LibreChat/api/app/clients/tools/util/fileSearch.js

const { z } = require('zod');
const axios = require('axios');
const { tool } = require('@langchain/core/tools');
const { Tools, EToolResources } = require('librechat-data-provider');
const { getFiles } = require('~/models/File');
const { logger } = require('~/config');

/**
 *
 * @param {Object} options
 * @param {ServerRequest} options.req
 * @param {Agent['tool_resources']} options.tool_resources
 * @returns {Promise<{
 *   files: Array<{ file_id: string; filename: string }>,
 *   toolContext: string
 * }>}
 */
const primeFiles = async (options) => {
  const { tool_resources } = options;
  const file_ids = tool_resources?.[EToolResources.file_search]?.file_ids ?? [];
  const agentResourceIds = new Set(file_ids);
  const resourceFiles = tool_resources?.[EToolResources.file_search]?.files ?? [];
  const dbFiles = ((await getFiles({ file_id: { $in: file_ids } })) ?? []).concat(resourceFiles);

  let toolContext = `- Note: Semantic search is available through the ${Tools.file_search} tool but no files are currently loaded. Request the user to upload documents to search through.`;

  const files = [];
  for (let i = 0; i < dbFiles.length; i++) {
    const file = dbFiles[i];
    if (!file) {
      continue;
    }
    if (i === 0) {
      toolContext = `- Note: Use the ${Tools.file_search} tool to find relevant information within:`;
    }
    toolContext += `\n\t- ${file.filename}${
      agentResourceIds.has(file.file_id) ? '' : ' (just attached by user)'
    }`;
    files.push({
      file_id: file.file_id,
      filename: file.filename,
    });
  }

  return { files, toolContext };
};

/**
 *
 * @param {Object} options
 * @param {ServerRequest} options.req
 * @param {Array<{ file_id: string; filename: string }>} options.files
 * @param {string} [options.entity_id]
 * @returns
 */
const createFileSearchTool = async ({ req, files, entity_id }) => {
  return tool(
    async ({ query }) => {
      if (files.length === 0) {
        return 'No files to search. Instruct the user to add files for the search.';
      }
      const jwtToken = req.headers.authorization.split(' ')[1];
      if (!jwtToken) {
        return 'There was an error authenticating the file search request.';
      }

      /**
       *
       * @param {import('librechat-data-provider').TFile} file
       * @returns {{ file_id: string, query: string, k: number, entity_id?: string }}
       */
      const createQueryBody = (file) => {
        const body = {
          file_id: file.file_id,
          query,
          k: 5,
        };
        if (!entity_id) {
          return body;
        }
        body.entity_id = entity_id;
        logger.debug(`[${Tools.file_search}] RAG API /query body`, body);
        return body;
      };

      const queryPromises = files.map((file) =>
        axios
          .post(`${process.env.RAG_API_URL}/query`, createQueryBody(file), {
            headers: {
              Authorization: `Bearer ${jwtToken}`,
              'Content-Type': 'application/json',
            },
          })
          .catch((error) => {
            logger.error('Error encountered in `file_search` while querying file:', error);
            return null;
          }),
      );

      const results = await Promise.all(queryPromises);
      const validResults = results.filter((result) => result !== null);

      if (validResults.length === 0) {
        return 'No results found or errors occurred while searching the files.';
      }

      const formattedResults = validResults
        .flatMap((result) =>
          result.data.map(([docInfo, distance]) => ({
            filename: docInfo.metadata.source.split('/').pop(),
            content: docInfo.page_content,
            distance,
          })),
        )
        // TODO: results should be sorted by relevance, not distance
        .sort((a, b) => a.distance - b.distance)
        // TODO: make this configurable
        .slice(0, 10);

      const formattedString = formattedResults
        .map(
          (result) =>
            `File: ${result.filename}\nRelevance: ${1.0 - result.distance.toFixed(4)}\nContent: ${
              result.content
            }\n`,
        )
        .join('\n---\n');

      return formattedString;
    },
    {
      name: Tools.file_search,
      description: `Performs semantic search across attached "${Tools.file_search}" documents using natural language queries. This tool analyzes the content of uploaded files to find relevant information, quotes, and passages that best match your query. Use this to extract specific information or find relevant sections within the available documents.`,
      schema: z.object({
        query: z
          .string()
          .describe(
            "A natural language query to search for relevant information in the files. Be specific and use keywords related to the information you're looking for. The query will be used for semantic similarity matching against the file contents.",
          ),
      }),
    },
  );
};

module.exports = { createFileSearchTool, primeFiles };