---
title: "LibreChat"
description: "Integrate LibreChat with Bifrost to access any AI provider through a modern open-source chat interface with virtual keys and observability."
icon: "message"
---

[LibreChat](https://github.com/danny-avila/LibreChat) is a modern, open-source chat client that supports multiple AI providers. By adding Bifrost as a custom provider, you get access to any model configured in Bifrost through a familiar chat interface, plus governance features like virtual keys and built-in observability.

<Note>
If your Allowed Headers are already set to `*`, you can skip this note. If not and you face issues integrating Bifrost with LibreChat, try switching to `*` or adding the specific headers required by your client. By default, Bifrost whitelists: `Content-Type`, `Authorization`, `X-Requested-With`, `X-Stainless-Timeout`, and `X-Api-Key`.
</Note>

## Setup

### 1. Install LibreChat

Follow the [LibreChat documentation](https://www.librechat.ai/docs/local) for local setup. There are multiple installation options (Docker, npm, etc.).

### 2. Add Bifrost as a Custom Provider

Add the following to your `librechat.yaml` file:

```yaml
custom:
  - name: "Bifrost"
    apiKey: "dummy"
    baseURL: "http://localhost:8080/v1"
    models:
      default: ["openai/gpt-4o"]
      fetch: true
    titleConvo: true
    titleModel: "openai/gpt-4o"
    summarize: false
    summaryModel: "openai/gpt-4o"
    forcePrompt: false
    modelDisplayLabel: "Bifrost"
    iconURL: https://getbifrost.ai/bifrost-logo.png
```

| Field | Description |
|-------|-------------|
| `apiKey` | Bifrost virtual key if authentication is enabled; use `dummy` otherwise |
| `baseURL` | Bifrost gateway URL + `/v1` (LibreChat uses OpenAI format) |
| `models.default` | Default models to show. Use Bifrost model IDs (`provider/model`) |
| `models.fetch` | Set `true` to fetch available models from Bifrost |
| `titleConvo` | Use AI for conversation title generation |
| `titleModel` | Model for title generation |
| `summarize` | Enable chat summary generation |
| `summaryModel` | Model for summaries |

<Tip>
Set `models.fetch: true` to automatically discover all models configured in Bifrost. This keeps your LibreChat model list in sync with your Bifrost provider configuration.
</Tip>

<Note>
If you're running LibreChat in Docker, it does not automatically use `librechat.yaml`. See [Step 1 of the LibreChat custom endpoints guide](https://www.librechat.ai/docs/quick_start/custom_endpoints#step-1-create-or-edit-a-docker-override-file) for how to mount or override the config.
</Note>

### 3. Docker Networking

Choose the correct `baseURL` for your setup:

| Setup | baseURL |
|-------|---------|
| LibreChat and Bifrost on same host | `http://localhost:8080/v1` |
| LibreChat in Docker Desktop, Bifrost on host | `http://host.docker.internal:8080/v1` |
| LibreChat in Docker Engine (Linux), Bifrost on host | Add `--add-host=host.docker.internal:host-gateway` to `docker run`, or `extra_hosts: ["host.docker.internal:host-gateway"]` in Compose, then use `http://host.docker.internal:8080/v1` |
| Both in same Docker network | `http://bifrost-container-name:8080/v1` |

### 4. Run LibreChat

Start LibreChat. Bifrost will appear as a provider with all configured models available.

## Virtual Keys

When Bifrost has [virtual key authentication](/features/governance/virtual-keys) enabled, set `apiKey` to your virtual key:

```yaml
apiKey: "bf-your-virtual-key-here"
```

This lets you enforce usage limits, budgets, and access control per user or team. For team deployments, create a separate virtual key for each team or environment — each key can have its own rate limits, budgets, and provider access rules configured in the Bifrost dashboard.

## Model Selection

LibreChat displays models from the `models.default` list or fetches them from Bifrost when `models.fetch` is enabled. Use Bifrost model IDs in `provider/model` format to access any configured provider:

```yaml
models:
  default:
    - "openai/gpt-5"
    - "anthropic/claude-sonnet-4-5-20250929"
    - "gemini/gemini-2.5-pro"
    - "groq/llama-3.3-70b-versatile"
  fetch: true
```

- Use powerful models like `openai/gpt-5` or `anthropic/claude-sonnet-4-5-20250929` for complex conversations
- Use fast models like `groq/llama-3.3-70b-versatile` for quick responses
- Set `titleModel` and `summaryModel` to lighter models to reduce cost for metadata generation

## Using Multiple Providers

Bifrost routes requests to the correct provider based on the model name. Use the `provider/model-name` format to access any configured provider through the single `/v1` endpoint:

```
anthropic/claude-sonnet-4-5-20250929
openai/gpt-5
gemini/gemini-2.5-pro
mistral/mistral-large-latest
```

### Supported Providers

Bifrost supports the following providers with the `provider/model-name` format:

`openai`, `azure`, `gemini`, `vertex`, `bedrock`, `mistral`, `groq`, `cerebras`, `cohere`, `perplexity`, `xai`, `ollama`, `openrouter`, `huggingface`, `nebius`, `parasail`, `replicate`, `vllm`, `sgl`

<Note>
LibreChat connects to Bifrost via a single OpenAI-compatible endpoint. Bifrost handles routing to the correct provider based on the model name — no per-provider configuration needed in LibreChat.
</Note>

## Observability

All LibreChat traffic through Bifrost is logged. Monitor it at `http://localhost:8080/logs` — filter by provider, model, or search through conversation content to track usage across your team.

## Next Steps

- [Provider Configuration](/quickstart/gateway/provider-configuration) — Configure AI providers in Bifrost
- [Virtual Keys](/features/governance/virtual-keys) — Set up usage limits and access control