Summary

• Problem:
  There was no beginner example demonstrating how to build a document research agent that processes PDFs and raw text using Bindu.

• Why it matters:
  Developers learning Bindu need a clear real-world example showing how an AI agent can be converted into a live service using bindufy().

• What changed:
  Added a new example agent pdf_research_agent.py under examples/beginner/.
  The agent accepts either a PDF file path or raw document text and returns a structured summary.

• What did NOT change:
  No changes were made to core Bindu functionality, APIs, storage, or scheduler components.

Change Type

• Feature
• Documentation

Scope

• Documentation
• CLI / utilities

Linked Issue/PR

None

User-Visible / Behavior Changes

A new beginner example agent is available:

examples/beginner/pdf_research_agent.py

This demonstrates how to:

• read PDF content using pypdf
• process document text with an LLM agent
• expose the agent as a live microservice using bindufy()

Security Impact

New permissions/capabilities? No
Secrets handling changed? No
New network calls? No
Database changes? No
Auth changes? No

Verification

Environment

OS: Windows 11
Python: 3.13
Storage backend: InMemoryStorage
Scheduler backend: InMemoryScheduler

Steps to Test

1. Run the agent

python pdf_research_agent.py

2. Send a request using curl

curl -X POST http://localhost:3775/

3. Retrieve task result using tasks/get.

Expected Behavior

Agent returns a structured summary of the provided document text or PDF content.

Actual Behavior

Agent successfully returns summarized output through the Bindu task system.

Human Verification

Verified scenarios:

• Agent starts successfully
• JSON-RPC request accepted
• Task completes and returns result

Edge cases checked:

• Raw text input
• Long document input

Not verified:

• Very large PDFs

Compatibility / Migration

Backward compatible: Yes

Risks and Mitigations

None

Checklist

• Tests pass locally
• Human verification completed
• Backward compatibility considered