Skip to content

amitabhanmolpain/Real-Estate-Multi-Agent

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

Real Estate Multi-Agent System 🏡

A multi-agent real estate platform with specialized agents for buyers, sellers, price estimation, and neighborhood analysis.

Project Structure

Real_Estate_Agent/
├── .env
├── requirements.txt
├── streamlit.py
├── agents/
│   ├── buyer_agent/
│   │   ├── __main__.py
│   │   ├── agent.py
│   │   └── task_manager.py
│   ├── seller_agent/
│   │   ├── __main__.py
│   │   ├── agent.py
│   │   └── task_manager.py
│   ├── price_agent/
│   │   ├── __main__.py
│   │   ├── agent.py
│   │   └── task_manager.py
│   ├── neighborhood_agent/
│   │   ├── __main__.py
│   │   ├── agent.py
│   │   └── task_manager.py
│   └── host_agent/
│       ├── __main__.py
│       ├── agent.py
│       └── task_manager.py
├── common/
│   ├── a2a_client.py
│   └── a2a_server.py
└── shared/
    └── schema.py

Required Dependencies

Install all packages from requirements.txt:

pip install -r requirements.txt

Package List:

  • google-adk
  • litellm
  • fastapi
  • uvicorn
  • httpx
  • pydantic
  • openai
  • streamlit
  • requests

Environment Configuration

Create .env file in project root:

GOOGLE_GENAI_USE_VERTEXAI=FALSE
GOOGLE_API_KEY=your_api_key_here

Running in VS Code

Method 1: Using VS Code Terminals

  1. Open project in VS Code
  2. Open 5 integrated terminals (Terminal > New Terminal)
  3. Run each FastAPI agent and Streamlit in separate terminals:
# Terminal 1 - Buyer Agent FastAPI (Port 8001)
python -m agents.buyer_agent

# Terminal 2 - Seller Agent FastAPI (Port 8002)
python -m agents.seller_agent

# Terminal 3 - Price Agent FastAPI (Port 8003)
python -m agents.price_agent

# Terminal 4 - Neighborhood Agent FastAPI (Port 8004)
python -m agents.neighborhood_agent

# Terminal 5 - Streamlit Web Interface (Port 8501)
streamlit run streamlit.py

Port Configuration:

  • Buyer Agent: http://localhost:8001
  • Seller Agent: http://localhost:8002
  • Price Agent: http://localhost:8003
  • Neighborhood Agent: http://localhost:8004
  • Streamlit App: http://localhost:8501

Method 2: Using VS Code Tasks

Create .vscode/tasks.json:

{
    "version": "2.0.0",
    "tasks": [
        {
            "label": "Start All Agents",
            "type": "shell",
            "command": "python",
            "args": ["-m", "agents.buyer_agent"],
            "group": "build",
            "presentation": {
                "echo": true,
                "reveal": "always",
                "panel": "new"
            }
        }
    ]
}

Access Application

  • Open browser to http://localhost:8501
  • Use VS Code's built-in browser: Ctrl+Shift+P → "Simple Browser"

About

A smart Real Estate AI Agent Build using ADK

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages