{"version":3,"file":"fireworks.cjs","names":["ChatOpenAICompletions"],"sources":["../../src/chat_models/fireworks.ts"],"sourcesContent":["import type {\n  BaseChatModelParams,\n  LangSmithParams,\n} from \"@langchain/core/language_models/chat_models\";\nimport {\n  type OpenAIClient,\n  type ChatOpenAICallOptions,\n  type OpenAIChatInput,\n  type OpenAICoreRequestOptions,\n  ChatOpenAICompletions,\n} from \"@langchain/openai\";\n\nimport { getEnvironmentVariable } from \"@langchain/core/utils/env\";\n\ntype FireworksUnsupportedArgs =\n  | \"frequencyPenalty\"\n  | \"presencePenalty\"\n  | \"logitBias\"\n  | \"functions\";\n\ntype FireworksUnsupportedCallOptions = \"functions\" | \"function_call\";\n\nexport type ChatFireworksCallOptions = Partial<\n  Omit<ChatOpenAICallOptions, FireworksUnsupportedCallOptions>\n>;\n\n/**\n * Wrapper around Fireworks API for large language models fine-tuned for chat\n *\n * Fireworks API is compatible to the OpenAI API with some limitations described in\n * https://readme.fireworks.ai/docs/openai-compatibility.\n *\n * To use, you should have the `FIREWORKS_API_KEY` environment variable set.\n *\n * Setup:\n * Install `@langchain/community` and set a environment variable called `FIREWORKS_API_KEY`.\n *\n * ```bash\n * npm install @langchain/community\n * export FIREWORKS_API_KEY=\"your-api-key\"\n * ```\n *\n * ## [Constructor args](https://api.js.langchain.com/classes/langchain_community_chat_models_fireworks.ChatFireworks.html#constructor)\n *\n * ## [Runtime args](https://api.js.langchain.com/interfaces/langchain_openai.ChatOpenAICallOptions.html)\n *\n * Because the Fireworks API extends OpenAI's, the call option type is the same.\n *\n * Runtime args can be passed as the second argument to any of the base runnable methods `.invoke`. `.stream`, `.batch`, etc.\n * They can also be passed via `.withConfig`, or the second arg in `.bindTools`, like shown in the examples below:\n *\n * ```typescript\n * // When calling `.withConfig`, call options should be passed via the first argument\n * const llmWithArgsBound = llm.withConfig({\n *   stop: [\"\\n\"],\n *   tools: [...],\n * });\n *\n * // When calling `.bindTools`, call options should be passed via the second argument\n * const llmWithTools = llm.bindTools(\n *   [...],\n *   {\n *     stop: [\"\\n\"],\n *   }\n * );\n * ```\n *\n * ## Examples\n *\n * <details open>\n * <summary><strong>Instantiate</strong></summary>\n *\n * ```typescript\n * import { ChatFireworks } from '@langchain/community/chat_models/fireworks';\n *\n * const llm = new ChatFireworks({\n *   model: \"command-r-plus\",\n *   temperature: 0,\n *   // other params...\n * });\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n * <summary><strong>Invoking</strong></summary>\n *\n * ```typescript\n * const input = `Translate \"I love programming\" into French.`;\n *\n * // Models also accept a list of chat messages or a formatted prompt\n * const result = await llm.invoke(input);\n * console.log(result);\n * ```\n *\n * ```txt\n * AIMessage {\n *   \"id\": \"dbc233df-532e-4aaa-8995-9d6ea65fea15\",\n *   \"content\": \"The translation of \\\"I love programming\\\" into French is:\\n\\n\\\"J'adore la programmation.\\\"\\n\\nHere's a breakdown of the translation:\\n\\n* \\\"I\\\" is translated to \\\"Je\\\" (but in informal writing, it's common to use \\\"J'\\\" instead of \\\"Je\\\" when it's followed by a vowel)\\n* \\\"love\\\" is translated to \\\"adore\\\"\\n* \\\"programming\\\" is translated to \\\"la programmation\\\"\\n\\nSo, the complete translation is \\\"J'adore la programmation.