Init

.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+*.so
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+
+# Virtual Environment
+venv/
+env/
+ENV/
+.venv/
+
+# IDE
+.idea/
+.vscode/
+*.swp
+*.swo
+
+# Gradio
+flagged/
+
+# Environment variables
+.env
+
+# Database
+*.db
+
+# Misc
+.DS_Store 
+.gradio/
+lib/

Readme.md

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+---
+title: Real Estate Projects
+emoji: 🏠
+colorFrom: blue
+colorTo: green
+sdk: gradio
+app_file: app.py
+pinned: false
+---
+
+# Real Estate Projects Scraper and Analyzer
+
+A Gradio interface that scrapes and analyzes real estate projects using LangChain and SQLite.
+
+## Features
+- Stores data in SQLite using Peewee ORM
+- Chat interface to query project data
+
+## Setup
+
+1. Create and activate a virtual environment:
+    ```sh
+    uv venv --python 3.12
+    ```
+
+2. Compile the requirements file:
+    ```sh
+    uv pip compile requirements.in --generate-hashes -o requirements.txt
+    ```
+
+3. Install the dependencies:
+    ```sh
+    uv pip install -r requirements.txt
+    ```
+
+4. Run the application:
+    ```sh
+    uv run app.py
+    ```
+
+5. Upgrade all packages to their latest versions:
+    ```sh
+    uv pip install --upgrade -r requirements.txt
+    ```

app.py

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+from langchain import hub
+from langchain.agents import AgentExecutor, create_openai_tools_agent
+from langchain_openai import ChatOpenAI
+from langchain_community.utilities import SQLDatabase
+from langchain_community.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
+import gradio as gr
+from dotenv import load_dotenv
+from langchain.schema import HumanMessage, AIMessage
+import os.path
+
+# Load environment variables
+load_dotenv()
+
+# Check if database exists
+if not os.path.exists('estate.db'):
+    raise FileNotFoundError(
+        "Database file 'estate.db' not found. Please run 'uv run init_db.py' first."
+    )
+
+# Initialize model and database
+model = ChatOpenAI(model="gpt-4", streaming=True)
+db = SQLDatabase.from_uri("sqlite:///estate.db")
+
+# Set up SQL toolkit and tools
+toolkit = SQLDatabaseToolkit(db=db, llm=model)
+tools = toolkit.get_tools()
+
+# Get the OpenAI tools agent prompt
+prompt = hub.pull("hwchase17/openai-tools-agent")
+
+# Create the agent with OpenAI tools format
+agent = create_openai_tools_agent(
+    llm=model,
+    tools=tools,
+    prompt=prompt
+)
+
+# Create agent executor
+agent_executor = AgentExecutor(
+    agent=agent,
+    tools=tools,
+    verbose=True
+)
+
+def chat_with_sql(message, history):
+    try:
+      history_langchain_format = []
+      for msg in history:
+          if msg['role'] == "user":
+              history_langchain_format.append(HumanMessage(content=msg['content']))
+          elif msg['role'] == "assistant":
+              history_langchain_format.append(AIMessage(content=msg['content']))
+      history_langchain_format.append(HumanMessage(content=message))
+      response = agent_executor.invoke({"input": message, "history": history_langchain_format})
+      for i in range(len(response["output"])):
+          yield response["output"][:i+1]
+    except Exception as e:
+        yield f"Error: {str(e)}"
+
+# Create the Gradio interface
+demo = gr.ChatInterface(
+    fn=chat_with_sql,
+    title="SQL Chat Assistant",
+    description="Ask questions about your SQLite database!",
+    examples=[
+        "What is project with the lowest deposit?",
+    ],
+    type="messages"
+)
+
+if __name__ == "__main__":
+    demo.launch(share=False, debug=True) 

requirements.in

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+gradio
+langchain
+langchain-community
+langchain-openai
+python-dotenv
+beautifulsoup4
+requests
+peewee
+browser_use
+openai