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Enhanced ChatGPT Clone: Features Agents, MCP, DeepSeek, Anthropic, AWS, OpenAI, Responses API, Azure, Groq, o1, GPT-5, Mistral, OpenRouter, Vertex AI, Gemini, Artifacts, AI model switching, message search, Code Interpreter, langchain, DALL-E-3, OpenAPI Actions, Functions, Secure Multi-User Auth, Presets, open-source for self-hosting. Active.
https://librechat.ai/
aianthropicartifactsawsazurechatgptchatgpt-cloneclaudeclonedeepseekgeminigooglegpt-5librechatmcpo1openairesponses-apivisionwebui
fda72ac621
* ♻️ refactor: Remove redundant scopedCacheKey caching, support user-provided key model fetching Remove redundant cache layers that used `scopedCacheKey()` (tenant-only scoping) on top of `getAppConfig()` which already caches per-principal (role+user+tenant). This caused config overrides for different principals within the same tenant to be invisible due to stale cached data. Changes: - Add `requireJwtAuth` to `/api/endpoints` route for proper user context - Remove ENDPOINT_CONFIG, STARTUP_CONFIG, PLUGINS, TOOLS, and MODELS_CONFIG cache layers — all derive from `getAppConfig()` with cheap computation - Enhance MODEL_QUERIES cache: hash(baseURL+apiKey) keys, 2-minute TTL, caching centralized in `fetchModels()` base function - Support fetching models with user-provided API keys in `loadConfigModels` via `getUserKeyValues` lookup (no caching for user keys) - Update all affected tests Closes #1028 * ♻️ refactor: Migrate config services to TypeScript in packages/api Move core config logic from CJS /api wrappers to typed TypeScript in packages/api using dependency injection factories: - `createEndpointsConfigService` — endpoint config merging + checkCapability - `createLoadConfigModels` — custom endpoint model loading with user key support - `createMCPToolCacheService` — MCP tool cache operations (update, merge, cache) /api files become thin wrappers that wire dependencies (getAppConfig, loadDefaultEndpointsConfig, getUserKeyValues, getCachedTools, etc.) into the typed factories. Also moves existing `endpoints/config.ts` → `endpoints/config/providers.ts` to accommodate the new `config/` directory structure. * 🔄 fix: Invalidate models query when user API key is set or revoked Without this, users had to refresh the page after entering their API key to see the updated model list fetched with their credentials. - Invalidate QueryKeys.models in useUpdateUserKeysMutation onSuccess - Invalidate QueryKeys.models in useRevokeUserKeyMutation onSuccess - Invalidate QueryKeys.models in useRevokeAllUserKeysMutation onSuccess * 🗺️ fix: Remap YAML-level override keys to AppConfig equivalents in mergeConfigOverrides Config overrides stored in the DB use YAML-level keys (TCustomConfig), but they're merged into the already-processed AppConfig where some fields have been renamed by AppService. This caused mcpServers overrides to land on a nonexistent key instead of mcpConfig, so config-override MCP servers never appeared in the UI. - Add OVERRIDE_KEY_MAP to remap mcpServers→mcpConfig, interface→interfaceConfig - Apply remapping before deep merge in mergeConfigOverrides - Add test for YAML-level key remapping behavior - Update existing tests to use AppConfig field names in assertions * 🧪 test: Update service.spec to use AppConfig field names after override key remapping * 🛡️ fix: Address code review findings — reliability, types, tests, and performance - Pass tenant context (getTenantId) in importers.js getEndpointsConfig call - Add 5 tests for user-provided API key model fetching (key found, no key, DB error, missing userId, apiKey-only with fixed baseURL) - Distinguish NO_USER_KEY (debug) from infrastructure errors (warn) in catch - Switch fetchPromisesMap from Promise.all to Promise.allSettled so one failing provider doesn't kill the entire model config - Parallelize getUserKeyValues DB lookups via batched Promise.allSettled instead of sequential awaits in the loop - Hoist standardCache instance in fetchModels to avoid double instantiation - Replace Record<string, unknown> types with Partial<TConfig>-based types; remove as unknown as T double-cast in endpoints config - Narrow Bedrock availableRegions to typed destructure - Narrow version field from string|number|undefined to string|undefined - Fix import ordering in mcp/tools.ts and config/models.ts per AGENTS.md - Add JSDoc to getModelsConfig alias clarifying caching semantics * fix: Guard against null getCachedTools in mergeAppTools * 🔍 fix: Address follow-up review — deduplicate extractEnvVariable, fix error discrimination, add log-level tests - Deduplicate extractEnvVariable calls: resolve apiKey/baseURL once, reuse for both the entry and isUserProvided checks (Finding A) - Move ResolvedEndpoint interface from function closure to module scope (Finding B) - Replace fragile msg.includes('NO_USER_KEY') with ErrorTypes.NO_USER_KEY enum check against actual error message format (Finding C). Also handle ErrorTypes.INVALID_USER_KEY as an expected "no key" case. - Add test asserting logger.warn is called for infra errors (not debug) - Add test asserting logger.debug is called for NO_USER_KEY errors (not warn) * fix: Preserve numeric assistants version via String() coercion * 🐛 fix: Address secondary review — Ollama cache bypass, cache tests, type safety - Fix Ollama success path bypassing cache write in fetchModels (CRITICAL): store result before returning so Ollama models