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| title: WaterScopeAI Search | |
| emoji: 🔎 | |
| colorFrom: blue | |
| colorTo: green | |
| sdk: docker | |
| app_port: 7860 | |
| pinned: false | |
| # WaterScopeAI Search System | |
| CPU-based hybrid publication search, retrieval, and MCP backend for WaterScope-AI. | |
| This Space is intentionally separated from the GPU model Space (`EnvironmentalAI/WaterScopeAI`). Large corpus assets and the canonical prebuilt Qdrant index will be connected from a Hugging Face Dataset repository in the next deployment phase. | |
| ## Initial deployment test | |
| - `/` — service information | |
| - `/api/health` — backend/resource health | |
| - `/api/search?q=activated+sludge&top_k=10` — publication search | |
| The first package includes `papers.csv` and the paper manifest so BM25 search can be tested before the prebuilt Qdrant index and document assets are connected. `METADATA_AUTO_REBUILD=0` prevents the CPU Space from rebuilding the vector index automatically; if no prebuilt Qdrant index is present, search falls back to BM25. | |