> 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

Configure LibreChat to use TensorX as an OpenAI-compatible provider.

***

## What is LibreChat?

[LibreChat](https://www.librechat.ai/) is a self-hosted chat interface that supports custom OpenAI-compatible providers.

***

## 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:
          - "<MODEL_ID>"
        fetch: true
      titleConvo: true
      titleModel: "<MODEL_ID>"
      summarize: false
      summaryModel: "z-ai/glm-5.2"
      forcePrompt: false
      modelDisplayLabel: "TensorX AI"
      dropParams: ["user"]
```

Replace both `<MODEL_ID>` values with an ID returned by `GET /v1/models`.

### 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

***

## Model selection

Call `GET /v1/models` with your TensorX API key and use one of the returned IDs. If the integration depends on a capability or token limit, query `GET /v1/model/info` before selecting the model. See [Models](/api-reference/models.md) for examples.

***

## Advanced Configuration

### Auto-Fetch All Models

To automatically discover all available TensorX models:

```yaml
models:
  fetch: true
  default:
    - "<MODEL_ID>"
```

### Custom Parameters

```yaml
endpoints:
  custom:
    - name: "TensorX AI"
      apiKey: "${TENSORX_API_KEY}"
      baseURL: "https://api.tensorx.ai/v1"
      models:
        default:
          - "<MODEL_ID>"
        fetch: false
      default: ["max_tokens", "temperature", "top_p"]
      additionalParameters:
        temperature: 0.7
        top_p: 0.9
```

***

## 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                              |
| `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": "<MODEL_ID>",
    "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. **Limit your model list** - Only include models you use
2. **Secure your API key** - Never commit `.env` files to version control
3. **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/object_structure/custom_endpoint)
* [TensorX Models & Pricing](https://tensorx.ai/models)
* [TensorX API Examples](/api-reference/api-examples.md)

***

## Need Help?

* **Email**: <support@tensorx.ai>
* **Contact Support**: [Contact page](/support/support.md)


---

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