_with_llm()
except Exception as e:
print(f"⚠️ Auto-optimization failed: {e}")
def add_command_dynamically(self, command, priority='normal'):
"""Add a single command dynamically during execution."""
if not command or not command.strip():
return False
new_command = {
'command': command.strip(),
'status': 'pending',
'index': len(self.commands),
'stdout': '',
'stderr': '',
'execution_time': None,
'fix_attempts': 0,
'max_fix_attempts': 3,
'priority': priority
}
if priority == 'high':
# Insert at the beginning of pending commands
self.commands.insert(self.current_index, new_command)
# Update indices for all commands after insertion
for i in range(self.current_index + 1, len(self.commands)):
self.commands[i]['index'] = i
else:
# Add to the end
self.commands.append(new_command)
self.total_commands = len(self.commands)
print(f"📋 Added dynamic command: {command.strip()}")
if self.auto_optimize_on_add:
try:
print("🤖 Optimizing command list with LLM after dynamic addition...")
self.update_command_list_with_llm()
except Exception as e:
print(f"⚠️ Auto-optimization failed: {e}")
return True
def add_suggested_fix(self, original_command, fix_command, reason=""):
"""Add a LLM-suggested fix for a failed command."""
fix_entry = {
'original_command': original_command,
'fix_command': fix_command,
'reason': reason,
'status': 'pending',
'index': len(self.suggested_fixes),
'stdout': '',
'stderr': '',
'execution_time': None
}
self.suggested_fixes.append(fix_entry)
print(f"🔧 Added suggested fix: {fix_command}")
if self.auto_optimize_on_add:
try:
print("🤖 Optimizing command list with LLM after suggested fix addition...")
self.update_command_list_with_llm()
except Exception as e:
print(f"⚠️ Auto-optimization failed: {e}")
return len(self.suggested_fixes) - 1
def get_next_command(self):
"""Get the next pending command to execute."""
# First, try to get a pending command from the main list
for i in range(self.current_index, len(self.commands)):
if self.commands[i]['status'] == 'pending':
return self.commands[i], 'main'
# If no pending commands in main list, check suggested fixes
for fix in self.suggested_fixes:
if fix['status'] == 'pending':
return fix, 'fix'
return None, None
def mark_command_executed(self, command_index, command_type='main', success=True, stdout='', stderr='', execution_time=None):
"""Mark a command as executed with results."""
if command_type == 'main':
if 0 <= command_index < len(self.commands):
self.commands[command_index].update({
'status': 'success' if success else 'failed',
'stdout': stdout,
'stderr': stderr,
'execution_time': execution_time
})
if success:
self.executed_commands.append(self.commands[command_index])
print(f"✅ Command {command_index + 1}/{self.total_commands} completed successfully")
else:
self.failed_commands.append(self.commands[command_index])
print(f"❌ Command {command_index + 1}/{self.total_commands} failed")
self.current_index = max(self.current_index, command_index + 1)
elif command_type == 'fix':
if 0 <= command_index < len(self.suggested_fixes):
self.suggested_fixes[command_index].update({
'status': 'success' if success else 'failed',
'stdout': stdout,
'stderr': stderr,
'execution_time': execution_time
})
if success:
print(f"✅ Fix command {command_index + 1} completed successfully")
# After a successful fix, decide whether to skip or modify the original command
try:
original_command = self.suggested_fixes[command_index].get('original_command', '')
fix_command = self.suggested_fixes[command_index].get('fix_command', '')
if original_command and fix_command:
should_skip, reason = self.should_skip_original_command(
original_command, fix_command, stdout, stderr
)
if should_skip:
# Find the original command in the main list and mark it as completed (skipped)
for i, cmd in enumerate(self.commands):
if cmd.get('command') == original_command and cmd.get('status') in ('pending', 'failed'):
self.mark_command_executed(
i, 'main', True,
f"Command skipped due to successful fix: {reason}",
'', 0
)
break
else:
# If we should not skip, try to optimize the list (may MODIFY or ADD_AFTER)
if getattr(self, 'auto_optimize_on_add', False):
print("🤖 Optimizing command list with LLM after fix success...")
self.update_command_list_with_llm()
except Exception as e:
print(f"⚠️ Post-fix optimization error: {e}")
else:
print(f"❌ Fix command {command_index + 1} failed")
def get_status_summary(self):
"""Get a summary of command execution status."""
total_main = len(self.commands)
total_fixes = len(self.suggested_fixes)
executed_main = len([c for c in self.commands if c['status'] == 'success'])
failed_main = len([c for c in self.commands if c['status'] == 'failed'])
pending_main = len([c for c in self.commands if c['status'] == 'pending'])
executed_fixes = len([f for f in self.suggested_fixes if f['status'] == 'success'])
failed_fixes = len([f for f in self.suggested_fixes if f['status'] == 'failed'])
return {
'total_main_commands': total_main,
'executed_main_commands': executed_main,
'failed_main_commands': failed_main,
'pending_main_commands': pending_main,
'total_fix_commands': total_fixes,
'executed_fix_commands': executed_fixes,
'failed_fix_commands': failed_fixes,
'progress_percentage': (executed_main / total_main * 100) if total_main > 0 else 0
}
def print_status(self):
"""Print current status of all commands."""
summary = self.get_status_summary()
print("\n" + "="*60)
print("📋 COMMAND EXECUTION STATUS")
print("="*60)
# Main commands status
print(f"📋 Main Commands: {summary['executed_main_commands']}/{summary['total_main_commands']} completed")
print(f" ✅ Successful: {summary['executed_main_commands']}")
print(f" ❌ Failed: {summary['failed_main_commands']}")
print(f" ⏳ Pending: {summary['pending_main_commands']}")
# Fix commands status
if summary['total_fix_commands'] > 0:
print(f"🔧 Fix Commands: {summary['executed_fix_commands']}/{summary['total_fix_commands']} completed")
print(f" ✅ Successful: {summary['executed_fix_commands']}")
print(f" ❌ Failed: {summary['failed_fix_commands']}")
# Progress bar
progress = summary['progress_percentage']
bar_length = 30
filled_length = int(bar_length * progress / 100)
bar = '█' * filled_length + '░' * (bar_length - filled_length)
print(f"📊 Progress: [{bar}] {progress:.1f}%")
# Show current command if any
next_cmd, cmd_type = self.get_next_command()
if next_cmd:
cmd_type_str = "main" if cmd_type == 'main' else "fix"
cmd_text = next_cmd.get('command', next_cmd.get('fix_command', 'Unknown command'))
print(f"🔄 Current: {cmd_type_str} command - {cmd_text[:50]}...")
print("="*60)
def print_all_commands(self):
"""Print all commands in the list for debugging/transparency."""
if not self.commands:
print("📋 No commands in the list")
return
print("\n" + "="*80)
print("📋 ALL SETUP COMMANDS")
print("="*80)
for i, cmd in enumerate(self.commands):
status_icon = {
'pending': '⏳',
'success': '✅',
'failed': '❌'
}.get(cmd['status'], '❓')
print(f" {i+1:2d}. {status_icon} {cmd['command']}")
print("="*80 + "\n")
def get_failed_commands_for_llm(self):
"""Get failed commands for LLM analysis."""
failed_commands = []
# Get failed main commands
for cmd in self.commands:
if cmd['status'] == 'failed':
failed_commands.append({
'command': cmd['command'],
'stderr': cmd['stderr'],
'stdout': cmd['stdout'],
'type': 'main'
})
# Get failed fix commands
for fix in self.suggested_fixes:
if fix['status'] == 'failed':
failed_commands.append({
'command': fix['fix_command'],
'stderr': fix['stderr'],
'stdout': fix['stdout'],
'type': 'fix',
'original_command': fix['original_command']
})
return failed_commands
def has_pending_commands(self):
"""Check if there are any pending commands."""
return any(cmd['status'] == 'pending' for cmd in self.commands) or \
any(fix['status'] == 'pending' for fix in self.suggested_fixes)
def get_all_commands(self):
"""Get all commands (main + fixes) in execution order."""
all_commands = []
# Add main commands
for cmd in self.commands:
all_commands.append({
**cmd,
'type': 'main'
})
# Add fix commands
for fix in self.suggested_fixes:
all_commands.append({
**fix,
'type': 'fix'
})
return all_commands
def analyze_failed_commands_with_llm(self, api_key=None, current_dir=None, sandbox=None, use_web_search=False):
"""Analyze all failed commands using LLM and add suggested fixes."""
failed_commands = self.get_failed_commands_for_llm()
if not failed_commands:
print("✅ No failed commands to analyze")
return []
print(f"🔍 Analyzing {len(failed_commands)} failed commands with LLM...")
# Use unified batch debugging for efficiency
fixes = call_llm_for_batch_debug(failed_commands, api_key, current_dir, sandbox, use_web_search)
# Add the fixes to the command list
added_fixes = []
for fix in fixes:
fix_index = self.add_suggested_fix(
fix['original_command'],
fix['fix_command'],
fix['reason']
)
added_fixes.append(fix_index)
print(f"🔧 Added {len(added_fixes)} LLM-suggested fixes to command list")
return added_fixes
def should_skip_original_command(self, original_command, fix_command, fix_stdout, fix_stderr, api_key=None):
"""
Use LLM to determine if the original command should be skipped after a successful fix.
Args:
original_command: The original command that failed
fix_command: The fix command that succeeded
fix_stdout: The stdout from the fix command
fix_stderr: The stderr from the fix command
api_key: OpenAI API key
Returns:
tuple: (should_skip, reason)
"""
try:
# Import required helpers once for this function scope
from llm_debugging import (
get_current_debug_model,
get_api_key,
make_api_request,
get_provider_rotation_order,
)
# Get all commands for context
all_commands = self.get_all_commands()
def _cmd_text(c):
return c.get('command') or c.get('fix_command') or 'UNKNOWN'
commands_context = "\n".join([f"{i+1}. {_cmd_text(cmd)} - {cmd.get('status', '')}" for i, cmd in enumerate(all_commands)])
# Prepare the prompt
prompt = f"""
I need to determine if an original command should be skipped after a successful fix command.
ENVIRONMENT: All commands are running on a Unix/Linux environment (bash shell), so only suggest Unix-compatible commands.
Original command (failed): {original_command}
Fix command (succeeded): {fix_command}
Fix command stdout:
{fix_stdout}
Fix command stderr:
{fix_stderr}
Current command list:
{commands_context}
Based on this information, should I skip running the original command again?
Consider:
1. If the fix command already accomplished what the original command was trying to do
2. If running the original command again would be redundant or cause errors
3. If the original command is still necessary after the fix
Respond with ONLY:
SKIP:
or
RUN:
"""
preferred = os.environ.get("GITARSENAL_DEBUG_MODEL", "openai")
providers = get_provider_rotation_order(preferred)
for provider in providers:
# Always fetch provider-specific key; don't reuse a different provider's key
provider_key = get_api_key(provider)
if not provider_key:
print(f"⚠️ No {provider} API key available for skip analysis. Trying next provider...")
continue
print(f"🔍 Analyzing if original command should be skipped using {provider}...")
response_text = make_api_request(provider, provider_key, prompt)
if not response_text:
print(f"⚠️ Failed to get response from {provider}. Trying next provider...")
continue
# Parse the response
if response_text.startswith("SKIP:"):
reason = response_text.replace("SKIP:", "").strip()
print(f"🔍 LLM suggests skipping original command: {reason}")
return True, reason
elif response_text.startswith("RUN:"):
reason = response_text.replace("RUN:", "").strip()
print(f"🔍 LLM suggests running original command: {reason}")
return False, reason
else:
# Try to interpret a free-form response
if "skip" in response_text.lower() and "should" in response_text.lower():
print(f"🔍 Interpreting response as SKIP: {response_text}")
return True, response_text
else:
print(f"🔍 Interpreting response as RUN: {response_text}")
return False, response_text
# If all providers failed
print("❌ All providers failed to analyze skip decision.")
return False, "No provider returned a response"
except Exception as e:
print(f"⚠️ Error analyzing command skip decision: {e}")
return False, f"Error: {e}"
def replace_command(self, command_index, new_command, reason=""):
"""
Replace a command in the list with a new command.
Args:
command_index: The index of the command to replace
new_command: The new command to use
reason: The reason for the replacement
Returns:
bool: True if the command was replaced, False otherwise
"""
if 0 <= command_index < len(self.commands):
old_command = self.commands[command_index]['command']
self.commands[command_index]['command'] = new_command
self.commands[command_index]['status'] = 'pending' # Reset status
self.commands[command_index]['stdout'] = ''
self.commands[command_index]['stderr'] = ''
self.commands[command_index]['execution_time'] = None
self.commands[command_index]['replacement_reason'] = reason
print(f"🔄 Replaced command {command_index + 1}: '{old_command}' with '{new_command}'")
print(f"🔍 Reason: {reason}")
return True
else:
print(f"❌ Invalid command index for replacement: {command_index}")
return False
def update_command_list_with_llm(self, api_key=None):
"""
Use LLM to analyze and update the entire command list.
Args:
api_key: OpenAI API key
Returns:
bool: True if the list was updated, False otherwise
"""
try:
from llm_debugging import (
get_current_debug_model,
get_api_key,
make_api_request,
get_provider_rotation_order,
)
# Get API key if not provided
preferred = os.environ.get("GITARSENAL_DEBUG_MODEL", "openai")
providers = get_provider_rotation_order(preferred)
# Get all commands for context
all_commands = self.get_all_commands()
def _cmd_text(c):
return c.get('command') or c.get('fix_command') or 'UNKNOWN'
commands_context = "\n".join([f"{i+1}. {_cmd_text(cmd)} - {cmd.get('status', '')}"
for i, cmd in enumerate(all_commands)])
# Get executed commands with their outputs for context
executed_context = ""
for cmd in self.executed_commands:
executed_context += f"Command: {cmd['command']}\n"
executed_context += f"Status: {cmd['status']}\n"
if cmd['stdout']:
executed_context += f"Stdout: {cmd['stdout'][:500]}...\n" if len(cmd['stdout']) > 500 else f"Stdout: {cmd['stdout']}\n"
if cmd['stderr']:
executed_context += f"Stderr: {cmd['stderr'][:500]}...\n" if len(cmd['stderr']) > 500 else f"Stderr: {cmd['stderr']}\n"
executed_context += "\n"
# Prepare the prompt
prompt = f"""
I need you to analyze and optimize this command list. Some commands have been executed,
and some are still pending. Based on what has already been executed, I need you to:
ENVIRONMENT: All commands are running on a Unix/Linux environment (bash shell), so only suggest Unix-compatible commands. Do not suggest Windows-specific commands or PowerShell commands.
1. Identify any pending commands that are now redundant or unnecessary
2. Identify any pending commands that should be modified based on previous command results
3. Suggest any new commands that should be added
Current command list:
{commands_context}
Details of executed commands:
{executed_context}
For each pending command (starting from the next command to be executed), tell me if it should be:
1. KEEP: Keep the command as is
2. SKIP: Skip the command (mark as completed without running)
3. MODIFY: Modify the command (provide the new command)
4. ADD_AFTER: Add a new command after this one
Format your response as a JSON array of actions:
[
{{
"command_index": ,
"action": "KEEP|SKIP|MODIFY|ADD_AFTER",
"new_command": "",
"reason": ""
}},
...
]
Only include commands that need changes (SKIP, MODIFY, ADD_AFTER), not KEEP actions.
"""
# Use the unified LLM API call
import json
response_text = None
for provider in providers:
provider_key = api_key if (api_key and provider == preferred) else get_api_key(provider)
if not provider_key:
print(f"⚠️ No {provider} API key available for command list analysis. Trying next provider...")
continue
print(f"🔍 Analyzing command list for optimizations using {provider}...")
response_text = make_api_request(provider, provider_key, prompt)
if response_text:
break
if not response_text:
print("⚠️ Failed to get response from all providers for command list optimization")
return False
# Extract JSON from the response
try:
# Find JSON array in the response
json_match = re.search(r'\[\s*\{.*\}\s*\]', response_text, re.DOTALL)
if json_match:
json_str = json_match.group(0)
actions = json.loads(json_str)
else:
# Try to parse the entire response as JSON
actions = json.loads(response_text)
if not isinstance(actions, list):
print("❌ Invalid response format from LLM - not a list")
return False
# Apply the suggested changes
changes_made = 0
commands_added = 0
# Process in reverse order to avoid index shifting issues
for action in sorted(actions, key=lambda x: x.get('command_index', 0), reverse=True):
cmd_idx = action.get('command_index')
action_type = action.get('action')
new_cmd = action.get('new_command', '')
reason = action.get('reason', 'No reason provided')
if cmd_idx is None or action_type is None:
continue
# Convert to 0-based index if needed
if cmd_idx > 0: # Assume 1-based index from LLM
cmd_idx -= 1
# Skip if the command index is invalid
if cmd_idx < 0 or cmd_idx >= len(self.commands):
print(f"❌ Invalid command index: {cmd_idx}")
continue
# Skip if the command has already been executed
if self.commands[cmd_idx]['status'] != 'pending':
print(f"⚠️ Command {cmd_idx + 1} already executed, skipping action")
continue
if action_type == "SKIP":
# Mark the command as successful without running it
self.mark_command_executed(
cmd_idx, 'main', True,
f"Command skipped: {reason}",
"", 0
)
print(f"🔄 Skipped command {cmd_idx + 1}: {reason}")
changes_made += 1
elif action_type == "MODIFY":
if new_cmd:
if self.replace_command(cmd_idx, new_cmd, reason):
changes_made += 1
else:
print(f"❌ No new command provided for MODIFY action on command {cmd_idx + 1}")
elif action_type == "ADD_AFTER":
if new_cmd:
# Add new command after the current one
insert_idx = cmd_idx + 1
new_cmd_obj = {
'command': new_cmd,
'status': 'pending',
'index': insert_idx,
'stdout': '',
'stderr': '',
'execution_time': None,
'fix_attempts': 0,
'max_fix_attempts': 3,
'added_reason': reason
}
# Insert the new command
self.commands.insert(insert_idx, new_cmd_obj)
# Update indices for all commands after insertion
for i in range(insert_idx + 1, len(self.commands)):
self.commands[i]['index'] = i
print(f"➕ Added new command after {cmd_idx + 1}: '{new_cmd}'")
print(f"🔍 Reason: {reason}")
commands_added += 1
else:
print(f"❌ No new command provided for ADD_AFTER action on command {cmd_idx + 1}")
# Update total commands count
self.total_commands = len(self.commands)
print(f"✅ Command list updated: {changes_made} changes made, {commands_added} commands added")
return changes_made > 0 or commands_added > 0
except json.JSONDecodeError as e:
print(f"❌ Failed to parse LLM response as JSON: {e}")
print(f"Raw response: {response_text}")
return False
except Exception as e:
print(f"❌ Error updating command list: {e}")
return False
except Exception as e:
print(f"⚠️ Error analyzing command list: {e}")
return False
================================================
FILE: python/credentials_manager.py
================================================
import os
import json
import getpass
from pathlib import Path
class CredentialsManager:
"""
Manages API keys and tokens for GitArsenal CLI.
Provides secure storage and retrieval of credentials.
"""
def __init__(self, config_dir=None):
"""Initialize the credentials manager with optional custom config directory"""
if config_dir:
self.config_dir = Path(config_dir)
else:
self.config_dir = Path.home() / ".gitarsenal"
self.credentials_file = self.config_dir / "credentials.json"
self.ensure_config_dir()
def ensure_config_dir(self):
"""Ensure the configuration directory exists"""
if not self.config_dir.exists():
self.config_dir.mkdir(parents=True)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
self.config_dir.chmod(0o700) # Only owner can read/write/execute
def load_credentials(self):
"""Load credentials from the credentials file"""
if not self.credentials_file.exists():
return {}
try:
with open(self.credentials_file, 'r') as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
print("⚠️ Error reading credentials file. Using empty credentials.")
return {}
def save_credentials(self, credentials):
"""Save credentials to the credentials file"""
try:
with open(self.credentials_file, 'w') as f:
json.dump(credentials, f)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
self.credentials_file.chmod(0o600) # Only owner can read/write
return True
except IOError as e:
print(f"❌ Error saving credentials: {e}")
return False
def get_credential(self, key, prompt=None, is_password=False, validate_func=None):
"""
Get a credential by key. If not found, prompt the user.
Args:
key: The credential key
prompt: Custom prompt message
is_password: Whether to mask input
validate_func: Optional function to validate the credential
Returns:
The credential value
"""
credentials = self.load_credentials()
# Check if credential exists and is valid
if key in credentials:
value = credentials[key]
if not validate_func or validate_func(value):
return value
# Credential not found or invalid, prompt user
if not prompt:
prompt = f"Please enter your {key}:"
print("\n" + "="*60)
print(f"🔑 {key.upper()} REQUIRED")
print("="*60)
print(prompt)
print("-" * 60)
try:
if is_password:
value = getpass.getpass("Input (hidden): ").strip()
else:
value = input("Input: ").strip()
if not value:
print("❌ No input provided.")
return None
# Validate if function provided
if validate_func and not validate_func(value):
print("❌ Invalid input.")
return None
# Save the credential
credentials[key] = value
self.save_credentials(credentials)
print("✅ Input received and saved successfully!")
return value
except KeyboardInterrupt:
print("\n❌ Input cancelled by user.")
return None
except Exception as e:
print(f"❌ Error getting input: {e}")
return None
def clear_credential(self, key):
"""Remove a specific credential"""
credentials = self.load_credentials()
if key in credentials:
del credentials[key]
self.save_credentials(credentials)
return True
return False
def clear_all_credentials(self):
"""Clear all saved credentials"""
return self.save_credentials({})
def has_credential(self, key):
"""Check if a credential exists without prompting"""
credentials = self.load_credentials()
return key in credentials and credentials[key]
def get_credential_silently(self, key):
"""Get a credential without prompting if it exists"""
credentials = self.load_credentials()
return credentials.get(key)
def cleanup_security_files(self):
"""Clean up all security-related files including legacy files"""
try:
# Clear all credentials from the main file
self.clear_all_credentials()
# Remove legacy OpenAI key file
openai_key_file = self.config_dir / "openai_key"
if openai_key_file.exists():
openai_key_file.unlink()
print("✅ Removed legacy OpenAI API key file")
# Remove environment variables
import os
security_vars = [
"OPENAI_API_KEY",
"ANTHROPIC_API_KEY",
"HUGGINGFACE_TOKEN",
"WANDB_API_KEY",
"MODAL_TOKEN_ID",
"MODAL_TOKEN",
"MODAL_TOKEN_SECRET",
"GROQ_API_KEY"
]
for var in security_vars:
if var in os.environ:
del os.environ[var]
print("✅ Security cleanup completed successfully")
return True
except Exception as e:
print(f"❌ Error during security cleanup: {e}")
return False
================================================
FILE: python/debug_modal_minimal.py
================================================
#!/usr/bin/env python3
"""
Minimal Modal container test to debug segmentation fault issues.
This script tests different base images and configurations to isolate the problem.
