anything-llm/server/utils/agents/aibitat/providers/ai-provider.js

/**
 * A service that provides an AI client to create a completion.
 */

/**
 * @typedef {Object} LangChainModelConfig
 * @property {(string|null)} baseURL - Override the default base URL process.env for this provider
 * @property {(string|null)} apiKey - Override the default process.env for this provider
 * @property {(number|null)} temperature - Override the default temperature
 * @property {(string|null)} model -  Overrides model used for provider.
 */

const { ChatOpenAI } = require("@langchain/openai");
const { ChatAnthropic } = require("@langchain/anthropic");
const { ChatBedrockConverse } = require("@langchain/aws");
const { ChatOllama } = require("@langchain/community/chat_models/ollama");
const { toValidNumber } = require("../../../http");

const DEFAULT_WORKSPACE_PROMPT =
  "You are a helpful ai assistant who can assist the user and use tools available to help answer the users prompts and questions.";

class Provider {
  _client;
  constructor(client) {
    if (this.constructor == Provider) {
      return;
    }
    this._client = client;
  }

  providerLog(text, ...args) {
    console.log(
      `\x1b[36m[AgentLLM${this?.model ? ` - ${this.model}` : ""}]\x1b[0m ${text}`,
      ...args
    );
  }

  get client() {
    return this._client;
  }

  /**
   *
   * @param {string} provider - the string key of the provider LLM being loaded.
   * @param {LangChainModelConfig} config - Config to be used to override default connection object.
   * @returns
   */
  static LangChainChatModel(provider = "openai", config = {}) {
    switch (provider) {
      // Cloud models
      case "openai":
        return new ChatOpenAI({
          apiKey: process.env.OPEN_AI_KEY,
          ...config,
        });
      case "anthropic":
        return new ChatAnthropic({
          apiKey: process.env.ANTHROPIC_API_KEY,
          ...config,
        });
      case "groq":
        return new ChatOpenAI({
          configuration: {
            baseURL: "https://api.groq.com/openai/v1",
          },
          apiKey: process.env.GROQ_API_KEY,
          ...config,
        });
      case "mistral":
        return new ChatOpenAI({
          configuration: {
            baseURL: "https://api.mistral.ai/v1",
          },
          apiKey: process.env.MISTRAL_API_KEY ?? null,
          ...config,
        });
      case "openrouter":
        return new ChatOpenAI({
          configuration: {
            baseURL: "https://openrouter.ai/api/v1",
            defaultHeaders: {
              "HTTP-Referer": "https://anythingllm.com",
              "X-Title": "AnythingLLM",
            },
          },
          apiKey: process.env.OPENROUTER_API_KEY ?? null,
          ...config,
        });
      case "perplexity":
        return new ChatOpenAI({
          configuration: {
            baseURL: "https://api.perplexity.ai",
          },
          apiKey: process.env.PERPLEXITY_API_KEY ?? null,
          ...config,
        });
      case "togetherai":
        return new ChatOpenAI({
          configuration: {
            baseURL: "https://api.together.xyz/v1",
          },
          apiKey: process.env.TOGETHER_AI_API_KEY ?? null,
          ...config,
        });
      case "generic-openai":
        return new ChatOpenAI({
          configuration: {
            baseURL: process.env.GENERIC_OPEN_AI_BASE_PATH,
          },
          apiKey: process.env.GENERIC_OPEN_AI_API_KEY,
          maxTokens: toValidNumber(
            process.env.GENERIC_OPEN_AI_MAX_TOKENS,
            1024
          ),
          ...config,
        });
      case "bedrock":
        return new ChatBedrockConverse({
          model: process.env.AWS_BEDROCK_LLM_MODEL_PREFERENCE,
          region: process.env.AWS_BEDROCK_LLM_REGION,
          credentials: {
            accessKeyId: process.env.AWS_BEDROCK_LLM_ACCESS_KEY_ID,
            secretAccessKey: process.env.AWS_BEDROCK_LLM_ACCESS_KEY,
          },
          ...config,
        });

      // OSS Model Runners
      // case "anythingllm_ollama":
      //   return new ChatOllama({
      //     baseUrl: process.env.PLACEHOLDER,
      //     ...config,
      //   });
      case "ollama":
        return new ChatOllama({
          baseUrl: process.env.OLLAMA_BASE_PATH,
          ...config,
        });
      case "lmstudio":
        return new ChatOpenAI({
          configuration: {
            baseURL: process.env.LMSTUDIO_BASE_PATH?.replace(/\/+$/, ""),
          },
          apiKey: "not-used", // Needs to be specified or else will assume OpenAI
          ...config,
        });
      case "koboldcpp":
        return new ChatOpenAI({
          configuration: {
            baseURL: process.env.KOBOLD_CPP_BASE_PATH,
          },
          apiKey: "not-used",
          ...config,
        });
      case "localai":
        return new ChatOpenAI({
          configuration: {
            baseURL: process.env.LOCAL_AI_BASE_PATH,
          },
          apiKey: process.env.LOCAL_AI_API_KEY ?? "not-used",
          ...config,
        });
      case "textgenwebui":
        return new ChatOpenAI({
          configuration: {
            baseURL: process.env.TEXT_GEN_WEB_UI_BASE_PATH,
          },
          apiKey: process.env.TEXT_GEN_WEB_UI_API_KEY ?? "not-used",
          ...config,
        });
      default:
        throw new Error(`Unsupported provider ${provider} for this task.`);
    }
  }

  static contextLimit(provider = "openai") {
    switch (provider) {
      case "openai":
        return 8_000;
      case "anthropic":
        return 100_000;
      default:
        return 8_000;
    }
  }

  // For some providers we may want to override the system prompt to be more verbose.
  // Currently we only do this for lmstudio, but we probably will want to expand this even more
  // to any Untooled LLM.
  static systemPrompt(provider = null) {
    switch (provider) {
      case "lmstudio":
        return "You are a helpful ai assistant who can assist the user and use tools available to help answer the users prompts and questions. Tools will be handled by another assistant and you will simply receive their responses to help answer the user prompt - always try to answer the user's prompt the best you can with the context available to you and your general knowledge.";
      default:
        return DEFAULT_WORKSPACE_PROMPT;
    }
  }
}

module.exports = Provider;