NLQ Lang Graph POC

A proof-of-concept application for natural language querying using language models and graph-based workflows. This project demonstrates how to process natural language queries, interact with knowledge bases, and provide results through a Streamlit web interface.

Features

• Natural language query processing
• Integration with language models (e.g., OpenAI)
• Modular agent and tool architecture
• Streamlit-based user interface
• Easily extensible for new data sources and tools

Folder Structure

nlq_lang_graph_poc_docker/
├── lang_graph_poc/         # Main application code
├── streamlit_apps/         # Streamlit UI apps
├── tests/                  # Unit and integration tests
├── requirements/           # Dependency files
├── requirements.txt        # Main requirements file
├── Dockerfile              # Docker build file
├── docker-compose.yml      # (Optional) Docker Compose file
├── README.md               # Project documentation
└── ...

Prerequisites

• Python 3.10+
• pip
• (Optional) Docker and Docker Compose

---

Running Locally (Without Docker)

1. Clone the repository:

   git clone <your-repo-url>
   cd nlq_lang_graph_poc_docker

2. Create and activate a virtual environment:

   python3 -m venv venv
   source venv/bin/activate

3. Install dependencies:

   pip install --upgrade pip
   pip install -r requirements.txt

4. Set up environment variables:

   • Create a .env file in the project root and add any required API keys or settings, for example:

     OPENAI_API_KEY=your-key-here
     

5. Run the Streamlit app:

   streamlit run streamlit_apps/streamlit_app_0.py

   • Visit http://localhost:8501 in your browser.

---

Running with Docker

1. Build the Docker image:

   docker build -t nlq-lang-graph-poc .

2. Run the container:

   docker run --env-file .env -p 8501:8501 nlq-lang-graph-poc

   • The app will be available at http://localhost:8501.

3. (Optional) Using Docker Compose:

   • If you have a docker-compose.yml:

     docker-compose up --build

---

Running Tests

pytest

After Successful Initialization,we can see home screen as below

Home page:

Test Query with Result:

1. Test with Steps upto Generate & Validate SQL

2. Test With All Steps, Generate SQL >> Verify SQL >> Clarification >> Exectute >> Process >> Summarisation