Perplexica/src/lib/providers.ts

import { ChatOpenAI, OpenAIEmbeddings } from "@langchain/openai";
import { ChatOllama } from "@langchain/community/chat_models/ollama";
import { OllamaEmbeddings } from "@langchain/community/embeddings/ollama";
import { HuggingFaceTransformersEmbeddings } from "./huggingfaceTransformer";
import { getGroqApiKey, getOllamaApiEndpoint, getOpenaiApiKey } from "../config";
import logger from "../utils/logger";

export const getAvailableChatModelProviders = async () => {
  const openAIApiKey = getOpenaiApiKey();
  const groqApiKey = getGroqApiKey();
  const ollamaEndpoint = getOllamaApiEndpoint();

  const models = {};

  if (openAIApiKey) {
    try {
      models["openai"] = {
        "GPT-3.5 turbo": new ChatOpenAI({
          openAIApiKey,
          modelName: "gpt-3.5-turbo",
          temperature: 0.7,
        }),
        "GPT-4": new ChatOpenAI({
          openAIApiKey,
          modelName: "gpt-4",
          temperature: 0.7,
        }),
        "GPT-4 turbo": new ChatOpenAI({
          openAIApiKey,
          modelName: "gpt-4-turbo",
          temperature: 0.7,
        }),
        "GPT-4 omni": new ChatOpenAI({
          openAIApiKey,
          modelName: "gpt-4o",
          temperature: 0.7,
        }),
      };
    } catch (error) {
      logger.error(`Error loading OpenAI models: ${error}`);
    }
  }

  if (groqApiKey) {
    try {
      models["groq"] = {
        "LLaMA3 8b": new ChatOpenAI(
          {
            openAIApiKey: groqApiKey,
            modelName: "llama3-8b-8192",
            temperature: 0.7,
          },
          {
            baseURL: "https://api.groq.com/openai/v1",
          },
        ),
        "LLaMA3 70b": new ChatOpenAI(
          {
            openAIApiKey: groqApiKey,
            modelName: "llama3-70b-8192",
            temperature: 0.7,
          },
          {
            baseURL: "https://api.groq.com/openai/v1",
          },
        ),
        "Mixtral 8x7b": new ChatOpenAI(
          {
            openAIApiKey: groqApiKey,
            modelName: "mixtral-8x7b-32768",
            temperature: 0.7,
          },
          {
            baseURL: "https://api.groq.com/openai/v1",
          },
        ),
        "Gemma 7b": new ChatOpenAI(
          {
            openAIApiKey: groqApiKey,
            modelName: "gemma-7b-it",
            temperature: 0.7,
          },
          {
            baseURL: "https://api.groq.com/openai/v1",
          },
        ),
      };
    } catch (error) {
      logger.error(`Error loading Groq models: ${error}`);
    }
  }

  if (ollamaEndpoint) {
    try {
      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
        headers: {
          "Content-Type": "application/json",
        },
      });

      // eslint-disable-next-line @typescript-eslint/no-explicit-any
      const { models: ollamaModels } = (await response.json()) as any;

      // eslint-disable-next-line unicorn/no-array-reduce
      models["ollama"] = ollamaModels.reduce((accumulator, model) => {
        accumulator[model.model] = new ChatOllama({
          baseUrl: ollamaEndpoint,
          model: model.model,
          temperature: 0.7,
        });
        return accumulator;
      }, {});
    } catch (error) {
      logger.error(`Error loading Ollama models: ${error}`);
    }
  }

  models["custom_openai"] = {};

  return models;
};

export const getAvailableEmbeddingModelProviders = async () => {
  const openAIApiKey = getOpenaiApiKey();
  const ollamaEndpoint = getOllamaApiEndpoint();

  const models = {};

  if (openAIApiKey) {
    try {
      models["openai"] = {
        "Text embedding 3 small": new OpenAIEmbeddings({
          openAIApiKey,
          modelName: "text-embedding-3-small",
        }),
        "Text embedding 3 large": new OpenAIEmbeddings({
          openAIApiKey,
          modelName: "text-embedding-3-large",
        }),
      };
    } catch (error) {
      logger.error(`Error loading OpenAI embeddings: ${error}`);
    }
  }

  if (ollamaEndpoint) {
    try {
      const response = await fetch(`${ollamaEndpoint}/api/tags`, {
        headers: {
          "Content-Type": "application/json",
        },
      });

      // eslint-disable-next-line @typescript-eslint/no-explicit-any
      const { models: ollamaModels } = (await response.json()) as any;

      // eslint-disable-next-line unicorn/no-array-reduce
      models["ollama"] = ollamaModels.reduce((accumulator, model) => {
        accumulator[model.model] = new OllamaEmbeddings({
          baseUrl: ollamaEndpoint,
          model: model.model,
        });
        return accumulator;
      }, {});
    } catch (error) {
      logger.error(`Error loading Ollama embeddings: ${error}`);
    }
  }

  try {
    models["local"] = {
      "BGE Small": new HuggingFaceTransformersEmbeddings({
        modelName: "Xenova/bge-small-en-v1.5",
      }),
      "GTE Small": new HuggingFaceTransformersEmbeddings({
        modelName: "Xenova/gte-small",
      }),
      "Bert Multilingual": new HuggingFaceTransformersEmbeddings({
        modelName: "Xenova/bert-base-multilingual-uncased",
      }),
    };
  } catch (error) {
    logger.error(`Error loading local embeddings: ${error}`);
  }

  return models;
};