---
title: TTS
emoji: 🤖
colorFrom: blue
colorTo: purple
sdk: docker
app_port: 7860
models:
  - unsloth/Qwen3-8B-GGUF
---

# Qwen3-8B-GGUF API Space

![Status](https://img.shields.io/badge/Status-Active-success?style=for-the-badge)
![Model](https://img.shields.io/badge/Model-Qwen3--8B--GGUF-blue?style=for-the-badge)
![License](https://img.shields.io/badge/License-Apache--2.0-orange?style=for-the-badge)
![Framework](https://img.shields.io/badge/Framework-FastAPI-009688?style=for-the-badge&logo=fastapi&logoColor=white)

A Hugging Face Space that exposes the [`unsloth/Qwen3-8B-GGUF`](https://huggingface.co/unsloth/Qwen3-8B-GGUF) model (8-bit) as a REST API using **FastAPI** and **llama-cpp-python**.

## Endpoints

| Method | Path        | Description                                  |
|--------|-------------|----------------------------------------------|
| GET    | `/`         | HTML documentation page                      |
| POST   | `/generate` | Send a message and receive an AI response    |
| GET    | `/health`   | Health check (model status)                  |
| GET    | `/docs`     | Interactive Swagger UI                       |
| GET    | `/redoc`    | ReDoc documentation                          |

## POST `/generate` — Request Format

```json
{
  "instructions": "optional system instructions",
  "message": "required user message",
  "user": "optional username"
}
```

| Field          | Type   | Required | Description                          |
|----------------|--------|----------|--------------------------------------|
| `instructions` | string | No       | System-level instructions            |
| `message`      | string | **Yes**  | The message to process               |
| `user`         | string | No       | Username identifier                  |

## Prompt Construction

The prompt sent to the model is built as:

```
{instructions}
{user} said {message}
```

**Example input:**
```json
{"instructions": "idk", "message": "thisissupermario", "user": "admin"}
```

**Prompt sent to model:**
```
idk
admin said thisissupermario
```

## Example Usage

### Python
```python
import requests

response = requests.post(
    "https://dreamlongyt-agent.hf.space/generate",
    json={
        "instructions": "idk",
        "message": "thisissupermario",
        "user": "admin"
    }
)
print(response.json())
```

### cURL
```bash
curl -X POST "https://dreamlongyt-agent.hf.space/generate" \
     -H "Content-Type: application/json" \
     -d \'{"instructions":"idk","message":"thisissupermario","user":"admin"}\'
```

## Deployment

1. Go to [huggingface.co/new-space](https://huggingface.co/new-space)
2. Name your Space and select **Docker** as the SDK
3. Clone the Space repo and push these files:
   - `app.py`
   - `Dockerfile`
   - `requirements.txt`
   - `README.md`
4. The Space will build automatically and be available at `https://YOUR-USERNAME-YOUR-SPACE-NAME.hf.space`

> **Note:** The first request may be slow as the model (~4.7 GB) is downloaded from Hugging Face Hub on startup.
> The `llama-cpp-python` library is now installed using pre-compiled wheels for faster setup.
> Consider upgrading to a paid hardware tier for faster inference.