# Repository: danny-avila/LibreChat # Stars: 35721 ## CLAUDE.md # LibreChat ## Project Overview LibreChat is a monorepo with the following key workspaces: | Workspace | Language | Side | Dependency | Purpose | |---|---|---|---|---| | `/api` | JS (legacy) | Backend | `packages/api`, `packages/data-schemas`, `packages/data-provider`, `@librechat/agents` | Express server — minimize changes here | | `/packages/api` | **TypeScript** | Backend | `packages/data-schemas`, `packages/data-provider` | New backend code lives here (TS only, consumed by `/api`) | | `/packages/data-schemas` | TypeScript | Backend | `packages/data-provider` | Database models/schemas, shareable across backend projects | | `/packages/data-provider` | TypeScript | Shared | — | Shared API types, endpoints, data-service — used by both frontend and backend | | `/client` | TypeScript/React | Frontend | `packages/data-provider`, `packages/client` | Frontend SPA | | `/packages/client` | TypeScript | Frontend | `packages/data-provider` | Shared frontend utilities | The source code for `@librechat/agents` (major backend dependency, same team) is at `/home/danny/agentus`. --- ## Workspace Boundaries - **All new backend code must be TypeScript** in `/packages/api`. - Keep `/api` changes to the absolute minimum (thin JS wrappers calling into `/packages/api`). - Database-specific shared logic goes in `/packages/data-schemas`. - Frontend/backend shared API logic (endpoints, types, data-service) goes in `/packages/data-provider`. - Build data-provider from project root: `npm run build:data-provider`. --- ## Code Style ### Naming and File Organization - **Single-word file names** whenever possible (e.g., `permissions.ts`, `capabilities.ts`, `service.ts`). - When multiple words are needed, prefer grouping related modules under a **single-word directory** rather than using multi-word file names (e.g., `admin/capabilities.ts` not `adminCapabilities.ts`). - The directory already provides context — `app/service.ts` not `app/appConfigService.ts`. ### Structure and Clarity - **Never-nesting**: early returns, flat code, minimal indentation. Break complex operations into well-named helpers. - **Functional first**: pure functions, immutable data, `map`/`filter`/`reduce` over imperative loops. Only reach for OOP when it clearly improves domain modeling or state encapsulation. - **No dynamic imports** unless absolutely necessary. ### DRY - Extract repeated logic into utility functions. - Reusable hooks / higher-order components for UI patterns. - Parameterized helpers instead of near-duplicate functions. - Constants for repeated values; configuration objects over duplicated init code. - Shared validators, centralized error handling, single source of truth for business rules. - Shared typing system with interfaces/types extending common base definitions. - Abstraction layers for external API interactions. ### Iteration and Performance - **Minimize looping** — especially over shared data structures like message arrays, which are iterated frequently throughout the codebase. Every additional pass adds up at scale. - Consolidate sequential O(n) operations into a single pass whenever possible; never loop over the same collection twice if the work can be combined. - Choose data structures that reduce the need to iterate (e.g., `Map`/`Set` for lookups instead of `Array.find`/`Array.includes`). - Avoid unnecessary object creation; consider space-time tradeoffs. - Prevent memory leaks: careful with closures, dispose resources/event listeners, no circular references. ### Type Safety - **Never use `any`**. Explicit types for all parameters, return values, and variables. - **Limit `unknown`** — avoid `unknown`, `Record`, and `as unknown as T` assertions. A `Record` almost always signals a missing explicit type definition. - **Don't duplicate types** — before defining a new type, check whether it already exists in the project (especially `packages/data-provider`). Reuse and extend existing types rather than creating redundant definitions. - Use union types, generics, and interfaces appropriately. - All TypeScript and ESLint warnings/errors must be addressed — do not leave unresolved diagnostics. ### Comments and Documentation - Write self-documenting code; no inline comments narrating what code does. - JSDoc only for complex/non-obvious logic or intellisense on public APIs. - Single-line JSDoc for brief docs, multi-line for complex cases. - Avoid standalone `//` comments unless absolutely necessary. ### Import Order Imports are organized into three sections: 1. **Package imports** — sorted shortest to longest line length (`react` always first). 