import { ProviderV1, LanguageModelV1, EmbeddingModelV1 } from '@ai-sdk/provider';

type OllamaChatModelId = 'athene-v2' | 'athene-v2:72b' | 'aya-expanse' | 'aya-expanse:8b' | 'aya-expanse:32b' | 'codegemma' | 'codegemma:2b' | 'codegemma:7b' | 'codellama' | 'codellama:7b' | 'codellama:13b' | 'codellama:34b' | 'codellama:70b' | 'codellama:code' | 'codellama:python' | 'command-r' | 'command-r:35b' | 'command-r-plus' | 'command-r-plus:104b' | 'command-r7b' | 'command-r7b:7b' | 'deepseek-coder-v2' | 'deepseek-coder-v2:16b' | 'deepseek-coder-v2:236b' | 'deepseek-v3' | 'deepseek-v3:671b' | 'dolphin3' | 'dolphin3:8b' | 'exaone3.5' | 'exaone3.5:2.4b' | 'exaone3.5:7.8b' | 'exaone3.5:32b' | 'falcon2' | 'falcon2:11b' | 'falcon3' | 'falcon3:1b' | 'falcon3:3b' | 'falcon3:7b' | 'falcon3:10b' | 'firefunction-v2' | 'firefunction-v2:70b' | 'gemma' | 'gemma:2b' | 'gemma:7b' | 'gemma2' | 'gemma2:2b' | 'gemma2:9b' | 'gemma2:27b' | 'granite3-dense' | 'granite3-dense:2b' | 'granite3-dense:8b' | 'granite3-guardian' | 'granite3-guardian:2b' | 'granite3-guardian:8b' | 'granite3-moe' | 'granite3-moe:1b' | 'granite3-moe:3b' | 'granite3.1-dense' | 'granite3.1-dense:2b' | 'granite3.1-dense:8b' | 'granite3.1-moe' | 'granite3.1-moe:1b' | 'granite3.1-moe:3b' | 'llama2' | 'llama2:7b' | 'llama2:13b' | 'llama2:70b' | 'llama3' | 'llama3:8b' | 'llama3:70b' | 'llama3-chatqa' | 'llama3-chatqa:8b' | 'llama3-chatqa:70b' | 'llama3-gradient' | 'llama3-gradient:8b' | 'llama3-gradient:70b' | 'llama3.1' | 'llama3.1:8b' | 'llama3.1:70b' | 'llama3.1:405b' | 'llama3.2' | 'llama3.2:1b' | 'llama3.2:3b' | 'llama3.2-vision' | 'llama3.2-vision:11b' | 'llama3.2-vision:90b' | 'llama3.3' | 'llama3.3:70b' | 'llama-guard3' | 'llama-guard3:1b' | 'llama-guard3:8b' | 'llava' | 'llava:7b' | 'llava:13b' | 'llava:34b' | 'llava-llama3' | 'llava-llama3:8b' | 'llava-phi3' | 'llava-phi3:3.8b' | 'marco-o1' | 'marco-o1:7b' | 'mistral' | 'mistral:7b' | 'mistral-large' | 'mistral-large:123b' | 'mistral-nemo' | 'mistral-nemo:12b' | 'mistral-small' | 'mistral-small:22b' | 'mixtral' | 'mixtral:8x7b' | 'mixtral:8x22b' | 'moondream' | 'moondream:1.8b' | 'openhermes' | 'openhermes:v2.5' | 'nemotron' | 'nemotron:70b' | 'nemotron-mini' | 'nemotron-mini:4b' | 'olmo' | 'olmo:7b' | 'olmo:13b' | 'opencoder' | 'opencoder:1.5b' | 'opencoder:8b' | 'phi3' | 'phi3:3.8b' | 'phi3:14b' | 'phi3.5' | 'phi3.5:3.8b' | 'phi4' | 'phi4:14b' | 'qwen' | 'qwen:7b' | 'qwen:14b' | 'qwen:32b' | 'qwen:72b' | 'qwen:110b' | 'qwen2' | 'qwen2:0.5b' | 'qwen2:1.5b' | 'qwen2:7b' | 'qwen2:72b' | 'qwen2.5' | 'qwen2.5:0.5b' | 'qwen2.5:1.5b' | 'qwen2.5:3b' | 'qwen2.5:7b' | 'qwen2.5:14b' | 'qwen2.5:32b' | 'qwen2.5:72b' | 'qwen2.5-coder' | 'qwen2.5-coder:0.5b' | 'qwen2.5-coder:1.5b' | 'qwen2.5-coder:3b' | 'qwen2.5-coder:7b' | 'qwen2.5-coder:14b' | 'qwen2.5-coder:32b' | 'qwq' | 'qwq:32b' | 'sailor2' | 'sailor2:1b' | 'sailor2:8b' | 'sailor2:20b' | 'shieldgemma' | 'shieldgemma:2b' | 'shieldgemma:9b' | 'shieldgemma:27b' | 'smallthinker' | 'smallthinker:3b' | 'smollm' | 'smollm:135m' | 'smollm:360m' | 'smollm:1.7b' | 'tinyllama' | 'tinyllama:1.1b' | 'tulu3' | 'tulu3:8b' | 'tulu3:70b' | (string & NonNullable<unknown>);
interface OllamaChatSettings {
    /**
     * Until Ollama officially supports tool calling in streams, the provider can try to detect function calls. Enabled by
     * default to maintain backward compatibility, disable it if you encounter any issues.
     *
     * @deprecated Use `simulateStreaming` instead.
     */
    experimentalStreamTools?: boolean;
    /**
     * Enables the use of half-precision floating point values for key-value memory. This helps in optimizing memory usage. (Default: true)
     */
    f16Kv?: boolean;
    /**
     * If set to true, reduces the VRAM usage by trading off speed for memory. (Default: false)
     */
    lowVram?: boolean;
    /**
     * Sets which GPU is the main one.
     */
    mainGpu?: number;
    /**
     * Minimum cumulative probability for tokens to be considered. (Default: 0.0)
     */
    minP?: number;
    /**
     * Enable Mirostat sampling for controlling perplexity. (default: 0, 0 = disabled, 1 = Mirostat, 2 = Mirostat 2.0)
     */
    mirostat?: 0 | 1 | 2;
    /**
     * Influences how quickly the algorithm responds to feedback from the generated text. A lower learning rate will
     * result in slower adjustments, while a higher learning rate will make the algorithm more responsive. (Default: 0.1)
     */
    mirostatEta?: number;
    /**
     * Controls the balance between coherence and diversity of the output. A lower value will result in more focused and
     * coherent text. (Default: 5.0)
     */
    mirostatTau?: number;
    /**
     * Controls whether to use Non-Uniform Memory Access (NUMA) for more efficient memory management. (Default: false)
     */
    numa?: boolean;
    /**
     * Sets the number of batches to be processed. (Default: 512)
     */
    numBatch?: number;
    /**
     * Sets the size of the context window used to generate the next token. (Default: 2048)
     */
    numCtx?: number;
    /**
     * Controls the number of GPUs to use for the operation. (Default: -1, indicates that NumGPU should be set dynamically)
     */
    numGpu?: number;
    /**
     * Keeps a number of tokens from the context. Controls how many of the previous tokens are retained. (Default: 4)
     */
    numKeep?: number;
    /**
     * Controls the number of tokens to predict in a single generation. (Default: -1)
     */
    numPredict?: number;
    /**
     * Sets the number of CPU threads to use. (Default: 0, indicates let the runtime decide)
     */
    numThread?: number;
    /**
     * Penalizes the model for generating newline characters. If set to true, it discourages the model from generating too many newlines. (Default: true)
     */
    penalizeNewline?: boolean;
    /**
     * Sets how far back for the model to look back to prevent repetition. (Default: 64, 0 = disabled, -1 = num_ctx)
     */
    repeatLastN?: number;
    /**
     * Sets how strongly to penalize repetitions. A higher value (e.g., 1.5) will penalize repetitions more strongly
     * , while a lower value (e.g., 0.9) will be more lenient. (Default: 1.1)
     */
    repeatPenalty?: number;
    /**
     Simulates streaming by using a normal generate call and returning it as a stream.
     Enable this if the model that you are using does not support streaming.
  
