| # Contributing and Usage Guide | |
| This project implements a SQL-based feedback analysis system using LLM-generated queries. | |
| Goals: | |
| - Make the API easy to run locally and deploy to Runpod or any container platform. | |
| - Keep sensitive keys out of the repo; use environment variables. | |
| Quick workflow: | |
| 1. Create branch: `git checkout -b feat/improve-intents` | |
| 2. Make changes and run tests locally. | |
| 3. Commit and push: `git add . && git commit -m "feat: ..." && git push --set-upstream origin feat/improve-intents` | |
| 4. Open a Pull Request and request review. | |
| Building the image: | |
| 1. Update `Dockerfile` if you need to pre-bake models. | |
| 2. Build and tag: | |
| ```bash | |
| docker build -t youruser/feedback-analysis:v1 . | |
| docker push youruser/feedback-analysis:v1 | |
| ``` | |
| Run on Runpod: | |
| - See `README.md` section "Run on Runpod - Full guide" for step-by-step. | |
| Tests: | |
| - No unit tests included yet. Prefer adding `pytest` tests for `app/analysis.py` and the API layer. | |
| Contact: | |
| - For major changes, create an issue first describing the design and performance considerations. | |