2. **`import type` imports** — sorted longest to shortest (package types first, then local types; length resets between sub-groups). 3. **Local/project imports** — sorted longest to shortest. Multi-line imports count total character length across all lines. Consolidate value imports from the same module. Always use standalone `import type { ... }` — never inline `type` inside value imports. ### JS/TS Loop Preferences - **Limit looping as much as possible.** Prefer single-pass transformations and avoid re-iterating the same data. - `for (let i = 0; ...)` for performance-critical or index-dependent operations. - `for...of` for simple array iteration. - `for...in` only for object property enumeration. --- ## Frontend Rules (`client/src/**/*`) ### Localization - All user-facing text must use `useLocalize()`. - Only update English keys in `client/src/locales/en/translation.json` (other languages are automated externally). - Semantic key prefixes: `com_ui_`, `com_assistants_`, etc. ### Components - TypeScript for all React components with proper type imports. - Semantic HTML with ARIA labels (`role`, `aria-label`) for accessibility. - Group related components in feature directories (e.g., `SidePanel/Memories/`). - Use index files for clean exports. ### Data Management - Feature hooks: `client/src/data-provider/[Feature]/queries.ts` → `[Feature]/index.ts` → `client/src/data-provider/index.ts`. - React Query (`@tanstack/react-query`) for all API interactions; proper query invalidation on mutations. - QueryKeys and MutationKeys in `packages/data-provider/src/keys.ts`. ### Data-Provider Integration - Endpoints: `packages/data-provider/src/api-endpoints.ts` - Data service: `packages/data-provider/src/data-service.ts` - Types: `packages/data-provider/src/types/queries.ts` - Use `encodeURIComponent` for dynamic URL parameters. ### Performance - Prioritize memory and speed efficiency at scale. - Cursor pagination for large datasets. - Proper dependency arrays to avoid unnecessary re-renders. - Leverage React Query caching and background refetching. --- ## Development Commands | Command | Purpose | |---|---| | `npm run smart-reinstall` | Install deps (if lockfile changed) + build via Turborepo | | `npm run reinstall` | Clean install — wipe `node_modules` and reinstall from scratch | | `npm run backend` | Start the backend server | | `npm run backend:dev` | Start backend with file watching (development) | | `npm run build` | Build all compiled code via Turborepo (parallel, cached) | | `npm run frontend` | Build all compiled code sequentially (legacy fallback) | | `npm run frontend:dev` | Start frontend dev server with HMR (port 3090, requires backend running) | | `npm run build:data-provider` | Rebuild `packages/data-provider` after changes | - Node.js: v20.19.0+ or ^22.12.0 or >= 23.0.0 - Database: MongoDB - Backend runs on `http://localhost:3080/`; frontend dev server on `http://localhost:3090/` --- ## Testing - Framework: **Jest**, run per-workspace. - Run tests from their workspace directory: `cd api && npx jest `, `cd packages/api && npx jest `, etc. - Frontend tests: `__tests__` directories alongside components; use `test/layout-test-utils` for rendering. - Cover loading, success, and error states for UI/data flows. ### Philosophy - **Real logic over mocks.** Exercise actual code paths with real dependencies. Mocking is a last resort. - **Spies over mocks.