144 lines
5.5 KiB
TypeScript
144 lines
5.5 KiB
TypeScript
import type { BaseLanguageModelCallOptions } from "@langchain/core/language_models/base";
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import { SimpleChatModel, type BaseChatModelParams, LangSmithParams } from "@langchain/core/language_models/chat_models";
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import { CallbackManagerForLLMRun } from "@langchain/core/callbacks/manager";
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import { BaseMessage } from "@langchain/core/messages";
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import { ChatGenerationChunk } from "@langchain/core/outputs";
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import type { StringWithAutocomplete } from "@langchain/core/utils/types";
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import { type OllamaInput, type OllamaMessage } from "../utils/ollama.js";
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/**
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* @deprecated Deprecated in favor of the `@langchain/ollama` package. Import from `@langchain/ollama` instead.
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*/
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export interface ChatOllamaInput extends OllamaInput {
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}
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/**
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* @deprecated Deprecated in favor of the `@langchain/ollama` package. Import from `@langchain/ollama` instead.
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*/
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export interface ChatOllamaCallOptions extends BaseLanguageModelCallOptions {
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}
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/**
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* @deprecated Deprecated in favor of the `@langchain/ollama` package. Import from `@langchain/ollama` instead.
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*
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* A class that enables calls to the Ollama API to access large language
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* models in a chat-like fashion. It extends the SimpleChatModel class and
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* implements the OllamaInput interface.
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* @example
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* ```typescript
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* const prompt = ChatPromptTemplate.fromMessages([
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* [
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* "system",
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* `You are an expert translator. Format all responses as JSON objects with two keys: "original" and "translated".`,
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* ],
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* ["human", `Translate "{input}" into {language}.`],
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* ]);
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*
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* const model = new ChatOllama({
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* baseUrl: "http://api.example.com",
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* model: "llama2",
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* format: "json",
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* });
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*
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* const chain = prompt.pipe(model);
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*
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* const result = await chain.invoke({
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* input: "I love programming",
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* language: "German",
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* });
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*
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* ```
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*/
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export declare class ChatOllama extends SimpleChatModel<ChatOllamaCallOptions> implements ChatOllamaInput {
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static lc_name(): string;
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lc_serializable: boolean;
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model: string;
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baseUrl: string;
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keepAlive: string;
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embeddingOnly?: boolean;
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f16KV?: boolean;
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frequencyPenalty?: number;
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headers?: Record<string, string>;
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logitsAll?: boolean;
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lowVram?: boolean;
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mainGpu?: number;
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mirostat?: number;
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mirostatEta?: number;
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mirostatTau?: number;
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numBatch?: number;
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numCtx?: number;
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numGpu?: number;
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numGqa?: number;
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numKeep?: number;
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numPredict?: number;
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numThread?: number;
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penalizeNewline?: boolean;
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presencePenalty?: number;
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repeatLastN?: number;
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repeatPenalty?: number;
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ropeFrequencyBase?: number;
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ropeFrequencyScale?: number;
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temperature?: number;
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stop?: string[];
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tfsZ?: number;
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topK?: number;
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topP?: number;
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typicalP?: number;
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useMLock?: boolean;
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useMMap?: boolean;
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vocabOnly?: boolean;
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format?: StringWithAutocomplete<"json">;
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constructor(fields: OllamaInput & BaseChatModelParams);
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getLsParams(options: this["ParsedCallOptions"]): LangSmithParams;
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_llmType(): string;
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/**
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* A method that returns the parameters for an Ollama API call. It
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* includes model and options parameters.
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* @param options Optional parsed call options.
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* @returns An object containing the parameters for an Ollama API call.
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*/
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invocationParams(options?: this["ParsedCallOptions"]): {
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model: string;
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format: StringWithAutocomplete<"json"> | undefined;
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keep_alive: string;
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options: {
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embedding_only: boolean | undefined;
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f16_kv: boolean | undefined;
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frequency_penalty: number | undefined;
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logits_all: boolean | undefined;
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low_vram: boolean | undefined;
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main_gpu: number | undefined;
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mirostat: number | undefined;
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mirostat_eta: number | undefined;
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mirostat_tau: number | undefined;
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num_batch: number | undefined;
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num_ctx: number | undefined;
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num_gpu: number | undefined;
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num_gqa: number | undefined;
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num_keep: number | undefined;
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num_predict: number | undefined;
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num_thread: number | undefined;
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penalize_newline: boolean | undefined;
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presence_penalty: number | undefined;
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repeat_last_n: number | undefined;
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repeat_penalty: number | undefined;
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rope_frequency_base: number | undefined;
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rope_frequency_scale: number | undefined;
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temperature: number | undefined;
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stop: string[] | undefined;
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tfs_z: number | undefined;
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top_k: number | undefined;
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top_p: number | undefined;
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typical_p: number | undefined;
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use_mlock: boolean | undefined;
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use_mmap: boolean | undefined;
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vocab_only: boolean | undefined;
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};
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};
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_combineLLMOutput(): {};
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/** @deprecated */
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_streamResponseChunksLegacy(input: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<ChatGenerationChunk>;
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_streamResponseChunks(input: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): AsyncGenerator<ChatGenerationChunk>;
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protected _convertMessagesToOllamaMessages(messages: BaseMessage[]): OllamaMessage[];
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/** @deprecated */
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protected _formatMessagesAsPrompt(messages: BaseMessage[]): string;
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/** @ignore */
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_call(messages: BaseMessage[], options: this["ParsedCallOptions"], runManager?: CallbackManagerForLLMRun): Promise<string>;
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}
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