# LangGraph Chatbot

A conversational AI chatbot built with LangGraph, Streamlit, and Google Gemini.

## Features
- Multi-tool support (Calculator, Stock prices, Web search)
- Conversation history with thread management
- Persistent storage with SQLite
- Real-time streaming responses

## Setup

1. Clone the repository
2. Install dependencies: `pip install -r requirements.txt`
3. Create `.env` file with your `GOOGLE_API_KEY`
4. Run: `streamlit run app.py`

## Deployment
See deployment guide for instructions on deploying to Streamlit Cloud, Render, or Railway.

---

🚀 Local Installation & Running

Step 1: Create Project Directory

mkdir langgraph-chatbot
cd langgraph-chatbot

Step 2: Create All Files

Create all the files listed above with their respective content.

Step 3: Install Dependencies

# Create virtual environment (recommended)
python -m venv venv

# Activate virtual environment
# On Windows:
venv\Scripts\activate
# On Mac/Linux:
source venv/bin/activate

# Install packages
pip install -r requirements.txt

Step 4: Configure Environment

1. Get a Google API key from: https://makersuite.google.com/app/apikey
2. Create .env file and add:

   GOOGLE_API_KEY=your_actual_api_key_here
   

Step 5: Run Locally

streamlit run app.py

The app will open at http://localhost:8501

---

🌐 Deployment Options

Option 1: Streamlit Cloud (FREE & EASIEST)

Steps:

1. Push to GitHub

   git init
   git add .
   git commit -m "Initial commit"
   git remote add origin https://github.com/yourusername/langgraph-chatbot.git
   git push -u origin main

2. Deploy on Streamlit Cloud

   • Go to https://share.streamlit.io/
   • Click "New app"
   • Connect your GitHub repository
   • Select the repository and branch
   • Set main file path: app.py
   • Click "Advanced settings" → Add secrets:

     GOOGLE_API_KEY = "your_api_key_here"
     

   • Click "Deploy"

3. Your app will be live at: https://yourusername-langgraph-chatbot.streamlit.app

---

Option 2: Render (FREE)

Steps:

1. Push to GitHub (same as above)

2. Deploy on Render

   • Go to https://render.com/
   • Click "New +" → "Web Service"
   • Connect your GitHub repository
   • Configure:
     • Name: langgraph-chatbot
     • Environment: Python 3
     • Build Command: pip install -r requirements.txt
     • Start Command: streamlit run app.py --server.port=$PORT --server.address=0.0.0.0
   • Add Environment Variable:
     • Key: GOOGLE_API_KEY
     • Value: your_api_key
   • Click "Create Web Service"

3. Your app will be live at: https://langgraph-chatbot.onrender.com

---

Option 3: Railway (FREE)

Steps:

1. Push to GitHub (same as above)

2. Deploy on Railway

   • Go to https://railway.app/
   • Click "New Project" → "Deploy from GitHub repo"
   • Select your repository
   • Railway will auto-detect it's a Python app
   • Add Environment Variable:
     • Key: GOOGLE_API_KEY
     • Value: your_api_key
   • Click "Deploy"

3. Your app will be live at: Railway will provide a URL

---

Option 4: Hugging Face Spaces (FREE)

Steps:

1. Go to https://huggingface.co/spaces
2. Click "Create new Space"
3. Choose "Streamlit" as SDK
4. Upload all your files
5. Add your GOOGLE_API_KEY in Settings → Repository secrets
6. Your app will be live!

---

🔧 Troubleshooting

Common Issues:

1. "No module named 'streamlit'"

   • Solution: pip install -r requirements.txt

2. "GOOGLE_API_KEY not found"

   • Solution: Create .env file with your API key

3. Database locked error

   • Solution: Delete chatbot.db and restart

4. Port already in use

   • Solution: streamlit run app.py --server.port=8502

---

📊 Testing Your Deployment

After deployment, test these features:

1. ✅ Send a message
2. ✅ Ask for a calculation: "What is 25 * 4?"
3. ✅ Ask for stock price: "What's the price of AAPL?"
4. ✅ Ask to search web: "Latest news about AI"
5. ✅ Create a new chat
6. ✅ Switch between conversations

---

🎉 Success!

Your chatbot is now deployed and accessible worldwide! Share the URL with anyone.

Need help? Check the respective platform's documentation:

• Streamlit Cloud: https://docs.streamlit.io/streamlit-community-cloud
• Render: https://render.com/docs
• Railway: https://docs.railway.app/

Happy chatting! 🚀