"""
import os
import sys
import modal
import datetime
# Set up Modal tokens
from fetch_modal_tokens import get_tokens
token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key = get_tokens()
if token_id is None or token_secret is None:
raise ValueError("Could not get valid tokens")
os.environ["MODAL_TOKEN_ID"] = token_id
os.environ["MODAL_TOKEN_SECRET"] = token_secret
def test_minimal_container():
"""Test 1: Minimal container with debian base"""
print("🔬 Testing minimal Debian container...")
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
app_name = f"debug-minimal-{timestamp}"
# Minimal debian image
minimal_image = (
modal.Image.debian_slim()
.apt_install("curl", "wget")
.pip_install("requests")
)
app = modal.App(app_name, image=minimal_image)
@app.function(timeout=300, serialized=True)
def minimal_test():
print("✅ Minimal container started successfully!")
import sys
print(f"Python version: {sys.version}")
import platform
print(f"Platform: {platform.platform()}")
return "success"
try:
with app.run():
result = minimal_test.remote()
print(f"✅ Minimal test result: {result}")
return True
except Exception as e:
print(f"❌ Minimal test failed: {e}")
return False
def test_cuda_base():
"""Test 2: CUDA base without additional packages"""
print("🔬 Testing CUDA base image...")
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
app_name = f"debug-cuda-{timestamp}"
# CUDA base image without extras
cuda_image = modal.Image.from_registry("nvidia/cuda:12.4.0-runtime-ubuntu22.04", add_python="3.11")
app = modal.App(app_name, image=cuda_image)
@app.function(timeout=300, gpu="t4", serialized=True)
def cuda_test():
print("✅ CUDA container started successfully!")
import sys
print(f"Python version: {sys.version}")
# Test CUDA availability
try:
import subprocess
result = subprocess.run(["nvidia-smi"], capture_output=True, text=True)
print(f"NVIDIA-SMI output: {result.stdout[:200]}...")
except Exception as e:
print(f"NVIDIA-SMI error: {e}")
return "cuda_success"
try:
with app.run():
result = cuda_test.remote()
print(f"✅ CUDA test result: {result}")
return True
except Exception as e:
print(f"❌ CUDA test failed: {e}")
return False
def test_cuda_devel():
"""Test 3: CUDA devel image (current failing one)"""
print("🔬 Testing CUDA devel image...")
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
app_name = f"debug-cuda-devel-{timestamp}"
# CUDA devel image (the one that's failing)
cuda_devel_image = modal.Image.from_registry("nvidia/cuda:12.4.0-devel-ubuntu22.04", add_python="3.11")
app = modal.App(app_name, image=cuda_devel_image)
@app.function(timeout=300, gpu="t4", serialized=True)
def cuda_devel_test():
print("✅ CUDA devel container started successfully!")
import sys
print(f"Python version: {sys.version}")
return "cuda_devel_success"
try:
with app.run():
result = cuda_devel_test.remote()
print(f"✅ CUDA devel test result: {result}")
return True
except Exception as e:
print(f"❌ CUDA devel test failed: {e}")
return False
def test_with_packages():
"""Test 4: Add packages incrementally"""
print("🔬 Testing with SSH packages...")
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
app_name = f"debug-ssh-{timestamp}"
# Add SSH packages to working base
ssh_image = (
modal.Image.debian_slim()
.apt_install("openssh-server", "sudo", "curl")
.pip_install("requests")
.run_commands(
"mkdir -p /var/run/sshd",
"ssh-keygen -A"
)
)
app = modal.App(app_name, image=ssh_image)
@app.function(timeout=300, serialized=True)
def ssh_test():
print("✅ SSH container started successfully!")
import subprocess
result = subprocess.run(["service", "ssh", "status"], capture_output=True, text=True)
print(f"SSH service status: {result.returncode}")
return "ssh_success"
try:
with app.run():
result = ssh_test.remote()
print(f"✅ SSH test result: {result}")
return True
except Exception as e:
print(f"❌ SSH test failed: {e}")
return False
def main():
"""Run all tests to isolate the segfault issue"""
print("🐛 DEBUGGING MODAL SEGMENTATION FAULT")
print("=" * 50)
tests = [
("Minimal Debian", test_minimal_container),
("CUDA Runtime", test_cuda_base),
("CUDA Devel", test_cuda_devel),
("SSH Packages", test_with_packages),
]
results = {}
for test_name, test_func in tests:
print(f"\n{'=' * 20} {test_name} {'=' * 20}")
try:
results[test_name] = test_func()
except Exception as e:
print(f"❌ {test_name} failed with exception: {e}")
results[test_name] = False
print(f"\n{'=' * 50}")
print("🔍 TEST RESULTS SUMMARY:")
print("=" * 50)
for test_name, success in results.items():
status = "✅ PASS" if success else "❌ FAIL"
print(f"{test_name:<20} {status}")
# Analysis
print(f"\n{'=' * 50}")
print("📊 ANALYSIS:")
print("=" * 50)
if results.get("Minimal Debian", False):
print("✅ Basic Modal functionality works")
else:
print("❌ Basic Modal functionality broken - check Modal setup")
return
if results.get("CUDA Runtime", False):
print("✅ CUDA runtime works")
else:
print("❌ CUDA runtime broken - GPU/CUDA issue")
if not results.get("CUDA Devel", False):
print("❌ CUDA devel broken - likely the source of segfault")
print("💡 RECOMMENDATION: Use CUDA runtime instead of devel")
if results.get("SSH Packages", False):
print("✅ SSH packages work on debian")
if __name__ == "__main__":
main()
================================================
FILE: python/fetch_modal_tokens.py
================================================
#!/usr/bin/env python3
"""
Fetch Modal Tokens and OpenAI API Key
This script fetches Modal tokens and OpenAI API key from the proxy server.
"""
import os
import sys
import json
import requests
import subprocess
from pathlib import Path
def fetch_default_tokens_from_gitarsenal():
"""
Fetch default Modal tokens and OpenAI API key from gitarsenal.dev API.
Returns:
tuple: (token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key) if successful, (None, None, None, None, None, None) otherwise
"""
endpoint = "https://gitarsenal.dev/api/credentials"
try:
headers = {
'User-Agent': 'Python-Modal-Token-Fetcher/1.0',
'Accept': 'application/json'
}
# print(f"🔗 Fetching default tokens from: {endpoint}")
response = requests.get(endpoint, headers=headers, timeout=30)
# print(f"📊 Status: {response.status_code}")
if response.status_code == 200:
try:
data = response.json()
token_id = data.get("modalTokenId")
token_secret = data.get("modalTokenSecret")
openai_api_key = data.get("openaiApiKey")
anthropic_api_key = data.get("anthropicApiKey")
openrouter_api_key = data.get("openrouterApiKey")
groq_api_key = data.get("groqApiKey")
if token_id and token_secret:
# print("✅ Successfully fetched default tokens from gitarsenal.dev")
return token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key
else:
print("❌ Modal tokens not found in gitarsenal.dev response")
return None, None, None, None, None, None
except json.JSONDecodeError:
print("❌ Invalid JSON response from gitarsenal.dev")
return None, None, None, None, None, None
else:
print(f"❌ Failed to fetch from gitarsenal.dev: {response.status_code} - {response.text[:200]}")
return None, None, None, None, None, None
except requests.exceptions.Timeout:
print("❌ Request timeout when fetching from gitarsenal.dev")
return None, None, None, None, None, None
except requests.exceptions.ConnectionError:
print("❌ Connection failed to gitarsenal.dev")
return None, None, None, None, None, None
except requests.exceptions.RequestException as e:
print(f"❌ Request failed to gitarsenal.dev: {e}")
return None, None, None, None, None, None
def fetch_tokens_from_proxy(proxy_url=None, api_key=None):
"""
Fetch Modal tokens and OpenAI API key from the proxy server.
Args:
proxy_url: URL of the proxy server
api_key: API key for authentication
Returns:
tuple: (token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key) if successful, (None, None, None, None, None, None) otherwise
"""
# Use environment variables if not provided
if not proxy_url:
proxy_url = os.environ.get("MODAL_PROXY_URL")
if proxy_url:
print(f"📋 Using proxy URL from environment")
if not api_key:
api_key = os.environ.get("MODAL_PROXY_API_KEY")
if api_key:
print(f"📋 Using API key from environment (length: {len(api_key)})")
# Check if we have the necessary information
if not proxy_url:
# print("❌ No proxy URL provided or found in environment")
# print("💡 Set MODAL_PROXY_URL environment variable or use --proxy-url argument")
return None, None, None, None, None, None
if not api_key:
print("❌ No API key provided or found in environment")
print("💡 Set MODAL_PROXY_API_KEY environment variable or use --proxy-api-key argument")
return None, None, None, None, None, None
# Ensure the URL ends with a slash
if not proxy_url.endswith("/"):
proxy_url += "/"
# Add the endpoint for fetching tokens
token_url = f"{proxy_url}api/modal-tokens"
try:
# Make the request
print(f"🔄 Fetching tokens from proxy server")
response = requests.get(
token_url,
headers={"X-API-Key": api_key}
)
# Check if the request was successful
if response.status_code == 200:
data = response.json()
token_id = data.get("token_id")
token_secret = data.get("token_secret")
openai_api_key = data.get("openai_api_key")
anthropic_api_key = data.get("anthropic_api_key")
openrouter_api_key = data.get("openrouter_api_key")
groq_api_key = data.get("groq_api_key")
if token_id and token_secret:
print("✅ Successfully fetched tokens from proxy server")
return token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key
else:
print("❌ Tokens not found in response")
return None, None, None, None, None, None
else:
print(f"❌ Failed to fetch tokens: {response.status_code} - {response.text}")
return None, None, None, None, None, None
except Exception as e:
print(f"❌ Error fetching tokens: {e}")
return None, None, None, None, None, None
def get_tokens():
"""
Get Modal tokens, OpenAI API key, Anthropic API key, and Groq API key, trying to fetch from the proxy server first.
Also sets the tokens in environment variables.
Returns:
tuple: (token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key)
"""
# Try to fetch from the proxy server
token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key = fetch_tokens_from_proxy()
# If we couldn't fetch from the server, try to get default tokens from gitarsenal.dev
if not token_id or not token_secret:
# print("⚠️ Proxy server failed, trying to fetch default tokens from gitarsenal.dev")
token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key = fetch_default_tokens_from_gitarsenal()
# If we still don't have tokens, we can't proceed
if not token_id or not token_secret:
print("❌ Failed to fetch tokens from both proxy server and gitarsenal.dev")
print("💡 Please check your network connection and API endpoints")
return None, None, None, None, None, None
# Set the tokens in environment variables
os.environ["MODAL_TOKEN_ID"] = token_id
os.environ["MODAL_TOKEN_SECRET"] = token_secret
# print(f"✅ Set MODAL_TOKEN_ID and MODAL_TOKEN_SECRET environment variables")
# Set OpenAI API key if available
if openai_api_key:
os.environ["OPENAI_API_KEY"] = openai_api_key
# Set Anthropic API key if available
if anthropic_api_key:
os.environ["ANTHROPIC_API_KEY"] = anthropic_api_key
# Set OpenRouter API key if available
if openrouter_api_key:
os.environ["OPENROUTER_API_KEY"] = openrouter_api_key
# Set Groq API key if available
if groq_api_key:
os.environ["GROQ_API_KEY"] = groq_api_key
return token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key
if __name__ == "__main__":
# Parse command-line arguments if run directly
import argparse
parser = argparse.ArgumentParser(description='Fetch Modal tokens and OpenAI API key from the proxy server')
parser.add_argument('--proxy-url', help='URL of the proxy server')
parser.add_argument('--proxy-api-key', help='API key for the proxy server')
args = parser.parse_args()
# Set proxy URL and API key in environment variables if provided
if args.proxy_url:
os.environ["MODAL_PROXY_URL"] = args.proxy_url
print(f"✅ Set MODAL_PROXY_URL from command line: {args.proxy_url}")
if args.proxy_api_key:
os.environ["MODAL_PROXY_API_KEY"] = args.proxy_api_key
print(f"✅ Set MODAL_PROXY_API_KEY from command line")
# Get tokens
token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key = get_tokens()
print(f"Token ID: {token_id}")
print(f"Token Secret: {token_secret}")
print(f"OpenAI API Key: {openai_api_key[:5] + '...' if openai_api_key else None}")
print(f"Anthropic API Key: {anthropic_api_key[:5] + '...' if anthropic_api_key else None}")
print(f"OpenRouter API Key: {openrouter_api_key[:5] + '...' if openrouter_api_key else None}")
print(f"Groq API Key: {groq_api_key[:5] + '...' if groq_api_key else None}")
# Check if tokens are set in environment variables
# print(f"\n🔍 DEBUG: Checking environment variables")
print(f"🔍 MODAL_TOKEN_ID exists: {'Yes' if os.environ.get('MODAL_TOKEN_ID') else 'No'}")
print(f"🔍 MODAL_TOKEN_SECRET exists: {'Yes' if os.environ.get('MODAL_TOKEN_SECRET') else 'No'}")
print(f"🔍 OPENAI_API_KEY exists: {'Yes' if os.environ.get('OPENAI_API_KEY') else 'No'}")
print(f"🔍 ANTHROPIC_API_KEY exists: {'Yes' if os.environ.get('ANTHROPIC_API_KEY') else 'No'}")
print(f"🔍 OPENROUTER_API_KEY exists: {'Yes' if os.environ.get('OPENROUTER_API_KEY') else 'No'}")
print(f"🔍 GROQ_API_KEY exists: {'Yes' if os.environ.get('GROQ_API_KEY') else 'No'}")
if os.environ.get('MODAL_TOKEN_ID'):
print(f"🔍 MODAL_TOKEN_ID length: {len(os.environ.get('MODAL_TOKEN_ID'))}")
if os.environ.get('MODAL_TOKEN_SECRET'):
print(f"🔍 MODAL_TOKEN_SECRET length: {len(os.environ.get('MODAL_TOKEN_SECRET'))}")
if os.environ.get('OPENAI_API_KEY'):
print(f"🔍 OPENAI_API_KEY length: {len(os.environ.get('OPENAI_API_KEY'))}")
if os.environ.get('ANTHROPIC_API_KEY'):
print(f"🔍 ANTHROPIC_API_KEY length: {len(os.environ.get('ANTHROPIC_API_KEY'))}")
if os.environ.get('OPENROUTER_API_KEY'):
print(f"🔍 OPENROUTER_API_KEY length: {len(os.environ.get('OPENROUTER_API_KEY'))}")
if os.environ.get('GROQ_API_KEY'):
print(f"🔍 GROQ_API_KEY length: {len(os.environ.get('GROQ_API_KEY'))}")
# Write the tokens to a file for use by other scripts
tokens_file = Path(__file__).parent / "modal_tokens.json"
with open(tokens_file, 'w') as f:
json.dump({
"token_id": token_id,
"token_secret": token_secret,
"openai_api_key": openai_api_key,
"anthropic_api_key": anthropic_api_key,
"openrouter_api_key": openrouter_api_key,
"groq_api_key": groq_api_key
}, f)
print(f"\n✅ Tokens written to {tokens_file}")
# Create token files in standard locations
modal_dir = Path.home() / ".modal"
modal_dir.mkdir(exist_ok=True)
token_file = modal_dir / "token.json"
with open(token_file, 'w') as f:
json.dump({
"token_id": token_id,
"token_secret": token_secret
}, f)
print(f"✅ Created token file at {token_file}")
modalconfig_file = Path.home() / ".modalconfig"
with open(modalconfig_file, 'w') as f:
f.write(f"token_id = {token_id}\n")
f.write(f"token_secret = {token_secret}\n")
print(f"✅ Created .modalconfig file at {modalconfig_file}")
# Create or update .env file with API keys
env_file = Path.home() / ".env"
env_content = ""
if env_file.exists():
with open(env_file, 'r') as f:
env_content = f.read()
# Update or add OPENAI_API_KEY
if openai_api_key:
if "OPENAI_API_KEY" in env_content:
# Replace existing key
import re
env_content = re.sub(r'OPENAI_API_KEY=.*\n', f'OPENAI_API_KEY={openai_api_key}\n', env_content)
else:
# Add new key
env_content += f'\nOPENAI_API_KEY={openai_api_key}\n'
with open(env_file, 'w') as f:
f.write(env_content)
print(f"✅ Updated OpenAI API key in {env_file}")
# Update or add ANTHROPIC_API_KEY
if anthropic_api_key:
if "ANTHROPIC_API_KEY" in env_content:
# Replace existing key
import re
env_content = re.sub(r'ANTHROPIC_API_KEY=.*\n', f'ANTHROPIC_API_KEY={anthropic_api_key}\n', env_content)
else:
# Add new key
env_content += f'\nANTHROPIC_API_KEY={anthropic_api_key}\n'
with open(env_file, 'w') as f:
f.write(env_content)
print(f"✅ Updated Anthropic API key in {env_file}")
# Update or add OPENROUTER_API_KEY
if openrouter_api_key:
if "OPENROUTER_API_KEY" in env_content:
import re
env_content = re.sub(r'OPENROUTER_API_KEY=.*\n', f'OPENROUTER_API_KEY={openrouter_api_key}\n', env_content)
else:
env_content += f'\nOPENROUTER_API_KEY={openrouter_api_key}\n'
with open(env_file, 'w') as f:
f.write(env_content)
print(f"✅ Updated OpenRouter API key in {env_file}")
# Update or add GROQ_API_KEY
if groq_api_key:
if "GROQ_API_KEY" in env_content:
import re
env_content = re.sub(r'GROQ_API_KEY=.*\n', f'GROQ_API_KEY={groq_api_key}\n', env_content)
else:
env_content += f'\nGROQ_API_KEY={groq_api_key}\n'
with open(env_file, 'w') as f:
f.write(env_content)
print(f"✅ Updated Groq API key in {env_file}")
# Try to use the Modal CLI to set the token
try:
print(f"\n🔄 Setting token via Modal CLI...")
result = subprocess.run(
["modal", "token", "set", "--token-id", token_id, "--token-secret", token_secret, "--profile=fr8mafia", "--no-verify"],
capture_output=True, text=True
)
if result.returncode == 0:
print(f"✅ Successfully set token via Modal CLI")
else:
print(f"❌ Failed to set token via Modal CLI: {result.stderr}")
except Exception as e:
print(f"❌ Error using Modal CLI: {e}")
print(f"\n✅ All token setup completed successfully")
================================================
FILE: python/fix_modal_token.py
================================================
[Binary file]
================================================
FILE: python/fix_modal_token_advanced.py
================================================
#!/usr/bin/env python3
"""
Advanced Modal Token Fixer
This script tries multiple approaches to fix Modal token issues, including:
1. Setting environment variables
2. Creating token files in various formats
3. Using Modal CLI
4. Directly modifying Modal's internal configuration
5. Monkey-patching Modal's authentication system
"""
import os
import sys
import json
import subprocess
import importlib
import inspect
from pathlib import Path
import time
# print("🔧 Advanced Modal Token Fixer")
# Approach 1: Set environment variables
# print("\n📋 Approach 1: Setting environment variables")
# os.environ["MODAL_TOKEN_ID"] = TOKEN_ID
# os.environ["MODAL_TOKEN_SECRET"] = TOKEN_SECRET
# print(f"✅ Set MODAL_TOKEN_ID = [HIDDEN]")
# print(f"✅ Set MODAL_TOKEN_SECRET = [HIDDEN]")
# Approach 2: Create token files in various formats
# print("\n📋 Approach 2: Creating token files in various formats")
modal_dir = Path.home() / ".modal"
modal_dir.mkdir(exist_ok=True)
# Format 1: Standard token.json
token_file = modal_dir / "token.json"
with open(token_file, 'w') as f:
token_data = {
"token_id": TOKEN_ID,
"token_secret": TOKEN_SECRET
}
json.dump(token_data, f)
# print(f"✅ Created token file at {token_file}")
# Format 2: Alternative token.json format
token_file_alt = modal_dir / "token_alt.json"
with open(token_file_alt, 'w') as f:
token_data_alt = {
"id": TOKEN_ID,
"secret": TOKEN_SECRET
}
json.dump(token_data_alt, f)
# print(f"✅ Created alternative token file at {token_file_alt}")
# Format 3: Create .modalconfig file
modalconfig_file = Path.home() / ".modalconfig"
with open(modalconfig_file, 'w') as f:
f.write(f"token_id = {TOKEN_ID}\n")
f.write(f"token_secret = {TOKEN_SECRET}\n")
# print(f"✅ Created .modalconfig file at {modalconfig_file}")
# Format 4: Create config.json file
config_file = modal_dir / "config.json"
with open(config_file, 'w') as f:
config_data = {
"token_id": TOKEN_ID,
"token_secret": TOKEN_SECRET
}
json.dump(config_data, f)
# print(f"✅ Created config.json file at {config_file}")
# Approach 3: Use Modal CLI to set token
# print("\n📋 Approach 3: Using Modal CLI")
try:
# Use the CLI to set the token directly
result = subprocess.run(
["modal", "token", "set", "--token-id", TOKEN_ID, "--token-secret", TOKEN_SECRET, "--profile=fr8mafia", "--no-verify"],
capture_output=True, text=True
)
if result.returncode == 0:
pass
# print(f"✅ Successfully set token via Modal CLI")
else:
pass
# print(f"❌ Failed to set token via Modal CLI: {result.stderr}")
except Exception as e:
pass
# print(f"❌ Error using Modal CLI: {e}")
# Approach 4: Use Modal Python API to set token
# print("\n📋 Approach 4: Using Modal Python API")
try:
import modal
# print(f"✅ Successfully imported Modal")
# Try to set token directly in Modal's config
try:
import modal.config
# Try different approaches to set the token
try:
# Approach 4.1: Set token via _auth_config
if hasattr(modal.config, '_auth_config'):
modal.config._auth_config.token_id = TOKEN_ID
modal.config._auth_config.token_secret = TOKEN_SECRET
# print(f"✅ Set tokens via _auth_config")
except Exception as e:
# print(f"❌ Error setting tokens via _auth_config: {e}")
print("")
try:
# Approach 4.2: Set token via set_token() if it exists
if hasattr(modal.config, 'set_token'):
modal.config.set_token(TOKEN_ID, TOKEN_SECRET)
# print(f"✅ Set tokens via set_token()")
except Exception as e:
# print(f"❌ Error setting tokens via set_token(): {e}")
print("")
try:
# Approach 4.3: Set token via Config
if hasattr(modal.config, 'Config'):
modal.config.Config.token_id = TOKEN_ID
modal.config.Config.token_secret = TOKEN_SECRET
# print(f"✅ Set tokens via Config")
except Exception as e:
# print(f"❌ Error setting tokens via Config: {e}")
print("")
# Approach 4.4: Inspect modal.config and try to find token-related attributes
# print("\n🔍 Inspecting modal.config for token-related attributes...")
for name in dir(modal.config):
if "token" in name.lower() or "auth" in name.lower():
# print(f"Found potential token-related attribute: {name}")
try:
attr = getattr(modal.config, name)
if hasattr(attr, "token_id"):
# print(f" - Setting token_id in {name}")
setattr(attr, "token_id", TOKEN_ID)
if hasattr(attr, "token_secret"):
# print(f" - Setting token_secret in {name}")
setattr(attr, "token_secret", TOKEN_SECRET)
except Exception as e:
# print(f" - Error setting tokens in {name}: {e}")
print("")
except Exception as e:
# print(f"❌ Error setting tokens in Modal config: {e}")
print("")
except Exception as e:
print(f"❌ Error importing Modal: {e}")
# Approach 5: Monkey-patch Modal's authentication system
# print("\n📋 Approach 5: Monkey-patching Modal's authentication system")
try:
import modal
# Define functions that will always return our tokens
def get_token_id(*args, **kwargs):
return TOKEN_ID
def get_token_secret(*args, **kwargs):
return TOKEN_SECRET
# Find all authentication-related classes and functions
auth_related = []
for module_name in dir(modal):
if "auth" in module_name.lower() or "token" in module_name.lower() or "config" in module_name.lower():
try:
module = getattr(modal, module_name)
auth_related.append((module_name, module))
# print(f"Found potential auth-related module: {module_name}")
except Exception:
pass
# Try to monkey-patch auth functions to always return valid credentials
for name, module in auth_related:
if inspect.ismodule(module):
for func_name in dir(module):
if "get" in func_name.lower():
if "token_id" in func_name.lower():
try:
original_func = getattr(module, func_name)
if callable(original_func):
# print(f" - Patching {name}.{func_name} to return token_id")
setattr(module, func_name, get_token_id)
except Exception as e:
# print(f" - Error patching {name}.{func_name}: {e}")
print("")
elif "token_secret" in func_name.lower() or "token" in func_name.lower():
try:
original_func = getattr(module, func_name)
if callable(original_func):
# print(f" - Patching {name}.{func_name} to return token_secret")
setattr(module, func_name, get_token_secret)
except Exception as e:
# print(f" - Error patching {name}.{func_name}: {e}")
print("")
# print(f"✅ Monkey-patching completed")
except Exception as e:
# print(f"❌ Error during monkey-patching: {e}")
print("")
# Approach 6: Test Modal authentication
# print("\n📋 Approach 6: Testing Modal authentication")
try:
import modal
# Create a simple test app
app = modal.App("test-auth-app")
@app.function()
def hello():
return "Hello, world!"
