LangChain-Streamlit-RAG

This project provides a FastAPI interface to serve Ollama models. It allows other applications to send queries to the model and receive responses.

Features

• LangChain: Manages and processes language models.
• Ollama: The core language model used for generating responses.
• RAG: RAG for pdf.

Installation

1. Clone the repository:

   git clone https://github.com/ersinaksar/LangChain-Streamlit-RAG.git
   cd serve-ollama-models

2. Create a virtual environment and activate it:

   python3 -m venv .venv
   source venv/bin/activate  # On Windows use `venv\Scripts\activate`

3. Install the dependencies:

   pip install -r requirements.txt

Usage

1. Start the streamlit application:

   streamlit run main.py 

License

This project is licensed under the MIT License.