mirror of
https://github.com/danny-avila/LibreChat.git
synced 2025-09-22 06:00:56 +02:00
🧠 feat: User Memories for Conversational Context (#7760)
* 🧠 feat: User Memories for Conversational Context
chore: mcp typing, use `t`
WIP: first pass, Memories UI
- Added MemoryViewer component for displaying, editing, and deleting user memories.
- Integrated data provider hooks for fetching, updating, and deleting memories.
- Implemented pagination and loading states for better user experience.
- Created unit tests for MemoryViewer to ensure functionality and interaction with data provider.
- Updated translation files to include new UI strings related to memories.
chore: move mcp-related files to own directory
chore: rename librechat-mcp to librechat-api
WIP: first pass, memory processing and data schemas
chore: linting in fileSearch.js query description
chore: rename librechat-api to @librechat/api across the project
WIP: first pass, functional memory agent
feat: add MemoryEditDialog and MemoryViewer components for managing user memories
- Introduced MemoryEditDialog for editing memory entries with validation and toast notifications.
- Updated MemoryViewer to support editing and deleting memories, including pagination and loading states.
- Enhanced data provider to handle memory updates with optional original key for better management.
- Added new localization strings for memory-related UI elements.
feat: add memory permissions management
- Implemented memory permissions in the backend, allowing roles to have specific permissions for using, creating, updating, and reading memories.
- Added new API endpoints for updating memory permissions associated with roles.
- Created a new AdminSettings component for managing memory permissions in the frontend.
- Integrated memory permissions into the existing roles and permissions schemas.
- Updated the interface to include memory settings and permissions.
- Enhanced the MemoryViewer component to conditionally render admin settings based on user roles.
- Added localization support for memory permissions in the translation files.
feat: move AdminSettings component to a new position in MemoryViewer for better visibility
refactor: clean up commented code in MemoryViewer component
feat: enhance MemoryViewer with search functionality and improve MemoryEditDialog integration
- Added a search input to filter memories in the MemoryViewer component.
- Refactored MemoryEditDialog to accept children for better customization.
- Updated MemoryViewer to utilize the new EditMemoryButton and DeleteMemoryButton components for editing and deleting memories.
- Improved localization support by adding new strings for memory filtering and deletion confirmation.
refactor: optimize memory filtering in MemoryViewer using match-sorter
- Replaced manual filtering logic with match-sorter for improved search functionality.
- Enhanced performance and readability of the filteredMemories computation.
feat: enhance MemoryEditDialog with triggerRef and improve updateMemory mutation handling
feat: implement access control for MemoryEditDialog and MemoryViewer components
refactor: remove commented out code and create runMemory method
refactor: rename role based files
feat: implement access control for memory usage in AgentClient
refactor: simplify checkVisionRequest method in AgentClient by removing commented-out code
refactor: make `agents` dir in api package
refactor: migrate Azure utilities to TypeScript and consolidate imports
refactor: move sanitizeFilename function to a new file and update imports, add related tests
refactor: update LLM configuration types and consolidate Azure options in the API package
chore: linting
chore: import order
refactor: replace getLLMConfig with getOpenAIConfig and remove unused LLM configuration file
chore: update winston-daily-rotate-file to version 5.0.0 and add object-hash dependency in package-lock.json
refactor: move primeResources and optionalChainWithEmptyCheck functions to resources.ts and update imports
refactor: move createRun function to a new run.ts file and update related imports
fix: ensure safeAttachments is correctly typed as an array of TFile
chore: add node-fetch dependency and refactor fetch-related functions into packages/api/utils, removing the old generators file
refactor: enhance TEndpointOption type by using Pick to streamline endpoint fields and add new properties for model parameters and client options
feat: implement initializeOpenAIOptions function and update OpenAI types for enhanced configuration handling
fix: update types due to new TEndpointOption typing
fix: ensure safe access to group parameters in initializeOpenAIOptions function
fix: remove redundant API key validation comment in initializeOpenAIOptions function
refactor: rename initializeOpenAIOptions to initializeOpenAI for consistency and update related documentation
refactor: decouple req.body fields and tool loading from initializeAgentOptions
chore: linting
refactor: adjust column widths in MemoryViewer for improved layout
refactor: simplify agent initialization by creating loadAgent function and removing unused code
feat: add memory configuration loading and validation functions
WIP: first pass, memory processing with config
feat: implement memory callback and artifact handling
feat: implement memory artifacts display and processing updates
feat: add memory configuration options and schema validation for validKeys
fix: update MemoryEditDialog and MemoryViewer to handle memory state and display improvements
refactor: remove padding from BookmarkTable and MemoryViewer headers for consistent styling
WIP: initial tokenLimit config and move Tokenizer to @librechat/api
refactor: update mongoMeili plugin methods to use callback for better error handling
feat: enhance memory management with token tracking and usage metrics
- Added token counting for memory entries to enforce limits and provide usage statistics.
