LibreChat

Connect LibreChat to TensorX.ai and access leading open-source models like DeepSeek, Llama, Qwen, and GLM through a single self-hosted interface.

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What is LibreChat?

LibreChat is an open-source ChatGPT alternative that supports multiple AI providers through OpenAI-compatible APIs. With TensorX, you get a privacy-focused, self-hosted chat interface with access to all our models.

Why LibreChat + TensorX?

• 🔒 Self-hosted - Your conversations stay on your infrastructure
• 🌍 EU-hosted models - Privacy-focused European hosting
• 🚀 Multiple models - DeepSeek, Llama, Qwen, GLM, and more
• 💰 Simple pricing - One API key, transparent costs

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Prerequisites

• LibreChat installed and running (follow the official LibreChat installation guide)
• A TensorX API key (sign up here)

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Configuration

Step 1: Add Your API Key

Add your TensorX API key to LibreChat's .env file:

TENSORX_API_KEY=your-tensorx-api-key-here

Step 2: Configure the TensorX Endpoint

Create or edit your librechat.yaml file:

version: 1.1.7
cache: true

endpoints:
  custom:
    - name: "TensorX AI"
      apiKey: "${TENSORX_API_KEY}"
      baseURL: "https://api.tensorx.ai/v1"
      models:
        default:
          - "deepseek/deepseek-chat-v3.1"
          - "deepseek/deepseek-r1-0528"
          - "z-ai/glm-5.1"
          - "meta-llama/llama-3.3-70b-instruct"
          - "meta-llama/llama-4-maverick"
          - "qwen/qwen3-235b-a22b-2507"
          - "openai/gpt-oss-120b"
          - "minimax/minimax-m2.5"
        fetch: false
      titleConvo: true
      titleModel: "deepseek/deepseek-chat-v3.1"
      summarize: false
      summaryModel: "deepseek/deepseek-chat-v3.1"
      forcePrompt: false
      modelDisplayLabel: "TensorX AI"
      dropParams: ["user"]

Step 3: Mount the Configuration

Add this to your docker-compose.override.yml:

services:
  api:
    volumes:
      - ./librechat.yaml:/app/librechat.yaml:ro

Step 4: Restart LibreChat

docker compose restart api

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Using TensorX in LibreChat

1. Open LibreChat in your browser
2. Start a new conversation
3. Click the model selector dropdown
4. Select TensorX AI as the provider
5. Choose your preferred model

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Available Models

Model	Features	Best For
z-ai/glm-5.1 ⭐	Functions, Reasoning	Coding, reasoning, general use
minimax/minimax-m2.5	Functions, Reasoning	Reasoning, general purpose
moonshotai/kimi-k2.5	Vision, Functions	Vision, long context
deepseek/deepseek-chat-v3.1	Functions, Reasoning	General chat, fast reasoning
deepseek/deepseek-r1-0528	Functions, Reasoning	Complex reasoning tasks
minimax/minimax-m2	Coding, Functions	Coding, fast responses
meta-llama/llama-4-maverick	Functions	Long context, multimodal
openai/gpt-oss-120b	Functions, Reasoning	GPT-4 alternative

View full model list and pricing: tensorx.ai/models

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Model Recommendations

Task	Recommended Models
General chat	deepseek/deepseek-chat-v3.1, meta-llama/llama-3.3-70b-instruct
Complex reasoning	deepseek/deepseek-r1-0528, openai/gpt-oss-120b
Coding	z-ai/glm-5.1, minimax/minimax-m2
Vision tasks	moonshotai/kimi-k2.5, meta-llama/llama-4-maverick
Multilingual	z-ai/glm-5.1

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Advanced Configuration

Auto-Fetch All Models

To automatically discover all available TensorX models:

models:
  fetch: true
  default:
    - "deepseek/deepseek-chat-v3.1"

Custom Parameters

endpoints:
  custom:
    - name: "TensorX AI"
      apiKey: "${TENSORX_API_KEY}"
      baseURL: "https://api.tensorx.ai/v1"
      models:
        default:
          - "deepseek/deepseek-chat-v3.1"
        fetch: false
      default: ["max_tokens", "temperature", "top_p"]
      additionalParameters:
        max_tokens: 4000
        temperature: 0.7
        top_p: 0.9

Organize by Category

Create multiple endpoints for different model types:

endpoints:
  custom:
    - name: "TensorX - Reasoning"
      apiKey: "${TENSORX_API_KEY}"
      baseURL: "https://api.tensorx.ai/v1"
      models:
        default:
          - "deepseek/deepseek-r1-0528"
          - "openai/gpt-oss-120b"
    
    - name: "TensorX - General"
      apiKey: "${TENSORX_API_KEY}"
      baseURL: "https://api.tensorx.ai/v1"
      models:
        default:
          - "meta-llama/llama-3.3-70b-instruct"
          - "z-ai/glm-5.1"

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Configuration Options

Option	Description
apiKey	Your TensorX API key from environment variables
baseURL	TensorX API endpoint (https://api.tensorx.ai/v1)
models.default	List of models shown in the dropdown
fetch	Set true to auto-fetch available models
titleConvo	Auto-generate conversation titles
titleModel	Model used for titles (use a fast model)
dropParams	Remove parameters that may cause issues

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Troubleshooting

Models Not Appearing

1. Verify your API key is set in .env
2. Check that librechat.yaml is properly mounted
3. Restart the API container: docker compose restart api
4. Check logs: docker compose logs api

Test Your API Key

curl https://api.tensorx.ai/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -d '{
    "model": "deepseek/deepseek-chat-v3.1",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

Configuration Not Loading

• Use proper YAML indentation (2 spaces)
• Verify quotes around strings
• Check version number matches your LibreChat version

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Best Practices

1. Use fast models for titles - Set titleModel to deepseek/deepseek-chat-v3.1
2. Limit your model list - Only include models you actually use
3. Secure your API key - Never commit .env files to version control
4. Monitor usage - Track API usage in your TensorX dashboard

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Resources

• LibreChat Documentation
• LibreChat Custom Endpoints Guide
• TensorX Models & Pricing
• TensorX API Examples

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Need Help?

• 📧 Email: [e-mail]
• 💬 Contact Support: Contact page