LibreChat - Eden AI Documentation

Configure LibreChat, the open-source ChatGPT alternative, to use Eden AI for access to 500+ AI models.

Overview

LibreChat is a free, open-source AI chat platform that supports multiple providers. By connecting it to Eden AI, you get:

500+ models: Access OpenAI, Anthropic, Google, Cohere, and more through one interface
Self-hosted: Full control over your data and infrastructure
Cost savings: Leverage Eden AI’s competitive pricing
Unified experience: Single chat interface for all providers

Prerequisites

Docker and Docker Compose installed
Eden AI API key from https://app.edenai.run
Basic knowledge of environment variables

Installation

Option 1: Docker Compose (Recommended)

Clone LibreChat and set up with Docker:

# Clone LibreChat
git clone https://github.com/danny-avila/LibreChat.git
cd LibreChat

# Copy example environment file
cp .env.example .env

# Start LibreChat
docker compose up -d

Option 2: Manual Installation

# Clone repository
git clone https://github.com/danny-avila/LibreChat.git
cd LibreChat

# Install dependencies
npm install

# Set up environment
cp .env.example .env

# Build and start
npm run build
npm run backend

Configuration

Step 1: Configure Environment Variables

Edit the .env file to add Eden AI configuration:

# Eden AI Configuration
OPENAI_API_KEY=YOUR_EDEN_AI_API_KEY
OPENAI_REVERSE_PROXY=https://api.edenai.run/v3

# Optional: Enable multiple endpoints
ANTHROPIC_API_KEY=YOUR_EDEN_AI_API_KEY
ANTHROPIC_REVERSE_PROXY=https://api.edenai.run/v3

GOOGLE_API_KEY=YOUR_EDEN_AI_API_KEY
GOOGLE_REVERSE_PROXY=https://api.edenai.run/v3

# Application settings
HOST=localhost
PORT=3080
MONGO_URI=mongodb://127.0.0.1:27017/LibreChat

# Session secret (generate your own)
SESSION_SECRET=your_random_secret_here
JWT_SECRET=your_jwt_secret_here
JWT_REFRESH_SECRET=your_refresh_secret_here

Step 2: Configure librechat.yaml

Create or edit librechat.yaml for advanced configuration:

version: 1.0.5
cache: true

endpoints:
  custom:
    - name: "Eden AI"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "anthropic/claude-sonnet-4-5"
          - "openai/gpt-4"
          - "openai/gpt-4-turbo"
          - "google/gemini-2.5-pro"
          - "google/gemini-2.5-flash"
          - "cohere/command-r-plus"
          - "openai/gpt-3.5-turbo"
        fetch: false
      titleConvo: true
      titleModel: "openai/gpt-3.5-turbo"
      summarize: false
      summaryModel: "openai/gpt-3.5-turbo"
      forcePrompt: false
      modelDisplayLabel: "Eden AI"

Step 3: Start LibreChat

# With Docker
docker compose up -d

# Without Docker
npm run backend

Access LibreChat at http://localhost:3080

Available Models

Configure which models appear in the LibreChat interface:

endpoints:
  custom:
    - name: "Eden AI - Claude"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "anthropic/claude-sonnet-4-5"
          - "anthropic/claude-opus-4-5"
          - "anthropic/claude-sonnet-4-5"
          - "anthropic/claude-haiku-4-5"
      modelDisplayLabel: "Claude (Eden AI)"

    - name: "Eden AI - OpenAI"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "openai/gpt-4"
          - "openai/gpt-4-turbo"
          - "openai/gpt-4o"
          - "openai/gpt-3.5-turbo"
      modelDisplayLabel: "OpenAI (Eden AI)"

    - name: "Eden AI - Google"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "google/gemini-2.5-pro"
          - "google/gemini-2.5-flash"
      modelDisplayLabel: "Google (Eden AI)"

Features

Multi-Model Conversations

Switch between models mid-conversation:

Start a conversation with Claude
Click the model selector
Switch to GPT-4 or Gemini
Continue the conversation seamlessly

File Attachments

Upload files for vision-capable models:

endpoints:
  custom:
    - name: "Eden AI - Vision"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "openai/gpt-4o"
          - "google/gemini-2.5-pro"
          - "anthropic/claude-sonnet-4-5"
      # Enable file uploads
      fileConfig:
        endpoints:
          assistants:
            fileLimit: 5
            fileSizeLimit: 10
            totalSizeLimit: 50
            supportedMimeTypes:
              - "image/jpeg"
              - "image/png"
              - "image/webp"
              - "image/gif"
      modelDisplayLabel: "Vision Models"

Preset Prompts

Create custom prompts for common tasks:

endpoints:
  custom:
    - name: "Eden AI"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "anthropic/claude-sonnet-4-5"
          - "openai/gpt-4"
      # Add custom presets
      presets:
        - title: "Code Assistant"
          model: "anthropic/claude-sonnet-4-5"
          temperature: 0.1
          system_message: "You are an expert programmer. Provide clean, well-documented code."