# Try to run the function to test authentication
# print("Creating a test Modal app...")
with app.run() as running_app:
# print("Running the test function...")
result = running_app.hello.remote()
# print(f"✅ Successfully ran Modal function: {result}")
# print("🎉 Modal authentication is working!")
except Exception as e:
# print(f"❌ Error testing Modal authentication: {e}")
print("")
# print("\n✅ Done fixing Modal token. Please try your command again.")
================================================
FILE: python/gitarsenal_keys.py
================================================
#!/usr/bin/env python3
"""
GitArsenal Keys Management Script
Handles API key storage and retrieval for GitArsenal CLI
"""
import os
import sys
import json
import argparse
from pathlib import Path
from credentials_manager import CredentialsManager
def main():
parser = argparse.ArgumentParser(description='GitArsenal Keys Management')
parser.add_argument('command', choices=['add', 'list', 'view', 'delete'], help='Command to execute')
parser.add_argument('--service', help='Service name (openai_api_key, WANDB_API_KEY, HUGGINGFACE_TOKEN, modal_token)')
parser.add_argument('--key', help='API key (for add command)')
parser.add_argument('--json', action='store_true', help='Output in JSON format (for list command)')
args = parser.parse_args()
# Initialize credentials manager
credentials_manager = CredentialsManager()
if args.command == 'add':
handle_add(credentials_manager, args)
elif args.command == 'list':
handle_list(credentials_manager, args)
elif args.command == 'view':
handle_view(credentials_manager, args)
elif args.command == 'delete':
handle_delete(credentials_manager, args)
def handle_add(credentials_manager, args):
"""Handle adding a new API key"""
service = args.service
key = args.key
if not service:
print("❌ Service name is required. Use --service option.")
print("💡 Available service names:")
print(" openai_api_key")
print(" WANDB_API_KEY")
print(" HUGGINGFACE_TOKEN")
print(" modal_token")
print(" gitarsenal_openai_api_key")
print("\n💡 Example: gitarsenal keys add --service openai_api_key")
sys.exit(1)
if not key:
# Prompt for the API key interactively
print(f"\n🔑 {service.upper()} REQUIRED")
print("=" * 50)
# Get appropriate prompt based on service
prompts = {
'openai_api_key': "Please enter your OpenAI API key:\nYou can get your API key from: https://platform.openai.com/api-keys",
'WANDB_API_KEY': "Please enter your Weights & Biases API key:\nYou can get your API key from: https://wandb.ai/authorize",
'HUGGINGFACE_TOKEN': "Please enter your Hugging Face token:\nYou can get your token from: https://huggingface.co/settings/tokens",
'gitarsenal_openai_api_key': "Please enter GitArsenal's OpenAI API key for debugging:",
'modal_token': "Please enter your Modal token:\nYou can get your token from: https://modal.com/account/tokens"
}
prompt = prompts.get(service, f"Please enter your {service}:")
print(prompt)
print("-" * 50)
try:
import getpass
key = getpass.getpass("API Key (hidden): ").strip()
if not key:
print("❌ No API key provided.")
sys.exit(1)
print("✅ API key received successfully!")
except KeyboardInterrupt:
print("\n❌ API key input cancelled by user.")
sys.exit(1)
except Exception as e:
print(f"❌ Error getting API key: {e}")
sys.exit(1)
# Use the service name directly as the credential key
credential_key = service
# Save the credential
credentials = credentials_manager.load_credentials()
credentials[credential_key] = key
success = credentials_manager.save_credentials(credentials)
if success:
print(f"✅ API key for {service} added successfully")
print(f"📁 Stored in: {credentials_manager.credentials_file}")
else:
print("❌ Failed to save API key")
sys.exit(1)
def handle_list(credentials_manager, args=None):
"""Handle listing all stored API keys"""
credentials = credentials_manager.load_credentials()
if args and args.json:
# Return JSON format for programmatic access
print(json.dumps(credentials))
return
if not credentials:
print("📭 No API keys stored")
return
print("🔑 Stored API Keys:")
print("=" * 50)
# Map credential keys to display names (for known services)
key_mapping = {
'openai_api_key': 'OpenAI',
'WANDB_API_KEY': 'Weights & Biases',
'HUGGINGFACE_TOKEN': 'Hugging Face',
'gitarsenal_openai_api_key': 'GitArsenal OpenAI',
'claude_api_key': 'Claude',
'modal_token': 'Modal'
}
for key, value in credentials.items():
# Generate display name from key if not in mapping
if key in key_mapping:
display_name = key_mapping[key]
else:
# Use the key name directly for unknown services
display_name = key
masked_value = value[:8] + "*" * (len(value) - 12) + value[-4:] if len(value) > 12 else "*" * len(value)
print(f" {display_name}: {masked_value}")
print(f"\n📁 Storage location: {credentials_manager.credentials_file}")
print("\n💡 To delete a key, use the exact service name:")
for key in credentials.keys():
print(f" gitarsenal keys delete --service {key}")
def handle_view(credentials_manager, args):
"""Handle viewing a specific API key (masked)"""
service = args.service
if not service:
print("❌ Service name is required. Use --service option.")
print("💡 Available service names:")
print(" openai_api_key")
print(" WANDB_API_KEY")
print(" HUGGINGFACE_TOKEN")
print(" modal_token")
sys.exit(1)
# Use the service name directly as the credential key
credential_key = service
credentials = credentials_manager.load_credentials()
if credential_key not in credentials:
print(f"❌ No API key found for {service}")
print(f"💡 Available keys: {list(credentials.keys())}")
sys.exit(1)
value = credentials[credential_key]
masked_value = value[:8] + "*" * (len(value) - 12) + value[-4:] if len(value) > 12 else "*" * len(value)
print(f"🔑 {service}:")
print(f" {masked_value}")
print(f"📁 Stored in: {credentials_manager.credentials_file}")
def handle_delete(credentials_manager, args):
"""Handle deleting an API key"""
service = args.service
if not service:
print("❌ Service name is required. Use --service option.")
print("💡 Available service names:")
print(" openai_api_key")
print(" WANDB_API_KEY")
print(" HUGGINGFACE_TOKEN")
print(" modal_token")
sys.exit(1)
# Use the service name directly as the credential key
credential_key = service
success = credentials_manager.clear_credential(credential_key)
if success:
print(f"✅ API key for {service} deleted successfully")
else:
print(f"❌ No API key found for {service}")
print("💡 Use 'gitarsenal keys list' to see available keys")
if __name__ == "__main__":
main()
================================================
FILE: python/gitarsenal_proxy_client.py
================================================
#!/usr/bin/env python3
"""
GitArsenal Proxy Client - Integration for Modal Proxy Service
This module provides integration between gitarsenal-cli and the Modal proxy service,
allowing users to use Modal services without exposing the server's Modal token.
"""
import os
import json
import requests
import time
import sys
from pathlib import Path
import getpass
class GitArsenalProxyClient:
"""Client for interacting with the Modal Proxy Service from gitarsenal-cli"""
def __init__(self, base_url=None, api_key=None):
"""Initialize the client with base URL and API key"""
self.base_url = base_url or os.environ.get("MODAL_PROXY_URL")
self.api_key = api_key or os.environ.get("MODAL_PROXY_API_KEY")
# If no URL/API key provided, try to load from config
if not self.base_url or not self.api_key:
config = self.load_config()
if not self.base_url:
self.base_url = config.get("proxy_url")
if not self.api_key:
self.api_key = config.get("api_key")
# If still no URL, use default localhost
if not self.base_url:
self.base_url = "http://127.0.0.1:5001" # Default to local server
# Warn if no API key
if not self.api_key:
print("⚠️ No API key provided. You will need to authenticate with the proxy service.")
def load_config(self):
"""Load proxy configuration from user's home directory"""
config_file = Path.home() / ".gitarsenal" / "proxy_config.json"
if not config_file.exists():
return {}
try:
with open(config_file, 'r') as f:
return json.load(f)
except (json.JSONDecodeError, IOError):
return {}
def save_config(self, config):
"""Save proxy configuration to user's home directory"""
config_dir = Path.home() / ".gitarsenal"
config_file = config_dir / "proxy_config.json"
# Ensure directory exists
if not config_dir.exists():
config_dir.mkdir(parents=True)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
config_dir.chmod(0o700) # Only owner can read/write/execute
try:
with open(config_file, 'w') as f:
json.dump(config, f)
# Set restrictive permissions on Unix-like systems
if os.name == 'posix':
config_file.chmod(0o600) # Only owner can read/write
return True
except IOError as e:
print(f"❌ Error saving proxy configuration: {e}")
return False
def configure(self, interactive=True):
"""Configure the proxy client with URL and API key"""
config = self.load_config()
if interactive:
print("\n" + "="*60)
print("🔧 MODAL PROXY CONFIGURATION")
print("="*60)
print("Configure GitArsenal to use a Modal proxy service.")
print("This allows you to use Modal services without having your own Modal token.")
print("-" * 60)
# Get proxy URL
default_url = config.get("proxy_url", self.base_url)
print(f"\nEnter the URL of the Modal proxy service")
print(f"(Press Enter to use default: {default_url})")
proxy_url = input("Proxy URL: ").strip()
if not proxy_url:
proxy_url = default_url
# Get API key
print("\nEnter your API key for the Modal proxy service")
print("(Contact the proxy service administrator if you don't have one)")
api_key = getpass.getpass("API Key (hidden): ").strip()
# Save configuration
config["proxy_url"] = proxy_url
if api_key:
config["api_key"] = api_key
self.save_config(config)
# Update current instance
self.base_url = proxy_url
if api_key:
self.api_key = api_key
print("\n✅ Proxy configuration saved successfully!")
return True
else:
# Non-interactive configuration
if "proxy_url" in config:
self.base_url = config["proxy_url"]
if "api_key" in config:
self.api_key = config["api_key"]
return "proxy_url" in config and "api_key" in config
def _make_request(self, method, endpoint, data=None, params=None):
"""Make a request to the proxy service"""
url = f"{self.base_url}{endpoint}"
headers = {"X-API-Key": self.api_key} if self.api_key else {}
print(f"🔍 Making {method.upper()} request to: {url}")
try:
if method.lower() == "get":
response = requests.get(url, headers=headers, params=params, timeout=30)
elif method.lower() == "post":
response = requests.post(url, headers=headers, json=data, timeout=30)
else:
raise ValueError(f"Unsupported HTTP method: {method}")
print(f"📥 Response status code: {response.status_code}")
# Check if the response is valid JSON
try:
response_data = response.json()
print(f"📄 Response data received: {str(response_data)[:100]}...")
# Check for errors
if response.status_code >= 400:
return {
"success": False,
"error": response_data.get("error", "Unknown error"),
"status_code": response.status_code
}
# Return successful response
return {
"success": True,
"data": response_data,
"status_code": response.status_code
}
except json.JSONDecodeError:
print(f"⚠️ Invalid JSON response: {response.text[:100]}...")
# If it's HTML and status code is 200, it might be a redirect or proxy issue
if response.status_code == 200 and response.text.strip().startswith(""):
return {
"success": False,
"error": "Received HTML instead of JSON. The proxy server might be behind another proxy or firewall.",
"status_code": response.status_code
}
return {
"success": False,
"error": f"Invalid JSON response: {response.text[:100]}...",
"status_code": response.status_code
}
except requests.exceptions.RequestException as e:
print(f"❌ Request failed: {str(e)}")
return {
"success": False,
"error": f"Request failed: {str(e)}",
"status_code": None
}
def health_check(self):
"""Check if the proxy service is running"""
# Try the API health endpoint first
response = self._make_request("get", "/api/health")
if response["success"]:
return response
# Fall back to the root endpoint
return self._make_request("get", "/")
def create_sandbox(self, gpu_type="A10G", repo_url=None, repo_name=None,
setup_commands=None, volume_name=None, wait=False):
"""Create a Modal sandbox through the proxy service"""
data = {
"gpu_type": gpu_type,
"repo_url": repo_url,
"repo_name": repo_name,
"setup_commands": setup_commands or [],
"volume_name": volume_name
}
response = self._make_request("post", "/api/create-sandbox", data=data)
if not response["success"]:
print(f"❌ Failed to create sandbox: {response['error']}")
return None
sandbox_id = response["data"].get("sandbox_id")
print(f"🚀 Sandbox creation started. ID: {sandbox_id}")
# If wait is True, poll for sandbox status
if wait and sandbox_id:
print("⏳ Waiting for sandbox to be ready...")
max_wait_time = 300 # 5 minutes
poll_interval = 10 # 10 seconds
start_time = time.time()
while time.time() - start_time < max_wait_time:
status_response = self.get_container_status(sandbox_id)
if status_response["success"]:
status_data = status_response["data"]
if status_data.get("status") == "active":
print(f"✅ Sandbox is ready!")
return status_data.get("info")
print(".", end="", flush=True)
time.sleep(poll_interval)
print("\n⚠️ Timed out waiting for sandbox to be ready")
return {"sandbox_id": sandbox_id}
def create_ssh_container(self, gpu_type="A10G", repo_url=None, repo_name=None,
setup_commands=None, volume_name=None, timeout=60, wait=False):
"""Create a Modal SSH container through the proxy service"""
# Verify we have a valid API key
if not self.api_key:
print("❌ No API key provided. Please configure the proxy client first:")
print(" ./gitarsenal.py proxy configure")
return None
# Verify proxy URL is set
if not self.base_url:
print("❌ No proxy URL provided. Please configure the proxy client first:")
print(" ./gitarsenal.py proxy configure")
return None
# Check if proxy is reachable
health = self.health_check()
if not health["success"]:
print(f"❌ Could not connect to proxy service at {self.base_url}")
print(f" Error: {health.get('error', 'Unknown error')}")
print(" Please check if the proxy service is running and properly configured.")
return None
print(f"✅ Connected to proxy service at {self.base_url}")
data = {
"gpu_type": gpu_type,
"repo_url": repo_url,
"repo_name": repo_name,
"setup_commands": setup_commands or [],
"volume_name": volume_name,
"timeout": timeout
}
print("🔄 Sending request to create SSH container...")
response = self._make_request("post", "/api/create-ssh-container", data=data)
if not response["success"]:
print(f"❌ Failed to create SSH container: {response['error']}")
print(f" Status code: {response.get('status_code', 'Unknown')}")
# Additional error handling for common issues
if response.get('status_code') == 401:
print(" Authentication failed. Please check your API key.")
print(" Run './gitarsenal.py proxy configure' to set up a new API key.")
elif response.get('status_code') == 500:
print(" Server error. The proxy service might be misconfigured.")
print(" Check if the MODAL_TOKEN is properly set on the server.")
return None
container_id = response["data"].get("container_id")
ssh_password = response["data"].get("ssh_password")
print(f"🚀 SSH container creation started. ID: {container_id}")
if ssh_password:
print(f"🔐 SSH Password: {ssh_password}")
# If wait is True, poll for container status
if wait and container_id:
print("⏳ Waiting for SSH container to be ready...")
max_wait_time = 300 # 5 minutes
poll_interval = 10 # 10 seconds
start_time = time.time()
while time.time() - start_time < max_wait_time:
status_response = self.get_container_status(container_id)
if status_response["success"]:
status_data = status_response["data"]
if status_data.get("status") == "active":
print(f"✅ SSH container is ready!")
container_info = status_data.get("info", {})
# Add the password back since it's removed in the status endpoint
container_info["ssh_password"] = ssh_password
return container_info
print(".", end="", flush=True)
time.sleep(poll_interval)
print("\n⚠️ Timed out waiting for SSH container to be ready")
print("The container may still be initializing. Check status with:")
print(f"./gitarsenal.py proxy status {container_id}")
return {"container_id": container_id, "ssh_password": ssh_password}
def get_container_status(self, container_id):
"""Get the status of a container"""
return self._make_request("get", f"/api/container-status/{container_id}")
def terminate_container(self, container_id):
"""Terminate a container"""
data = {"container_id": container_id}
return self._make_request("post", "/api/terminate-container", data=data)
if __name__ == "__main__":
# Example usage
if len(sys.argv) < 2:
print("Usage: python gitarsenal_proxy_client.py [command] [options]")
print("Commands: configure, health, create-sandbox, create-ssh, status, terminate")
sys.exit(1)
client = GitArsenalProxyClient()
command = sys.argv[1]
if command == "configure":
client.configure(interactive=True)
elif command == "health":
response = client.health_check()
if response["success"]:
print(f"✅ Proxy service is running: {response['data']['message']}")
else:
print(f"❌ Proxy service health check failed: {response['error']}")
elif command == "create-sandbox":
import argparse
parser = argparse.ArgumentParser(description="Create a Modal sandbox")
parser.add_argument("--gpu", type=str, default="A10G", help="GPU type")
parser.add_argument("--repo", type=str, help="Repository URL")
parser.add_argument("--name", type=str, help="Repository name")
parser.add_argument("--volume", type=str, help="Volume name")
parser.add_argument("--wait", action="store_true", help="Wait for sandbox to be ready")
args = parser.parse_args(sys.argv[2:])
result = client.create_sandbox(
gpu_type=args.gpu,
repo_url=args.repo,
repo_name=args.name,
volume_name=args.volume,
wait=args.wait
)
if result:
print(f"🚀 Sandbox creation initiated: {result}")
elif command == "create-ssh":
import argparse
parser = argparse.ArgumentParser(description="Create a Modal SSH container")
parser.add_argument("--gpu", type=str, default="A10G", help="GPU type")
parser.add_argument("--repo", type=str, help="Repository URL")
parser.add_argument("--name", type=str, help="Repository name")
parser.add_argument("--volume", type=str, help="Volume name")
parser.add_argument("--timeout", type=int, default=60, help="Timeout in minutes")
parser.add_argument("--wait", action="store_true", help="Wait for container to be ready")
args = parser.parse_args(sys.argv[2:])
result = client.create_ssh_container(
gpu_type=args.gpu,
repo_url=args.repo,
repo_name=args.name,
volume_name=args.volume,
timeout=args.timeout,
wait=args.wait
)
if result:
print(f"🚀 SSH container creation initiated: {result}")
elif command == "status":
if len(sys.argv) < 3:
print("Usage: python gitarsenal_proxy_client.py status [container_id]")
sys.exit(1)
container_id = sys.argv[2]
response = client.get_container_status(container_id)
if response["success"]:
print(f"✅ Container status: {json.dumps(response['data'], indent=2)}")
else:
print(f"❌ Failed to get container status: {response['error']}")
elif command == "terminate":
if len(sys.argv) < 3:
print("Usage: python gitarsenal_proxy_client.py terminate [container_id]")
sys.exit(1)
container_id = sys.argv[2]
response = client.terminate_container(container_id)
if response["success"]:
print(f"✅ Container terminated: {response['data']['message']}")
else:
print(f"❌ Failed to terminate container: {response['error']}")
else:
print(f"❌ Unknown command: {command}")
print("Available commands: configure, health, create-sandbox, create-ssh, status, terminate")
sys.exit(1)
================================================
FILE: python/llm_debugging.py
================================================
import os
import re
import json
import requests
import time
import getpass
from pathlib import Path
def get_stored_credentials():
"""Load stored credentials from ~/.gitarsenal/credentials.json"""
credentials_file = Path.home() / ".gitarsenal" / "credentials.json"
if credentials_file.exists():
with open(credentials_file, 'r') as f:
return json.load(f)
return {}
def generate_auth_context(stored_credentials):
"""Generate authentication context for the LLM prompt"""
if not stored_credentials:
return "No stored credentials available."
