Simple text-RAG question and answering script using Langchain, Ollama, and ChromaDB.

To run this code, you need to have Ollama installed and running in the background. You also need to have a text file named "text.txt" with the text you want to use as a knowledge base.

1. Install Ollama: https://ollama.com/
2. Keep Ollama running in the background
3. Pull desired model from Ollama. In the terminal:

   $ ollama pull <model_name>
   

4. Create a virtual environment and activate it:

   $ python -m venv .venv
   

   $ source .venv/bin/activate
   

5. Install the necessary packages:

   $ pip install --upgrade pip
   

   $ pip install langchain langchain-community langchain-huggingface sentence_transformers chromadb unstructured
   

6. Create a text file named "text.txt" with the text you want to use as a knowledge base. In this example, the text.txt file contains the 3 volumes from "The Lord of the Rings" by J.R.R. Tolkien.
7. Run the code below:

   python3 main.py
   

Stack: Python, LangChain, Ollama, ChromaDB

• Based on the article Using Langchain and Open Source Vector DB Chroma for Semantic Search with OpenAI's LLM from Pradip Nichite.