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---
title: TTS
emoji: πŸ€–
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` β€” 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.