Skip to content

Latest commit

 

History

History
23 lines (19 loc) · 1.11 KB

README.md

File metadata and controls

23 lines (19 loc) · 1.11 KB
Raw

Data agent with RAG

Sieve through structured and unstructured Data. Respond to Query. AI This repository is an exercise walkthrough, a proof of concept of information sieveing with prompts. Data Agent with Python coding. LLM (leverages llama_index), Pylance, Pandas. Use cases : Data ingestion Q&A, Augmented Chatbots, Knowledge agents, analytics.

Setup

  1. Vs code/Terminal Command Prompt, To create the ai environment: For win: type: python -m venv ai

  2. To To activate the ai environment: -For win : type in command prompt: .\ai\Scripts\activate.bat ; Deactivate : replace activate -> deactivate -For mac : type: source ai/bin/activate

  3. type in command prompt : pip3 install llama-index pypdf python-dotenv pandas (install python packages and dependencies)

  4. create .env file with OPENAI_API_KEY , get API key and insert

Create Agent

  1. Gather data. Source type, csv, pdf, notes.

  2. Write the main.py file -Write imports.

  3. Ctrl+Shift+P : Select Python interpreter --> choose Global, then run.

  4. To activate ai environment, In command prompt, type : .\ai\Scripts\activate

  5. Create note_engine.py