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---
title: LLM Error Classifier API
emoji: 🚀
colorFrom: blue
colorTo: purple
sdk: docker
sdk_version: 20.10.24
app_file: main.py
pinned: false
license: mit
---
# LLM Error Classifier API
FastAPI backend serving the fine-tuned Llama-3.2-3B model for tool-use error classification.
## API Endpoints
- `POST /api/classify` - Classify a tool call
- `GET /api/examples` - Get example inputs
- `GET /health` - Health check
## Model
Model: `daoqm123/llm-error-classifier`
## Usage
The API will automatically load the model from HuggingFace Hub on startup.
## Deploying to Hugging Face Spaces
1. **Create a Space**
- Go to https://huggingface.co/spaces/new and choose `Docker` as the SDK (this repo already contains a Dockerfile).
- Give the space a name such as `llm-error-classifier-api` and select the desired hardware (CPU is fine unless you need GPU acceleration).
- After the space is created, copy the Git commands shown in the “Files” tab; you will push the contents of this `api/` folder there.
2. **Authenticate locally**
```bash
pip install -U "huggingface_hub[cli]"
huggingface-cli login
```
Use a write token from https://huggingface.co/settings/tokens.
3. **Push the backend code**
```bash
cd /work/cssema416/202610/12/llm-frontend-for-quang\ \(1\)/api
rm -rf .git
git init
git remote add origin https://huggingface.co/spaces/<username>/<space-name>
git add .
git commit -m "Deploy FastAPI backend"
git push origin main
```
Replace `<username>` and `<space-name>` with your actual values. Hugging Face will build the Docker image automatically; the server becomes available at `https://<space-name>.<username>.hf.space`.
4. **Configure runtime behavior (optional)**
- Set a custom `MODEL_PATH` or other environment variables from the “Settings → Repository secrets” tab inside the Space.
- If you need GPU, request the proper hardware tier in the hardware selector.
5. **Wire up the Vercel frontend**
- In `frontend/lib/api.ts` the app reads `process.env.NEXT_PUBLIC_API_URL`.
- On Vercel, set `NEXT_PUBLIC_API_URL=https://<space-name>.<username>.hf.space` (no trailing slash) and redeploy the frontend so calls go directly to the Space backend.
6. **Verify**
- Open the Space URL to confirm the FastAPI app is live (you should see the default 404 JSON from FastAPI or add a `/health` suffix).
- Visit your Vercel deployment and ensure inference requests succeed using the new backend endpoint.
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