\\\"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"tokenUsage\": {\n *       \"completionTokens\": 105,\n *       \"promptTokens\": 19,\n *       \"totalTokens\": 124\n *     },\n *     \"finish_reason\": \"stop\"\n *   },\n *   \"tool_calls\": [],\n *   \"invalid_tool_calls\": [],\n *   \"usage_metadata\": {\n *     \"input_tokens\": 19,\n *     \"output_tokens\": 105,\n *     \"total_tokens\": 124\n *   }\n * }\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n * <summary><strong>Streaming Chunks</strong></summary>\n *\n * ```typescript\n * for await (const chunk of await llm.stream(input)) {\n *   console.log(chunk);\n * }\n * ```\n *\n * ```txt\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \"The translation\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \" of \\\"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \"I love\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \" programming\\\"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \" into French\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \" is:\\n\\n\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \"\\\"J\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * ...\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \"ation.\\\"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": null\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"id\": \"ed5fc403-b7ed-4447-819f-f9645ea0277c\",\n *   \"content\": \"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": \"stop\"\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": []\n * }\n * AIMessageChunk {\n *   \"content\": \"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {},\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": [],\n *   \"usage_metadata\": {\n *     \"input_tokens\": 19,\n *     \"output_tokens\": 105,\n *     \"total_tokens\": 124\n *   }\n * }\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n * <summary><strong>Aggregate Streamed Chunks</strong></summary>\n *\n * ```typescript\n * import { AIMessageChunk } from '@langchain/core/messages';\n * import { concat } from '@langchain/core/utils/stream';\n *\n * const stream = await llm.stream(input);\n * let full: AIMessageChunk | undefined;\n * for await (const chunk of stream) {\n *   full = !full ? chunk : concat(full, chunk);\n * }\n * console.log(full);\n * ```\n *\n * ```txt\n * AIMessageChunk {\n *   \"id\": \"9b80e5af-0f50-4fb7-b700-6d431a819556\",\n *   \"content\": \"The translation of \\\"I love programming\\\" into French is:\\n\\n\\\"J'adore la programmation.\\\"\\n\\nHere's a breakdown of the translation:\\n\\n* \\\"I\\\" is translated to \\\"Je\\\" (but in informal writing, it's common to use \\\"J'\\\" instead of \\\"Je\\\" when it's followed by a vowel)\\n* \\\"love\\\" is translated to \\\"adore\\\"\\n* \\\"programming\\\" is translated to \\\"la programmation\\\"\\n\\nSo, the complete translation is \\\"J'adore la programmation.\\\"\",\n *   \"additional_kwargs\": {},\n *   \"response_metadata\": {\n *     \"prompt\": 0,\n *     \"completion\": 0,\n *     \"finish_reason\": \"stop\"\n *   },\n *   \"tool_calls\": [],\n *   \"tool_call_chunks\": [],\n *   \"invalid_tool_calls\": [],\n *   \"usage_metadata\": {\n *     \"input_tokens\": 19,\n *     \"output_tokens\": 105,\n *     \"total_tokens\": 124\n *   }\n * }\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n * <summary><strong>Bind tools</strong></summary>\n *\n * ```typescript\n * import { z } from 'zod';\n *\n * const llmForToolCalling = new ChatFireworks({\n *   // Use a model with tool calling capability\n *   model: \"accounts/fireworks/models/firefunction-v2\",\n *   temperature: 0,\n *   // other params...