     Defaults to `false`.
     */
    simulateStreaming?: boolean;
    /**
     * Whether to use structured outputs. Defaults to false.
     *
     * When enabled, tool calls and object generation will be strict and follow the provided schema.
     */
    structuredOutputs?: boolean;
    /**
     * Tail free sampling is used to reduce the impact of less probable tokens from the output. A higher value (e.g., 2.0)
     * will reduce the impact more, while a value of 1.0 disables this setting. (default: 1)
     */
    tfsZ?: number;
    /**
     * Controls the "typical" sampling probability. (Default: 1.0)
     */
    typicalP?: number;
    /**
     * Locks the memory to prevent swapping, which can be useful for performance optimization. (Default: false)
     */
    useMlock?: boolean;
    /**
     * Enables memory mapping to reduce RAM usage. (Default: false)
     */
    useMmap?: boolean;
    /**
     * If true, the model will only load the vocabulary without performing further computation. (Default: false)
     */
    vocabOnly?: boolean;
}

type OllamaEmbeddingModelId = 'all-minilm' | 'all-minilm:22m' | 'all-minilm:33m' | 'bge-large' | 'bge-m3' | 'granite-embedding' | 'granite-embedding:30m' | 'granite-embedding:278m' | 'mxbai-embed-large' | 'nomic-embed-text' | 'paraphrase-multilingual' | 'snowflake-arctic-embed' | 'snowflake-arctic-embed:110m' | 'snowflake-arctic-embed:137m' | 'snowflake-arctic-embed:22m' | 'snowflake-arctic-embed:335m' | 'snowflake-arctic-embed:33m' | 'snowflake-arctic-embed2' | 'snowflake-arctic-embed2:568m' | OllamaChatModelId | (string & NonNullable<unknown>);
interface OllamaEmbeddingSettings {
    maxEmbeddingsPerCall?: number;
    truncate?: boolean;
}

interface OllamaProvider extends ProviderV1 {
    (modelId: OllamaChatModelId, settings?: OllamaChatSettings): LanguageModelV1;
    chat(modelId: OllamaChatModelId, settings?: OllamaChatSettings): LanguageModelV1;
    embedding(modelId: OllamaEmbeddingModelId, settings?: OllamaEmbeddingSettings): EmbeddingModelV1<string>;
    languageModel(modelId: OllamaChatModelId, settings?: OllamaChatSettings): LanguageModelV1;
    textEmbeddingModel(modelId: OllamaEmbeddingModelId, settings?: OllamaEmbeddingSettings): EmbeddingModelV1<string>;
}
interface OllamaProviderSettings {
    /**
     * Base URL for Ollama API calls.
     */
    baseURL?: string;
    /**
     * Custom fetch implementation. You can use it as a middleware to intercept
     * requests or to provide a custom fetch implementation for e.g. testing
     */
    fetch?: typeof fetch;
    /**
     * Custom headers to include in the requests.
     */
    headers?: Record<string, string>;
}
declare function createOllama(options?: OllamaProviderSettings): OllamaProvider;
declare const ollama: OllamaProvider;

export { type OllamaProvider, type OllamaProviderSettings, createOllama, ollama };