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| title: StockMatch | |
| emoji: 📈 | |
| colorFrom: indigo | |
| colorTo: yellow | |
| sdk: gradio | |
| sdk_version: 5.49.1 | |
| python_version: '3.12' | |
| app_file: app.py | |
| pinned: false | |
| license: mit | |
| # StockMatch AI | |
| Matching everyday savers to stocks that help protect against inflation. | |
| Answer six questions, or click one of three preset investor profiles, and the app | |
| retrieves matching stocks and writes a personalised explanation. | |
| **How it works** | |
| 1. **Dataset** — 12,500 synthetic stock records generated with `Qwen2.5-1.5B-Instruct`, | |
| hosted at [Kogann/stockmatch-synthetic](https://huggingface.co/datasets/Kogann/stockmatch-synthetic) | |
| 2. **Retrieval** — numeric features are verbalised into text, embedded with | |
| `BAAI/bge-small-en-v1.5`, and searched with FAISS | |
| 3. **Filtering** — risk, budget, sector and market are enforced as hard constraints; | |
| semantic similarity ranks what remains | |
| 4. **Generation** — `SmolLM2-1.7B-Instruct` writes one explanatory sentence per stock | |
| All figures shown are printed directly from the dataset, so the language model | |
| cannot fabricate them. | |
| ⚠️ All data is synthetic and generated for an educational project. This is not | |
| investment advice. |