🤖 SWE-agent - Deep Dive & Build-Your-Own Guide 📘

It sounds like you're summarizing and discussing the key components of SWE-Agent, an AI-driven software engineering assistant designed to work within specific guidelines called the Agent-Computer Interface (ACI). Let's break down each part for clarity:

1. SWE-Agent Overview

• Core Functionality: SWE-Agent is a tool that uses large language models (LLMs) like GPT-4 to assist software engineers in tasks such as debugging and code review.
• Architecture: It consists of templates, parsers, and bash scripts integrated into a 5-phase framework: render prompt, call model, parse response, validate action, execute action.

2. Five Phases of SWE-Agent

• Render Prompt: The agent constructs the context for the LLM by processing the conversation history.
• Call Model: The agent queries an LLM (e.g., GPT-4) and tracks costs to ensure they don't exceed predefined limits.
• Parse Response: The response from the model is parsed into a thought (rationale) and action (command).
• Validate Action: Actions are checked against blocklists and syntax-checked using bash -n before

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