92 lines
2.4 KiB
Markdown
92 lines
2.4 KiB
Markdown
---
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name: local-places
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description: "通过Google Places API代理在本地搜索地点（餐厅、咖啡馆等）。"
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homepage: https://github.com/Hyaxia/local_places
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metadata: {"clawdbot":{"emoji":"📍","requires":{"bins":["uv"],"env":["GOOGLE_PLACES_API_KEY"]},"primaryEnv":"GOOGLE_PLACES_API_KEY"}}
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---
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# 📍 Local Places
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*Find places, Go fast*
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Search for nearby places using a local Google Places API proxy. Two-step flow: resolve location first, then search.
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## Setup
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```bash
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cd {baseDir}
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echo "GOOGLE_PLACES_API_KEY=your-key" > .env
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uv venv && uv pip install -e ".[dev]"
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uv run --env-file .env uvicorn local_places.main:app --host 127.0.0.1 --port 8000
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```
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Requires `GOOGLE_PLACES_API_KEY` in `.env` or environment.
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## Quick Start
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1. **Check server:** `curl http://127.0.0.1:8000/ping`
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2. **Resolve location:**
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```bash
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curl -X POST http://127.0.0.1:8000/locations/resolve \
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-H "Content-Type: application/json" \
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-d '{"location_text": "Soho, London", "limit": 5}'
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```
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3. **Search places:**
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```bash
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curl -X POST http://127.0.0.1:8000/places/search \
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-H "Content-Type: application/json" \
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-d '{
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"query": "coffee shop",
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"location_bias": {"lat": 51.5137, "lng": -0.1366, "radius_m": 1000},
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"filters": {"open_now": true, "min_rating": 4.0},
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"limit": 10
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}'
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```
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4. **Get details:**
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```bash
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curl http://127.0.0.1:8000/places/{place_id}
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```
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## Conversation Flow
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1. If user says "near me" or gives vague location → resolve it first
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2. If multiple results → show numbered list, ask user to pick
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3. Ask for preferences: type, open now, rating, price level
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4. Search with `location_bias` from chosen location
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5. Present results with name, rating, address, open status
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6. Offer to fetch details or refine search
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## Filter Constraints
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- `filters.types`: exactly ONE type (e.g., "restaurant", "cafe", "gym")
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- `filters.price_levels`: integers 0-4 (0=free, 4=very expensive)
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- `filters.min_rating`: 0-5 in 0.5 increments
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- `filters.open_now`: boolean
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- `limit`: 1-20 for search, 1-10 for resolve
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- `location_bias.radius_m`: must be > 0
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## Response Format
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```json
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{
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"results": [
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{
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"place_id": "ChIJ...",
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"name": "Coffee Shop",
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"address": "123 Main St",
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"location": {"lat": 51.5, "lng": -0.1},
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"rating": 4.6,
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"price_level": 2,
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"types": ["cafe", "food"],
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"open_now": true
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}
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],
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"next_page_token": "..."
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}
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```
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Use `next_page_token` as `page_token` in next request for more results.
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