- Updated memory retrieval and update routes to include total token usage and limit.
- Enhanced MemoryEditDialog and MemoryViewer components to display memory usage and token information.
- Refactored memory processing functions to handle token limits and provide feedback on memory capacity.
feat: implement memory artifact handling in attachment handler
- Enhanced useAttachmentHandler to process memory artifacts when receiving updates.
- Introduced handleMemoryArtifact utility to manage memory updates and deletions.
- Updated query client to reflect changes in memory state based on incoming data.
refactor: restructure web search key extraction logic
- Moved the logic for extracting API keys from the webSearchAuth configuration into a dedicated function, getWebSearchKeys.
- Updated webSearchKeys to utilize the new function for improved clarity and maintainability.
- Prevents build time errors
feat: add personalization settings and memory preferences management
- Introduced a new Personalization tab in settings to manage user memory preferences.
- Implemented API endpoints and client-side logic for updating memory preferences.
- Enhanced user interface components to reflect personalization options and memory usage.
- Updated permissions to allow users to opt out of memory features.
- Added localization support for new settings and messages related to personalization.
style: personalization switch class
feat: add PersonalizationIcon and align Side Panel UI
feat: implement memory creation functionality
- Added a new API endpoint for creating memory entries, including validation for key and value.
- Introduced MemoryCreateDialog component for user interface to facilitate memory creation.
- Integrated token limit checks to prevent exceeding user memory capacity.
- Updated MemoryViewer to include a button for opening the memory creation dialog.
- Enhanced localization support for new messages related to memory creation.
feat: enhance message processing with configurable window size
- Updated AgentClient to use a configurable message window size for processing messages.
- Introduced messageWindowSize option in memory configuration schema with a default value of 5.
- Improved logic for selecting messages to process based on the configured window size.
chore: update librechat-data-provider version to 0.7.87 in package.json and package-lock.json
chore: remove OpenAPIPlugin and its associated tests
chore: remove MIGRATION_README.md as migration tasks are completed
ci: fix backend tests
chore: remove unused translation keys from localization file
chore: remove problematic test file and unused var in AgentClient
chore: remove unused import and import directly for JSDoc
* feat: add api package build stage in Dockerfile for improved modularity
* docs: reorder build steps in contributing guide for clarity
This commit is contained in:
Danny Avila
GitHub
parent
cd7dd576c1
commit
29ef91b4dd
170 changed files with 5700 additions and 3632 deletions
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@ -10,6 +10,7 @@ const {
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validateVisionModel,
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} = require('librechat-data-provider');
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const { SplitStreamHandler: _Handler } = require('@librechat/agents');
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const { Tokenizer, createFetch, createStreamEventHandlers } = require('@librechat/api');
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const {
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truncateText,
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formatMessage,
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@ -26,8 +27,6 @@ const {
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const { getModelMaxTokens, getModelMaxOutputTokens, matchModelName } = require('~/utils');
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const { spendTokens, spendStructuredTokens } = require('~/models/spendTokens');
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const { encodeAndFormat } = require('~/server/services/Files/images/encode');
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const { createFetch, createStreamEventHandlers } = require('./generators');
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const Tokenizer = require('~/server/services/Tokenizer');
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const { sleep } = require('~/server/utils');
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const BaseClient = require('./BaseClient');
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const { logger } = require('~/config');
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@ -2,6 +2,7 @@ const { Keyv } = require('keyv');
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const crypto = require('crypto');
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const { CohereClient } = require('cohere-ai');
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const { fetchEventSource } = require('@waylaidwanderer/fetch-event-source');
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const { constructAzureURL, genAzureChatCompletion } = require('@librechat/api');
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const { encoding_for_model: encodingForModel, get_encoding: getEncoding } = require('tiktoken');
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const {
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ImageDetail,
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@ -10,9 +11,9 @@ const {
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CohereConstants,
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mapModelToAzureConfig,
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} = require('librechat-data-provider');
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const { extractBaseURL, constructAzureURL, genAzureChatCompletion } = require('~/utils');
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const { createContextHandlers } = require('./prompts');
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const { createCoherePayload } = require('./llm');
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const { extractBaseURL } = require('~/utils');
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const BaseClient = require('./BaseClient');
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const { logger } = require('~/config');
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@ -1,4 +1,5 @@
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const { google } = require('googleapis');
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const { Tokenizer } = require('@librechat/api');
