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Category: Data & AnalyticsAPI key required

使用RAG支持的市场分析研究房地产属性

引导代理通过房产搜索、买家/租客偏好捕捉，并从结构化列表数据中生成有证据支持的候选名单备注。

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使用RAG支持的市场分析研究房地产属性

Guide an agent through property search, buyer/renter preference capture, and evidence-backed shortlist notes from structured listing data.

Prerequisites

Python 3.11+, Streamlit, LangChain, OpenAI GPT or Llama model access, Pandas, FastEmbed, DocArrayInMemorySearch or ChromaDB, Poetry

Installation

Use the upstream install or setup path that matches your environment:

  • git clone https://github.com/1991513ccie-png/skills
  • docker compose -f deploy/compose/docker-compose.yml up --build
  • uv pip install -e ".[dev]" && python -m uvicorn api.main:app --reload --port 8000

Requirements and caveats from upstream:

  • Python
  • Note: The demo uses simulated AI responses for instant exploration. Production deployment requires API keys.
  • | Lines of Code | 60,000+ (27K Python + 34K TypeScript) |

Basic usage or getting-started notes:

  • Quick Start

  • 🚀 Quick Start

  • cp deploy/compose/.env.example deploy/compose/.env

  • Source: https://github.com/1991513ccie-png/skills

  • Extracted from upstream docs: https://raw.githubusercontent.com/AleksNeStu/ai-real-estate-assistant/HEAD/README.md

Documentation

  • https://github.com/1991513ccie-png/skills