** Assert that real functions are called with expected arguments and frequency without replacing underlying logic. - **MongoDB**: use `mongodb-memory-server` for a real in-memory MongoDB instance. Test actual queries and schema validation, not mocked DB calls. - **MCP**: use real `@modelcontextprotocol/sdk` exports for servers, transports, and tool definitions. Mirror real scenarios, don't stub SDK internals. - Only mock what you cannot control: external HTTP APIs, rate-limited services, non-deterministic system calls. - Heavy mocking is a code smell, not a testing strategy. --- ## Formatting Fix all formatting lint errors (trailing spaces, tabs, newlines, indentation) using auto-fix when available. All TypeScript/ESLint warnings and errors **must** be resolved. ## README.md

LibreChat

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# ✨ Features - 🖥️ **UI & Experience** inspired by ChatGPT with enhanced design and features - 🤖 **AI Model Selection**: - Anthropic (Claude), AWS Bedrock, OpenAI, Azure OpenAI, Google, Vertex AI, OpenAI Responses API (incl. Azure) - [Custom Endpoints](https://www.librechat.ai/docs/quick_start/custom_endpoints): Use any OpenAI-compatible API with LibreChat, no proxy required - Compatible with [Local & Remote AI Providers](https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints): - Ollama, groq, Cohere, Mistral AI, Apple MLX, koboldcpp, together.ai, - OpenRouter, Helicone, Perplexity, ShuttleAI, Deepseek, Qwen, and more - 🔧 **[Code Interpreter API](https://www.librechat.ai/docs/features/code_interpreter)**: - Secure, Sandboxed Execution in Python, Node.js (JS/TS), Go, C/C++, Java, PHP, Rust, and Fortran - Seamless File Handling: Upload, process, and download files directly - No Privacy Concerns: Fully isolated and secure execution - 🔦 **Agents & Tools Integration**: - **[LibreChat Agents](https://www.librechat.ai/docs/features/agents)**: - No-Code Custom Assistants: Build specialized, AI-driven helpers - Agent Marketplace: Discover and deploy community-built agents - Collaborative Sharing: Share agents with specific users and groups - Flexible & Extensible: Use MCP Servers, tools, file search, code execution, and more - Compatible with Custom Endpoints, OpenAI, Azure, Anthropic, AWS Bedrock, Google, Vertex AI, Responses API, and more - [Model Context Protocol (MCP) Support](https://modelcontextprotocol.io/clients#librechat) for Tools - 🔍 **Web Search**: - Search the internet and retrieve relevant information to enhance your AI context - Combines search providers, content scrapers, and result rerankers for optimal results - **Customizable Jina Reranking**: Configure custom Jina API URLs for reranking services - **[Learn More →](https://www.librechat.ai/docs/features/web_search)** - 🪄 **Generative UI with Code Artifacts**: - [Code Artifacts](https://youtu.be/GfTj7O4gmd0?si=WJbdnemZpJzBrJo3) allow creation of React, HTML, and Mermaid diagrams directly in chat - 🎨 **Image Generation & Editing** - Text-to-image and image-to-image with [GPT-Image-1](https://www.librechat.ai/docs/features/image_gen#1--openai-image-tools-recommended) - Text-to-image with [DALL-E (3/2)](https://www.librechat.ai/docs/features/image_gen#2--dalle-legacy), [Stable Diffusion](https://www.librechat.ai/docs/features/image_gen#3--stable-diffusion-local), [Flux](https://www.librechat.ai/docs/features/image_gen#4--flux), or any [MCP server](https://www.librechat.ai/docs/features/image_gen#5--model-context-protocol-mcp) - Produce stunning visuals from prompts or refine existing images with a single instruction - 💾 **Presets & Context Management**: - Create, Save, & Share Custom Presets - Switch between AI Endpoints and Presets mid-chat - Edit, Resubmit, and Continue Messages with Conversation branching - Create and share prompts with specific users and groups - [Fork Messages & Conversations](https://www.librechat.ai/docs/features/fork) for Advanced Context control - 💬 **Multimodal & File Interactions**: - Upload and analyze images with Claude 3, GPT-4.5, GPT-4o, o1, Llama-Vision, and Gemini 📸 - Chat with Files using Custom