PDF Agents

• Key points are in the visual diagram above.

PDFs are the universal format for contracts, invoices, research papers, and reports. Agents that read PDFs unlock RAG over document libraries, automated data entry, and compliance review.

A PDF agent is a paralegal who reads stacks of contracts, highlights key clauses, and fills in summary spreadsheets.

Scenario

Invoice processing agent: receives PDF invoice → extracts vendor, line items, total → validates against PO in ERP → flags discrepancies → routes for approval.

Solution

In Voice & Multimodal Agents, apply PDF Agents to this scenario: Invoice processing agent: receives PDF invoice → extracts vendor, line items, total → validates against PO in ERP → flags discrepancies → routes for approval. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.

Do this before moving to the next module — reading alone is not enough.

Open the Code Walkthrough below and run it locally. Change one parameter related to PDF Agents (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.

Highlighted lines show where PDF Agents happens in the code.

1import pymupdf  # import dependencies2
3def extract_pdf_text(path: str) -> list[str]:  # define a reusable function4    doc = pymupdf.open(path)5    pages = []6    for page in doc:7        pages.append(page.get_text())8    return pages  # return the result9
10# Then: chunk → embed → RAG, or send to vision LLM

• Treating PDF Agents as a black box without evaluation
• Ignoring cost and latency in production
• Skipping error handling for pdf agents

Quick recap — the most important points from this module.