Indie devsShip a real RAG product over one weekend.
AgenciesSell "docs Q&A / knowledge bot" builds.
SaaS teamsAdd grounded AI answers to your app.
ConsultantsDeploy internal knowledge bots for clients.
Preview -- actual content inside
A sample from the RAG code templates and eval harness -- this is what you get.
Python: RAG Retrieval Function
def retrieve(query: str, k: int = 5):
"""Embed query, search vector DB,
return top-k chunks with scores."""
q_emb = embedder.encode([query])
scores, idxs = index.search(q_emb, k)
chunks = [documents[i] for i in idxs[0]]
return [
{"text": c, "score": float(s)}
for c, s in zip(chunks, scores[0])
]
def build_prompt(query, chunks):
context = "\\n---\\n".join(
c["text"] for c in chunks
)
return f"""Answer using only this context.
If unsure, say you don't know.
Context:
{context}
Question: {query}"""
Eval Harness (sample queries):
Q: "What's our refund policy?"
Expected: mentions 7-day money-back
Score: 0.94
Q: "How do I integrate the API?"
Expected: references /api/products
Score: 0.87
+ 3 runnable templates (Python + Next.js), tuning guide, and full eval suite.
Built by operators shipping AI apps in production.