\n * });\n * const GetWeather = {\n *   name: \"GetWeather\",\n *   description: \"Get the current weather in a given location\",\n *   schema: z.object({\n *     location: z.string().describe(\"The city and state, e.g. San Francisco, CA\")\n *   }),\n * }\n *\n * const GetPopulation = {\n *   name: \"GetPopulation\",\n *   description: \"Get the current population in a given location\",\n *   schema: z.object({\n *     location: z.string().describe(\"The city and state, e.g. San Francisco, CA\")\n *   }),\n * }\n *\n * const llmWithTools = llmForToolCalling.bindTools([GetWeather, GetPopulation]);\n * const aiMsg = await llmWithTools.invoke(\n *   \"Which city is hotter today and which is bigger: LA or NY?\"\n * );\n * console.log(aiMsg.tool_calls);\n * ```\n *\n * ```txt\n * [\n *   {\n *     name: 'GetWeather',\n *     args: { location: 'Los Angeles, CA' },\n *     type: 'tool_call',\n *     id: 'call_9DE0WnhgKDbxu6HyHOkDQFub'\n *   },\n *   {\n *     name: 'GetWeather',\n *     args: { location: 'New York, NY' },\n *     type: 'tool_call',\n *     id: 'call_58lcAPTqQyiqepxynwARhGs8'\n *   },\n *   {\n *     name: 'GetPopulation',\n *     args: { location: 'Los Angeles, CA' },\n *     type: 'tool_call',\n *     id: 'call_r0m6AFoqaMvPp4Zt5aEAc0oE'\n *   },\n *   {\n *     name: 'GetPopulation',\n *     args: { location: 'New York, NY' },\n *     type: 'tool_call',\n *     id: 'call_mENaPG1ryOF44BmaW4VkBaSi'\n *   }\n * ]\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n * <summary><strong>Structured Output</strong></summary>\n *\n * ```typescript\n * import { z } from 'zod';\n *\n * const Joke = z.object({\n *   setup: z.string().describe(\"The setup of the joke\"),\n *   punchline: z.string().describe(\"The punchline to the joke\"),\n *   rating: z.number().optional().describe(\"How funny the joke is, from 1 to 10\")\n * }).describe('Joke to tell user.');\n *\n * const structuredLlm = llmForToolCalling.withStructuredOutput(Joke, { name: \"Joke\" });\n * const jokeResult = await structuredLlm.invoke(\"Tell me a joke about cats\");\n * console.log(jokeResult);\n * ```\n *\n * ```txt\n * {\n *   setup: 'Why did the cat join a band?',\n *   punchline: 'Because it wanted to be the purr-cussionist!',\n *   rating: 8\n * }\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n *\n * <summary><strong>Usage Metadata</strong></summary>\n *\n * ```typescript\n * const aiMsgForMetadata = await llm.invoke(input);\n * console.log(aiMsgForMetadata.usage_metadata);\n * ```\n *\n * ```txt\n * { input_tokens: 277, output_tokens: 8, total_tokens: 285 }\n * ```\n * </details>\n *\n * <br />\n *\n * <details>\n * <summary><strong>Response Metadata</strong></summary>\n *\n * ```typescript\n * const aiMsgForResponseMetadata = await llm.invoke(input);\n * console.log(aiMsgForResponseMetadata.response_metadata);\n * ```\n *\n * ```txt\n * {\n *   tokenUsage: { completionTokens: 8, promptTokens: 277, totalTokens: 285 },\n *   finish_reason: 'stop'\n * }\n * ```\n * </details>\n *\n * <br />\n */\nexport class ChatFireworks extends ChatOpenAICompletions<ChatFireworksCallOptions> {\n  static lc_name() {\n    return \"ChatFireworks\";\n  }\n\n  _llmType() {\n    return \"fireworks\";\n  }\n\n  get lc_secrets(): { [key: string]: string } | undefined {\n    return {\n      fireworksApiKey: \"FIREWORKS_API_KEY\",\n      apiKey: \"FIREWORKS_API_KEY\",\n    };\n  }\n\n  lc_serializable = true;\n\n  fireworksApiKey?: string;\n\n  apiKey?: string;\n\n  constructor(\n    fields?: Partial<\n      Omit<OpenAIChatInput, \"openAIApiKey\" | FireworksUnsupportedArgs>\n    > &\n      BaseChatModelParams & {\n        /**\n         * Prefer `apiKey`\n         */\n        fireworksApiKey?: string;\n        /**\n         * The Fireworks API key to use.