norasalem88/rag_assistant_devops

DevOps RAG Assistant

Upload your DevOps PDFs and ask questions. Powered by Hugging Face.

Features

• —Local Execution: Uses ChromaDB for vector storage and Ollama (qwen2.5:7b) for generation.
• —English Only: Focused specifically on DevOps documentation in English.
• —Minimal UI: Streamlit interface for uploading PDFs and asking questions.

Setup

1. 1.Ensure Ollama is installed and the qwen2.5:7b model is pulled:

   ollama pull qwen2.5:7b

1. 1.Setup Python environment:

   python -m venv venv
   # Windows
   .\venv\Scripts\activate
   # Linux/Mac
   source venv/bin/activate

1. 1.Install dependencies:

   pip install -r requirements.txt

Running the Application

To run the Streamlit UI:

streamlit run app.py

Then open your browser to http://localhost:8501. You can upload DevOps PDFs (like Kubernetes & Docker documentation) via the sidebar.

Project Structure

• —data/: Contains uploaded PDF documents.
• —src/:
• —ingestion.py: Handles loading PDFs, chunking, and embedding creation.
• —retrieval.py: Setup for ChromaDB retriever.
• —generation.py: LangChain RAG pipeline connecting ChromaDB and Ollama.
• —utils.py: Common helper functions (logging, embeddings).
• —vectorstore/: Persisted ChromaDB embeddings.
• —app.py: Streamlit frontend.