auth_context = "Available stored credentials (use actual values in commands):\n"
for key, value in stored_credentials.items():
masked_value = value[:8] + "..." if len(value) > 8 else "***"
auth_context += f"- {key}: {masked_value} (actual value: {value})\n"
return auth_context
def get_current_debug_model():
"""Get the currently configured debugging model preference"""
return os.environ.get("GITARSENAL_DEBUG_MODEL", "anthropic")
def _to_str(maybe_bytes):
"""Convert bytes to string safely"""
try:
return maybe_bytes.decode('utf-8') if isinstance(maybe_bytes, (bytes, bytearray)) else maybe_bytes
except UnicodeDecodeError:
if isinstance(maybe_bytes, (bytes, bytearray)):
return maybe_bytes.decode('utf-8', errors='replace')
return str(maybe_bytes)
except Exception:
return str(maybe_bytes)
def get_api_key(provider):
"""Get API key for the specified provider from multiple sources"""
env_var_map = {
"openai": "OPENAI_API_KEY",
"anthropic": "ANTHROPIC_API_KEY",
"openrouter": "OPENROUTER_API_KEY",
"groq": "GROQ_API_KEY"
}
key_file_map = {
"openai": "openai_key",
"anthropic": "anthropic_key",
"openrouter": "openrouter_key",
"groq": "groq_key"
}
token_index_map = {
"openai": 2,
"anthropic": 3,
"openrouter": 4,
"groq": 5,
}
env_var = env_var_map.get(provider)
if not env_var:
return None
# Try environment variable first
api_key = os.environ.get(env_var)
if api_key:
return api_key
# Try fetch from server
try:
from fetch_modal_tokens import get_tokens
tokens = get_tokens()
token_index = token_index_map.get(provider)
if token_index is not None and len(tokens) > token_index:
api_key = tokens[token_index]
if api_key:
os.environ[env_var] = api_key
return api_key
except Exception:
pass
# Try credentials manager
try:
from credentials_manager import CredentialsManager
credentials_manager = CredentialsManager()
method_name = f"get_{provider}_api_key"
if hasattr(credentials_manager, method_name):
api_key = getattr(credentials_manager, method_name)()
if api_key:
os.environ[env_var] = api_key
return api_key
except Exception:
pass
# Try saved file
try:
key_file = Path.home() / ".gitarsenal" / key_file_map[provider]
if key_file.exists():
api_key = key_file.read_text().strip()
if api_key:
os.environ[env_var] = api_key
return api_key
except Exception:
pass
return None
def save_api_key(provider, api_key):
"""Save API key to persistent file"""
key_file_map = {
"openai": "openai_key",
"anthropic": "anthropic_key",
"openrouter": "openrouter_key",
"groq": "groq_key"
}
try:
gitarsenal_dir = Path.home() / ".gitarsenal"
gitarsenal_dir.mkdir(exist_ok=True)
key_file = gitarsenal_dir / key_file_map[provider]
key_file.write_text(api_key)
except Exception as e:
print(f"⚠️ Could not save {provider} API key: {e}")
def gather_context(sandbox, current_dir):
"""Gather system and directory context for debugging"""
system_info = ""
directory_context = ""
file_context = ""
if not sandbox:
return system_info, directory_context, file_context
# Get system information
try:
os_info_cmd = """
echo "OS Information:"
cat /etc/os-release 2>/dev/null || echo "OS release info not available"
echo -e "\nKernel Information:"
uname -a
echo -e "\nPython Information:"
python --version
pip --version
"""
os_result = sandbox.exec("bash", "-c", os_info_cmd)
os_output = ""
for line in os_result.stdout:
os_output += _to_str(line)
os_result.wait()
system_info = f"\nSystem Information:\n{os_output}"
except Exception:
system_info = "System information not available\n"
# Get directory context
if current_dir:
try:
ls_result = sandbox.exec("bash", "-c", "ls -la")
ls_output = ""
for line in ls_result.stdout:
ls_output += _to_str(line)
ls_result.wait()
directory_context = f"\nCurrent directory contents:\n{ls_output}"
# Check for common config files
common_config_files = ["package.json", "requirements.txt", "pyproject.toml", "setup.py"]
relevant_files = []
for config_file in common_config_files:
check_cmd = f"test -f {current_dir}/{config_file}"
check_result = sandbox.exec("bash", "-c", check_cmd)
check_result.wait()
if check_result.returncode == 0:
relevant_files.append(f"{current_dir}/{config_file}")
# Get content of relevant files (limit to 2)
if relevant_files:
file_context = "\nRelevant file contents:\n"
for file_path in relevant_files[:2]:
try:
cat_result = sandbox.exec("bash", "-c", f"cat {file_path}")
file_content = ""
for line in cat_result.stdout:
file_content += _to_str(line)
cat_result.wait()
if len(file_content) > 1000:
file_content = file_content[:1000] + "\n... (truncated)"
file_context += f"\n--- {file_path} ---\n{file_content}\n"
except Exception:
continue
except Exception:
directory_context = f"\nCurrent directory: {current_dir}\n"
return system_info, directory_context, file_context
def create_debug_prompt(command, error_output, system_info, directory_context, file_context, auth_context):
"""Create the debugging prompt for LLM"""
return f"""
I'm trying to run the following command in a Linux environment:
```
{command}
```
But it failed with this error:
```
{error_output}
```
{system_info}
{directory_context}
{file_context}
AVAILABLE CREDENTIALS:
{auth_context}
Please analyze the error and provide ONLY a single terminal command that would fix the issue.
Consider the current directory, system information, directory contents, and available credentials carefully before suggesting a solution.
IMPORTANT GUIDELINES:
1. For any commands that might ask for yes/no confirmation, use the appropriate non-interactive flag:
- For apt/apt-get: use -y or --yes
- For rm: use -f or --force
2. If the error indicates a file is not found:
- FIRST try to search for the file using: find . -name "filename" -type f 2>/dev/null
- If found, navigate to that directory using: cd /path/to/directory
- If not found, then consider creating the file or installing missing packages
3. For missing packages or dependencies:
- Use pip install for Python packages
- Use apt-get install -y for system packages
- Use npm install for Node.js packages
4. For authentication issues:
- Analyze the error to determine what type of authentication is needed
- ALWAYS use the actual credential values from the AVAILABLE CREDENTIALS section above (NOT placeholders)
- Look for the specific API key or token needed in the auth_context and use its exact value
5. Environment variable exports:
- Use export commands for API keys that need to be in environment
- ALWAYS use the actual credential values from auth_context, never use placeholders like "YOUR_API_KEY"
6. For Git SSH authentication failures:
- If the error contains "Host key verification failed" or "Could not read from remote repository"
- ALWAYS convert SSH URLs to HTTPS URLs for public repositories
- Replace git@github.com:username/repo.git with https://github.com/username/repo.git
Do not provide any explanations, just the exact command to run.
"""
def extract_command_from_response(response_text):
"""Extract the actual command from LLM response"""
fix_command = response_text.strip()
# Extract from code blocks
if "```" in fix_command:
code_blocks = re.findall(r'```(?:bash|sh)?\s*(.*?)\s*```', fix_command, re.DOTALL)
if code_blocks:
fix_command = code_blocks[0].strip()
# If multi-line, try to find the actual command
if len(fix_command.split('\n')) > 1:
command_prefixes = ['sudo', 'apt', 'pip', 'npm', 'yarn', 'git', 'cd', 'mv', 'cp', 'rm', 'mkdir', 'touch',
'chmod', 'chown', 'echo', 'cat', 'python', 'python3', 'node', 'export',
'curl', 'wget', 'docker', 'make', 'conda', 'uv', 'poetry']
command_lines = [line.strip() for line in fix_command.split('\n')
if any(line.strip().startswith(prefix) for prefix in command_prefixes)]
if command_lines:
fix_command = command_lines[0]
else:
# Try shell patterns
shell_patterns = [' | ', ' > ', ' >> ', ' && ', ' || ', ' ; ', '$(', '`', ' -y ', ' --yes ']
command_lines = [line.strip() for line in fix_command.split('\n')
if any(pattern in line for pattern in shell_patterns)]
if command_lines:
fix_command = command_lines[0]
else:
# Use shortest non-empty line
lines = [line.strip() for line in fix_command.split('\n') if line.strip()]
if lines:
valid_lines = [line for line in lines if len(line) > 5]
fix_command = min(valid_lines, key=len) if valid_lines else min(lines, key=len)
# Clean up the command
fix_command = fix_command.rstrip('.;"\'')
# Remove common prefixes
prefixes_to_remove = [
"Run: ", "Execute: ", "Try: ", "Command: ", "Fix: ", "Solution: ",
"You should run: ", "You can run: ", "You need to run: "
]
for prefix in prefixes_to_remove:
if fix_command.startswith(prefix):
fix_command = fix_command[len(prefix):].strip()
break
return fix_command
def make_api_request(provider, api_key, prompt, retries=2):
"""Make API request to the specified provider"""
if provider == "openai":
return make_openai_request(api_key, prompt, retries)
elif provider == "anthropic":
return make_anthropic_request(api_key, prompt, retries)
elif provider == "openrouter":
return make_openrouter_request(api_key, prompt, retries)
elif provider == "groq":
return make_groq_request(api_key, prompt, retries)
else:
return None
def make_openai_request(api_key, prompt, retries=2):
"""Make request to OpenAI API"""
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"model": "gpt-4.1",
"messages": [
{"role": "system", "content": "You are a debugging assistant. Provide only the terminal command to fix the issue."},
{"role": "user", "content": prompt}
],
"temperature": 0.2,
"max_tokens": 300
}
for attempt in range(retries + 1):
try:
if attempt > 0:
time.sleep(1.5 * (2 ** (attempt - 1)))
response = requests.post(
"https://api.openai.com/v1/chat/completions",
headers=headers,
json=payload,
timeout=45
)
if response.status_code == 200:
result = response.json()
return result["choices"][0]["message"]["content"]
elif response.status_code == 401:
print("❌ Invalid OpenAI API key")
return None
elif response.status_code in [429, 500]:
continue # Retry
else:
print(f"⚠️ OpenAI API error: {response.status_code}")
return None
except (requests.exceptions.Timeout, requests.exceptions.ConnectionError):
continue # Retry
except Exception as e:
print(f"⚠️ OpenAI request error: {e}")
return None
return None
def make_anthropic_request(api_key, prompt, retries=2):
"""Make request to Anthropic API"""
headers = {
"x-api-key": api_key,
"anthropic-version": "2023-06-01",
"content-type": "application/json"
}
payload = {
"model": "claude-sonnet-4-20250514",
"max_tokens": 300,
"messages": [{"role": "user", "content": prompt}]
}
for attempt in range(retries + 1):
try:
if attempt > 0:
time.sleep(1.5 * (2 ** (attempt - 1)))
response = requests.post(
"https://api.anthropic.com/v1/messages",
headers=headers,
json=payload,
timeout=45
)
if response.status_code == 200:
result = response.json()
return result["content"][0]["text"]
elif response.status_code == 401:
print("❌ Invalid Anthropic API key")
return None
elif response.status_code in [429, 500]:
continue # Retry
else:
print(f"⚠️ Anthropic API error: {response.status_code}")
return None
except (requests.exceptions.Timeout, requests.exceptions.ConnectionError):
continue # Retry
except Exception as e:
print(f"⚠️ Anthropic request error: {e}")
return None
return None
def make_openrouter_request(api_key, prompt, retries=2):
"""Make request to OpenRouter API"""
headers = {
"x-api-key": api_key,
"content-type": "application/json"
}
payload = {
"model": "openai/gpt-5-mini",
"max_tokens": 300,
"messages": [{"role": "user", "content": prompt}]
}
for attempt in range(retries + 1):
try:
if attempt > 0:
time.sleep(1.5 * (2 ** (attempt - 1)))
response = requests.post(
"https://openrouter.ai/api/v1/chat/completions",
headers=headers,
json=payload,
timeout=45
)
if response.status_code == 200:
result = response.json()
return result["choices"][0]["message"]["content"]
elif response.status_code == 401:
print("❌ Invalid OpenRouter API key")
return None
elif response.status_code in [429, 500]:
continue # Retry
else:
print(f"⚠️ OpenRouter API error: {response.status_code}")
return None
except (requests.exceptions.Timeout, requests.exceptions.ConnectionError):
continue # Retry
except Exception as e:
print(f"⚠️ OpenRouter request error: {e}")
return None
return None
def make_groq_request(api_key, prompt, retries=2):
"""Make request to Groq API (OpenAI-compatible endpoint)"""
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {api_key}"
}
payload = {
"model": os.environ.get("GROQ_MODEL", "openai/gpt-oss-20b"),
"messages": [
{"role": "system", "content": "You are a debugging assistant. Provide only the terminal command to fix the issue."},
{"role": "user", "content": prompt}
],
"temperature": 0.2,
"max_tokens": 300
}
endpoint = os.environ.get("GROQ_BASE_URL", "https://api.groq.com/openai/v1/chat/completions")
for attempt in range(retries + 1):
try:
if attempt > 0:
time.sleep(1.5 * (2 ** (attempt - 1)))
response = requests.post(
endpoint,
headers=headers,
json=payload,
timeout=45
)
if response.status_code == 200:
result = response.json()
return result["choices"][0]["message"]["content"]
elif response.status_code == 401:
print("❌ Invalid Groq API key")
return None
elif response.status_code in [429, 500]:
continue # Retry
else:
print(f"⚠️ Groq API error: {response.status_code}")
return None
except (requests.exceptions.Timeout, requests.exceptions.ConnectionError):
continue # Retry
except Exception as e:
print(f"⚠️ Groq request error: {e}")
return None
return None
def get_provider_rotation_order(preferred=None):
"""Return provider rotation order starting with preferred if valid."""
default_order = ["anthropic", "openai", "groq", "openrouter"]
if preferred and preferred in default_order:
return [preferred] + [p for p in default_order if p != preferred]
return default_order
def call_llm_for_debug(command, error_output, api_key=None, current_dir=None, sandbox=None, use_web_search=False):
"""Unified function to call LLM for debugging with provider rotation"""
# Skip debugging for test commands
if command.strip().startswith("test "):
return None
# Validate error output
if not error_output or not error_output.strip():
print("⚠️ Error output is empty. Cannot debug effectively.")
return None
# Gather context once
system_info, directory_context, file_context = gather_context(sandbox, current_dir)
stored_credentials = get_stored_credentials()
auth_context = generate_auth_context(stored_credentials)
prompt = create_debug_prompt(command, error_output, system_info, directory_context, file_context, auth_context)
# Determine rotation order
preferred = get_current_debug_model()
providers = get_provider_rotation_order(preferred)
# Try providers in order
for provider in providers:
print(f"🔍 Using {provider.upper()} for debugging...")
this_api_key = api_key if api_key and provider == preferred else get_api_key(provider)
if not this_api_key:
print(f"❌ No {provider} API key available. Skipping.")
continue
# Save key for reuse
save_api_key(provider, this_api_key)
# Make API request via unified adapter
response_text = make_api_request(provider, this_api_key, prompt)
if response_text:
fix_command = extract_command_from_response(response_text)
print(f"🔧 Suggested fix ({provider}): {fix_command}")
return fix_command
else:
print(f"⚠️ {provider} did not return a valid response. Trying next provider...")
print("❌ All providers failed to produce a fix command.")
return None
def call_llm_for_batch_debug(failed_commands, api_key=None, current_dir=None, sandbox=None, use_web_search=False):
"""Call LLM for batch debugging of multiple failed commands with provider rotation"""
if not failed_commands:
return []
# Prepare context for batch analysis
context_parts = [f"Current directory: {current_dir}", f"Sandbox available: {sandbox is not None}"]
for i, failed_cmd in enumerate(failed_commands, 1):
cmd_type = failed_cmd.get('type', 'main')
original_cmd = failed_cmd.get('original_command', '')
cmd_text = failed_cmd['command']
stderr = failed_cmd.get('stderr', '')
stdout = failed_cmd.get('stdout', '')
context_parts.append(f"\n--- Failed Command {i} ({cmd_type}) ---")
context_parts.append(f"Command: {cmd_text}")
if original_cmd and original_cmd != cmd_text:
context_parts.append(f"Original Command: {original_cmd}")
if stderr:
context_parts.append(f"Error Output: {stderr}")
if stdout:
context_parts.append(f"Standard Output: {stdout}")
# Create batch prompt once
prompt = f"""You are a debugging assistant analyzing multiple failed commands.
ENVIRONMENT: All commands are running on a Unix/Linux environment (bash shell), so only suggest Unix-compatible commands. Do not suggest Windows-specific commands or PowerShell commands.
Context:
{chr(10).join(context_parts)}
Please analyze each failed command and provide a fix command for each one. For each failed command, respond with:
FIX_COMMAND_{{i}}:
REASON_{{i}}:
Guidelines:
- For file not found errors, first search for the file using 'find . -name filename -type f'
- For missing packages, use appropriate package managers (pip, apt-get, npm)
- For Git SSH authentication failures, convert SSH URLs to HTTPS URLs
- For permission errors, suggest commands with sudo if appropriate
- Keep each fix command simple and focused on the specific error
Provide fixes for all {len(failed_commands)} failed commands:"""
# Determine rotation order
preferred = get_current_debug_model()
providers = get_provider_rotation_order(preferred)
# Try providers in order
for provider in providers:
print(f"🤖 Calling {provider.upper()} for batch debugging of {len(failed_commands)} commands...")
this_api_key = api_key if api_key and provider == preferred else get_api_key(provider)
if not this_api_key:
print(f"❌ No {provider} API key available for batch debugging. Skipping.")
continue
save_api_key(provider, this_api_key)
response_text = make_api_request(provider, this_api_key, prompt)
if not response_text:
print(f"⚠️ {provider} returned no response. Trying next provider...")
continue
# Parse the response to extract fix commands
fixes = []
for i in range(1, len(failed_commands) + 1):
fix_pattern = f"FIX_COMMAND_{i}: (.+)"
reason_pattern = f"REASON_{i}: (.+)"
fix_match = re.search(fix_pattern, response_text, re.MULTILINE)
reason_match = re.search(reason_pattern, response_text, re.MULTILINE)
if fix_match:
fix_command = fix_match.group(1).strip()
reason = reason_match.group(1).strip() if reason_match else "LLM suggested fix"
# Clean up the fix command
if fix_command.startswith('`') and fix_command.endswith('`'):
fix_command = fix_command[1:-1]
fixes.append({
'original_command': failed_commands[i-1]['command'],
'fix_command': fix_command,
'reason': reason,
'command_index': i-1
})
print(f"🔧 Generated {len(fixes)} fix commands from batch analysis using {provider}")
return fixes
print("❌ All providers failed to produce batch fixes.")
return []
# Legacy function aliases for backward compatibility
def call_openai_for_debug(command, error_output, api_key=None, current_dir=None, sandbox=None):
"""Legacy OpenAI-specific function - now routes to unified function"""
return call_llm_for_debug(command, error_output, api_key, current_dir, sandbox)
def call_anthropic_for_debug(command, error_output, api_key=None, current_dir=None, sandbox=None):
"""Legacy Anthropic-specific function - now routes to unified function"""
return call_llm_for_debug(command, error_output, api_key, current_dir, sandbox)
def call_openrouter_for_debug(command, error_output, api_key=None, current_dir=None, sandbox=None):
"""Legacy OpenRouter-specific function - now routes to unified function"""
return call_llm_for_debug(command, error_output, api_key, current_dir, sandbox)
def call_openai_for_batch_debug(failed_commands, api_key=None, current_dir=None, sandbox=None):
"""Legacy OpenAI batch function - now routes to unified function"""
return call_llm_for_batch_debug(failed_commands, api_key, current_dir, sandbox)
def call_anthropic_for_batch_debug(failed_commands, api_key=None, current_dir=None, sandbox=None):
"""Legacy Anthropic batch function - now routes to unified function"""
return call_llm_for_batch_debug(failed_commands, api_key, current_dir, sandbox)
def call_openrouter_for_batch_debug(failed_commands, api_key=None, current_dir=None, sandbox=None):
"""Legacy OpenRouter batch function - now routes to unified function"""
return call_llm_for_batch_debug(failed_commands, api_key, current_dir, sandbox)
def call_groq_for_debug(command, error_output, api_key=None, current_dir=None, sandbox=None):
"""Legacy Groq-specific function - now routes to unified function"""
return call_llm_for_debug(command, error_output, api_key, current_dir, sandbox)
def call_groq_for_batch_debug(failed_commands, api_key=None, current_dir=None, sandbox=None):
"""Legacy Groq batch function - now routes to unified function"""
return call_llm_for_batch_debug(failed_commands, api_key, current_dir, sandbox)
================================================
FILE: python/requirements.txt
================================================
modal
requests
pathlib
python-dotenv
flask
flask-cors
pexpect
anthropic
gitingest
exa-py
================================================
FILE: python/setup.py
================================================
from setuptools import setup, find_packages
setup(
name="gitarsenal-python",
version="0.1.0",
description="GitArsenal Python utilities for Modal containers",
packages=find_packages(),
install_requires=[
"modal",
"requests",
"openai",
"anthropic",
"exa-py"
],
python_requires=">=3.8",
)
================================================
FILE: python/setup_modal_token.py
================================================
#!/usr/bin/env python3
"""
Modal Token Setup Script for GitArsenal CLI
This script ensures that the Modal token is properly set up in the environment
before running any Modal operations. It uses a built-in token for the freemium service
instead of requiring user input.
"""
import os
import sys
from pathlib import Path
import logging
# Configure logging
logging.basicConfig(
level=logging.INFO,
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
)
logger = logging.getLogger("modal-setup")
# Built-in Modal token for the freemium service
# This token is used for all users of the package
# Modal tokens are in the format: ak-xxxxxxxxxxxxxxxxxx
BUILT_IN_MODAL_TOKEN = "ak-eNMIXRdfbvpxIXcSHKPFQW" # Your actual token
def setup_modal_token():
"""
Set up Modal token in the environment.
Uses the built-in token for the freemium service.
Returns:
bool: True if token was set up successfully, False otherwise
"""
# Check if token is already in environment
if os.environ.get("MODAL_TOKEN_ID") and os.environ.get("MODAL_TOKEN"):
logger.info("Modal token already set in environment")
return True
# Set the built-in token in the environment
os.environ["MODAL_TOKEN_ID"] = BUILT_IN_MODAL_TOKEN
os.environ["MODAL_TOKEN"] = BUILT_IN_MODAL_TOKEN
logger.info("Built-in Modal token set in environment")
# Also create the token file in the expected location
try:
modal_dir = Path.home() / ".modal"
modal_dir.mkdir(exist_ok=True)
token_file = modal_dir / "token.json"
with open(token_file, 'w') as f:
f.write(f'{{"token_id": "{BUILT_IN_MODAL_TOKEN}", "token": "{BUILT_IN_MODAL_TOKEN}"}}')
logger.info(f"Created Modal token file at {token_file}")
except Exception as e:
logger.warning(f"Failed to create Modal token file: {e}")
return True
if __name__ == "__main__":
if setup_modal_token():
print("✅ Modal token set up successfully")
sys.exit(0)
else:
print("❌ Failed to set up Modal token")
sys.exit(1)
================================================
FILE: python/shell.py
================================================
import threading
import subprocess
import os
import time
import uuid
import re
def get_stored_credentials():
"""Load stored credentials from ~/.gitarsenal/credentials.json"""
import json
from pathlib import Path
try:
credentials_file = Path.home() / ".gitarsenal" / "credentials.json"
if credentials_file.exists():
with open(credentials_file, 'r') as f:
credentials = json.load(f)
return credentials
else:
return {}
except Exception as e:
print(f"⚠️ Error loading stored credentials: {e}")
return {}
class PersistentShell:
"""A persistent bash shell using subprocess.Popen for executing commands with state persistence."""
def __init__(self, working_dir="/root", timeout=60):
self.working_dir = working_dir
self.timeout = timeout
self.process = None
self.stdout_lines = [] # Use list instead of queue
self.stderr_lines = [] # Use list instead of queue
self.stdout_lock = threading.Lock()
self.stderr_lock = threading.Lock()
self.stdout_thread = None
self.stderr_thread = None
self.command_counter = 0
self.is_running = False
self.virtual_env_path = None # Track activated virtual environment
self.suggested_alternative = None # Store suggested alternative commands
self.should_remove_command = False # Flag to indicate if a command should be removed
self.removal_reason = None # Reason for removing a command
def start(self):
"""Start the persistent bash shell."""
if self.is_running:
return
print(f"🐚 Starting persistent bash shell in {self.working_dir}")
# Start bash with unbuffered output
self.process = subprocess.Popen(
['bash', '-i'], # Interactive bash
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.PIPE,
text=True,
bufsize=0, # Unbuffered
cwd=self.working_dir,
preexec_fn=os.setsid # Create new process group
)
# Start threads to read stdout and stderr
self.stdout_thread = threading.Thread(target=self._read_stdout, daemon=True)
self.stderr_thread = threading.Thread(target=self._read_stderr, daemon=True)
self.stdout_thread.start()
self.stderr_thread.start()
self.is_running = True
# Initial setup commands
self._send_command_raw("set +h") # Disable hash table for commands
self._send_command_raw("export PS1='$ '") # Simpler prompt
self._send_command_raw("cd " + self.working_dir) # Change to working directory
time.sleep(0.5) # Let initial commands settle
def _read_stdout(self):
"""Read stdout in a separate thread."""
while self.process and self.process.poll() is None:
try:
line = self.process.stdout.readline()
if line:
with self.stdout_lock:
self.stdout_lines.append(line.rstrip('\n'))
else:
time.sleep(0.01)
except Exception as e:
print(f"Error reading stdout: {e}")
break
def _read_stderr(self):
"""Read stderr in a separate thread."""
while self.process and self.process.poll() is None:
try:
line = self.process.stderr.readline()
if line:
with self.stderr_lock:
self.stderr_lines.append(line.rstrip('\n'))
else:
time.sleep(0.01)
except Exception as e:
print(f"Error reading stderr: {e}")
break
def _send_command_raw(self, command):
"""Send a raw command to the shell without waiting for completion."""
if not self.is_running or not self.process:
raise RuntimeError("Shell is not running")
try:
self.process.stdin.write(command + '\n')
self.process.stdin.flush()
except Exception as e:
print(f"Error sending command: {e}")
raise
def _preprocess_command(self, command):
"""Preprocess commands to handle special cases like virtual environment activation."""
