study_agent_history.md

● API Keys

  Yes, you need both:
  - Anthropic API key -- powers the LLM (Claude) for question generation, answering, and evaluation
  - OpenAI API key -- powers the embeddings only (text-embedding-3-small for ChromaDB vectors)

  If you want to avoid needing OpenAI, I can switch embeddings to a free local model (like sentence-transformers) instead. Your call.

  My understanding of what you want

  Here's the step-by-step plan:

  Step 1: Run tests and make sure everything works
  - Run pytest to validate the existing code

  Step 2: Build the Gradio UI
  - Add a app.py at project root with a Gradio interface
  - Upload a document, set mastery threshold, click "Start Study Session"
  - Shows live progress (questions, scores) and final session report
  - Compatible with Hugging Face Spaces deployment

  Step 3: Write README.md
  - Portfolio framing (MOSAIC conceptual link as specified in your CLAUDE.md)
  - Architecture diagram, tech stack, setup instructions, usage
  - Clear and professional for a public GitHub repo

  Step 4: Give you the gh CLI commands
  - gh repo create command for a public repo
  - You run it yourself, push the code

  Step 5: Hugging Face deployment prep
  - Add a requirements.txt for HF Spaces
  - Add any HF-specific config if needed

  One question before I start

  Do you want me to switch embeddings to a free local model (no OpenAI key needed, simpler for HF deployment) or keep OpenAI embeddings?
  
  
  
  What's done

  - app.py -- Gradio UI (upload doc, set threshold, view live progress + report)
  - README.md -- professional, portfolio-ready, MOSAIC framing included
  - .gitignore -- keeps .env, __pycache__, .venv out of the repo
  - All 8 tests passing

  Your next steps

  1. Create the GitHub repo (run from the project directory):

  cd "D:\Halima's Data\more\LLM_Udemy\my_3_agentic_projects\study_agent"
  git init
  git add -A
  git commit -m "Initial commit: Adaptive Study Agent with LangGraph"
  gh repo create adaptive-study-agent --public --source . --push

  2. For Hugging Face Spaces deployment, you'll need to:
  - Create a new Space on huggingface.co (select Gradio as the SDK)
  - Add ANTHROPIC_API_KEY and OPENAI_API_KEY as Secrets in the Space settings
  - Push the code to the Space repo

  Want me to run the tests first to make sure everything still passes cleanly, or are you ready to go ahead with the git commands?