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const { concat } = require('@langchain/core/utils/stream');
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const { ChatVertexAI } = require('@langchain/google-vertexai');
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const { ChatGoogleGenerativeAI } = require('@langchain/google-genai');
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@ -19,7 +20,6 @@ const {
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} = require('librechat-data-provider');
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const { getSafetySettings } = require('~/server/services/Endpoints/google/llm');
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const { encodeAndFormat } = require('~/server/services/Files/images');
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const Tokenizer = require('~/server/services/Tokenizer');
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const { spendTokens } = require('~/models/spendTokens');
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const { getModelMaxTokens } = require('~/utils');
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const { sleep } = require('~/server/utils');
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@ -1,6 +1,14 @@
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const { OllamaClient } = require('./OllamaClient');
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const { HttpsProxyAgent } = require('https-proxy-agent');
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const { SplitStreamHandler, CustomOpenAIClient: OpenAI } = require('@librechat/agents');
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const {
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isEnabled,
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Tokenizer,
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createFetch,
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constructAzureURL,
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genAzureChatCompletion,
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createStreamEventHandlers,
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} = require('@librechat/api');
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const {
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Constants,
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ImageDetail,
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@ -16,13 +24,6 @@ const {
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validateVisionModel,
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mapModelToAzureConfig,
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} = require('librechat-data-provider');
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const {
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extractBaseURL,
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constructAzureURL,
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getModelMaxTokens,
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genAzureChatCompletion,
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getModelMaxOutputTokens,
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} = require('~/utils');
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const {
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truncateText,
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formatMessage,
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@ -30,10 +31,9 @@ const {
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titleInstruction,
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createContextHandlers,
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} = require('./prompts');
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const { extractBaseURL, getModelMaxTokens, getModelMaxOutputTokens } = require('~/utils');
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const { encodeAndFormat } = require('~/server/services/Files/images/encode');
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const { createFetch, createStreamEventHandlers } = require('./generators');
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const { addSpaceIfNeeded, isEnabled, sleep } = require('~/server/utils');
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const Tokenizer = require('~/server/services/Tokenizer');
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const { addSpaceIfNeeded, sleep } = require('~/server/utils');
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const { spendTokens } = require('~/models/spendTokens');
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const { handleOpenAIErrors } = require('./tools/util');
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const { createLLM, RunManager } = require('./llm');
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@ -1,71 +0,0 @@
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const fetch = require('node-fetch');
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const { GraphEvents } = require('@librechat/agents');
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const { logger, sendEvent } = require('~/config');
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const { sleep } = require('~/server/utils');
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/**
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* Makes a function to make HTTP request and logs the process.
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* @param {Object} params
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* @param {boolean} [params.directEndpoint] - Whether to use a direct endpoint.
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* @param {string} [params.reverseProxyUrl] - The reverse proxy URL to use for the request.
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* @returns {Promise<Response>} - A promise that resolves to the response of the fetch request.
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*/
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function createFetch({ directEndpoint = false, reverseProxyUrl = '' }) {
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/**
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* Makes an HTTP request and logs the process.
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* @param {RequestInfo} url - The URL to make the request to. Can be a string or a Request object.
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* @param {RequestInit} [init] - Optional init options for the request.
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* @returns {Promise<Response>} - A promise that resolves to the response of the fetch request.
