Build Your Own Jarvis — RAG Assistant (Cookbook)

This mini-cookbook spins up a personal AI assistant that:

• runs a self-hosted LLM via Ollama (default: llama3),
• ingests your local ./data files into a vector database (Chroma by default, Pinecone optional),
• answers questions using retrieval‑augmented generation (RAG),
• exposes a simple Streamlit chat UI.

Designed to be finished in ~40 mins for an assignment/demo.

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0) Prereqs

• Python 3.10+
• Ollama installed & running → https://ollama.com (then run ollama pull llama3)
• (Optional) Pinecone account + API key if you prefer cloud vector DB.

1) Setup

python -m venv .venv && source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install -r requirements.txt

2) Add your knowledge

Drop PDFs/TXTs/MD/DOCs into ./data. (You can add more later.)

3) Configure (optional)

Create .env in the project root if needed:

# Use Pinecone instead of local Chroma (True/False). Defaults to False.
USE_PINECONE=False

# When USE_PINECONE=True
PINECONE_API_KEY=YOUR_KEY
PINECONE_ENV=YOUR_ENV   # e.g., us-east-1-aws
PINECONE_INDEX_NAME=jarvis-index

# LLM model to use with Ollama
OLLAMA_MODEL=llama3
SYSTEM_PROMPT=You are Jarvis, a concise, helpful assistant for my files. Cite file names when relevant.

4) Ingest

python ingest.py

This reads ./data, builds embeddings, and populates Chroma or Pinecone.

5) Run the chat UI

streamlit run app.py

Open the local URL and start chatting.

6) Notes

• By default we use sentence-transformers/all-MiniLM-L6-v2 (dim=384) for embeddings → fast and Pinecone-friendly.
• To switch LLMs, change OLLAMA_MODEL in .env and run: ollama pull <model>.
• Everything is kept small and clear for an assignment. Extend as you like: tools, agents, structured output, file upload, etc.

7) Project tree

jarvis_cookbook/
  ├─ app.py              # Streamlit chat UI
  ├─ chain.py            # RAG chain (LangChain)
  ├─ ingest.py           # Parse -> chunk -> embed -> upsert
  ├─ vectordb.py         # Chroma (local) or Pinecone (cloud)
  ├─ requirements.txt
  ├─ README.md
  └─ data/