# Handle virtual environment creation and activation
if "uv venv" in command and "&&" in command and "source" in command:
# Split the compound command into separate parts
parts = [part.strip() for part in command.split("&&")]
return parts
elif command.strip().startswith("source ") and "/bin/activate" in command:
# Handle standalone source command
venv_path = command.replace("source ", "").replace("/bin/activate", "").strip()
self.virtual_env_path = venv_path
return [command]
elif "source" in command and "activate" in command:
# Handle any other source activation pattern
return [command]
elif "uv pip install" in command and self.is_in_venv():
# If we're in a virtual environment, ensure we use the right pip
return [command]
else:
return [command]
def execute(self, command, timeout=None):
"""Execute a command and return (success, stdout, stderr)."""
if not self.is_running:
self.start()
if timeout is None:
timeout = self.timeout
# Preprocess the command to handle special cases
command_parts = self._preprocess_command(command)
# If we have multiple parts, execute them sequentially
if len(command_parts) > 1:
print(f"🔧 Executing compound command in {len(command_parts)} parts")
all_stdout = []
all_stderr = []
for i, part in enumerate(command_parts):
print(f" Part {i+1}/{len(command_parts)}: {part}")
success, stdout, stderr = self._execute_single(part, timeout)
if stdout:
all_stdout.append(stdout)
if stderr:
all_stderr.append(stderr)
if not success:
# If any part fails, return the failure
return False, '\n'.join(all_stdout), '\n'.join(all_stderr)
# Small delay between parts to let environment changes take effect
time.sleep(0.1)
return True, '\n'.join(all_stdout), '\n'.join(all_stderr)
else:
return self._execute_single(command_parts[0], timeout)
def _execute_single(self, command, timeout):
"""Execute a single command and return (success, stdout, stderr)."""
self.command_counter += 1
marker = f"CMD_DONE_{self.command_counter}_{uuid.uuid4().hex[:8]}"
print(f"🔧 Executing: {command}", flush=True)
# Clear any existing output
self._clear_lines()
# Wait for shell to be ready (prompt should be visible)
if not self.wait_for_prompt(timeout=2):
# print("⚠️ Shell not ready, waiting...")
time.sleep(0.5)
# For source commands, we need special handling
if command.strip().startswith("source "):
# Send the source command in a way that preserves the environment
try:
# Extract the virtual environment path
venv_path = command.replace("source ", "").replace("/bin/activate", "").strip()
# Use a more robust approach that actually activates the environment
activation_script = f"""
if [ -f "{venv_path}/bin/activate" ]; then
source "{venv_path}/bin/activate"
echo "VIRTUAL_ENV=$VIRTUAL_ENV"
echo "PATH=$PATH"
echo 'SOURCE_SUCCESS'
else
echo 'SOURCE_FAILED - activation script not found'
fi
"""
self._send_command_raw(activation_script)
time.sleep(0.3) # Give more time for environment changes
self._send_command_raw(f'echo "EXIT_CODE:$?"')
self._send_command_raw(f'echo "{marker}"')
except Exception as e:
return False, "", f"Failed to send source command: {e}"
else:
# Send the command followed by markers
try:
self._send_command_raw(command)
# Wait a moment for the command to start
time.sleep(0.1)
self._send_command_raw(f'echo "EXIT_CODE:$?"')
self._send_command_raw(f'echo "{marker}"')
except Exception as e:
return False, "", f"Failed to send command: {e}"
# Collect output until we see the marker
command_stdout = []
command_stderr = []
start_time = time.time()
found_marker = False
exit_code = None
last_stdout_index = 0
last_stderr_index = 0
source_success = None
while time.time() - start_time < timeout:
# Check for new stdout lines
with self.stdout_lock:
current_stdout = self.stdout_lines[last_stdout_index:]
last_stdout_index = len(self.stdout_lines)
for line in current_stdout:
if line == marker:
found_marker = True
break
elif line.startswith("EXIT_CODE:"):
try:
exit_code = int(line.split(":", 1)[1])
except (ValueError, IndexError):
exit_code = 1
elif line == "SOURCE_SUCCESS":
source_success = True
elif line.startswith("SOURCE_FAILED"):
source_success = False
command_stderr.append(line)
elif line.startswith("VIRTUAL_ENV="):
# Extract and store the virtual environment path
venv_path = line.split("=", 1)[1]
self.virtual_env_path = venv_path
command_stdout.append(line)
elif line.startswith("PATH="):
# Store the updated PATH
command_stdout.append(line)
elif line.strip() and not line.startswith("$"): # Skip empty lines and prompt lines
command_stdout.append(line)
# Print line immediately for real-time streaming
print(line, flush=True)
if found_marker:
break
# Check for new stderr lines
with self.stderr_lock:
current_stderr = self.stderr_lines[last_stderr_index:]
last_stderr_index = len(self.stderr_lines)
for line in current_stderr:
if line.strip(): # Skip empty lines
command_stderr.append(line)
# Print stderr immediately for real-time streaming
print(f"{line}", flush=True)
# Check if command is waiting for user input
if not found_marker and time.time() - start_time > 5: # Wait at least 5 seconds before checking
if self._is_waiting_for_input(command_stdout, command_stderr):
print("⚠️ Command appears to be waiting for user input")
# Try to handle the input requirement
input_handled = self._handle_input_requirement(command, command_stdout, command_stderr)
if input_handled is True and self.should_remove_command:
# If LLM suggested to remove the command
self._send_command_raw("\x03") # Send Ctrl+C
time.sleep(0.5)
return False, '\n'.join(command_stdout), f"Command removed - {self.removal_reason}"
elif not input_handled:
# If we couldn't handle the input, abort the command
self._send_command_raw("\x03") # Send Ctrl+C
time.sleep(0.5)
return False, '\n'.join(command_stdout), "Command aborted - requires user input"
time.sleep(0.1)
if not found_marker:
print(f"⚠️ Command timed out after {timeout} seconds")
return False, '\n'.join(command_stdout), f"Command timed out after {timeout} seconds"
stdout_text = '\n'.join(command_stdout)
stderr_text = '\n'.join(command_stderr)
# Determine success based on multiple factors
if source_success is not None:
success = source_success
else:
success = exit_code == 0 if exit_code is not None else len(command_stderr) == 0
if success:
# Don't print the summary output since we already streamed it line by line
pass
# Track virtual environment activation
if command.strip().startswith("source ") and "/bin/activate" in command:
venv_path = command.replace("source ", "").replace("/bin/activate", "").strip()
self.virtual_env_path = venv_path
print(f"✅ Virtual environment activated: {venv_path}")
else:
print(f"❌ Command failed with exit code: {exit_code}")
if stderr_text:
print(f"❌ Error: {stderr_text}")
# Wait a moment for the shell to be ready for the next command
time.sleep(0.2)
return success, stdout_text, stderr_text
def _is_waiting_for_input(self, stdout_lines, stderr_lines):
"""Detect if a command is waiting for user input."""
# Common patterns that indicate waiting for user input
input_patterns = [
r'(?i)(y/n|yes/no)\??\s*$', # Yes/No prompts
r'(?i)password:?\s*$', # Password prompts
r'(?i)continue\??\s*$', # Continue prompts
r'(?i)proceed\??\s*$', # Proceed prompts
r'\[\s*[Yy]/[Nn]\s*\]\s*$', # [Y/n] style prompts
r'(?i)username:?\s*$', # Username prompts
r'(?i)token:?\s*$', # Token prompts
r'(?i)api key:?\s*$', # API key prompts
r'(?i)press enter to continue', # Press enter prompts
r'(?i)select an option:?\s*$', # Selection prompts
r'(?i)choose an option:?\s*$', # Choice prompts
]
# Check the last few lines of stdout and stderr for input patterns
last_lines = []
if stdout_lines:
last_lines.extend(stdout_lines[-3:]) # Check last 3 lines of stdout
if stderr_lines:
last_lines.extend(stderr_lines[-3:]) # Check last 3 lines of stderr
for line in last_lines:
for pattern in input_patterns:
if re.search(pattern, line):
print(f"🔍 Detected input prompt: {line}")
return True
# Check if there's no output for a while but the command is still running
if len(stdout_lines) == 0 and len(stderr_lines) == 0:
# This might be a command waiting for input without a prompt
# We'll be cautious and only return True if we're sure
return False
return False
def _handle_input_requirement(self, command, stdout_lines, stderr_lines):
"""Attempt to handle commands that require input."""
# Extract the last few lines to analyze what kind of input is needed
last_lines = []
if stdout_lines:
last_lines.extend(stdout_lines[-3:])
if stderr_lines:
last_lines.extend(stderr_lines[-3:])
last_line = last_lines[-1] if last_lines else ""
# Try to determine what kind of input is needed
if re.search(r'(?i)(y/n|yes/no|\[y/n\])', last_line):
# For yes/no prompts, usually 'yes' is safer
print("🔧 Auto-responding with 'y' to yes/no prompt")
self._send_command_raw("y")
return True
elif re.search(r'(?i)password', last_line):
# For password prompts, check if we have stored credentials
stored_creds = get_stored_credentials()
if stored_creds and 'ssh_password' in stored_creds:
print("🔧 Auto-responding with stored SSH password")
self._send_command_raw(stored_creds['ssh_password'])
return True
else:
print("⚠️ Password prompt detected but no stored password available")
return False
elif re.search(r'(?i)token|api.key', last_line):
# For token/API key prompts
stored_creds = get_stored_credentials()
if stored_creds:
if 'openai_api_key' in stored_creds and re.search(r'(?i)openai|api.key', last_line):
print("🔧 Auto-responding with stored OpenAI API key")
self._send_command_raw(stored_creds['openai_api_key'])
return True
elif 'hf_token' in stored_creds and re.search(r'(?i)hugg|hf|token', last_line):
print("🔧 Auto-responding with stored Hugging Face token")
self._send_command_raw(stored_creds['hf_token'])
return True
print("⚠️ Token/API key prompt detected but no matching stored credentials")
return False
elif re.search(r'(?i)press enter|continue|proceed', last_line):
# For "press enter to continue" prompts
print("🔧 Auto-responding with Enter to continue")
self._send_command_raw("") # Empty string sends just Enter
return True
# If we can't determine the type of input needed
print("⚠️ Couldn't determine the type of input needed")
# Try to use LLM to suggest an alternative command
try:
# Get current working directory for context
cwd = self.get_cwd()
# Reset command removal flags
self.should_remove_command = False
self.removal_reason = None
# Call LLM to suggest an alternative
alternative = self._suggest_alternative_command(command, stdout_lines, stderr_lines, cwd)
# Check if LLM suggested to remove the command
if self.should_remove_command:
print(f"🚫 Command will be removed: {self.removal_reason}")
return True # Return True to indicate the command has been handled (by removing it)
if alternative:
print(f"🔧 LLM suggested alternative command: {alternative}")
# We don't execute the alternative here, but return False so the calling code
# can handle it (e.g., by adding it to the command list)
# Store the suggested alternative for later use
self.suggested_alternative = alternative
return False
except Exception as e:
print(f"⚠️ Error getting LLM suggestion: {e}")
return False
def _suggest_alternative_command(self, command, stdout_lines, stderr_lines, current_dir):
"""Use LLM to suggest an alternative command that doesn't require user input."""
try:
# Get API key
api_key = os.environ.get("OPENAI_API_KEY")
if not api_key:
# Try to load from saved file
key_file = os.path.expanduser("~/.gitarsenal/openai_key")
if os.path.exists(key_file):
with open(key_file, "r") as f:
api_key = f.read().strip()
if not api_key:
print("⚠️ No OpenAI API key available for suggesting alternative command")
return None
# Prepare the prompt
stdout_text = '\n'.join(stdout_lines[-10:]) if stdout_lines else ""
stderr_text = '\n'.join(stderr_lines[-10:]) if stderr_lines else ""
prompt = f"""
The command '{command}' appears to be waiting for user input.
ENVIRONMENT: All commands are running on a Unix/Linux environment (bash shell), so only suggest Unix-compatible commands. Do not suggest Windows-specific commands or PowerShell commands.
Current directory: {current_dir}
Last stdout output:
{stdout_text}
Last stderr output:
{stderr_text}
Please analyze this command and determine if it's useful to continue with it.
If it's useful, suggest an alternative command that achieves the same goal but doesn't require user input.
For example, add flags like -y, --yes, --no-input, etc., or provide the required input in the command.
If the command is not useful or cannot be executed non-interactively, respond with "REMOVE_COMMAND" and explain why.
Format your response as:
ALTERNATIVE:
or
REMOVE_COMMAND:
"""
# Call OpenAI API
import openai
client = openai.OpenAI(api_key=api_key)
response = client.chat.completions.create(
model="gpt-5-mini",
messages=[
{"role": "system", "content": "You are a helpful assistant that suggests alternative commands that don't require user input."},
{"role": "user", "content": prompt}
],
max_tokens=150,
temperature=0.7
)
response_text = response.choices[0].message.content.strip()
# Check if the response suggests removing the command
if response_text.startswith("REMOVE_COMMAND:"):
reason = response_text.replace("REMOVE_COMMAND:", "").strip()
print(f"🚫 LLM suggests removing command: {reason}")
self.should_remove_command = True
self.removal_reason = reason
return None
# Extract the alternative command
if response_text.startswith("ALTERNATIVE:"):
alternative_command = response_text.replace("ALTERNATIVE:", "").strip()
else:
# Try to extract the command from a free-form response
lines = response_text.split('\n')
for line in lines:
line = line.strip()
if line and not line.startswith(('Here', 'I', 'You', 'The', 'This', 'Use', 'Try')):
alternative_command = line
break
else:
alternative_command = lines[0].strip()
return alternative_command
except Exception as e:
print(f"⚠️ Error suggesting alternative command: {e}")
return None
def _clear_lines(self):
"""Clear both output line lists."""
with self.stdout_lock:
self.stdout_lines.clear()
with self.stderr_lock:
self.stderr_lines.clear()
def get_cwd(self):
"""Get current working directory."""
success, output, _ = self._execute_single("pwd", 10)
if success:
return output.strip()
return self.working_dir
def get_virtual_env(self):
"""Get the currently activated virtual environment path."""
return self.virtual_env_path
def is_in_venv(self):
"""Check if we're currently in a virtual environment."""
return self.virtual_env_path is not None and self.virtual_env_path != ""
def get_venv_name(self):
"""Get the name of the current virtual environment if active."""
if self.is_in_venv():
return os.path.basename(self.virtual_env_path)
return None
def exec(self, *args, **kwargs):
"""Compatibility method to make PersistentShell work with call_openai_for_debug."""
# Convert exec call to execute method
if len(args) >= 2 and args[0] == "bash" and args[1] == "-c":
command = args[2]
success, stdout, stderr = self.execute(command)
# Create a mock result object that mimics the expected interface
class MockResult:
def __init__(self, stdout, stderr, returncode):
self.stdout = [stdout] if stdout else []
self.stderr = [stderr] if stderr else []
self.returncode = 0 if returncode else 1
def wait(self):
pass
return MockResult(stdout, stderr, success)
else:
raise NotImplementedError("exec method only supports bash -c commands")
def wait_for_prompt(self, timeout=5):
"""Wait for the shell prompt to appear, indicating readiness for next command."""
start_time = time.time()
while time.time() - start_time < timeout:
with self.stdout_lock:
if self.stdout_lines and self.stdout_lines[-1].strip().endswith('$'):
return True
time.sleep(0.1)
return False
def cleanup(self):
"""Clean up the shell process."""
print("🧹 Cleaning up persistent shell...")
self.is_running = False
if self.process:
try:
# Send exit command
self._send_command_raw("exit")
# Wait for process to terminate
try:
self.process.wait(timeout=5)
except subprocess.TimeoutExpired:
# Force kill if it doesn't exit gracefully
os.killpg(os.getpgid(self.process.pid), signal.SIGTERM)
try:
self.process.wait(timeout=2)
except subprocess.TimeoutExpired:
os.killpg(os.getpgid(self.process.pid), signal.SIGKILL)
except Exception as e:
print(f"Error during cleanup: {e}")
finally:
self.process = None
print("✅ Shell cleanup completed")
================================================
FILE: python/test_container_fail.py
================================================
import subprocess
import time
import secrets
import string
import modal
import sys
import os
def generate_random_password(length=16):
"""Generate a random password for SSH access"""
alphabet = string.ascii_letters + string.digits + "!@#$%^&*"
password = ''.join(secrets.choice(alphabet) for i in range(length))
return password
# Image building
print("Building Modal image...")
# base_image = modal.Image.from_registry("nvidia/cuda:12.4.0-devel-ubuntu22.04", add_python="3.11")
base_image = modal.Image.debian_slim()
ssh_image = (
base_image
.apt_install("openssh-server", "sudo", "curl", "wget", "vim", "htop", "git", "python3", "python3-pip")
.uv_pip_install("uv", "modal", "gitingest", "requests", "openai", "anthropic", "exa-py")
.run_commands(
"mkdir -p /var/run/sshd",
"mkdir -p /root/.ssh",
"chmod 700 /root/.ssh",
"sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config",
"sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config",
"sed -i 's/#PubkeyAuthentication yes/PubkeyAuthentication yes/' /etc/ssh/sshd_config",
"echo 'ClientAliveInterval 60' >> /etc/ssh/sshd_config",
"echo 'ClientAliveCountMax 3' >> /etc/ssh/sshd_config",
"ssh-keygen -A",
"echo 'export PS1=\"\\[\\e[1;32m\\]modal:\\[\\e[1;34m\\]\\w\\[\\e[0m\\]$ \"' >> /root/.bashrc",
"mkdir -p /python",
)
)
print("✅ SSH image built successfully")
# Create app
app = modal.App("test_container", image=ssh_image)
print("✅ Created app successfully")
@app.function(gpu="A10G", timeout=3600, memory=32768)
def get_ssh_connection(
test_data=None,
repo_info=None,
setup_commands=None,
env_vars=None,
credentials=None,
debug_config=None
):
"""Test complex remote parameter passing that causes segfault"""
print("🧪 TESTING COMPLEX REMOTE PARAMETER PASSING")
print("=" * 60)
# Test complex parameter handling
if test_data:
print(f"📦 Received extra_data: {type(test_data)} with {len(test_data) if hasattr(test_data, '__len__') else 'N/A'} items")
if isinstance(test_data, dict):
for key, value in test_data.items():
print(f" • {key}: {type(value)} = {str(value)[:100]}...")
if repo_info:
print(f"📂 Received repo_info: {repo_info}")
if setup_commands:
print(f"⚙️ Received {len(setup_commands)} setup commands:")
for i, cmd in enumerate(setup_commands[:3]):
print(f" {i+1}. {cmd}")
if len(setup_commands) > 3:
print(f" ... and {len(setup_commands) - 3} more")
if env_vars:
print(f"🔧 Received {len(env_vars)} environment variables:")
for key, value in list(env_vars.items())[:3]:
masked_value = str(value)[:8] + "..." if len(str(value)) > 8 else str(value)
print(f" • {key} = {masked_value}")
if credentials:
print(f"🔐 Received {len(credentials)} credentials")
for key in list(credentials.keys())[:3]:
print(f" • {key}: [MASKED]")
if debug_config:
print(f"🐛 Received debug_config: {debug_config}")
print("=" * 60)
# Generate SSH password
password = generate_random_password()
# Set root password
subprocess.run(["bash", "-c", f"echo 'root:{password}' | chpasswd"], check=True)
# Start SSH server
ssh_process = subprocess.Popen(["/usr/sbin/sshd", "-D"])
time.sleep(2)
# Test CUDA
cuda_info = {}
nvidia_result = subprocess.run(["nvidia-smi"], capture_output=True, text=True, timeout=30)
cuda_info["nvidia_smi_return_code"] = nvidia_result.returncode
cuda_info["nvidia_smi_output"] = nvidia_result.stdout[:500] if nvidia_result.stdout else "No output"
# nvcc_result = subprocess.run(["nvcc", "--version"], capture_output=True, text=True, timeout=30)
# cuda_info["nvcc_return_code"] = nvcc_result.returncode
# cuda_info["nvcc_output"] = nvcc_result.stdout[:500] if nvcc_result.stdout else "No output"
# Forward SSH port and return connection info
with modal.forward(port=22, unencrypted=True) as tunnel:
hostname, port = tunnel.tcp_socket
return {
"status": "success",
"hostname": hostname,
"port": port,
"password": password,
"cuda_info": cuda_info,
"ssh_command": f"ssh -p {port} root@{hostname}",
"parameters_received": {
"test_data": bool(test_data),
"repo_info": bool(repo_info),
"setup_commands": len(setup_commands) if setup_commands else 0,
"env_vars": len(env_vars) if env_vars else 0,
"credentials": len(credentials) if credentials else 0,
"debug_config": bool(debug_config),
}
}
if __name__ == "__main__":
print("Starting CUDA container setup...")
# Check Modal authentication
modal_toml = os.path.expanduser("~/.modal.toml")
modal_dir = os.path.expanduser("~/.modal/")
if os.path.exists(modal_toml):
print("✓ Modal configuration found")
elif os.path.exists(modal_dir):
print("✓ Modal configuration found")
else:
print("⚠️ Warning: No Modal configuration found")
print("Initializing Modal app...")
print("Building container image (this may take a while on first run)...")
try:
with app.run():
print("Getting SSH connection info...")
