
askrepo
Source code reading with LLM.
Stars: 186

askrepo is a tool that reads the content of Git-managed text files in a specified directory, sends it to the Google Gemini API, and provides answers to questions based on a specified prompt. It acts as a question-answering tool for source code by using a Google AI model to analyze and provide answers based on the provided source code files. The tool leverages modules for file processing, interaction with the Google AI API, and orchestrating the entire process of extracting information from source code files.
README:
This program reads the content of Git-managed text files in a specified directory, sends it to the Google Gemini API, and provides answers to questions based on the specified prompt.
❯ askrepo --help
Usage: askrepo [OPTIONS] [BASE_PATH]
Arguments:
[BASE_PATH]
Options:
-p, --prompt <PROMPT> [default: "Explain the code in the files provided"]
-m, --model <MODEL> [default: "gemini-1.5-flash"]
-a, --api-key <API_KEY>
-h, --help Print help
-V, --version Print version
❯ askrepo --prompt "What is the purpose of this code?" --model "gemini-1.5-flash" ./src
This code, primarily found in `src/main.rs`, is designed to **extract information from source code files and provide answers to questions about them using a Google AI model**. It leverages the `google_api` module (`src/google_api.rs`) to interact with the Google Generative Language API.
Here's a breakdown of its functionality:
1. **`src/file_utils.rs`:** This module handles file processing.
- `is_binary_file`: Determines if a file is binary based on its extension and magic numbers (lines 10-25).
- `get_git_tracked_files`: Lists all files tracked by Git within a given directory (lines 27-40).
- `get_files_content`: Reads content of text files (non-binary), escapes special characters, and formats it for use in the query (lines 42-58).
2. **`src/google_api.rs`:** This module handles interaction with the Google AI API.
- `get_google_api_data`: Sends a request to the API with the provided query, model name, and API key (lines 4-25).
- `parse_google_api_response`: Parses the JSON response from the API, extracting the generated text (lines 27-36).
3. **`src/main.rs`:** This module orchestrates the entire process.
- It parses command-line arguments:
- `base_path`: The directory containing the source code files.
- `model`: The Google AI model to use (defaults to "gemini-1.5-flash").
- `api_key`: The Google API key for authentication.
- `prompt`: The question to ask about the source code (defaults to "Explain the code in the files provided").
- It calls `file_utils::get_files_content` to get the formatted content of text files within the `base_path`.
- It constructs the prompt by combining the file information, the question, and the extracted source code content.
- It calls `google_api::get_google_api_data` to send the prompt to the Google AI model.
- Finally, it parses the response and prints the generated text.
**In essence, this code acts as a question-answering tool for source code by using a Google AI model to analyze and provide answers based on the provided source code files.**
Gemini API key is required to run this program. You can get it from
https://aistudio.google.com/app/apikey
cargo install askrepo
export GOOGLE_API_KEY="YOUR_API_KEY"
askrepo --prompt "What is the purpose of this code?" ../your-repo/src
cargo run -- --prompt "Find bugs in this code" ./src
cargo test
Gets a list of Git-managed files in the specified directory.
- The file contains null bytes or matches known binary file magic numbers.
- Determines whether a file is a text file. If the file contains null bytes or matches known binary file magic numbers, it is considered a binary file.
Reads the contents of Git-managed text files and combines them in CSV format.
Uses Google's generative AI model to generate comments based on the specified prompt. The generated comments are returned as an asynchronous generator.
When the script is executed directly, it retrieves the prompt and path from command line arguments, generates comments, and outputs them to the console.
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