Endpoints, OpenAI, Azure, Anthropic, AWS Bedrock, & Google 🗃️ - 🌎 **Multilingual UI**: - English, 中文 (简体), 中文 (繁體), العربية, Deutsch, Español, Français, Italiano - Polski, Português (PT), Português (BR), Русский, 日本語, Svenska, 한국어, Tiếng Việt - Türkçe, Nederlands, עברית, Català, Čeština, Dansk, Eesti, فارسی - Suomi, Magyar, Հայերեն, Bahasa Indonesia, ქართული, Latviešu, ไทย, ئۇيغۇرچە - 🧠 **Reasoning UI**: - Dynamic Reasoning UI for Chain-of-Thought/Reasoning AI models like DeepSeek-R1 - 🎨 **Customizable Interface**: - Customizable Dropdown & Interface that adapts to both power users and newcomers - 🌊 **[Resumable Streams](https://www.librechat.ai/docs/features/resumable_streams)**: - Never lose a response: AI responses automatically reconnect and resume if your connection drops - Multi-Tab & Multi-Device Sync: Open the same chat in multiple tabs or pick up on another device - Production-Ready: Works from single-server setups to horizontally scaled deployments with Redis - 🗣️ **Speech & Audio**: - Chat hands-free with Speech-to-Text and Text-to-Speech - Automatically send and play Audio - Supports OpenAI, Azure OpenAI, and Elevenlabs - 📥 **Import & Export Conversations**: - Import Conversations from LibreChat, ChatGPT, Chatbot UI - Export conversations as screenshots, markdown, text, json - 🔍 **Search & Discovery**: - Search all messages/conversations - 👥 **Multi-User & Secure Access**: - Multi-User, Secure Authentication with OAuth2, LDAP, & Email Login Support - Built-in Moderation, and Token spend tools - ⚙️ **Configuration & Deployment**: - Configure Proxy, Reverse Proxy, Docker, & many Deployment options - Use completely local or deploy on the cloud - 📖 **Open-Source & Community**: - Completely Open-Source & Built in Public - Community-driven development, support, and feedback [For a thorough review of our features, see our docs here](https://docs.librechat.ai/) 📚 ## 🪶 All-In-One AI Conversations with LibreChat LibreChat is a self-hosted AI chat platform that unifies all major AI providers in a single, privacy-focused interface. Beyond chat, LibreChat provides AI Agents, Model Context Protocol (MCP) support, Artifacts, Code Interpreter, custom actions, conversation search, and enterprise-ready multi-user authentication. Open source, actively developed, and built for anyone who values control over their AI infrastructure. --- ## 🌐 Resources **GitHub Repo:** - **RAG API:** [github.com/danny-avila/rag_api](https://github.com/danny-avila/rag_api) - **Website:** [github.com/LibreChat-AI/librechat.ai](https://github.com/LibreChat-AI/librechat.ai) **Other:** - **Website:** [librechat.ai](https://librechat.ai) - **Documentation:** [librechat.ai/docs](https://librechat.ai/docs) - **Blog:** [librechat.ai/blog](https://librechat.ai/blog) --- ## 📝 Changelog Keep up with the latest updates by visiting the releases page and notes: - [Releases](https://github.com/danny-avila/LibreChat/releases) - [Changelog](https://www.librechat.ai/changelog) **⚠️ Please consult the [changelog](https://www.librechat.ai/changelog) for breaking changes before updating.** --- ## ⭐ Star History

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danny-avila%2FLibreChat | Trendshift ROSS Index - Fastest Growing Open-Source Startups in Q1 2024 | Runa Capital

--- ## ✨ Contributions Contributions, suggestions, bug reports and fixes are welcome! For new features, components, or extensions, please open an issue and discuss before sending a PR. If you'd like to help translate LibreChat into your language, we'd love your contribution! Improving our translations not only makes LibreChat more accessible to users around the world but also enhances the overall user experience. Please check out our [Translation Guide](https://www.librechat.ai/docs/translation). --- ## 💖 This project exists in its current state thanks to all the people who contribute --- ## 🎉 Special Thanks We thank [Locize](https://locize.com) for their translation management tools that support multiple languages in LibreChat.

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