https://github.com/0xzee/streamlit_txt2sql_agent
Streamlit "Text-to-SQL" Agentic Chatbot App powered by Lang-Graph
https://github.com/0xzee/streamlit_txt2sql_agent
groq langchain langgraph llama3-2 memory-management mixtral-8x7b-instruct session-management sessionstorage sql sqlite3 streamlit
Last synced: over 1 year ago
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Streamlit "Text-to-SQL" Agentic Chatbot App powered by Lang-Graph
- Host: GitHub
- URL: https://github.com/0xzee/streamlit_txt2sql_agent
- Owner: 0xZee
- Created: 2024-12-30T13:16:13.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-11T16:38:56.000Z (over 1 year ago)
- Last Synced: 2025-02-11T17:42:42.969Z (over 1 year ago)
- Topics: groq, langchain, langgraph, llama3-2, memory-management, mixtral-8x7b-instruct, session-management, sessionstorage, sql, sqlite3, streamlit
- Language: Python
- Homepage:
- Size: 321 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# 🤖 Chat with Databases
## 🤖 `Text to SQL` Agentic langgraph chatbot
Streamlit `Text to SQL` Agentic ChatBot app built with `langgraph workflow` :
- Workflow : `LangGraph` Workflow with text-to-query, sqlite, and memory & session management
- Inference & LLM : `Groq Inference`, Model : `llama3.2 3b`
## Interface :
# Steps :
- Put `GROQ_API_KEY` in `.streamlit/secrets.toml`
- Put your csv file in `/data` folder
- Use script `/utils/csv_to_sqlite.py` to create `sqlite` databases
- Run the App :
```python
pip install -r requirements.txt
streamlit run main.py
```
# 📊 LangGraph WorkFlow
LangGraph Work-Flow
# ⌨ APP DOCKERFILE :
To build the App from Dockerfile
```bash
docker build -t chatbot-app .
docker run -p 8501:8501 \
-e GROQ_API_KEY=your_groq_api_key \
chatbot-app
```