        - title: "Creative Writer"
          model: "openai/gpt-4"
          temperature: 0.9
          system_message: "You are a creative writer. Be imaginative and engaging."

        - title: "Data Analyst"
          model: "google/gemini-2.5-pro"
          temperature: 0.3
          system_message: "You are a data analyst. Provide clear, data-driven insights."

Advanced Configuration

Custom Model Parameters

Configure temperature, max tokens, and other parameters:

endpoints:
  custom:
    - name: "Eden AI"
      apiKey: "${OPENAI_API_KEY}"
      baseURL: "https://api.edenai.run/v3"
      models:
        default:
          - "anthropic/claude-sonnet-4-5"
      # Default parameters
      default:
        temperature: 0.7
        max_tokens: 2000
        top_p: 1.0
        frequency_penalty: 0.0
        presence_penalty: 0.0
      # Allow users to override
      userProvidedParameters:
        - "temperature"
        - "max_tokens"
        - "top_p"

User Authentication

Enable user registration and authentication:

# Allow user registration
ALLOW_REGISTRATION=true

# Email verification (optional)
EMAIL_SERVICE=gmail
EMAIL_USERNAME=your-email@gmail.com
EMAIL_PASSWORD=your-app-password

# Social auth (optional)
GOOGLE_CLIENT_ID=your-google-client-id
GOOGLE_CLIENT_SECRET=your-google-client-secret
GOOGLE_CALLBACK_URL=http://localhost:3080/oauth/google/callback

Rate Limiting

Protect your API key with rate limiting:

rateLimits:
  fileUploads:
    ipMax: 100
    ipWindowInMinutes: 60
    userMax: 50
    userWindowInMinutes: 60

  conversationsImport:
    ipMax: 10
    ipWindowInMinutes: 60
    userMax: 5
    userWindowInMinutes: 60

Conversation History

Configure MongoDB for persistent conversations:

# MongoDB connection
MONGO_URI=mongodb://127.0.0.1:27017/LibreChat

# Or use MongoDB Atlas (cloud)
# MONGO_URI=mongodb+srv://username:password@cluster.mongodb.net/LibreChat

Docker Deployment

Production Docker Compose

version: '3.4'

services:
  api:
    image: ghcr.io/danny-avila/librechat:latest
    container_name: LibreChat
    ports:
      - 3080:3080
    depends_on:
      - mongodb
    restart: always
    environment:
      - HOST=0.0.0.0
      - MONGO_URI=mongodb://mongodb:27017/LibreChat
      - OPENAI_API_KEY=${OPENAI_API_KEY}
      - OPENAI_REVERSE_PROXY=https://api.edenai.run/v3
    volumes:
      - ./librechat.yaml:/app/librechat.yaml
      - ./images:/app/client/public/images

  mongodb:
    image: mongo
    container_name: chat-mongodb
    restart: always
    volumes:
      - ./data-node:/data/db
    ports:
      - 27017:27017

Deploy to Production

# Pull latest image
docker compose pull

# Start services
docker compose up -d

# View logs
docker compose logs -f api

# Check status
docker compose ps

Troubleshooting

Models Not Appearing

If models don’t show up in the interface:

Check librechat.yaml syntax:
```
# Validate YAML
docker compose config
```

Verify API key:

# Test Eden AI endpoint
curl -X POST https://api.edenai.run/v3/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "anthropic/claude-sonnet-4-5",
    "messages": [{"role": "user", "content": "test"}],
    "stream": true
  }'

Clear cache and restart:

docker compose down
docker compose up -d

Authentication Errors

If you see 401 errors:

Check .env has correct API key
Ensure no extra spaces in the key
Verify OPENAI_REVERSE_PROXY URL is correct
Restart services after changing .env

Slow Responses

If responses are slow:

Use faster models for chat titles:
```
titleModel: "openai/gpt-3.5-turbo"
```
Disable unnecessary features:
```
summarize: false
```
Check your internet connection and Eden AI status

Connection Refused

If LibreChat can’t connect to MongoDB:

Check MongoDB is running:
```
docker compose ps mongodb
```

Verify MONGO_URI in .env:

