RAG - lesson 4 | HackIndia Skills

RAG - lesson 4 | HackIndia Skills | HackIndia

Example

Prompt template

Use a template like this before calling your LLM. The important parts are the evidence labels and the fallback rule.

This example is plain Python. Connect it to whatever model call your app uses.

def build_prompt(question, retrieved_chunks):
    evidence_blocks = []

    for i, chunk in enumerate(retrieved_chunks, start=1):
        source_id = f"S{i}"
        file_name = chunk["metadata"].get("file", "unknown file")
        page = chunk["metadata"].get("page", "unknown page")
        text = chunk["text"].strip()

        evidence_blocks.append(
            f"[{source_id}] File: {file_name}, Page: {page}\n{text}"
        )

    evidence = "\n\n".join(evidence_blocks)

    return f"""
You are a document question-answering assistant.
Answer the user's question using only the evidence below.
If the evidence does not contain the answer, say: "I could not find this in the provided documents."
Do not use outside knowledge.
Keep the answer short and specific.

Evidence:
{evidence}

Question:
{question}

Answer:
""".strip()

Example

Weak versus better

A weak prompt asks the model to answer from documents but does not show boundaries. A better prompt makes the evidence visible and numbered.

This also prepares your app for lesson 5, where answers will cite sources users can verify.

Weak:
Answer this question using the uploaded documents: What is the refund window?

Better:
Use only the evidence below.
If the answer is missing, say you could not find it.

[S1] File: policy.pdf, Page: 2
Refund requests must be raised within 7 days of payment.

Question: What is the refund window?
Answer:

Put evidence into the prompt

The core rule

What the prompt needs

Build the prompt

Prompt template

Keep evidence small

Do not trust wording

Weak versus better

Do this now

Quick check