# THE COMPLEX DATA THAT CAUSES SEGFAULT
# Prepare test data to send to remote function
test_data = {
"message": "Hello from local machine!",
"number": 42,
"list": [1, 2, 3, "test"],
"nested": {
"key1": "value1",
"key2": 123
}
}
setup_commands = [
"apt-get update",
"pip install numpy",
"echo 'Setup complete'"
]
env_vars = {
"CUSTOM_VAR": "test_value",
"DEBUG_MODE": "true",
"API_URL": "https://api.example.com"
}
repo_info = {
"url": "https://github.com/test/repo.git",
"branch": "main"
}
credentials = {
"openai_api_key": "sk-test123456789abcdef",
"anthropic_api_key": "sk-ant-api-key-987654321",
"github_token": "ghp_github_token_123456",
"modal_token": "ak-modal-token-abcdef"
}
debug_config = {
"log_level": "INFO",
"enable_trace": True,
"output_file": "/tmp/debug.log",
"max_retries": 3
}
model_settings = {
"model_name": "gpt-4",
"temperature": 0.7,
"max_tokens": 2048,
"timeout": 30,
"provider": "openai"
}
print(f"📦 Sending complex data to remote function:")
print(f" • test_data: {len(test_data)} items (includes 1KB string)")
print(f" • repo_info: {len(repo_info)} items")
print(f" • setup_commands: {len(setup_commands)} commands")
print(f" • environment_vars: {len(env_vars)} variables")
print(f" • credentials: {len(credentials)} credentials")
print(f" • debug_config: {len(debug_config)} debug settings")
print("\n🚨 This should trigger the segfault...")
print()
# This call should cause the segfault
result = get_ssh_connection.remote(
test_data=test_data,
repo_info=repo_info,
setup_commands=setup_commands,
env_vars=env_vars,
credentials=credentials,
debug_config=debug_config
)
# If we get here, it didn't segfault
print("\n🎉 NO SEGFAULT! Function completed successfully")
print(f"SSH Command: {result['ssh_command']}")
print(f"Password: {result['password']}")
# Keep container running
while True:
time.sleep(60)
print("Container still running... (Press Ctrl+C to stop)")
except Exception as e:
print(f"\n💥 Error occurred: {e}")
print("This might be the segfault or another error")
print("Container stopped")
================================================
FILE: python/test_container_pass.py
================================================
import subprocess
import time
import secrets
import string
import modal
import sys
def generate_random_password(length=16):
"""Generate a random password for SSH access"""
alphabet = string.ascii_letters + string.digits + "!@#$%^&*"
password = ''.join(secrets.choice(alphabet) for i in range(length))
return password
base_image = modal.Image.from_registry("nvidia/cuda:12.4.0-devel-ubuntu22.04", add_python="3.11")
ssh_image = (
base_image
.apt_install("openssh-server", "sudo", "curl", "wget", "vim", "htop", "git", "python3", "python3-pip")
.uv_pip_install("uv", "modal", "gitingest", "requests", "openai", "anthropic", "exa-py")
.run_commands(
"mkdir -p /var/run/sshd",
"mkdir -p /root/.ssh",
"chmod 700 /root/.ssh",
"sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config",
"sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config",
"sed -i 's/#PubkeyAuthentication yes/PubkeyAuthentication yes/' /etc/ssh/sshd_config",
"echo 'ClientAliveInterval 60' >> /etc/ssh/sshd_config",
"echo 'ClientAliveCountMax 3' >> /etc/ssh/sshd_config",
"ssh-keygen -A",
"echo 'export PS1=\"\\[\\e[1;32m\\]modal:\\[\\e[1;34m\\]\\w\\[\\e[0m\\]$ \"' >> /root/.bashrc",
"mkdir -p /python",
)
)
print("✅ SSH image built successfully")
# Create app with image passed directly (THIS IS THE KEY CHANGE)
print("🔍 Testing app creation...")
app = modal.App("test_container", image=ssh_image) # Pass image here
print("✅ Created app successfully")
# Define the SSH container function (remove image from decorator)
@app.function(
timeout= 3600, # Convert to seconds
gpu="A10G", # Use the user-selected GPU type and count
serialized=True,
# volumes=volumes_config if volumes_config else None,
memory=32768,
)
def start_ssh():
# Generate SSH password
password = generate_random_password()
# Set root password
subprocess.run(["bash", "-c", f"echo 'root:{password}' | chpasswd"], check=True)
# Start SSH server
ssh_process = subprocess.Popen(["/usr/sbin/sshd", "-D"])
time.sleep(2)
# Test CUDA
cuda_info = {}
nvidia_result = subprocess.run(["nvidia-smi"], capture_output=True, text=True, timeout=30)
cuda_info["nvidia_smi_output"] = nvidia_result.stdout if nvidia_result.stdout else "No output"
nvcc_result = subprocess.run(["nvcc", "--version"], capture_output=True, text=True, timeout=30)
cuda_info["nvcc_output"] = nvcc_result.stdout if nvcc_result.stdout else "No output"
# Forward SSH port
with modal.forward(port=22, unencrypted=True) as tunnel:
hostname, port = tunnel.tcp_socket
# Return connection info to local terminal
connection_info = {
"hostname": hostname,
"port": port,
"password": password,
"cuda_info": cuda_info,
"status": "success"
}
# Keep alive with periodic status updates
counter = 0
while True:
counter += 1
time.sleep(60)
@app.function(gpu="A10G", timeout=3600)
def get_ssh_connection(test_data=None, setup_commands=None, env_vars=None, repo_info=None,
credentials=None, debug_config=None, model_settings=None):
"""Get SSH connection info and test remote parameter passing"""
print("🧪 REMOTE FUNCTION - Testing parameter passing...")
print("=" * 50)
if test_data:
print(f"📦 Received test_data: {type(test_data)}")
if isinstance(test_data, dict):
for key, value in test_data.items():
print(f" • {key}: {value}")
elif isinstance(test_data, list):
print(f" • List with {len(test_data)} items: {test_data}")
else:
print(f" • Value: {test_data}")
if setup_commands:
print(f"⚙️ Received {len(setup_commands)} setup commands:")
for i, cmd in enumerate(setup_commands):
print(f" {i+1}. {cmd}")
if env_vars:
print(f"🔧 Received {len(env_vars)} environment variables:")
for key, value in env_vars.items():
print(f" • {key} = {value}")
if repo_info:
print(f"📂 Received repo_info: {repo_info}")
if credentials:
print(f"🔐 Received {len(credentials)} credentials:")
for key, value in credentials.items():
# Mask sensitive data
masked_value = value[:8] + "..." if len(str(value)) > 8 else "***"
print(f" • {key}: {masked_value}")
if debug_config:
print(f"🐛 Received debug_config:")
for key, value in debug_config.items():
print(f" • {key}: {value}")
if model_settings:
print(f"🤖 Received model_settings:")
for key, value in model_settings.items():
print(f" • {key}: {value}")
print("=" * 50)
# Generate SSH password
password = generate_random_password()
# Set root password
subprocess.run(["bash", "-c", f"echo 'root:{password}' | chpasswd"], check=True)
# Start SSH server
ssh_process = subprocess.Popen(["/usr/sbin/sshd", "-D"])
time.sleep(2)
# Test CUDA
cuda_info = {}
nvidia_result = subprocess.run(["nvidia-smi"], capture_output=True, text=True, timeout=30)
cuda_info["nvidia_smi_return_code"] = nvidia_result.returncode
cuda_info["nvidia_smi_output"] = nvidia_result.stdout[:500] if nvidia_result.stdout else "No output"
nvcc_result = subprocess.run(["nvcc", "--version"], capture_output=True, text=True, timeout=30)
cuda_info["nvcc_return_code"] = nvcc_result.returncode
cuda_info["nvcc_output"] = nvcc_result.stdout[:500] if nvcc_result.stdout else "No output"
# Forward SSH port and return connection info
with modal.forward(port=22, unencrypted=True) as tunnel:
hostname, port = tunnel.tcp_socket
# Return connection info immediately
return {
"status": "success",
"hostname": hostname,
"port": port,
"password": password,
"cuda_info": cuda_info,
"ssh_command": f"ssh -p {port} root@{hostname}"
}
if __name__ == "__main__":
print("Starting CUDA container setup...")
# Check Modal authentication files
import os
modal_toml = os.path.expanduser("~/.modal.toml")
modal_dir = os.path.expanduser("~/.modal/")
if os.path.exists(modal_toml):
print("✓ Modal configuration found")
elif os.path.exists(modal_dir):
print("✓ Modal configuration found")
else:
print("⚠️ Warning: No Modal configuration found")
print("Initializing Modal app...")
print("Building container image (this may take a while on first run)...")
with app.run():
print("Getting SSH connection info...")
# Prepare test data to send to remote function
test_data = {
"message": "Hello from local machine!",
"number": 42,
"list": [1, 2, 3, "test"],
"nested": {
"key1": "value1",
"key2": 123
}
}
setup_commands = [
"apt-get update",
"pip install numpy",
"echo 'Setup complete'"
]
env_vars = {
"CUSTOM_VAR": "test_value",
"DEBUG_MODE": "true",
"API_URL": "https://api.example.com"
}
repo_info = {
"url": "https://github.com/test/repo.git",
"branch": "main"
}
credentials = {
"openai_api_key": "sk-test123456789abcdef",
"anthropic_api_key": "sk-ant-api-key-987654321",
"github_token": "ghp_github_token_123456",
"modal_token": "ak-modal-token-abcdef"
}
debug_config = {
"log_level": "INFO",
"enable_trace": True,
"output_file": "/tmp/debug.log",
"max_retries": 3
}
model_settings = {
"model_name": "gpt-4",
"temperature": 0.7,
"max_tokens": 2048,
"timeout": 30,
"provider": "openai"
}
print("📦 Sending test parameters to remote function:")
print(f" • test_data: {len(test_data)} items")
print(f" • setup_commands: {len(setup_commands)} commands")
print(f" • env_vars: {len(env_vars)} variables")
print(f" • repo_info: {repo_info}")
print(f" • credentials: {len(credentials)} items")
print(f" • debug_config: {len(debug_config)} items")
print(f" • model_settings: {len(model_settings)} items")
print()
# Get connection info with test parameters
result = get_ssh_connection.remote(
test_data=test_data,
setup_commands=setup_commands,
env_vars=env_vars,
repo_info=repo_info,
credentials=credentials,
debug_config=debug_config,
model_settings=model_settings
)
if result and "error" not in result:
print("\n" + "="*60)
print("🚀 CUDA CONTAINER READY!")
print("="*60)
print(f"SSH Command: {result['ssh_command']}")
print(f"Password: {result['password']}")
print("="*60)
print("\n📊 CUDA Information:")
if "nvidia_smi_output" in result["cuda_info"]:
print("nvidia-smi output:")
print(result["cuda_info"]["nvidia_smi_output"])
if "nvcc_output" in result["cuda_info"]:
print("\nnvcc output:")
print(result["cuda_info"]["nvcc_output"])
print("\n⚠️ Note: Container will stay running until you stop this script")
print("Press Ctrl+C to stop the container")
# Keep the local script running to maintain the container
while True:
time.sleep(60)
print("Container still running... (Press Ctrl+C to stop)")
else:
print(f"\n❌ Error: {result.get('error', 'Unknown error')}")
print("Container stopped")
================================================
FILE: python/test_modal.py
================================================
import subprocess
import time
import secrets
import string
import modal
def generate_random_password(length=16):
"""Generate a random password for SSH access"""
alphabet = string.ascii_letters + string.digits + "!@#$%^&*"
password = ''.join(secrets.choice(alphabet) for i in range(length))
return password
image = (
modal.Image.from_registry("nvidia/cuda:12.4.0-devel-ubuntu22.04", add_python="3.11")
.apt_install("openssh-server", "sudo", "curl", "wget", "git", "vim", "htop", "tmux", "nvtop")
.pip_install("cupy-cuda12x", "torch", "transformers")
.run_commands(
"mkdir -p /var/run/sshd",
"ssh-keygen -A",
"sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config",
"sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config",
"echo 'export PATH=/usr/local/cuda/bin:$PATH' >> /root/.bashrc"
)
)
app = modal.App("cuda-ssh-container", image=image)
@app.function(gpu="A10G", timeout=3600)
def start_ssh():
# Generate SSH password
password = generate_random_password()
subprocess.run(["bash", "-c", f"echo 'root:{password}' | chpasswd"], check=True)
# Start SSH server
subprocess.Popen(["/usr/sbin/sshd", "-D"])
time.sleep(2)
# Test CUDA
subprocess.run(["nvidia-smi"])
subprocess.run(["nvcc", "--version"])
# Forward SSH port
with modal.forward(port=22, unencrypted=True) as tunnel:
hostname, port = tunnel.tcp_socket
print(f"SSH: ssh -p {port} root@{hostname}")
print(f"Password: {password}")
# Keep alive
while True:
time.sleep(60)
if __name__ == "__main__":
with app.run():
start_ssh.remote()
================================================
FILE: python/test_modalSandboxScript.py
================================================
import os
import sys
import time
import subprocess
import json
import re
import datetime
import getpass
import secrets
import string
import argparse
from pathlib import Path
import modal
def generate_random_password(length=16):
"""Generate a random password for SSH access"""
alphabet = string.ascii_letters + string.digits + "!@#$%^&*"
password = ''.join(secrets.choice(alphabet) for i in range(length))
return password
def get_stored_credentials():
"""Load stored credentials from ~/.gitarsenal/credentials.json"""
import json
from pathlib import Path
try:
credentials_file = Path.home() / ".gitarsenal" / "credentials.json"
if credentials_file.exists():
with open(credentials_file, 'r') as f:
credentials = json.load(f)
return credentials
else:
return {}
except Exception as e:
print(f"⚠️ Error loading stored credentials: {e}")
return {}
# Global SSH container function (must be at global scope for Modal)
def ssh_container_function(ssh_password=None, repo_url=None, repo_name=None, setup_commands=None, openai_api_key=None, anthropic_api_key=None, stored_credentials=None):
"""Start SSH container with password authentication and intelligent repository setup using Agent."""
import subprocess
import time
import os
import json
import sys
# Set root password
subprocess.run(["bash", "-c", f"echo 'root:{ssh_password}' | chpasswd"], check=True)
# Set OpenAI API key if provided
if openai_api_key:
os.environ['OPENAI_API_KEY'] = openai_api_key
else:
print("⚠️ No OpenAI API key provided to container")
# Set up stored credentials in container environment
if stored_credentials:
print(f"🔐 Setting up {len(stored_credentials)} stored credentials in container...")
for key, value in stored_credentials.items():
# Set each credential as an environment variable
env_var_name = key.upper().replace('-', '_').replace(' ', '_')
os.environ[env_var_name] = value
print(f"✅ Set {env_var_name} in container environment")
# Also save credentials to a file in the container for easy access
credentials_dir = "/root/.gitarsenal"
os.makedirs(credentials_dir, exist_ok=True)
credentials_file = os.path.join(credentials_dir, "credentials.json")
with open(credentials_file, 'w') as f:
json.dump(stored_credentials, f, indent=2)
print(f"✅ Saved credentials to {credentials_file}")
# Print available credentials for user reference
print("\n🔐 AVAILABLE CREDENTIALS IN CONTAINER:")
print("="*50)
for key, value in stored_credentials.items():
masked_value = value[:8] + "..." if len(value) > 8 else "***"
env_var_name = key.upper().replace('-', '_').replace(' ', '_')
print(f" {key} -> {env_var_name} = {masked_value}")
print("="*50)
print("💡 These credentials are available as environment variables and in /root/.gitarsenal/credentials.json")
# Start SSH service
subprocess.run(["service", "ssh", "start"], check=True)
# Use Agent for intelligent repository setup
if repo_url:
print("🤖 Using Agent for intelligent repository setup...")
# Set up environment variables for the Agent
if openai_api_key:
os.environ['OPENAI_API_KEY'] = openai_api_key
if anthropic_api_key:
os.environ['ANTHROPIC_API_KEY'] = anthropic_api_key
# Set up Anthropic API key from stored credentials
if stored_credentials:
# Look for Anthropic API key in various possible names
for key_name in ['ANTHROPIC_API_KEY', 'anthropic_api_key', 'anthropic-api-key']:
if key_name in stored_credentials:
anthropic_api_key = stored_credentials[key_name]
os.environ['ANTHROPIC_API_KEY'] = anthropic_api_key
print(f"✅ Set Anthropic API key from stored credentials")
break
if not anthropic_api_key:
print("⚠️ No Anthropic API key found in stored credentials")
print("💡 Agent will require an Anthropic API key for operation")
try:
print("🔧 Running Agent for repository setup...")
print("\n" + "="*80)
print("🤖 AGENT REPOSITORY SETUP")
print("="*80)
print(f"Repository: {repo_url}")
print(f"Working Directory: /root")
if stored_credentials:
print(f"Available Credentials: {len(stored_credentials)} items")
print("="*80 + "\n")
# Call Agent directly as subprocess with real-time output
claude_prompt = f"clone, setup and run {repo_url}"
print(f"🚀 Executing the task: \"{claude_prompt}\"")
print("\n" + "="*60)
print("🎉 AGENT OUTPUT (LIVE)")
print("="*60)
# Use Popen for real-time output streaming with optimizations
import sys
import select
import fcntl
import os as os_module
process = subprocess.Popen(
["python", "-u", "/python/kill_claude/claude_code_agent.py", claude_prompt], # -u for unbuffered output
cwd="/root",
stdout=subprocess.PIPE,
stderr=subprocess.PIPE, # Keep separate for better handling
text=True,
bufsize=0, # Unbuffered for fastest output
universal_newlines=True,
env=dict(os.environ, PYTHONUNBUFFERED='1') # Force unbuffered Python output
)
# Make stdout and stderr non-blocking for faster reading
def make_non_blocking(fd):
flags = fcntl.fcntl(fd, fcntl.F_GETFL)
fcntl.fcntl(fd, fcntl.F_SETFL, flags | os_module.O_NONBLOCK)
make_non_blocking(process.stdout)
make_non_blocking(process.stderr)
# Stream output in real-time with robust error handling
try:
stdout_buffer = ""
stderr_buffer = ""
while process.poll() is None:
try:
# Use select for efficient I/O multiplexing with error handling
ready, _, _ = select.select([process.stdout, process.stderr], [], [], 0.1) # 100ms timeout
for stream in ready:
try:
if stream == process.stdout:
chunk = stream.read(1024) # Read in chunks for efficiency
if chunk is not None and chunk:
stdout_buffer += chunk
# Process complete lines immediately
while '\n' in stdout_buffer:
line, stdout_buffer = stdout_buffer.split('\n', 1)
print(line, flush=True) # Force immediate flush
elif stream == process.stderr:
chunk = stream.read(1024)
if chunk is not None and chunk:
stderr_buffer += chunk
# Process complete lines immediately
while '\n' in stderr_buffer:
line, stderr_buffer = stderr_buffer.split('\n', 1)
print(f"STDERR: {line}", flush=True)
except (BlockingIOError, OSError, ValueError):
# Handle various I/O errors gracefully
continue
except (select.error, OSError):
# If select fails, fall back to simple polling
time.sleep(0.1)
continue
# Process any remaining output after process ends
try:
# Read any remaining data from streams
remaining_stdout = process.stdout.read()
remaining_stderr = process.stderr.read()
if remaining_stdout:
stdout_buffer += remaining_stdout
if remaining_stderr:
stderr_buffer += remaining_stderr
# Output remaining buffered content
if stdout_buffer.strip():
print(stdout_buffer.strip(), flush=True)
if stderr_buffer.strip():
print(f"STDERR: {stderr_buffer.strip()}", flush=True)
except (OSError, ValueError):
# Handle cases where streams are already closed
pass
# Get final return code
return_code = process.returncode
print("\n" + "="*60)
if return_code == 0:
print("✅ Agent completed successfully!")
else:
print(f"⚠️ Agent exited with code: {return_code}")
print("="*60)
except subprocess.TimeoutExpired:
print("\n⚠️ Agent timed out after 10 minutes")
process.kill()
process.wait()
except Exception as stream_error:
pass
# Fallback to simple readline approach
try:
# Restart the process with simpler streaming
if process.poll() is None:
process.kill()
process.wait()
fallback_process = subprocess.Popen(
["python", "-u", "/python/kill_claude/claude_code_agent.py", claude_prompt],
cwd="/root",
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
text=True,
bufsize=1,
universal_newlines=True
)
# Simple line-by-line reading
while True:
line = fallback_process.stdout.readline()
if line == '' and fallback_process.poll() is not None:
break
if line:
print(line.rstrip(), flush=True)
return_code = fallback_process.returncode
print("\n" + "="*60)
if return_code == 0:
print("✅ Agent completed successfully!")
else:
print(f"⚠️ Agent exited with code: {return_code}")
print("="*60)
except Exception as fallback_error:
print(f"\n❌ Fallback streaming also failed: {fallback_error}")
print("⚠️ Agent may have completed, but output streaming failed")
return_code = 1
except Exception as e:
print(f"❌ Error during repository setup: {e}")
print("⚠️ Proceeding without setup...")
import traceback
traceback.print_exc()
else:
print("⚠️ No repository URL provided, skipping setup")
print("🔌 Creating SSH tunnel on port 22...")
# Create SSH tunnel
with modal.forward(22, unencrypted=True) as tunnel:
host, port = tunnel.tcp_socket
print("\n" + "=" * 80)
print("🎉 SSH CONTAINER IS READY!")
print("=" * 80)
print(f"🌐 SSH Host: {host}")
print(f"🔌 SSH Port: {port}")
print(f"👤 Username: root")
print(f"🔐 Password: {ssh_password}")
print()
print("🔗 CONNECT USING THIS COMMAND:")
print(f"ssh -p {port} root@{host}")
print("=" * 80)
print("🔄 Starting keep-alive loop...")
# Keep the container running
iteration = 0
while True:
iteration += 1
if iteration % 10 == 1: # Print every 5 minutes (10 * 30 seconds = 5 minutes)
print(f"💓 Container alive (iteration {iteration})")
time.sleep(30)
# Check if SSH service is still running
try:
subprocess.run(["service", "ssh", "status"], check=True,
capture_output=True)
except subprocess.CalledProcessError:
print("⚠️ SSH service stopped, restarting...")
subprocess.run(["service", "ssh", "start"], check=True)
# Create Modal SSH container with GPU support and intelligent repository setup using Agent
def create_modal_ssh_container(gpu_type, repo_url=None, repo_name=None, setup_commands=None,
volume_name=None, timeout_minutes=60, ssh_password=None, interactive=False, gpu_count=1):
"""Create a Modal SSH container with GPU support and intelligent repository setup.
When repo_url is provided, uses Agent for intelligent repository setup.
The setup_commands parameter is maintained for backwards compatibility but ignored when using Agent.
