Coding Agent
An autonomous coding agent built with Python and Groq that solves programming tasks through iterative tool calling. The agent plans one action at a time, observes tool outputs, and continues reasoning until the requested task is completed.
Overview
Coding Agent is an autonomous command-line AI agent capable of completing programming tasks through iterative reasoning and tool execution.
Instead of directly generating code for every request, the agent follows a structured reasoning loop: it plans a single action, invokes the appropriate tool, observes the result, and then decides the next step until the task is complete.
This project explores the core concepts behind modern agentic systems by combining LLM reasoning with external tool execution.
Motivation
Large Language Models are powerful at reasoning, but they cannot directly interact with a computer.
This project bridges that gap by allowing the language model to control a small set of trusted Python tools while keeping execution outside the model itself.
The result is a safer and more reliable workflow where the LLM focuses on planning and reasoning, while Python performs the actual operations.
Architecture
User
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LLM (Groq)
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JSON Decision
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Python Agent
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Tool Execution
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Observation
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LLM
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Repeat Until Finished
How It Works
The agent maintains a conversation history containing:
- System instructions
- User requests
- Assistant reasoning
- Tool observations