PolyCity Stay 🏙️

Kowloon 🇭🇰 long-stay hotel scout for master’s students — because fighting HK rental listings at 2am is not the vibe. Pick CityU or PolyU, dial in your MTR / shower / desk / budget non-negotiables, and let a small team of agents dig through seed data (plus optional page fetch) to spit out a ranked, emoji-friendly report. Typhoon day? Near the MTR. External monitor? They’ll side-eye the desk notes. Milk tea not included 🧋

Under the hood it’s a Python app: OpenAI Agents SDK + Ollama (default qwen2.5:7b) + SQLite so runs don’t vanish into the void. Report language: English or 简体中文 — hotel names show English · 简体 for easy copy-paste to maps and chats.

UI: Streamlit form — campus, report language, MTR / shower / desk / budget, and optional notes.

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Architecture

• Pattern: Hierarchical / sequential pipeline — Retrieval → Scoring → Verification → Buddy (student-facing Markdown).
• Agents: PolyCityRetrieval, PolyCityScoring, PolyCityChecker, PolyCityBuddy.
• Tools: Seed JSON per campus + optional fetch_webpage_text for extra context.
• Memory: polycity_memory.db stores each run and stage outputs.

More detail: ARCHITECTURE.md. Demo screenshots live in demo/.

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Setup

1. Install Ollama and pull the model:

   ollama pull qwen2.5:7b

2. From this folder:

   cp .env.example .env
   uv sync
   uv run streamlit run app.py

3. Open the local URL Streamlit prints (usually http://localhost:8501).

Choose report language (English / 简体中文) in the form; the Buddy agent writes the final Markdown in that language, and scoring JSON blurbs follow it in nerd mode.

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Notes

• Seed hotels in data/seed_hotels.json are demo / illustrative — always confirm with the hotel before paying. Each row has name_en, name_zh (简体中文 hotel names for reference), and name (English · 中文) for display.
• Live fetch_webpage_text may fail on bot protection; the pipeline still works from seed data.

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Theme

Custom Streamlit theme (indigo primary) lives in .streamlit/config.toml — run streamlit run app.py from this directory so it loads.