benefit from 2-minute TTL - Add 4 fetchModels cache behavior tests: cache write with TTL, cache hit short-circuits HTTP, skipCache bypasses read+write, empty results not cached - Type-safe OVERRIDE_KEY_MAP: Partial<Record<keyof TCustomConfig, keyof AppConfig>> so compiler catches future field rename mismatches - Fix import ordering in config/models.ts (package types longest→shortest) - Rename ToolCacheDeps → MCPToolCacheDeps for naming consistency - Expand getModelsConfig JSDoc to explain caching granularity * fix: Narrow OVERRIDE_KEY_MAP index to satisfy strict tsconfig * 🧩 fix: Add allowedProviders to TConfig, remove Record<string, unknown> from PartialEndpointEntry The agents endpoint config includes allowedProviders (used by the frontend AgentPanel to filter available providers), but it was missing from TConfig. This forced PartialEndpointEntry to use & Record<string, unknown> as an escape hatch, violating AGENTS.md type policy. - Add allowedProviders?: (string | EModelEndpoint)[] to TConfig - Remove Record<string, unknown> from PartialEndpointEntry — now just Partial<TConfig> * 🛡️ fix: Isolate Ollama cache write from fetch try-catch, add Ollama cache tests - Separate Ollama fetch and cache write into distinct scopes so a cache failure (e.g., Redis down) doesn't misattribute the error as an Ollama API failure and fall through to the OpenAI-compatible path (Issue A) - Add 2 Ollama-specific cache tests: models written with TTL on fetch, cached models returned without hitting server (Issue B) - Replace hardcoded 120000 with Time.TWO_MINUTES constant in cache TTL test assertion (Issue C) - Fix OVERRIDE_KEY_MAP JSDoc to accurately describe runtime vs compile-time type enforcement (Issue D) - Add global beforeEach for cache mock reset to prevent cross-test leakage * 🧪 fix: Address third review — DI consistency, cache key width, MCP tests - Inject loadCustomEndpointsConfig via EndpointsConfigDeps with default fallback, matching loadDefaultEndpointsConfig DI pattern (Finding 3) - Widen modelsCacheKey from 64-bit (.slice(0,16)) to 128-bit (.slice(0,32)) for collision-sensitive cross-credential cache key (Finding 4) - Add fetchModels.mockReset() in loadConfigModels.spec beforeEach to prevent mock implementation leaks across tests (Finding 5) - Add 11 unit tests for createMCPToolCacheService covering all three functions: null/empty input, successful ops, error propagation, cold-cache merge (Finding 2) - Simplify getModelsConfig JSDoc to @see reference (Finding 10) * ♻️ refactor: Address remaining follow-ups from reviews OVERRIDE_KEY_MAP completeness: - Add missing turnstile→turnstileConfig mapping - Add exhaustiveness test verifying all three renamed keys are remapped and original YAML keys don't leak through Import role context: - Pass userRole through importConversations job → importLibreChatConvo so role-based endpoint overrides are honored during conversation import - Update convos.js route to include req.user.role in the job payload createEndpointsConfigService unit tests: - Add 8 tests covering: default+custom merge, Azure/AzureAssistants/ Anthropic Vertex/Bedrock config enrichment, assistants version coercion, agents allowedProviders, req.config bypass Plugins/tools efficiency: - Use Set for includedTools/filteredTools lookups (O(1) vs O(n) per plugin) - Combine auth check + filter into single pass (eliminates intermediate array) - Pre-compute toolDefKeys Set for O(1) tool definition lookups * fix: Scope model query cache by user when userIdQuery is enabled * fix: Skip model cache for userIdQuery endpoints, fix endpoints test types - When userIdQuery is true, skip caching entirely (like user_provided keys) to avoid cross-user model list leakage without duplicating cache data - Fix AgentCapabilities type error in endpoints.spec.ts — use enum values and appConfig() helper for partial mock typing * 🐛 fix: Restore filteredTools+includedTools composition, add checkCapability tests - Fix filteredTools regression: whitelist and blacklist are now applied independently (two flat guards), matching original behavior where includedTools=['a','b'] + filteredTools=['b'] produces ['a'] (Finding A) - Fix Set spread in toolkit loop: pre-compute toolDefKeysList array once alongside the Set, reuse for .some() without per-plugin allocation (Finding B) - Add 2 filteredTools tests: blacklist-only path and combined whitelist+blacklist composition (Finding C) - Add 3 checkCapability tests: capability present, capability absent, fallback to defaultAgentCapabilities for non-agents endpoints (Finding D) * 🔑 fix: Include config-override MCP servers in filterAuthorizedTools Config-override MCP servers (defined via admin config overrides for roles/groups) were rejected by filterAuthorizedTools because it called getAllServerConfigs(userId) without the configServers parameter. Only YAML and DB-backed user servers were included in the access check. - Add configServers parameter to filterAuthorizedTools - Resolve config servers via resolveConfigServers(req) at all 4 callsites (create, update, duplicate, revert) using parallel Promise.all - Pass configServers through to getAllServerConfigs(userId, configServers) so the registry merges config-source servers into the access check - Update filterAuthorizedTools.spec.js mock for resolveConfigServers * fix: Skip model cache for userIdQuery endpoints, fix endpoints test types For user-provided key endpoints (userProvide: true), skip the