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*/
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return async (_url, init) => {
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let url = _url;
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if (directEndpoint) {
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url = reverseProxyUrl;
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}
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logger.debug(`Making request to ${url}`);
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if (typeof Bun !== 'undefined') {
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return await fetch(url, init);
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}
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return await fetch(url, init);
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};
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}
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// Add this at the module level outside the class
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/**
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* Creates event handlers for stream events that don't capture client references
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* @param {Object} res - The response object to send events to
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* @returns {Object} Object containing handler functions
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*/
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function createStreamEventHandlers(res) {
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return {
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[GraphEvents.ON_RUN_STEP]: (event) => {
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if (res) {
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sendEvent(res, event);
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}
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},
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[GraphEvents.ON_MESSAGE_DELTA]: (event) => {
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if (res) {
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sendEvent(res, event);
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}
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},
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[GraphEvents.ON_REASONING_DELTA]: (event) => {
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if (res) {
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sendEvent(res, event);
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}
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},
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};
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}
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function createHandleLLMNewToken(streamRate) {
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return async () => {
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if (streamRate) {
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await sleep(streamRate);
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}
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};
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}
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module.exports = {
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createFetch,
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createHandleLLMNewToken,
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createStreamEventHandlers,
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};
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@ -1,6 +1,5 @@
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const { ChatOpenAI } = require('@langchain/openai');
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const { sanitizeModelName, constructAzureURL } = require('~/utils');
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const { isEnabled } = require('~/server/utils');
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const { isEnabled, sanitizeModelName, constructAzureURL } = require('@librechat/api');
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/**
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* Creates a new instance of a language model (LLM) for chat interactions.
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@ -33,7 +33,9 @@ jest.mock('~/models', () => ({
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const { getConvo, saveConvo } = require('~/models');
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jest.mock('@librechat/agents', () => {
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const { Providers } = jest.requireActual('@librechat/agents');
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return {
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Providers,
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ChatOpenAI: jest.fn().mockImplementation(() => {
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return {};
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}),
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@ -1,184 +0,0 @@
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require('dotenv').config();
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const fs = require('fs');
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const { z } = require('zod');
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const path = require('path');
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const yaml = require('js-yaml');
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const { createOpenAPIChain } = require('langchain/chains');
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const { DynamicStructuredTool } = require('@langchain/core/tools');
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const { ChatPromptTemplate, HumanMessagePromptTemplate } = require('@langchain/core/prompts');
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const { logger } = require('~/config');
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function addLinePrefix(text, prefix = '// ') {
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return text
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.split('\n')
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.map((line) => prefix + line)
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.join('\n');
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}
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function createPrompt(name, functions) {
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const prefix = `// The ${name} tool has the following functions. Determine the desired or most optimal function for the user's query:`;
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const functionDescriptions = functions
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.map((func) => `// - ${func.name}: ${func.description}`)
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.join('\n');
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return `${prefix}\n${functionDescriptions}
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// You are an expert manager and scrum master. You must provide a detailed intent to better execute the function.
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// Always format as such: {{"func": "function_name", "intent": "intent and expected result"}}`;
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}
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const AuthBearer = z