\n         */\n        apiKey?: string;\n      }\n  ) {\n    const fireworksApiKey =\n      fields?.apiKey ||\n      fields?.fireworksApiKey ||\n      getEnvironmentVariable(\"FIREWORKS_API_KEY\");\n\n    if (!fireworksApiKey) {\n      throw new Error(\n        `Fireworks API key not found. Please set the FIREWORKS_API_KEY environment variable or provide the key into \"fireworksApiKey\"`\n      );\n    }\n\n    super({\n      ...fields,\n      model:\n        fields?.model ||\n        fields?.modelName ||\n        \"accounts/fireworks/models/llama-v3p1-8b-instruct\",\n      apiKey: fireworksApiKey,\n      configuration: {\n        baseURL: \"https://api.fireworks.ai/inference/v1\",\n      },\n      streamUsage: false,\n    });\n\n    this.fireworksApiKey = fireworksApiKey;\n    this.apiKey = fireworksApiKey;\n  }\n\n  getLsParams(options: this[\"ParsedCallOptions\"]): LangSmithParams {\n    const params = super.getLsParams(options);\n    params.ls_provider = \"fireworks\";\n    return params;\n  }\n\n  toJSON() {\n    const result = super.toJSON();\n\n    if (\n      \"kwargs\" in result &&\n      typeof result.kwargs === \"object\" &&\n      result.kwargs != null\n    ) {\n      delete result.kwargs.openai_api_key;\n      delete result.kwargs.configuration;\n    }\n\n    return result;\n  }\n\n  async completionWithRetry(\n    request: OpenAIClient.Chat.ChatCompletionCreateParamsStreaming,\n    options?: OpenAICoreRequestOptions\n  ): Promise<AsyncIterable<OpenAIClient.Chat.Completions.ChatCompletionChunk>>;\n\n  async completionWithRetry(\n    request: OpenAIClient.Chat.ChatCompletionCreateParamsNonStreaming,\n    options?: OpenAICoreRequestOptions\n  ): Promise<OpenAIClient.Chat.Completions.ChatCompletion>;\n\n  /**\n   * Calls the Fireworks API with retry logic in case of failures.\n   * @param request The request to send to the Fireworks API.\n   * @param options Optional configuration for the API call.\n   * @returns The response from the Fireworks API.\n   */\n  async completionWithRetry(\n    request:\n      | OpenAIClient.Chat.ChatCompletionCreateParamsStreaming\n      | OpenAIClient.Chat.ChatCompletionCreateParamsNonStreaming,\n    options?: OpenAICoreRequestOptions\n  ): Promise<\n    | AsyncIterable<OpenAIClient.Chat.Completions.ChatCompletionChunk>\n    | OpenAIClient.Chat.Completions.ChatCompletion\n  > {\n    delete request.frequency_penalty;\n    delete request.presence_penalty;\n    delete request.logit_bias;\n    delete request.functions;\n\n    if (request.stream === true) {\n      return super.completionWithRetry(request, options);\n    }\n\n    return super.completionWithRetry(request, options);\n  }\n}\n"],"mappings":";;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;AAicA,IAAa,gBAAb,cAAmCA,kBAAAA,sBAAgD;CACjF,OAAO,UAAU;AACf,SAAO;;CAGT,WAAW;AACT,SAAO;;CAGT,IAAI,aAAoD;AACtD,SAAO;GACL,iBAAiB;GACjB,QAAQ;GACT;;CAGH,kBAAkB;CAElB;CAEA;CAEA,YACE,QAaA;EACA,MAAM,kBACJ,QAAQ,UACR,QAAQ,oBAAA,GAAA,0BAAA,wBACe,oBAAoB;AAE7C,MAAI,CAAC,gBACH,OAAM,IAAI,MACR,+HACD;AAGH,QAAM;GACJ,GAAG;GACH,OACE,QAAQ,SACR,QAAQ,aACR;GACF,QAAQ;GACR,eAAe,EACb,SAAS,yCACV;GACD,aAAa;GACd,CAAC;AAEF,OAAK,kBAAkB;AACvB,OAAK,SAAS;;CAGhB,YAAY,SAAqD;EAC/D,MAAM,SAAS,MAAM,YAAY,QAAQ;AACzC,SAAO,cAAc;AACrB,SAAO;;CAGT,SAAS;EACP,MAAM,SAAS,MAAM,QAAQ;AAE7B,MACE,YAAY,UACZ,OAAO,OAAO,WAAW,YACzB,OAAO,UAAU,MACjB;AACA,UAAO,OAAO,OAAO;AACrB,UAAO,OAAO,OAAO;;AAGvB,SAAO;;;;;;;;CAmBT,MAAM,oBACJ,SAGA,SAIA;AACA,SAAO,QAAQ;AACf,SAAO,QAAQ;AACf,SAAO,QAAQ;AACf,SAAO,QAAQ;AAEf,MAAI,QAAQ,WAAW,KACrB,QAAO,MAAM,oBAAoB,SAAS,QAAQ;AAGpD,SAAO,MAAM,oBAAoB,SAAS,QAAQ"}