> For the complete documentation index, see [llms.txt](https://docs.tensorx.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tensorx.ai/chat-interfaces/librechat.md). # LibreChat Connect LibreChat to TensorX.ai and access leading open-source models like DeepSeek, Llama, Qwen, and GLM through a single self-hosted interface. *** ## What is LibreChat? [LibreChat](https://www.librechat.ai/) 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. {% hint style="success" %} **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 {% endhint %} *** ## Prerequisites * LibreChat installed and running (follow the [official LibreChat installation guide](https://www.librechat.ai/docs/configuration/docker_override)) * A TensorX API key ([sign up here](https://app.tensorx.ai)) *** ## Configuration ### Step 1: Add Your API Key Add your TensorX API key to LibreChat's `.env` file: ```bash TENSORX_API_KEY=your-tensorx-api-key-here ``` ### Step 2: Configure the TensorX Endpoint Create or edit your `librechat.yaml` file: ```yaml 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`: ```yaml services: api: volumes: - ./librechat.yaml:/app/librechat.yaml:ro ``` ### Step 4: Restart LibreChat ```bash docker compose restart api ``` *** ## 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 *** ## 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 | {% hint style="info" %} **View full model list and pricing**: [tensorx.ai/models](https://tensorx.ai/models) {% endhint %} *** ## 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` | *** ## Advanced Configuration ### Auto-Fetch All Models To automatically discover all available TensorX models: ```yaml models: fetch: true default: - "deepseek/deepseek-chat-v3.1" ``` ### Custom Parameters ```yaml 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: ```yaml 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" ``` *** ## 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 | *** ## 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 ```bash 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 *** ## 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](https://app.tensorx.ai/dashboard) *** ## Resources * [LibreChat Documentation](https://www.librechat.ai/docs) * [LibreChat Custom Endpoints Guide](https://www.librechat.ai/docs/configuration/librechat_yaml/ai_endpoints/custom) * [TensorX Models & Pricing](https://tensorx.ai/models) * [TensorX API Examples](https://github.com/Tensorix-ai/tensorix-docs/blob/main/api-examples/README.md) *** ## Need Help? * 📧 **Email**: * 💬 **Contact Support**: [Contact page](https://github.com/Tensorix-ai/tensorix-docs/blob/main/support/support/README.md) --- # Agent Instructions This documentation is published with GitBook. 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