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.object({
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type: z.string().includes('service_http'),
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authorization_type: z.string().includes('bearer'),
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verification_tokens: z.object({
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openai: z.string(),
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}),
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})
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.catch(() => false);
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const AuthDefinition = z
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.object({
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type: z.string(),
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authorization_type: z.string(),
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verification_tokens: z.object({
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openai: z.string(),
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}),
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})
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.catch(() => false);
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async function readSpecFile(filePath) {
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try {
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const fileContents = await fs.promises.readFile(filePath, 'utf8');
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if (path.extname(filePath) === '.json') {
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return JSON.parse(fileContents);
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}
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return yaml.load(fileContents);
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} catch (e) {
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logger.error('[readSpecFile] error', e);
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return false;
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}
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}
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async function getSpec(url) {
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const RegularUrl = z
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.string()
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.url()
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.catch(() => false);
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if (RegularUrl.parse(url) && path.extname(url) === '.json') {
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const response = await fetch(url);
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return await response.json();
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}
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const ValidSpecPath = z
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.string()
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.url()
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.catch(async () => {
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const spec = path.join(__dirname, '..', '.well-known', 'openapi', url);
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if (!fs.existsSync(spec)) {
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return false;
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}
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return await readSpecFile(spec);
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});
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return ValidSpecPath.parse(url);
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}
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async function createOpenAPIPlugin({ data, llm, user, message, memory, signal }) {
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let spec;
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try {
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spec = await getSpec(data.api.url);
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} catch (error) {
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logger.error('[createOpenAPIPlugin] getSpec error', error);
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return null;
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}
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if (!spec) {
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logger.warn('[createOpenAPIPlugin] No spec found');
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return null;
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}
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const headers = {};
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const { auth, name_for_model, description_for_model, description_for_human } = data;
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if (auth && AuthDefinition.parse(auth)) {
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logger.debug('[createOpenAPIPlugin] auth detected', auth);
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const { openai } = auth.verification_tokens;
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if (AuthBearer.parse(auth)) {
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headers.authorization = `Bearer ${openai}`;
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logger.debug('[createOpenAPIPlugin] added auth bearer', headers);
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}
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}
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const chainOptions = { llm };
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if (data.headers && data.headers['librechat_user_id']) {
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logger.debug('[createOpenAPIPlugin] id detected', headers);
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headers[data.headers['librechat_user_id']] = user;
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}
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if (Object.keys(headers).length > 0) {
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logger.debug('[createOpenAPIPlugin] headers detected', headers);
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chainOptions.headers = headers;
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}
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if (data.params) {
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logger.debug('[createOpenAPIPlugin] params detected', data.params);
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chainOptions.params = data.params;
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}
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let history = '';
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if (memory) {
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logger.debug('[createOpenAPIPlugin] openAPI chain: memory detected', memory);
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const { history: chat_history } = await memory.loadMemoryVariables({});
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history = chat_history?.length > 0 ? `\n\n## Chat History:\n${chat_history}\n` : '';
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}
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chainOptions.prompt = ChatPromptTemplate.fromMessages([
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HumanMessagePromptTemplate.fromTemplate(
