docs/guides/QUICK_START_RAG.md

Quick Start: Product Design RAG

Setup (One-Time)

Step 1: Copy Documents to Modal Volume

# Documents should already be uploaded, but if needed:
modal volume put mcp-hack-ins-products \
  docs/tokyo_auto_insurance_product_design_filled.md \
  docs/tokyo_auto_insurance_product_design.docx

Step 2: Index the Documents

# Option A: Using the CLI tool (auto-detects venv)
python3 query_product_design.py --index

# Option B: Using helper script (activates venv automatically)
./run_with_venv.sh --index

# Option C: Activate venv first, then run
source venv/bin/activate
python query_product_design.py --index

# Option D: Direct Modal command (if venv is activated)
modal run src/modal-rag-product-design.py::index_product_design

This will:

• Load the markdown and Word documents
• Split them into chunks
• Generate embeddings
• Store in ChromaDB collection product_design

Expected time: 2-5 minutes

Querying

Option 1: Interactive Mode (Recommended)

python query_product_design.py --interactive

Then type your questions:

❓ Your question: What are the three product tiers?
❓ Your question: What is the Year 3 premium volume?
❓ Your question: exit

Option 2: Single Query

python query_product_design.py --query "What are the three product tiers and their premium ranges?"

Option 3: Direct Modal Command

modal run src/modal-rag-product-design.py::query_product_design \
  --question "What coverage does the Standard tier include?"

Example Questions

Product Features

python query_product_design.py --query "What are the three product tiers and their premium ranges?"
python query_product_design.py --query "What coverage does the Standard tier include?"
python query_product_design.py --query "What are the unique features of TokyoDrive Insurance?"
python query_product_design.py --query "What add-on services are available?"

Financial Projections

python query_product_design.py --query "What is the Year 3 premium volume projection?"
python query_product_design.py --query "What is the target loss ratio for Year 2?"
python query_product_design.py --query "What are the break-even projections?"

Market & Strategy

python query_product_design.py --query "What is the target market size in Tokyo?"
python query_product_design.py --query "Who are the main competitors?"
python query_product_design.py --query "What are the key value propositions?"

Technical Requirements

python query_product_design.py --query "What are the technology requirements?"
python query_product_design.py --query "What is the claims processing workflow?"
python query_product_design.py --query "What mobile app features are planned?"

Compliance

python query_product_design.py --query "What are the FSA licensing requirements?"
python query_product_design.py --query "What is the minimum capital requirement?"
python query_product_design.py --query "What data privacy requirements apply?"

Troubleshooting

"No documents found"

• Make sure documents are in the Modal volume
• Check: modal volume list mcp-hack-ins-products

"Collection not found"

• Run indexing first: python query_product_design.py --index

Slow queries

• First query may be slow (cold start)
• Subsequent queries should be faster (warm container)

Next Steps

1. Test with your questions: Try asking questions your team would actually need
2. Create query templates: Build common queries for different use cases
3. Integrate with workflows: Use RAG to extract requirements for development tickets
4. Share with team: Let stakeholders query the document themselves