Skip to content

README.md

Latest commit

 

History

History
48 lines (27 loc) · 2.66 KB

README.md

File metadata and controls

48 lines (27 loc) · 2.66 KB

GitHubAgent Module Documentation

Overview

The GitHubAgent module is part of a larger codebase named Patchwork, specifically located in the patchwork/steps/GitHubAgent/ directory. This module contains tools and configuration for creating a GitHub-supported task runner using pre-trained models to assist in data extraction and task automation through GitHub's CLI. It leverages components like AioLlmClient, AgenticStrategyV2, and a GitHubTool for execution, configuration, and API interaction, respectively.

Files

1. GitHubAgent.py

This file defines the GitHubAgent class, which serves as a controller for initiating tasks on GitHub using the command-line interface. It incorporates agentic strategy with messaging models for instruction following and execution planning.

Inputs

  • base_path: A string specifying the working directory path, defaults to the current working directory.
  • prompt_value: A dictionary containing additional data for rendering task templates.
  • github_api_key: A required string for authenticating GitHub API requests.
  • task: Required task description, typically a string formatted with Mustache templating.
  • example_json: JSON-formatted string with example output structure.
  • Optionally, keys for major LLM API platforms (openai, anthropic, google) as annotations for client configuration.

Outputs

  • result: Dictionary combining the execution result and usage metrics, such as token counts.

Usage

To use GitHubAgent, instantiate it with the necessary input parameters and invoke run(). It operates through LLM models to facilitate data retrieval tasks on GitHub without performing extraneous actions beyond the specified task.

2. typed.py

This file provides input and output type definitions for the GitHubAgent using TypedDict, enabling structured input validation and documentation.

Inputs

  • GitHubAgentInputs: Extends required inputs, annotating key fields for configuration support and API key validation.

Outputs

  • GitHubAgentOutputs: Includes request_tokens and response_tokens for reporting on API usage.

3. __init__.py

This file initializes the GitHubAgent module, currently empty but reserved for future package-level imports or configurations.

Conclusion

The GitHubAgent module is ideally suited for developers needing to automate GitHub data fetching tasks. By configuring and deploying these classes, users can harness pre-trained LLMs to interact with GitHub’s architecture efficiently. This module embodies the intersection of LLM application within traditional command-line interfaces, augmenting software task automation.