MONGO_URI=mongodb://mongodb:27017/LibreChat

Check network connectivity:
```
docker compose logs mongodb
```

Security Best Practices

1. Secure API Keys

Never commit API keys to version control:

2. Use Environment-Specific Configs

# Production settings
NODE_ENV=production
ALLOW_REGISTRATION=false
SESSION_SECRET=strong_random_secret_here

3. Enable HTTPS

Use a reverse proxy like Nginx:

server {
  listen 443 ssl;
  server_name chat.yourdomain.com;

  ssl_certificate /path/to/cert.pem;
  ssl_certificate_key /path/to/key.pem;

  location / {
    proxy_pass http://localhost:3080;
    proxy_http_version 1.1;
    proxy_set_header Upgrade $http_upgrade;
    proxy_set_header Connection 'upgrade';
    proxy_set_header Host $host;
    proxy_cache_bypass $http_upgrade;
  }
}

4. Implement Rate Limiting

Protect against abuse:

rateLimits:
  fileUploads:
    ipMax: 50
    ipWindowInMinutes: 60
  conversationsImport:
    ipMax: 5
    ipWindowInMinutes: 60

Cost Optimization

1. Use Appropriate Models

Configure cheaper models for simple tasks:

endpoints:
  custom:
    - name: "Eden AI"
      # Use GPT-3.5 for titles (cheaper)
      titleModel: "openai/gpt-3.5-turbo"
      # Use Claude Haiku for summaries (fast & cheap)
      summaryModel: "anthropic/claude-haiku-4-5"

2. Monitor Usage

Track costs through Eden AI dashboard:

View usage at https://app.edenai.run
Set up billing alerts
Review monthly reports

3. Limit Token Usage

endpoints:
  custom:
    - name: "Eden AI"
      default:
        max_tokens: 1000  # Limit response length

Example Use Cases

1. Team Collaboration

Set up LibreChat for your team:

Enable user registration for team members
Configure multiple endpoints for different projects
Use presets for common workflows (code review, documentation, etc.)

2. Customer Support

Deploy as an internal support tool:

Create presets for support responses
Use conversation history to maintain context
Configure rate limits to prevent abuse

3. Development Assistant

Integrate with your development workflow:

Code assistance with Claude or GPT-4
Documentation generation with presets
Bug analysis with vision models (screenshots)

Next Steps

Open WebUI - Alternative chat interface
OpenAI SDK (Python) - Programmatic access
Monitoring - Track usage and spending

V3 Documentation

Quick Start

Overview

LLMs

Expert Models

General

Data Governance

Integrations

Documentation Index

​Overview

​Prerequisites

​Installation

​Option 1: Docker Compose (Recommended)

​Option 2: Manual Installation

​Configuration

​Step 1: Configure Environment Variables

​Step 2: Configure librechat.yaml

​Step 3: Start LibreChat

​Available Models

​Features

​Multi-Model Conversations

​File Attachments

​Preset Prompts

​Advanced Configuration

​Custom Model Parameters

​User Authentication

​Rate Limiting

​Conversation History

​Docker Deployment

​Production Docker Compose

​Deploy to Production

​Troubleshooting

​Models Not Appearing

​Authentication Errors

​Slow Responses

​Connection Refused

​Security Best Practices

​1. Secure API Keys

​2. Use Environment-Specific Configs

​3. Enable HTTPS

​4. Implement Rate Limiting

​Cost Optimization

​1. Use Appropriate Models

​2. Monitor Usage

​3. Limit Token Usage

​Example Use Cases

​1. Team Collaboration

​2. Customer Support

​3. Development Assistant

​Next Steps

Overview

Prerequisites

Installation

Option 1: Docker Compose (Recommended)

Option 2: Manual Installation

Configuration

Step 1: Configure Environment Variables

Step 2: Configure librechat.yaml

Step 3: Start LibreChat

Available Models

Features

Multi-Model Conversations

File Attachments

Preset Prompts

Advanced Configuration

Custom Model Parameters

User Authentication

Rate Limiting

Conversation History

Docker Deployment

Production Docker Compose

Deploy to Production

Troubleshooting

Models Not Appearing

Authentication Errors

Slow Responses

Connection Refused

Security Best Practices

1. Secure API Keys

2. Use Environment-Specific Configs

3. Enable HTTPS

4. Implement Rate Limiting

Cost Optimization

1. Use Appropriate Models

2. Monitor Usage

3. Limit Token Usage

Example Use Cases

1. Team Collaboration

2. Customer Support

3. Development Assistant

Next Steps