full model list re-fetch during message validation — the user already selected from a list we served them, and re-fetching with skipCache:true on every message send is both slow and fragile (5s provider timeout = rejected model). Instead, validate the model string format only: - Must be a string, max 256 chars - Must match [a-zA-Z0-9][a-zA-Z0-9_.:\-/@+ ]* (covers all known provider model ID formats while rejecting injection attempts) System-configured endpoints still get full model list validation as before. * 🧪 test: Add regression tests for filterAuthorizedTools configServers and validateModel filterAuthorizedTools: - Add test verifying configServers is passed to getAllServerConfigs and config-override server tools are allowed through - Guard resolveConfigServers in createAgentHandler to only run when MCP tools are present (skip for tool-free agent creates) validateModel (12 new tests): - Format validation: missing model, non-string, length overflow, leading special char, script injection, standard model ID acceptance - userProvide early-return: next() called immediately, getModelsConfig not invoked (regression guard for the exact bug this fixes) - System endpoint list validation: reject unknown model, accept known model, handle null/missing models config Also fix unnecessary backslash escape in MODEL_PATTERN regex. * 🧹 fix: Remove space from MODEL_PATTERN, trim input, clean up nits - Remove space character from MODEL_PATTERN regex — no real model ID uses spaces; prevents spurious violation logs from whitespace artifacts - Add model.trim() before validation to handle accidental whitespace - Remove redundant filterUniquePlugins call on already-deduplicated output - Add comment documenting intentional whitelist+blacklist composition - Add getUserKeyValues.mockReset() in loadConfigModels.spec beforeEach - Remove narrating JSDoc from getModelsConfig one-liner - Add 2 tests: trim whitespace handling, reject spaces in model ID * fix: Match startup tool loader semantics — includedTools takes precedence over filteredTools The startup tool loader (loadAndFormatTools) explicitly ignores filteredTools when includedTools is set, with a warning log. The PluginController was applying both independently, creating inconsistent behavior where the same config produced different results at startup vs plugin listing time. Restored mutually exclusive semantics: when includedTools is non-empty, filteredTools is not evaluated. * 🧹 chore: Simplify validateModel flow, note auth requirement on endpoints route - Separate missing-model from invalid-model checks cleanly: type+presence guard first, then trim+format guard (reviewer NIT) - Add route comment noting auth is required for role/tenant scoping * fix: Write trimmed model back to req.body.model for downstream consumers |
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LibreChat
English · 中文
✨ 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: Use any OpenAI-compatible API with LibreChat, no proxy required
- Compatible with Local & Remote AI Providers:
- Ollama, groq, Cohere, Mistral AI, Apple MLX, koboldcpp, together.ai,
- OpenRouter, Helicone, Perplexity, ShuttleAI, Deepseek, Qwen, and more
-
- 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:
- 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 for Tools
- LibreChat Agents:
-
🔍 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 →
-
🪄 Generative UI with Code Artifacts:
- Code Artifacts 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
- Text-to-image with DALL-E (3/2), Stable Diffusion, Flux, or any MCP server
- 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 for Advanced Context control
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💬 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
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🧠 Reasoning UI:
- Dynamic Reasoning UI for Chain-of-Thought/Reasoning AI models like DeepSeek-R1
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🎨 Customizable Interface:
- Customizable Dropdown & Interface that adapts to both power users and newcomers
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- 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
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📥 Import & Export Conversations:
- Import Conversations from LibreChat, ChatGPT, Chatbot UI
- Export conversations as screenshots, markdown, text, json
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🔍 Search & Discovery:
- Search all messages/conversations
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👥 Multi-User & Secure Access:
- Multi-User, Secure Authentication with OAuth2, LDAP, & Email Login Support
- Built-in Moderation, and Token spend tools
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⚙️ 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 📚
🪶 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
- Website: github.com/LibreChat-AI/librechat.ai
Other:
- Website: librechat.ai
- Documentation: librechat.ai/docs
- Blog: librechat.ai/blog
📝 Changelog
Keep up with the latest updates by visiting the releases page and notes:
⚠️ Please consult the changelog for breaking changes before updating.
⭐ Star History
✨ 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.
💖 This project exists in its current state thanks to all the people who contribute
🎉 Special Thanks
We thank Locize for their translation management tools that support multiple languages in LibreChat.