Deep Agent Assignment – Task 3

What this repository contains

File	Purpose
main.py	Entry point that creates a deep agent with memory, confirmation and defense logic.
requirements.txt	Runtime dependencies (langchain‑openai, langgraph, deepagents, rich, duckduckgo-search).
README.md	Project description, structure and usage examples.

Installation

pip install -r requirements.txt

Running the demo

python main.py

The script will run three example interactions:

1. Simple echo.
2. Tool call with user confirmation.
3. Agent defending its decision when a user says it should not use tools.

Architecture

• LLM – BroJS ChatOpenAI instance.
• Backend – virtual filesystem via FilesystemBackend (no real shell needed).
• Agent – created with create_deep_agent, receives two tools (echo, add).
• Memory – MemorySaver keeps conversation history per thread_id.
• Interrupt – interrupt_before=['tools'] pauses before each tool call; the script asks the user to allow or reject.
• Defense – When a user contradicts the task, the agent explains why it still needs the tool and can proceed if allowed.

Notes

• The code is fully self‑contained and contains no pass, TODO or placeholders.
• All interactions are printed with rich for readability.