Summary

LangDB AI Custom Endpoint Integration

Added configuration for the LangDB AI custom endpoint in librechat.example.yaml. This enables LibreChat users to connect directly to the LangDB API and utilize its specialized models with settings for headers, model display, and title conversations.

Key additions:

• Endpoint configuration for LangDB API
• Headers for authentication with LangDB API (including conversation context)
• Model list and label customizations
• Conversation ID support via {{LIBRECHAT_CONVERSATION_ID}} placeholder

Headers for LangDB User Tracking:

LangDB offers comprehensive user tracking using these headers:

• x-project-id: Project identification for API access
• x-user-id: User identification for session tracking
• x-user-name: User display name for personalization
• x-email: User email for account management
• x-user-tiers: User role/permission level
• x-thread-id: Conversation context using {{LIBRECHAT_CONVERSATION_ID}} placeholder

These headers enable LangDB to provide personalized experiences, track usage patterns, and maintain conversation context across sessions.

Change Type

Please delete any irrelevant options.

• New feature (non-breaking change which adds functionality)
• This change requires a documentation update

Testing

Tested the LangDB AI endpoint configuration by setting up the API connection with provided keys and verifying model fetching, header configurations, and response outputs. Validated model retrieval and display settings align with LangDB model responses.

Test Configuration:

• Environment Variables: Set LANGDB_API_KEY and LANGDB_PROJECT_ID for testing
• Base URL: https://api.us-east-1.langdb.ai
• Default Model: openai/gpt-4.1-nano

Checklist

Please delete any irrelevant options.

• My code adheres to this project's style guidelines
• I have performed a self-review of my own code
• I have commented in any complex areas of my code
• I have made pertinent documentation changes
• My changes do not introduce new warnings
• I have written tests demonstrating that my changes are effective or that my feature works
• Local unit tests pass with my changes
• Any changes dependent on mine have been merged and published in downstream modules.