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From: "patched.codes[bot]"
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Date: Mon, 14 Apr 2025 07:53:45 +0000
Subject: [PATCH] Patched patchwork/steps/GitHubAgent/README.md

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+# GitHubAgent Documentation
+
+## Overview
+
+The `GitHubAgent` is a Python module designed to facilitate interactions with GitHub through automated steps, leveraging a conversational AI model. It is implemented within a larger framework, likely used for workflow automation. The `GitHubAgent` utilizes an AI model to help execute GitHub-related tasks using the GitHub CLI, tailored through a specified task prompt. This component can be particularly useful for developers or program managers looking to automate GitHub data retrieval and operations in a structured environment.
+
+## Inputs
+
+The inputs are structured using `TypedDict` to define what parameters the `GitHubAgent` must receive to perform its function. They include:
+
+- **github_api_key (str):** A required input to authenticate API requests to GitHub.
+- **task (str):** A string defining the task to be executed by the agent.
+- **base_path (str, optional):** The base filesystem path for the execution context; defaults to the current working directory if not specified.
+- **prompt_value (Dict[str, Any], optional):** Additional data to be used in task rendering.
+- **max_llm_calls (int, optional):** Configurable limit on the number of calls to the language model.
+- **example_json (str, optional):** Example JSON structure used in prompting.
+- **API keys (str, optional):** Options for different API keys (openai, anthropic, google) with configuration options for mutual exclusivity.
+
+## Outputs
+
+The outputs are captured in a structured format as follows:
+
+- **request_tokens (int):** Number of tokens used in the LLM request.
+- **response_tokens (int):** Number of tokens received in the LLM response.
+
+These outputs are combined with the results of the agentic strategy execution to provide a comprehensive view of the task outcomes and model usage.
+
+## Usage
+
+The `GitHubAgent` is instantiated with specific inputs, such as authentication keys and a defined task. The primary method for operation is `run()`, which engages the conversational AI model to perform the specified task using the GitHub CLI. The output comprises the results of the task and model usage statistics.
+
+This module can be part of a larger automated data pipeline or workflow system, where users need to regularly extract or manipulate information from GitHub programmatically. By encapsulating the complexity of language model interactions and GitHub API dealings, the `GitHubAgent` streamlines operations that would typically require manual scripting or command-line expertise.