Ship AI Systems
That Scale

import anthropic
from supabase import create_client

# Initialize clients
claude = anthropic.Anthropic()
supabase = create_client(SUPABASE_URL, SUPABASE_KEY)

def ask_dave(question: str) -> str:
    """RAG-powered Q&A over RE investing content"""
    
    # Generate embedding for the question
    embedding = get_embedding(question)
    
    # Search Supabase pgvector for relevant chunks
    results = supabase.rpc(
        "match_documents",
        {"query_embedding": embedding, "match_count": 5}
    ).execute()
    
    # Build context from matched documents
    context = "\n".join([r["content"] for r in results.data])
    
    # Ask Claude with retrieved context
    response = claude.messages.create(
        model="claude-sonnet-4-20250514",
        system=f"Answer using this context:\n{context}",
        messages=[{"role": "user", "content": question}]
    )
    
    return response.content[0].text