vllora

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<img src="assets/images/logos/logo_dark.svg" width="200px" alt="vLLora Logo">

#### Lightweight, Real-time Debugging for AI Agents

Debug your Agents in Real Time. Trace, analyze, and optimize instantly. Seamless with LangChain, Google ADK, OpenAI, and all major frameworks.

**[Documentation](https://vllora.dev/docs)** | **[Issues](https://github.com/vllora/vllora/issues)** 


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## Quick Start

First, install [Homebrew](https://brew.sh) if you haven't already, then:

```bash
brew tap vllora/vllora
brew install vllora
```


### Start the vLLora:

```bash
vllora
```

> The server will start on `http://localhost:9090` and the UI will be available at `http://localhost:9091`. 

vLLora uses OpenAI-compatible chat completions API, so when your AI agents make calls through vLLora, it automatically collects traces and debugging information for every 
interaction.

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![vLLora Demo](https://raw.githubusercontent.com/vllora/vllora/main/assets/gifs/traces.gif)


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### Test Send your First Request

1. **Configure API Keys**: Visit `http://localhost:9091` to configure your AI provider API keys through the UI
2. **Make a request** to see debugging in action:

```bash
curl http://localhost:9090/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o-mini",
    "messages": [{"role": "user", "content": "What is the capital of France?"}]
  }'
```

### Rust streaming example (OpenAI-compatible)

In `llm/examples/openai_stream_basic/src/main.rs` you can find a minimal Rust example that:

- **Builds an OpenAI-style request** using `CreateChatCompletionRequestArgs` with:
  - `model("gpt-4.1-mini")`
  - a **system message**: `"You are a helpful assistant."`
  - a **user message**: `"Stream numbers 1 to 20 in separate lines."`
- **Constructs a `VlloraLLMClient`** and configures credentials via:

```bash
export VLLORA_OPENAI_API_KEY="your-openai-compatible-key"
```

Inside the example, the client is crea