Build a Notes Q&A Agent with Cited Answers
Subham Chand
Sep 3, 20264 min read1 view
Learning outcome: By the end of Day 15, you will understand how to turn a RAG pipeline into a Notes Q&A Agent that answers from your documents, includes citations, and admits when the evidence is missing.
This lesson is part of the AI Agents in 30 Days roadmap.
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From a RAG pipeline to a useful agent
During Days 11 to 14, we learned why models hallucinate, how embeddings represent meaning, why chunking affects retrieval, and how a RAG pipeline supplies trusted context.
Today we connect those pieces into one practical project: a Notes Q&A Agent.
The core mental model is:
Question -> evidence -> cited answer
The agent does not need to place an entire PDF into every prompt. It can search an indexed knowledge base for relevant passages, then provide those passages to the model as context. OpenAI's Retrieval guide describes semantic search as finding relevant results by meaning, even when they share few or no keywords with the question. Its File search guide also shows that answers can include file-citation annotations.
The Notes Q&A flow
Step | What happens | Why it matters |
|---|---|---|
1. Ask | The learner asks a question in natural language. | The user does not need to know the document's exact wording. |
2. Retrieve | The system finds the most relevant passages from the notes or PDF. | Only useful context is sent to the model. |
3. Answer | The model answers using the retrieved evidence. | The response is grounded in the learner's material. |
4. Cite | The response identifies the supporting file, page, or passage. | The learner can verify the claim. |
5. Abstain | If strong evidence is missing, the agent says it could not find the answer. | The system avoids hiding uncertainty behind confident wording. |
Practical example: ask your programming notes
Imagine you upload a PDF containing your object-oriented programming notes.
You ask:
What is polymorphism?
The system retrieves passages from pages 12 and 14. The model uses those passages to explain that polymorphism allows different objects to respond through a shared interface, and the answer links back to those pages.
The citation does not prove that every sentence in the generated explanation is correct. It gives you a path to inspect the evidence and compare the answer with the original notes.
Try this today
Choose one PDF that you already understand.
Write three questions about it.
Make one question intentionally unanswerable from the PDF.
Require every answer to include a citation.
Require the agent to say, “I couldn't find that in the provided source,” when evidence is missing.
This exercise tests both useful answers and safe refusal behavior.
A completed instruction you can copy
Answer the question using only the retrieved passages from my notes.
For every factual claim:
1. Cite the supporting file and page or passage.
2. Do not invent a citation.
3. If the retrieved context does not contain enough evidence, say:
"I couldn't find that in the provided source."
Question: What is polymorphism?
For an optional build exercise, store one PDF in a vector store, retrieve the top relevant passages for each question, and pass both the question and those passages to the model. Keep the citation metadata attached to the final answer.
Common mistakes
Treating citations as proof of correctness
A citation makes an answer inspectable. You still need to check whether the cited passage actually supports the claim.
Forcing an answer every time
If the evidence is missing, guessing defeats the purpose of grounding. Add an explicit abstain instruction.
Retrieving too much context
More passages are not automatically better. Irrelevant context can distract the model and make the answer harder to verify.
Losing citation metadata
If your retrieval layer returns a chunk without its file or page information, the final answer cannot produce a useful source reference.
Knowledge check
1. Why retrieve passages instead of sending the entire PDF every time?
To provide focused context and avoid repeatedly sending unrelated content.
2. Does a citation guarantee the generated answer is correct?
No. It lets you inspect the evidence supporting the answer.
3. What should the agent do when the PDF does not contain the answer?
State that it could not find sufficient evidence instead of guessing.
Download the handwritten notes
day-15-handwritten-notes.pdfUse the one-page notes as a quick reference for the complete Question -> Evidence -> Cited Answer flow.
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Continue the series
Previous: Day 14 - Building a RAG Pipeline
Roadmap: AI Agents in 30 Days
Next: Day 16 - Workflow vs Agent (link after publication)
