https://github.com/akarshankapoor7/chatbot-using-langgraph

A LangGraph-powered chatbot project with Streamlit frontends, supporting both in-memory and SQLite-based conversation persistence, real-time streaming responses, and multi-session chat management.
https://github.com/akarshankapoor7/chatbot-using-langgraph

chatbot groq-api langgraph persistence streamlit-webapp

Last synced: 9 months ago
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A LangGraph-powered chatbot project with Streamlit frontends, supporting both in-memory and SQLite-based conversation persistence, real-time streaming responses, and multi-session chat management.

• Host: GitHub
• URL: https://github.com/akarshankapoor7/chatbot-using-langgraph
• Owner: akarshankapoor7
• License: mit
• Created: 2025-09-15T19:57:13.000Z (10 months ago)
• Default Branch: main
• Last Pushed: 2025-09-15T20:23:06.000Z (10 months ago)
• Last Synced: 2025-09-15T21:31:48.858Z (10 months ago)
• Topics: chatbot, groq-api, langgraph, persistence, streamlit-webapp
• Language: Jupyter Notebook
• Homepage:
• Size: 222 KB
• Stars: 1
• Watchers: 0
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

          
# ChatBot-using-LangGraph

🤖 LangGraph Chatbot with Streamlit UI

An interactive **Generative AI chatbot** built using **LangGraph** and **Streamlit**, featuring persistent chat storage, multi-session handling, and a clean ChatGPT-like sidebar for navigating previous conversations.

---

## 🚀 Features

- **Multi-session chat**: Start a **new chat** anytime and revisit old ones (sessions displayed as `session-1`, `session-2`, etc.).

- **Persistent storage**: Chats are saved using **SQLite** (`SqliteSaver`) so history is retained even after restarting.

- **Sidebar navigation**: A non-collapsible **sidebar on the left**, showing all active sessions with the latest user message or session number.

- **Simple & clean UI**: Chat interface similar to ChatGPT with smooth session switching.

---

## 🛠️ Tech Stack

- [LangGraph](https://github.com/langchain-ai/langgraph) – for conversation flow and state management.

- [LangGraph Checkpoint SQLite](https://pypi.org/project/langgraph-checkpoint-sqlite/) – for saving chat history.

- [Streamlit](https://streamlit.io) – for frontend UI.

- [SQLite3](https://www.sqlite.org/index.html) – for lightweight local storage.

---

📂 Project Structure

.

├── .env                               # Store your API keys here

├── requirements.txt                   # Python dependencies

├── 01_ChatBot_with_memory_checkpoint.ipynb   # Jupyter Notebook for experimentation

│

├── ChatBot_backend.py                 # Backend (memory only) -->

├── Streamlit_ChatBot_frontend.py      # Streamlit frontend (memory only) 

├── Streamlit_Chatbot_frontend_UI_1.png   # Screenshot for memory-only chatbot

│

├── ChatBot_database_backend.py        # Backend (with SQLite database) -->

├── Streamlit_frontend_database.py     # Streamlit frontend (with SQLite DB) 

├── Streamlit_frontend_database_UI_2.png   # Screenshot for DB chatbot 

│

├── chatbot_memory.db                  # SQLite database (created at runtime)

│

├── LICENSE

└── README.md

2️⃣ Create virtual environment

python -m venv lgraph

source lgraph/bin/activate   # Mac/Linux

lgraph\Scripts\activate      # Windows

3️⃣ Install dependencies

pip install -r requirements.txt