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`# Use the provided API's to respond to this query:\n\n{query}\n\n## Instructions:\n${addLinePrefix(
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description_for_model,
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)}${history}`,
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),
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]);
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const chain = await createOpenAPIChain(spec, chainOptions);
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const { functions } = chain.chains[0].lc_kwargs.llmKwargs;
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return new DynamicStructuredTool({
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name: name_for_model,
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description_for_model: `${addLinePrefix(description_for_human)}${createPrompt(
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name_for_model,
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functions,
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)}`,
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description: `${description_for_human}`,
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schema: z.object({
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func: z
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.string()
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.describe(
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`The function to invoke. The functions available are: ${functions
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.map((func) => func.name)
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.join(', ')}`,
|
||||
),
|
||||
intent: z
|
||||
.string()
|
||||
.describe('Describe your intent with the function and your expected result'),
|
||||
}),
|
||||
func: async ({ func = '', intent = '' }) => {
|
||||
const filteredFunctions = functions.filter((f) => f.name === func);
|
||||
chain.chains[0].lc_kwargs.llmKwargs.functions = filteredFunctions;
|
||||
const query = `${message}${func?.length > 0 ? `\n// Intent: ${intent}` : ''}`;
|
||||
const result = await chain.call({
|
||||
query,
|
||||
signal,
|
||||
});
|
||||
return result.response;
|
||||
},
|
||||
});
|
||||
}
|
||||
|
||||
module.exports = {
|
||||
getSpec,
|
||||
readSpecFile,
|
||||
createOpenAPIPlugin,
|
||||
};
|
||||
|
|
@ -1,72 +0,0 @@
|
|||
const fs = require('fs');
|
||||
const { createOpenAPIPlugin, getSpec, readSpecFile } = require('./OpenAPIPlugin');
|
||||
|
||||
global.fetch = jest.fn().mockImplementationOnce(() => {
|
||||
return new Promise((resolve) => {
|
||||
resolve({
|
||||
ok: true,
|
||||
json: () => Promise.resolve({ key: 'value' }),
|
||||
});
|
||||
});
|
||||
});
|
||||
jest.mock('fs', () => ({
|
||||
promises: {
|
||||
readFile: jest.fn(),
|
||||
},
|
||||
existsSync: jest.fn(),
|
||||
}));
|
||||
|
||||
describe('readSpecFile', () => {
|
||||
it('reads JSON file correctly', async () => {
|
||||
fs.promises.readFile.mockResolvedValue(JSON.stringify({ test: 'value' }));
|
||||
const result = await readSpecFile('test.json');
|
||||
expect(result).toEqual({ test: 'value' });
|
||||
});
|
||||
|
||||
it('reads YAML file correctly', async () => {
|
||||
fs.promises.readFile.mockResolvedValue('test: value');
|
||||
const result = await readSpecFile('test.yaml');
|
||||
expect(result).toEqual({ test: 'value' });
|
||||
});
|
||||
|
||||
it('handles error correctly', async () => {
|
||||
fs.promises.readFile.mockRejectedValue(new Error('test error'));
|
||||
const result = await readSpecFile('test.json');
|
||||
expect(result).toBe(false);
|
||||
});
|
||||
});
|
||||
|
||||
describe('getSpec', () => {
|
||||
it('fetches spec from url correctly', async () => {
|
||||
const parsedJson = await getSpec('https://www.instacart.com/.well-known/ai-plugin.json');
|
||||
const isObject = typeof parsedJson === 'object';
|
||||
expect(isObject).toEqual(true);
|
||||
});
|
||||
|
||||
it('reads spec from file correctly', async () => {
|
||||
fs.existsSync.mockReturnValue(true);
|
||||
fs.promises.readFile.mockResolvedValue(JSON.stringify({ test: 'value' }));
|
||||
const result = await getSpec('test.json');
|
||||
expect(result).toEqual({ test: 'value' });
|
||||
});
|
||||
|
||||
it('returns false when file does not exist', async () => {
|
||||
fs.existsSync.mockReturnValue(false);
|
||||
const result = await getSpec('test.json');
|
||||
expect(result).toBe(false);
|
||||
});
|
||||
});
|
||||
|
||||
describe('createOpenAPIPlugin', () => {
|
||||
it('returns null when getSpec throws an error', async () => {
|
||||
const result = await createOpenAPIPlugin({ data: { api: { url: 'invalid' } } });
|
||||
expect(result).toBe(null);
|
||||
});
|
||||
|
||||
it('returns null when no spec is found', async () => {
|
||||
const result = await createOpenAPIPlugin({});
|
||||
expect(result).toBe(null);
|
||||
});
|
||||
|
||||
// Add more tests here for different scenarios
|
||||
});
|
||||
|
|
@ -8,10 +8,10 @@ const { HttpsProxyAgent } = require('https-proxy-agent');
|
|||
const { FileContext, ContentTypes } = require('librechat-data-provider');
|
||||
const { getImageBasename } = require('~/server/services/Files/images');
|
||||
const extractBaseURL = require('~/utils/extractBaseURL');
|
||||
const { logger } = require('~/config');
|
||||
const logger = require('~/config/winston');
|
||||
|
||||
const displayMessage =
|
||||
'DALL-E displayed an image. All generated images are already plainly visible, so don\'t repeat the descriptions in detail. Do not list download links as they are available in the UI already. The user may download the images by clicking on them, but do not mention anything about downloading to the user.';
|
||||
"DALL-E displayed an image. All generated images are already plainly visible, so don't repeat the descriptions in detail. Do not list download links as they are available in the UI already. The user may download the images by clicking on them, but do not mention anything about downloading to the user.";
|
||||
class DALLE3 extends Tool {
|
||||
constructor(fields = {}) {
|
||||
super();
|
||||
|
|
|
|||
|
|
@ -1,10 +1,29 @@
|
|||
const OpenAI = require('openai');
|
||||
const DALLE3 = require('../DALLE3');
|
||||
|
||||
const { logger } = require('~/config');
|
||||
const logger = require('~/config/winston');
|
||||
|
||||
jest.mock('openai');
|
||||
|
||||
jest.mock('@librechat/data-schemas', () => {
|
||||
return {
|
||||
logger: {
|
||||
info: jest.fn(),
|
||||
warn: jest.fn(),
|
||||
debug: jest.fn(),
|
||||
error: jest.fn(),
|
||||
},
|
||||
};
|
||||
});
|
||||
|
||||
jest.mock('tiktoken', () => {
|
||||
return {
|
||||
encoding_for_model: jest.fn().mockReturnValue({
|
||||
encode: jest.fn(),
|
||||
decode: jest.fn(),
|
||||
}),
|
||||
};
|
||||
});
|
||||
|
||||
const processFileURL = jest.fn();
|
||||
|
||||
jest.mock('~/server/services/Files/images', () => ({
|
||||
|
|
@ -37,6 +56,11 @@ jest.mock('fs', () => {
|
|||
return {
|
||||
existsSync: jest.fn(),
|
||||
mkdirSync: jest.fn(),
|
||||
promises: {
|
||||
writeFile: jest.fn(),
|
||||
readFile: jest.fn(),
|
||||
unlink: jest.fn(),
|
||||
},
|
||||
};
|
||||
});
|
||||
|
||||
|
|
|
|||
|
|
@ -135,7 +135,7 @@ const createFileSearchTool = async ({ req, files, entity_id }) => {
|
|||
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.',
|
||||
"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.",
|
||||
),
|
||||
}),
|
||||
},
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue