Dispatch to appropriate function [chapter] deterministic

if tool == "get_blog_post": result = get_blog_post(**args) elif tool == "analyze_threat": result = analyze_threat(**args) else: raise ValueError(f"Unknown tool: {tool}") return {"success": True, "result": result} except Exception as e: logging.error("Tool call failed: %s", e) return {"success": False, "error": str(e)}

`

This handler demonstrates the core responsibilities: parsing, dispatching, logging, and error handling. In a production you would add schema validation (e.g., using pydantic), retry logic, and rate limiting.

Building a Basic Autonomous Agent With the fundamentals in place, you can assemble a minimal autonomous agent. The agent will: 1. Listen for input via a REPL environment. 2. Reason about the input using a local language model. 3. Decide whether to generate a blog post or invoke a cybersecurity analysis. 4. Execute the selected action via function calling. 5. Return the result to the . The following sketch illustrates this flow:

```python import json import logging import os