docs/QUICKSTART.md

---

# docs/QUICKSTART.md

````markdown
# Quickstart

This guide will get you up and running with **AnyCoder** in minutes.

## 1. Clone the Repository
```bash
git clone https://github.com/your-org/anycoder.git
cd anycoder
````

## 2. Install Dependencies

Make sure you have Python 3.9+ installed.

```bash
pip install --upgrade pip
pip install -r requirements.txt
```

## 3. Set Environment Variables

```bash
export HF_TOKEN=<YOUR_HUGGINGFACE_TOKEN>
export OPENAI_API_KEY=<YOUR_OPENAI_API_KEY>
export GEMINI_API_KEY=<YOUR_GEMINI_API_KEY>
```

## 4. Run the App Locally

```bash
python app.py
```

Open [http://localhost:7860](http://localhost:7860) in your browser to access the UI.

## 5. Explore Features

* **Model selector**: Choose from Groq, OpenAI, Gemini, Fireworks, and HF models.
* **Input**: Enter prompts, upload files or images for context.
* **Generate**: View code, preview, and conversation history.

---

# docs/API\_REFERENCE.md

````markdown
# API Reference

This document describes the public Python modules and functions available in AnyCoder.

## `models.py`

### `ModelInfo` dataclass

```python
@dataclass
class ModelInfo:
    name: str
    id: str
    description: str
    default_provider: str = "auto"
````

### `AVAILABLE_MODELS: List[ModelInfo]`

A list of supported models with metadata.

### `find_model(identifier: str) -> Optional[ModelInfo]`

Lookup a model by name or ID.

---

## `inference.py`

### `chat_completion(model_id: str, messages: List[Dict[str,str]], provider: Optional[str]=None, max_tokens: int=4096) -> str`

Send a one-shot chat completion request.

### `stream_chat_completion(model_id: str, messages: List[Dict[str,str]], provider: Optional[str]=None, max_tokens: int=4096) -> Generator[str]`

Stream partial generation results.

---

## `hf_client.py`

### `get_inference_client(model_id: str, provider: str="auto") -> InferenceClient`

Creates an HF InferenceClient with provider routing logic.

---

# docs/ARCHITECTURE.md

```markdown
# Architecture Overview

Below is a high-level diagram of AnyCoder's components and data flow:

```

```
                          +------------+
                          |   User     |
                          +-----+------+
                                |
                                v
                      +---------+----------+
                      |   Gradio UI (app.py)|
                      +---------+----------+
                                |
       +------------------------+------------------------+
       |                         |                        |
       v                         v                        v
 models.py                 inference.py              plugins.py
```

(model registry)      (routing & chat\_completion)  (extension points)
\|                         |                        |
+---------------------+   +------------------------+
|
v
hf\_client.py                           deploy.py
(HF/OpenAI/Gemini/etc routing)         (HF Spaces integration)

```

- **UI Layer** (`app.py` + Gradio): handles inputs, outputs, and state.
- **Model Registry** (`models.py`): metadata-driven list of supported models.
- **Inference Layer** (`inference.py`, `hf_client.py`): abstracts provider selection and API calls.
- **Extensions** (`plugins.py`): plugin architecture for community or custom integrations.
- **Deployment** (`deploy.py`): Helpers to preview in an iframe or push to Hugging Face Spaces.

This separation ensures modularity, testability, and easy extensibility.

```