"""
# Use interactive mode if specified
if interactive:
# If GPU type is not specified, use default
if not gpu_type:
gpu_type = "A10G"
print(f"✅ Using default GPU type: {gpu_type}")
else:
print(f"✅ Using provided GPU type: {gpu_type}")
# If repo URL is not specified, prompt for it
if not repo_url:
try:
repo_url = input("? Enter GitHub repository URL: ").strip()
if not repo_url:
print("❌ Repository URL is required.")
return None
except KeyboardInterrupt:
print("\n🛑 Setup cancelled.")
return None
# If volume name is not specified, ask about persistent volume
if not volume_name:
try:
use_volume = input("? Use persistent volume for faster installs? (Y/n): ").strip().lower()
if use_volume in ('', 'y', 'yes'):
volume_name = input("? Enter volume name: ").strip()
if not volume_name:
volume_name = "gitarsenal-volume"
print(f"Using default volume name: {volume_name}")
except KeyboardInterrupt:
print("\n🛑 Setup cancelled.")
sys.exit(1)
# Check if Modal is authenticated
try:
modal_token_id = os.environ.get("MODAL_TOKEN_ID")
modal_token = os.environ.get("MODAL_TOKEN")
openai_api_key = os.environ.get("OPENAI_API_KEY")
# Try to access Modal token to check authentication
try:
# Check if token is set in environment
modal_token_id = os.environ.get("MODAL_TOKEN_ID")
if not modal_token_id:
print("⚠️ MODAL_TOKEN_ID not found in environment.")
# Try to get from MODAL_TOKEN
modal_token = os.environ.get("MODAL_TOKEN")
if modal_token:
print("✅ Found token in environment variable")
os.environ["MODAL_TOKEN_ID"] = modal_token
modal_token_id = modal_token
print(f"✅ Set token (length: {len(modal_token)})")
except Exception as e:
print(f"⚠️ Error checking Modal token: {e}")
# Try to use the token from environment
modal_token_id = os.environ.get("MODAL_TOKEN_ID")
modal_token = os.environ.get("MODAL_TOKEN")
if modal_token_id:
print(f"🔄 Using token from environment (length: {len(modal_token_id)})")
elif modal_token:
print(f"🔄 Using token from environment (length: {len(modal_token)})")
os.environ["MODAL_TOKEN_ID"] = modal_token
modal_token_id = modal_token
else:
print("❌ No Modal token available. Cannot proceed.")
return None
# Set it in both environment variables
os.environ["MODAL_TOKEN_ID"] = modal_token_id
os.environ["MODAL_TOKEN"] = modal_token_id
print("✅ Set both token and id environment variables")
except Exception as e:
print(f"⚠️ Error checking Modal authentication: {e}")
print("Continuing anyway, but Modal operations may fail")
# Generate a unique app name with timestamp to avoid conflicts
timestamp = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
app_name = f"ssh-container-{timestamp}"
gpu_configs = {
'T4': {'gpu': 't4', 'memory': 16},
'L4': {'gpu': 'l4', 'memory': 24},
'A10G': {'gpu': 'a10g', 'memory': 24},
'A100-40GB': {'gpu': 'a100', 'memory': 40},
'A100-80GB': {'gpu': 'a100-80gb', 'memory': 80},
'L40S': {'gpu': 'l40s', 'memory': 48},
'H100': {'gpu': 'h100', 'memory': 80},
'H200': {'gpu': 'h200', 'memory': 141},
'B200': {'gpu': 'b200', 'memory': 96}
}
if gpu_type not in gpu_configs:
print(f"⚠️ Unknown GPU type: {gpu_type}. Using A10G as default.")
gpu_type = 'A10G'
gpu_spec = gpu_configs[gpu_type]
# Configure GPU string for Modal (support multiple GPUs)
if gpu_count > 1:
modal_gpu_spec = f"{gpu_spec['gpu']}:{gpu_count}"
total_memory = gpu_spec['memory'] * gpu_count
print(f"🚀 Creating SSH container with {gpu_count}x {gpu_spec['gpu']} GPUs ({total_memory}GB total VRAM)")
else:
modal_gpu_spec = gpu_spec['gpu']
print(f"🚀 Creating SSH container with {gpu_spec['gpu']} GPU ({gpu_spec['memory']}GB VRAM)")
# Store the modal GPU specification for the decorator
gpu_spec['modal_gpu'] = modal_gpu_spec
# Generate or use provided SSH password
if not ssh_password:
ssh_password = generate_random_password()
print(f"🔐 Generated SSH password: {ssh_password}")
# Setup volume if specified
volume = None
volume_mount_path = "/persistent"
if volume_name:
print(f"📦 Setting up volume: {volume_name}")
try:
volume = modal.Volume.from_name(volume_name, create_if_missing=True)
print(f"✅ Volume '{volume_name}' ready for use")
except Exception as e:
print(f"⚠️ Could not setup volume '{volume_name}': {e}")
print("⚠️ Continuing without persistent volume")
volume = None
else:
# Create a default volume for this session
default_volume_name = f"ssh-vol-{timestamp}"
print(f"📦 Creating default volume: {default_volume_name}")
try:
volume = modal.Volume.from_name(default_volume_name, create_if_missing=True)
volume_name = default_volume_name
print(f"✅ Default volume '{default_volume_name}' created")
except Exception as e:
print(f"⚠️ Could not create default volume: {e}")
print("⚠️ Continuing without persistent volume")
volume = None
modal_token = os.environ.get("MODAL_TOKEN_ID")
# Create SSH-enabled image
print("📦 Building SSH-enabled image...")
# Get the current directory path for mounting local Python sources
current_dir = os.path.dirname(os.path.abspath(__file__))
# Get the gitarsenal-cli root directory for kill_claude files
gitarsenal_root = os.path.dirname(current_dir)
# Choose base image to avoid CUDA segfault issues
print("⚠️ Using CUDA base image - this may cause segfaults on some systems")
base_image = modal.Image.from_registry("nvidia/cuda:12.4.0-devel-ubuntu22.04", add_python="3.11")
# base_image = modal.Image.debian_slim()
# Build the SSH image with the chosen base
ssh_image = (
base_image
.apt_install(
"openssh-server", "sudo", "curl", "wget", "vim", "htop", "git",
"python3", "python3-pip"
)
)
# Add Python packages using the appropriate method
ssh_image = ssh_image.uv_pip_install("uv", "modal", "gitingest", "requests", "openai", "anthropic", "exa-py")
# Add the rest of the configuration
ssh_image = ssh_image.run_commands(
# Create SSH directory
"mkdir -p /var/run/sshd",
"mkdir -p /root/.ssh",
"chmod 700 /root/.ssh",
"ssh-keygen -A",
"sed -i 's/#PermitRootLogin prohibit-password/PermitRootLogin yes/' /etc/ssh/sshd_config",
"sed -i 's/#PasswordAuthentication yes/PasswordAuthentication yes/' /etc/ssh/sshd_config",
"echo 'export PATH=/usr/local/cuda/bin:$PATH' >> /root/.bashrc"
# Create base directories (subdirectories will be created automatically when mounting)
"mkdir -p /python",
).add_local_dir(current_dir, "/python", ignore=lambda p: not p.name.endswith('.py')).add_local_dir(os.path.join(gitarsenal_root, "kill_claude"), "/python/kill_claude")
print("✅ SSH image built successfully")
# Configure volumes if available
volumes_config = {}
if volume:
volumes_config[volume_mount_path] = volume
# Create app with image passed directly (THIS IS THE KEY CHANGE)
print("🔍 Testing app creation...")
app = modal.App(app_name, image=ssh_image) # Pass image here
print("✅ Created app successfully")
# Apply the decorator to the global SSH container function
decorated_ssh_function = app.function(
timeout=timeout_minutes * 60, # Convert to seconds
gpu=gpu_spec['modal_gpu'], # Use the user-selected GPU type and count
volumes=volumes_config if volumes_config else None,
)(ssh_container_function)
# Run the container
try:
print("⏳ Starting container... This may take 1-2 minutes...")
# Start the container and wait for it to complete (blocking)
with modal.enable_output():
with app.run():
# Get the API key from environment
openai_api_key = os.environ.get("OPENAI_API_KEY")
anthropic_api_key = os.environ.get("ANTHROPIC_API_KEY")
# Get stored credentials from local file
stored_credentials = get_stored_credentials()
if stored_credentials:
print(f"🔐 Found {len(stored_credentials)} stored credentials to send to container")
else:
print("⚠️ No stored credentials found")
# Use spawn() to get a FunctionCall handle, then wait for it
print("🚀 Spawning SSH container...")
try:
function_call = decorated_ssh_function.spawn(ssh_password, repo_url, repo_name, setup_commands, openai_api_key, anthropic_api_key, stored_credentials)
print(f"✅ Container spawned with call ID: {function_call.object_id}")
print(f"🔍 Function call status: {function_call}")
except Exception as spawn_error:
print(f"❌ Error during spawn: {spawn_error}")
raise
try:
# Wait for the function to start and print connection info (with timeout)
print("⏳ Waiting for container to initialize...")
try:
print("\n⏳ Monitoring container (press Ctrl+C to stop monitoring)...")
result = function_call.get() # Wait indefinitely
print(f"🔚 Container function completed with result: {result}")
except KeyboardInterrupt:
print("\n🛑 Stopped monitoring. Container is still running remotely.")
print("💡 Use Modal's web UI or CLI to stop the container when done.")
print("🔒 Keeping tokens active since container is still running.")
return {
"app_name": app_name,
"ssh_password": ssh_password,
"volume_name": volume_name,
"status": "monitoring_stopped",
"function_call_id": function_call.object_id
}
except KeyboardInterrupt:
print("\n🛑 Interrupted by user. Container may still be running remotely.")
print("💡 Use Modal's web UI or CLI to check running containers.")
print("🔒 Keeping tokens active since container may still be running.")
return {
"app_name": app_name,
"ssh_password": ssh_password,
"volume_name": volume_name,
"status": "interrupted",
"function_call_id": function_call.object_id
}
except Exception as e:
print(f"⚠️ Container execution error: {e}")
print("💡 Container may still be accessible via SSH if it started successfully.")
print("🧹 Cleaning up tokens due to execution error.")
cleanup_modal_token()
raise
# Only clean up tokens if container actually completed normally
print("🧹 Container completed normally, cleaning up tokens.")
cleanup_modal_token()
return {
"app_name": app_name,
"ssh_password": ssh_password,
"volume_name": volume_name
}
except Exception as e:
print(f"❌ Error running container: {e}")
return None
def cleanup_security_tokens():
"""Delete all security tokens and API keys after SSH container is started"""
print("🧹 Cleaning up security tokens and API keys...")
try:
# Remove Modal tokens from environment variables
modal_env_vars = ["MODAL_TOKEN_ID", "MODAL_TOKEN", "MODAL_TOKEN_SECRET"]
for var in modal_env_vars:
if var in os.environ:
del os.environ[var]
# Remove OpenAI API key from environment
if "OPENAI_API_KEY" in os.environ:
del os.environ["OPENAI_API_KEY"]
# Delete ~/.modal.toml file
home_dir = os.path.expanduser("~")
modal_toml = os.path.join(home_dir, ".modal.toml")
if os.path.exists(modal_toml):
os.remove(modal_toml)
# Delete ~/.gitarsenal/openai_key file
openai_key_file = os.path.join(home_dir, ".gitarsenal", "openai_key")
if os.path.exists(openai_key_file):
os.remove(openai_key_file)
except Exception as e:
print(f"❌ Error during security cleanup: {e}")
# Keep the old function for backward compatibility
def cleanup_modal_token():
"""Legacy function - now calls the comprehensive cleanup"""
cleanup_security_tokens()
def show_usage_examples():
"""Display usage examples for the script."""
print("Usage Examples\n")
print("🔐 Authentication Commands")
print("┌────────────────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --register # Register new account │")
print("│ gitarsenal --login # Login to existing account │")
print("│ gitarsenal --logout # Logout from account │")
print("│ gitarsenal --user-info # Show current user information │")
print("│ gitarsenal --change-password # Change password │")
print("│ gitarsenal --delete-account # Delete account │")
print("│ gitarsenal --store-api-key openai # Store OpenAI API key │")
print("│ gitarsenal --auth # Interactive auth management │")
print("└────────────────────────────────────────────────────────────────────────────────────┘\n")
print("Basic Container Creation with Agent")
print("┌────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --gpu A10G --repo-url https://github.com/username/repo.git │")
print("│ # Agent will intelligently clone and setup the repository │")
print("└────────────────────────────────────────────────────────────────────────┘\n")
print("With Persistent Storage")
print("┌────────────────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --gpu A10G --repo-url https://github.com/username/repo.git \\ │")
print("│ --volume-name my-persistent-volume │")
print("└────────────────────────────────────────────────────────────────────────────────────┘\n")
print("With Multiple GPUs")
print("┌────────────────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --gpu A100-80GB --gpu-count 4 \\ │")
print("│ --repo-url https://github.com/username/repo.git │")
print("└────────────────────────────────────────────────────────────────────────────────────┘\n")
print("Intelligent Repository Setup (default)")
print("┌────────────────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --gpu A10G --repo-url https://github.com/username/repo.git │")
print("│ # Agent analyzes repo and sets up environment automatically │")
print("└────────────────────────────────────────────────────────────────────────────────────┘\n")
print("With Manual Setup Commands (Advanced)")
print("┌────────────────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --gpu A10G --setup-commands \"pip install torch\" \"python train.py\" │")
print("│ # Only use when not providing --repo-url (bypasses Agent) │")
print("└────────────────────────────────────────────────────────────────────────────────────┘\n")
print("Development Mode (Skip Authentication)")
print("┌────────────────────────────────────────────────────────────────────────────────────┐")
print("│ gitarsenal --skip-auth --gpu A10G --repo-url https://github.com/username/repo.git │")
print("└────────────────────────────────────────────────────────────────────────────────────┘\n")
print("Available GPU Options:")
print(" T4, L4, A10G, A100-40GB, A100-80GB, L40S, H100, H200, B200")
print(" Use --gpu-count to specify multiple GPUs (1-8)")
print()
print("Authentication Behavior:")
print(" • First time: Interactive registration/login required")
print(" • Subsequent runs: Automatic login with stored session")
print(" • Use --skip-auth for development (bypasses auth)")
print()
print("GPU Selection Behavior:")
print(" • With --gpu: Uses specified GPU without prompting")
print(" • Without --gpu: Shows interactive GPU selection menu")
print()
print("Repository Setup Behavior:")
print(" • With --repo-url Agent intelligently clones and sets up repository")
print(" • Without --repo-url: Manual container setup (no automatic repository setup)")
print(" • Legacy --setup-commands: Only used when --repo-url not provided")
print()
print("Examples:")
print(" # Intelligent repository setup (recommended):")
print(" gitarsenal --gpu A10G --repo-url https://github.com/username/repo.git")
print()
print(" # Development mode (skip authentication):")
print(" gitarsenal --skip-auth --gpu A10G --repo-url https://github.com/username/repo.git")
print()
print(" # Manual setup (advanced users):")
print(" gitarsenal --gpu A10G --setup-commands \"pip install torch\" \"python train.py\"")
def _check_authentication(auth_manager):
"""Check if user is authenticated, prompt for login if not"""
if auth_manager.is_authenticated():
user = auth_manager.get_current_user()
print(f"✅ Authenticated as: {user['username']}")
return True
print("\n🔐 Authentication required")
return auth_manager.interactive_auth_flow()
def _handle_auth_commands(auth_manager, args):
"""Handle authentication-related commands"""
if args.login:
print("\n🔐 LOGIN")
username = input("Username: ").strip()
password = getpass.getpass("Password: ").strip()
if auth_manager.login_user(username, password):
print("✅ Login successful!")
else:
print("❌ Login failed.")
elif args.register:
print("\n🔐 REGISTRATION")
username = input("Username (min 3 characters): ").strip()
email = input("Email: ").strip()
password = getpass.getpass("Password (min 8 characters): ").strip()
confirm_password = getpass.getpass("Confirm password: ").strip()
if password != confirm_password:
print("❌ Passwords do not match.")
return
if auth_manager.register_user(username, email, password):
print("✅ Registration successful!")
# Auto-login after registration
if auth_manager.login_user(username, password):
print("✅ Auto-login successful!")
else:
print("❌ Registration failed.")
elif args.logout:
auth_manager.logout_user()
elif args.user_info:
auth_manager.show_user_info()
elif args.change_password:
if not auth_manager.is_authenticated():
print("❌ Not logged in. Please login first.")
return
current_password = getpass.getpass("Current password: ").strip()
new_password = getpass.getpass("New password (min 8 characters): ").strip()
confirm_password = getpass.getpass("Confirm new password: ").strip()
if new_password != confirm_password:
print("❌ New passwords do not match.")
return
if auth_manager.change_password(current_password, new_password):
print("✅ Password changed successfully!")
else:
print("❌ Failed to change password.")
elif args.delete_account:
if not auth_manager.is_authenticated():
print("❌ Not logged in. Please login first.")
return
password = getpass.getpass("Enter your password to confirm deletion: ").strip()
if auth_manager.delete_account(password):
print("✅ Account deleted successfully!")
else:
print("❌ Failed to delete account.")
elif args.store_api_key:
if not auth_manager.is_authenticated():
print("❌ Not logged in. Please login first.")
return
service = args.store_api_key
api_key = getpass.getpass(f"Enter {service} API key: ").strip()
if auth_manager.store_api_key(service, api_key):
print(f"✅ {service} API key stored successfully!")
else:
print(f"❌ Failed to store {service} API key.")
elif args.auth:
# Interactive authentication management
while True:
print("\n" + "="*60)
print("🔐 AUTHENTICATION MANAGEMENT")
print("="*60)
print("1. Login")
print("2. Register")
print("3. Show user info")
print("4. Change password")
print("5. Store API key")
print("6. Delete account")
print("7. Logout")
print("8. Exit")
choice = input("\nSelect an option (1-8): ").strip()
if choice == "1":
username = input("Username: ").strip()
password = getpass.getpass("Password: ").strip()
auth_manager.login_user(username, password)
elif choice == "2":
username = input("Username (min 3 characters): ").strip()
email = input("Email: ").strip()
password = getpass.getpass("Password (min 8 characters): ").strip()
confirm_password = getpass.getpass("Confirm password: ").strip()
if password == confirm_password:
auth_manager.register_user(username, email, password)
else:
print("❌ Passwords do not match.")
elif choice == "3":
auth_manager.show_user_info()
elif choice == "4":
if auth_manager.is_authenticated():
current_password = getpass.getpass("Current password: ").strip()
new_password = getpass.getpass("New password (min 8 characters): ").strip()
confirm_password = getpass.getpass("Confirm new password: ").strip()
if new_password == confirm_password:
auth_manager.change_password(current_password, new_password)
else:
print("❌ New passwords do not match.")
else:
print("❌ Not logged in.")
elif choice == "5":
if auth_manager.is_authenticated():
service = input("Service name (e.g., openai, modal): ").strip()
api_key = getpass.getpass(f"Enter {service} API key: ").strip()
auth_manager.store_api_key(service, api_key)
else:
print("❌ Not logged in.")
elif choice == "6":
if auth_manager.is_authenticated():
password = getpass.getpass("Enter your password to confirm deletion: ").strip()
auth_manager.delete_account(password)
else:
print("❌ Not logged in.")
elif choice == "7":
auth_manager.logout_user()
elif choice == "8":
print("👋 Goodbye!")
break
else:
print("❌ Invalid option. Please try again.")
# Replace the existing GPU argument parsing in the main section
if __name__ == "__main__":
# Parse command line arguments when script is run directly
import argparse
import sys
parser = argparse.ArgumentParser()
parser.add_argument('--repo-name', type=str, help='Repository name override')
parser.add_argument('--setup-commands', type=str, nargs='+', help='Setup commands to run (deprecated)')
parser.add_argument('--setup-commands-json', type=str, help='Setup commands as JSON array')
parser.add_argument('--commands-file', type=str, help='Path to file containing setup commands (one per line)')
parser.add_argument('--setup-script', type=str, help='Path to bash script containing setup commands')
parser.add_argument('--working-dir', type=str, help='Working directory for the setup script')
parser.add_argument('--volume-name', type=str, help='Name of the Modal volume for persistent storage')
parser.add_argument('--timeout', type=int, default=60, help='Container timeout in minutes (default: 60)')
parser.add_argument('--ssh-password', type=str, help='SSH password (random if not provided)')
parser.add_argument('--show-examples', action='store_true', help='Show usage examples')
parser.add_argument('--list-gpus', action='store_true', help='List available GPU types with their specifications')
parser.add_argument('--interactive', action='store_true', help='Run in interactive mode with prompts')
parser.add_argument('--yes', action='store_true', help='Automatically confirm prompts (non-interactive)')
parser.add_argument('--gpu', default='A10G', help='GPU type to use')
parser.add_argument('--gpu-count', type=int, default=1, help='Number of GPUs to use (default: 1)')
parser.add_argument('--repo-url', help='Repository URL')
# Authentication-related arguments
parser.add_argument('--auth', action='store_true', help='Manage authentication (login, register, logout)')
parser.add_argument('--login', action='store_true', help='Login to GitArsenal')
parser.add_argument('--register', action='store_true', help='Register new account')
parser.add_argument('--logout', action='store_true', help='Logout from GitArsenal')
parser.add_argument('--user-info', action='store_true', help='Show current user information')
parser.add_argument('--change-password', action='store_true', help='Change password')
parser.add_argument('--delete-account', action='store_true', help='Delete account')
parser.add_argument('--store-api-key', type=str, help='Store API key for a service (e.g., openai, modal)')
parser.add_argument('--skip-auth', action='store_true', help='Skip authentication check (for development)')
# User credential arguments (passed from JavaScript CLI)
parser.add_argument('--user-id', type=str, help='User email address (passed from JavaScript CLI)')
parser.add_argument('--user-name', type=str, help='Username (passed from JavaScript CLI)')
parser.add_argument('--display-name', type=str, help='Display name (passed from JavaScript CLI)')
args = parser.parse_args()
# Initialize tokens (import here to avoid container import issues)
from fetch_modal_tokens import get_tokens
token_id, token_secret, openai_api_key, anthropic_api_key, openrouter_api_key, groq_api_key = get_tokens()
# Check if we got valid tokens
if token_id is None or token_secret is None:
raise ValueError("Could not get valid tokens")
# Explicitly set the environment variables again to be sure
os.environ["MODAL_TOKEN_ID"] = token_id
os.environ["MODAL_TOKEN_SECRET"] = token_secret
if openai_api_key:
os.environ["OPENAI_API_KEY"] = openai_api_key
if anthropic_api_key:
os.environ["ANTHROPIC_API_KEY"] = anthropic_api_key
# Also set the old environment variable for backward compatibility
os.environ["MODAL_TOKEN"] = token_id
# Set token variables for later use
token = token_id # For backward compatibility
# Initialize authentication manager (import here to avoid container import issues)
from auth_manager import AuthManager
auth_manager = AuthManager()
# Handle authentication-related commands
if args.auth or args.login or args.register or args.logout or args.user_info or args.change_password or args.delete_account or args.store_api_key:
_handle_auth_commands(auth_manager, args)
sys.exit(0)
# If --list-gpus is specified, just show GPU options and exit
if args.list_gpus:
print("\n📊 Available GPU Options:")
print("┌──────────────┬─────────┐")
print("│ GPU Type │ VRAM │")
print("├──────────────┼─────────┤")
print("│ 1. T4 │ 16GB │")
print("│ 2. L4 │ 24GB │")
print("│ 3. A10G │ 24GB │")
print("│ 4. A100-40 │ 40GB │")
print("│ 5. A100-80 │ 80GB │")
print("│ 6. L40S │ 48GB │")
print("│ 7. H100 │ 80GB │")
print("│ 8. H200 │ 141GB │")
print("│ 9. B200 │ 141GB │")
print("└──────────────┴─────────┘")
print("Use --gpu to specify a GPU type")
print("Use --gpu-count to specify multiple GPUs (1-8)")
print("\nExample: --gpu A100-80GB --gpu-count 4 (for 4x A100-80GB GPUs)")
sys.exit(0)
# If no arguments or only --show-examples is provided, show usage examples
if len(sys.argv) == 1 or args.show_examples:
show_usage_examples()
sys.exit(0)
# Authentication is handled by the JavaScript CLI when credentials are passed
if args.user_id and args.user_name and args.display_name:
print(f"✅ Authenticated as: {args.display_name} ({args.user_id})")
elif not args.skip_auth:
# Only perform authentication check if running Python script directly (not from CLI)
if not _check_authentication(auth_manager):
print("\n❌ Authentication required. Please login or register first.")
print("Use --login to login or --register to create an account.")
sys.exit(1)
# Check for dependencies
print("⠏ Checking dependencies...")
print("--- Dependency Check ---")
# Check Python version
python_version = sys.version.split()[0]
print(f"✓ Python {python_version} found")
# Check Modal CLI
try:
subprocess.run(["modal", "--version"], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
print("✓ Modal CLI found")
except (subprocess.SubprocessError, FileNotFoundError):
print("❌ Modal CLI not found. Please install with: pip install modal")
# Check Gitingest CLI
try:
subprocess.run(["gitingest", "--help"], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
print("✓ Gitingest CLI found")
except (subprocess.SubprocessError, FileNotFoundError):
print("⚠️ Gitingest CLI not found (optional)")
# Check Git
try:
subprocess.run(["git", "--version"], check=True, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
print("✓ Git found")
except (subprocess.SubprocessError, FileNotFoundError):
print("❌ Git not found. Please install Git.")
print("------------------------")
print("\n✔ Dependencies checked")
# Use provided GPU argument or prompt for selection
if args.gpu:
gpu_type = args.gpu
# Validate the provided GPU type
valid_gpus = ['T4', 'L4', 'A10G', 'A100-40GB', 'A100-80GB', 'L40S', 'H100', 'H200', 'B200']
if gpu_type not in valid_gpus:
print(f"⚠️ Warning: '{gpu_type}' is not in the list of known GPU types.")
print(f"Available GPU types: {', '.join(valid_gpus)}")
print(f"Proceeding with '{gpu_type}' anyway...")
else:
print(f"✅ Using specified GPU: {gpu_type}")
else:
print("\n📋 No GPU type specified with --gpu flag.")
print("🔄 Using default GPU type: A10G")
gpu_type = "A10G"
args.gpu = gpu_type
# Display configuration after GPU selection
print("\n📋 Container Configuration:")
print(f"Repository URL: {args.repo_url or 'Not specified'}")
gpu_count = getattr(args, 'gpu_count', 1)
if gpu_count > 1:
print(f"GPU Type: {gpu_count}x {gpu_type}")
else:
print(f"GPU Type: {gpu_type}")
print(f"Volume: {args.volume_name or 'None'}")
if args.repo_url:
print("Repository Setup: Agent (intelligent)")
elif args.setup_commands:
print(f"Setup Commands: {len(args.setup_commands)} custom commands")
else:
print("Setup Commands: None")
# Confirm settings (skip if --yes specified)
if not getattr(args, 'yes', False):
try:
proceed = input("Proceed with these settings? (Y/n): ").strip().lower()
if proceed in ('n', 'no'):
print("🛑 Operation cancelled by user.")
sys.exit(0)
except KeyboardInterrupt:
print("\n🛑 Operation cancelled by user.")
sys.exit(0)
else:
print("")
# Interactive mode or missing required arguments
if args.interactive or not args.repo_url or not args.volume_name:
# Get repository URL if not provided
repo_url = args.repo_url
if not repo_url:
try:
repo_url = input("? Enter GitHub repository URL: ").strip()
if not repo_url:
print("❌ Repository URL is required.")
sys.exit(1)
except KeyboardInterrupt:
print("\n🛑 Setup cancelled.")
sys.exit(1)
# Ask about persistent volume
volume_name = args.volume_name
if not volume_name:
try:
use_volume = input("? Use persistent volume for faster installs? (Y/n): ").strip().lower()
if use_volume in ('', 'y', 'yes'):
volume_name = input("? Enter volume name: ").strip()
if not volume_name:
volume_name = "gitarsenal-volume"
print(f"Using default volume name: {volume_name}")
except KeyboardInterrupt:
print("\n🛑 Setup cancelled.")
sys.exit(1)
# Ask about GPU count if not specified
gpu_count = getattr(args, 'gpu_count', 1)
if not hasattr(args, 'gpu_count') or args.gpu_count == 1:
try:
gpu_count_input = input("? How many GPUs do you need? (1-8, default: 1): ").strip()
if gpu_count_input:
try:
gpu_count = int(gpu_count_input)
if gpu_count < 1 or gpu_count > 8:
print("⚠️ GPU count must be between 1 and 8. Using default: 1")
gpu_count = 1
except ValueError:
print("⚠️ Invalid GPU count. Using default: 1")
gpu_count = 1
except KeyboardInterrupt:
print("\n🛑 Setup cancelled.")
sys.exit(1)
# Update args with interactive values
args.repo_url = repo_url
args.volume_name = volume_name
args.gpu_count = gpu_count
try:
# Setup commands are no longer used when repo_url is provided (Agent handles setup)
setup_commands = args.setup_commands or []
# Repository setup approach
if args.repo_url:
print("🤖 Repository setup will be handled by Agent in container")
setup_commands = [] # Agent will handle setup intelligently
else:
print("⚠️ No repository URL provided - setup commands may be needed manually")
# Parse setup commands from JSON if provided
if args.setup_commands_json:
try:
json_commands = json.loads(args.setup_commands_json)
if isinstance(json_commands, list):
setup_commands = json_commands
print(f"📋 Parsed {len(setup_commands)} commands from JSON:")
for i, cmd in enumerate(setup_commands, 1):
print(f" {i}. {cmd}")
else:
print(f"⚠️ Invalid JSON format for setup commands: not a list")
except json.JSONDecodeError as e:
print(f"⚠️ Error parsing JSON setup commands: {e}")
print(f"Received JSON string: {args.setup_commands_json}")
# Load commands from file if specified
if args.commands_file and os.path.exists(args.commands_file):
try:
with open(args.commands_file, 'r') as f:
# Check if the file contains JSON or line-by-line commands
content = f.read().strip()
if content.startswith('[') and content.endswith(']'):
# JSON format
try:
json_commands = json.loads(content)
if isinstance(json_commands, list):
setup_commands.extend(json_commands)
print(f"📋 Loaded {len(json_commands)} commands from JSON file {args.commands_file}")
else:
print(f"⚠️ Invalid JSON format in commands file: not a list")
except json.JSONDecodeError as json_err:
print(f"⚠️ Error parsing JSON commands file: {json_err}")
# Fall back to line-by-line parsing
file_commands = [line.strip() for line in content.split('\n') if line.strip()]
setup_commands.extend(file_commands)
print(f"📋 Loaded {len(file_commands)} commands from file (line-by-line fallback)")
else:
# Line-by-line format
file_commands = [line.strip() for line in content.split('\n') if line.strip()]
setup_commands.extend(file_commands)
print(f"📋 Loaded {len(file_commands)} commands from file (line-by-line format)")
except Exception as e:
print(f"⚠️ Error loading commands from file: {e}")
# Load commands from setup script if specified
if args.setup_script and os.path.exists(args.setup_script):
try:
with open(args.setup_script, 'r') as f:
script_content = f.read().strip()
# Convert script to individual commands
script_commands = [line.strip() for line in script_content.split('\n')
if line.strip() and not line.strip().startswith('#')]
setup_commands.extend(script_commands)
print(f"📋 Loaded {len(script_commands)} commands from script {args.setup_script}")
except Exception as e:
print(f"⚠️ Error loading commands from script: {e}")
# Create the container with the specified options
if args.ssh_password:
print(f"🔑 Using provided SSH password")
ssh_password = args.ssh_password
else:
ssh_password = generate_random_password()
print(f"🔑 Generated random SSH password: {ssh_password}")
# Extract repository name from URL if not provided
repo_name = args.repo_name
if not repo_name and args.repo_url:
# Try to extract repo name from URL
url_parts = args.repo_url.rstrip('/').split('/')
if url_parts:
repo_name = url_parts[-1]
if repo_name.endswith('.git'):
repo_name = repo_name[:-4]
# Create the container
result = create_modal_ssh_container(
gpu_type=args.gpu,
repo_url=args.repo_url,
repo_name=repo_name,
setup_commands=setup_commands,
volume_name=args.volume_name,
timeout_minutes=args.timeout,
ssh_password=ssh_password,
interactive=args.interactive,
gpu_count=getattr(args, 'gpu_count', 1),
)
if result:
print(f"\n✅ Container operation completed: {result.get('status', 'success')}")
if result.get('function_call_id'):
print(f"🆔 Function Call ID: {result['function_call_id']}")
print("💡 You can use this ID to check container status via Modal CLI")
else:
print("\n❌ Container creation failed")
except KeyboardInterrupt:
print("\n🛑 Operation cancelled by user")
cleanup_modal_token()
sys.exit(1)
except Exception as e:
print(f"\n❌ Unexpected error: {e}")
print("📋 Error details:")
import traceback
traceback.print_exc()
cleanup_modal_token()
sys.exit(1)
================================================
FILE: python/.env.example
================================================
# Modal Proxy Service Environment Variables
# Your Modal token (required)
MODAL_TOKEN=ak-eNMIXRdfbvpxIXcSHKPFQW
# Admin key for creating API keys (will be auto-generated if not set)
# ADMIN_KEY=your_admin_key_here
# Comma-separated list of pre-approved API keys (optional)
# API_KEYS=key1,key2,key3
# Port to run the server on (default: 5001)
PORT=5001
================================================
FILE: scripts/postinstall.js
================================================
#!/usr/bin/env node
const fs = require('fs-extra');
const path = require('path');
const { promisify } = require('util');
const { exec } = require('child_process');
const chalk = require('chalk');
const execAsync = promisify(exec);
// Path to the Python script in the package
const pythonScriptDir = path.join(__dirname, '..', 'python');
const pythonScriptPath = path.join(pythonScriptDir, 'test_modalSandboxScript.py');
// Path to the original Python script
const originalScriptPath = path.join(__dirname, '..', '..', '..', 'mcp-server', 'src', 'utils', 'test_modalSandboxScript.py');
// Function to check and install uv
async function checkAndInstallUv() {
try {
// Check if uv is already installed
const { stdout } = await execAsync('uv --version');
console.log(chalk.green(`✅ uv is already installed: ${stdout.trim()}`));
return true;
} catch (error) {
console.log(chalk.yellow('⚠️ uv not found. Attempting to install...'));
// Detect platform for appropriate installation methods
const platform = process.platform;
let installMethods = [];
if (platform === 'darwin') {
// macOS - prioritize Homebrew
installMethods = [
'curl -LsSf https://astral.sh/uv/install.sh | sh',
'pip install uv',
'pip3 install uv',
'brew install uv',
'cargo install uv'
];
} else if (platform === 'win32') {
// Windows - use PowerShell script and pip
installMethods = [
'powershell -c "irm https://astral.sh/uv/install.ps1 | iex"',
'pip install uv',
'pip3 install uv',
'cargo install uv'
];
} else {
// Linux and others
installMethods = [
'curl -LsSf https://astral.sh/uv/install.sh | sh',
'pip3 install uv',
'pip install uv',
'cargo install uv'
];
}
for (const method of installMethods) {
try {
console.log(chalk.gray(`🔄 Trying to install uv with: ${method}`));
if (method.includes('curl')) {
// For curl installation, we need to handle the shell script
await execAsync(method, {
env: { ...process.env, SHELL: '/bin/bash' },
stdio: 'inherit'
});
} else if (method.includes('powershell')) {
// For Windows PowerShell installation
await execAsync(method, {
shell: 'powershell.exe',
stdio: 'inherit'
});
} else {
await execAsync(method, { stdio: 'inherit' });
}
// Verify installation
const { stdout } = await execAsync('uv --version');
console.log(chalk.green(`✅ uv installed successfully: ${stdout.trim()}`));
return true;
} catch (installError) {
console.log(chalk.gray(`⚠️ ${method} failed: ${installError.message}`));
}
}
return false;
}
}
// Function to create and activate virtual environment using uv
async function createVirtualEnvironment() {
const packages = ['modal', 'gitingest', 'requests', 'anthropic'];
const packageDir = path.join(__dirname, '..');
console.log(chalk.yellow(`📦 Creating virtual environment with uv and installing packages: ${packages.join(', ')}`));
console.log(chalk.gray(`📁 Working directory: ${packageDir}`));
try {
// First, ensure uv is available
let uvAvailable = false;
try {
const { stdout } = await execAsync('uv --version');
console.log(chalk.green(`✅ uv found: ${stdout.trim()}`));
uvAvailable = true;
} catch (error) {
console.log(chalk.yellow('⚠️ uv not found, attempting to install...'));
uvAvailable = await checkAndInstallUv();
}
if (!uvAvailable) {
console.log(chalk.red('❌ uv is required but not available'));
return false;
}
// Check if virtual environment already exists
const venvPath = path.join(packageDir, '.venv');
if (await fs.pathExists(venvPath)) {
console.log(chalk.yellow('⚠️ Virtual environment already exists, removing it...'));
await fs.remove(venvPath);
}
console.log(chalk.gray(`🔄 Creating virtual environment with uv...`));
// Create virtual environment using uv
await execAsync('uv venv', {
cwd: packageDir,
env: { ...process.env, PYTHONIOENCODING: 'utf-8' },
stdio: 'inherit'
});
// Verify virtual environment was created
if (!(await fs.pathExists(venvPath))) {
throw new Error('Virtual environment was not created');
}
console.log(chalk.green('✅ Virtual environment created successfully with uv!'));
console.log(chalk.gray(`🔄 Installing packages in virtual environment with uv...`));
// Install packages using uv pip from requirements.txt
const requirementsPath = path.join(packageDir, 'python', 'requirements.txt');
if (await fs.pathExists(requirementsPath)) {
console.log(chalk.gray(`📦 Installing packages from requirements.txt...`));
await execAsync(`uv pip install -r ${requirementsPath}`, {
cwd: packageDir,
env: { ...process.env, PYTHONIOENCODING: 'utf-8' },
stdio: 'inherit'
});
} else {
console.log(chalk.gray(`📦 Installing packages: ${packages.join(', ')}`));
await execAsync(`uv pip install ${packages.join(' ')}`, {
cwd: packageDir,
env: { ...process.env, PYTHONIOENCODING: 'utf-8' },
stdio: 'inherit'
});
}
console.log(chalk.green('✅ Python packages installed successfully in virtual environment!'));
// Verify packages are installed
const pythonPath = path.join(venvPath, 'bin', 'python');
const packagesToVerify = [...packages, 'anthropic']; // Ensure anthropic is checked
for (const pkg of packagesToVerify) {
try {
await execAsync(`${pythonPath} -c "import ${pkg}; print('${pkg} imported successfully')"`);
console.log(chalk.green(`✅ ${pkg} verified`));
} catch (error) {
console.log(chalk.yellow(`⚠️ ${pkg} verification failed: ${error.message}`));
}
}
// Create a script to activate the virtual environment
const isWindows = process.platform === 'win32';
const activateScript = isWindows ?
`@echo off
cd /d "%~dp0"
call ".venv\\Scripts\\activate.bat"
%*` :
`#!/bin/bash
cd "$(dirname "$0")"
source ".venv/bin/activate"
exec "$@"`;
const activateScriptPath = path.join(packageDir, 'activate_venv' + (isWindows ? '.bat' : '.sh'));
await fs.writeFile(activateScriptPath, activateScript);
if (!isWindows) {
await fs.chmod(activateScriptPath, 0o755);
}
console.log(chalk.green(`✅ Virtual environment activation script created: ${activateScriptPath}`));
// Create a status file to indicate successful installation
const statusFile = path.join(packageDir, '.venv_status.json');
await fs.writeJson(statusFile, {
created: new Date().toISOString(),
packages: packages,
uv_version: (await execAsync('uv --version')).stdout.trim()
});
console.log(chalk.green('✅ Virtual environment setup completed successfully!'));
return true;
} catch (error) {
console.log(chalk.red(`❌ Error creating virtual environment with uv: ${error.message}`));
console.log(chalk.yellow('💡 Please run manually:'));
console.log(chalk.yellow(' cd /root/.nvm/versions/node/v22.18.0/lib/node_modules/gitarsenal-cli'));
console.log(chalk.yellow(' uv venv'));
console.log(chalk.yellow(' uv pip install -r python/requirements.txt'));
return false;
}
}
// Function to check Python
async function checkPython() {
const pythonCommands = ['python3', 'python', 'py'];
for (const cmd of pythonCommands) {
try {
const { stdout } = await execAsync(`${cmd} --version`);
console.log(chalk.green(`✅ Python found: ${stdout.trim()}`));
return true;
} catch (error) {
// Continue to next command
}
}
console.log(chalk.red('❌ Python not found. Please install Python 3.7+'));
console.log(chalk.yellow('💡 Download from: https://www.python.org/downloads/'));
return false;
}
// Function to check Git
async function checkGit() {
try {
const { stdout } = await execAsync('git --version');
console.log(chalk.green(`✅ Git found: ${stdout.trim()}`));
return true;
} catch (error) {
console.log(chalk.yellow('⚠️ Git not found. Please install Git:'));
console.log(chalk.yellow(' macOS: brew install git'));
console.log(chalk.yellow(' Ubuntu: sudo apt-get install git'));
console.log(chalk.yellow(' Windows: https://git-scm.com/download/win'));
return false;
}
}
async function postinstall() {
try {
console.log(chalk.blue('📦 Running GitArsenal CLI postinstall script...'));
console.log(chalk.gray(`📁 Package directory: ${path.join(__dirname, '..')}`));
// Check Python first
console.log(chalk.blue('🔍 Checking Python installation...'));
const pythonOk = await checkPython();
if (!pythonOk) {
console.log(chalk.red('❌ Python is required for GitArsenal CLI'));
process.exit(1);
}
// Check Git
console.log(chalk.blue('🔍 Checking Git installation...'));
await checkGit();
// Check and install uv if needed
console.log(chalk.blue('🔍 Checking for uv package manager...'));
await checkAndInstallUv();
// Install Python packages in virtual environment
console.log(chalk.blue('🔍 Installing Python dependencies in virtual environment...'));
const venvCreated = await createVirtualEnvironment();
if (!venvCreated) {
console.log(chalk.red('❌ Failed to create virtual environment'));
process.exit(1);
}
// Create the Python directory if it doesn't exist
await fs.ensureDir(pythonScriptDir);
// Check if the Python script already exists and has content
let scriptFound = false;
if (await fs.pathExists(pythonScriptPath)) {
const stats = await fs.stat(pythonScriptPath);
// If the file is larger than 5KB, assume it's the full script
if (stats.size > 5000) {
console.log(chalk.green('✅ Found existing full Python script. Keeping it.'));
scriptFound = true;
} else {
console.log(chalk.yellow('⚠️ Existing Python script appears to be minimal. Looking for full version...'));
}
}
// Only try to copy if the script doesn't exist or is minimal
if (!scriptFound) {
// Check if the original script exists in a different location
if (await fs.pathExists(originalScriptPath)) {
console.log(chalk.green('✅ Found original Python script in mcp-server'));
await fs.copy(originalScriptPath, pythonScriptPath);
scriptFound = true;
} else {
// Try to find the script in common locations
console.log(chalk.yellow('⚠️ Original script not found in expected location. Searching for alternatives...'));
const possibleLocations = [
path.join(process.cwd(), 'python', 'test_modalSandboxScript.py'),
];
for (const location of possibleLocations) {
if (await fs.pathExists(location) && location !== pythonScriptPath) {
console.log(chalk.green(`✅ Found Python script at ${location}`));
await fs.copy(location, pythonScriptPath);
scriptFound = true;
break;
}
}
}
}
// If script not found, create it from embedded content
if (!scriptFound) {
console.log(chalk.yellow('⚠️ Python script not found. Creating from embedded content...'));
// Create a minimal version of the script
const minimalScript = `#!/usr/bin/env python3
# This is a minimal version of the Modal sandbox script
# For full functionality, please ensure the original script is available
import os
import sys
import argparse
import subprocess
def main():
parser = argparse.ArgumentParser(description='Create a Modal sandbox with GPU')
parser.add_argument('--gpu', type=str, default='A10G', help='GPU type (default: A10G)')
parser.add_argument('--repo-url', type=str, help='Repository URL to clone')
parser.add_argument('--repo-name', type=str, help='Repository name override')
parser.add_argument('--volume-name', type=str, help='Name of the Modal volume for persistent storage')
parser.add_argument('--commands-file', type=str, help='Path to file containing setup commands (one per line)')
args = parser.parse_args()
# Check if modal is installed
try:
subprocess.run(['modal', '--version'], check=True, capture_output=True)
except (subprocess.SubprocessError, FileNotFoundError):
print("❌ Modal CLI not found. Please install it with: pip install modal")
sys.exit(1)
# Build the modal command
cmd = [
'modal', 'run', '--gpu', args.gpu.lower(),
'--command', f'git clone {args.repo_url} && cd $(basename {args.repo_url} .git) && bash'
]
# Execute the command
print(f"🚀 Launching Modal sandbox with {args.gpu} GPU...")
print(f"📥 Cloning repository: {args.repo_url}")
try:
subprocess.run(cmd)
except Exception as e:
print(f"❌ Error: {e}")
sys.exit(1)
if __name__ == "__main__":
main()
`;
await fs.writeFile(pythonScriptPath, minimalScript);
console.log(chalk.yellow('⚠️ Created minimal Python script. For full functionality, please install the original script.'));
}
// Make the script executable
try {
await fs.chmod(pythonScriptPath, 0o755);
console.log(chalk.green('✅ Made Python script executable'));
} catch (error) {
console.log(chalk.yellow(`⚠️ Could not make script executable: ${error.message}`));
}
// Final success message
console.log(chalk.green(`
✅ GitArsenal CLI Installation Complete!
========================================
What was installed:
• GitArsenal CLI (npm package)
• Virtual environment with Python packages:
- Modal
- GitIngest
- Requests
- Anthropic (for Claude fallback)
💡 Next steps:
• Run: gitarsenal --help
• Run: gitarsenal setup
• Visit: https://gitarsenal.dev
💡 To activate the virtual environment:
• Unix/macOS: source .venv/bin/activate
• Windows: .venv\\Scripts\\activate.bat
• Or use: ./activate_venv.sh (Unix/macOS) or activate_venv.bat (Windows)
💡 Claude Fallback:
• Set ANTHROPIC_API_KEY for Claude fallback functionality
• Run: python test_claude_fallback.py to test
Having issues? Run: gitarsenal --debug
`));
} catch (error) {
console.error(chalk.red(`❌ Error during postinstall: ${error.message}`));
process.exit(1);
}
}
postinstall();