SageAI
S
Sageai
Overview :
Storia-AI/sage is an AI-driven tool for engaging with code repositories, utilizing large language models (LLMs) and retrieval-augmented generation (RAG) technology to allow users to query information from codebases through chat. Key advantages of this product include a straightforward setup process, documented responses, support for local or cloud-based operation, and the ease of replacing algorithm components to meet diverse needs. Storia-AI/sage aims to help developers quickly and intuitively understand codebases, thus enhancing development efficiency. Currently, this product is free and particularly beneficial for the open-source community.
Target Users :
The target audience primarily includes developers and programming enthusiasts who frequently need to comprehend and utilize large codebases. Storia-AI/sage offers a chat-based interface that allows users to quickly obtain required information without the need for in-depth code reading, making it particularly suitable for those looking to swiftly learn and understand new codebases.
Total Visits: 474.6M
Top Region: US(19.34%)
Website Views : 50.8K
Use Cases
Developers use Storia-AI/sage to query the usage and contextual information of specific functions.
Open-source project maintainers utilize this tool to create a chat interface for their projects, enhancing community interaction.
Programming beginners quickly grasp complex codebase structures and functions through Storia-AI/sage.
Features
Easy installation using pipx or a virtual environment, making it user-friendly.
Supports local operation, leveraging the open-source Marqo project for code indexing.
Integrates with external APIs like OpenAI, Voyage, etc., to improve retrieval quality.
Enables interactive chat commands to engage with the code repository.
Provides detailed documentation and code context, enhancing the reliability of AI responses.
Supports various retrieval strategies, including vector-based retrieval and LLM-only retrieval.
Allows indexing of GitHub issues, extending the context information of code repositories.
How to Use
1. Install Storia-AI/sage using pipx or create a virtual environment and install it.
2. Configure environment variables as needed, such as API keys and index settings.
3. Select the GitHub code repository to be indexed, and run the sage-index command to begin the indexing process.
4. After indexing is complete, use the sage-chat command to interact with the code repository.
5. Customize the chat interface through command-line flags, such as setting a public URL or adjusting retrieval strategies.
6. Specify lists of files to include or exclude during indexing if required.
7. Index private repositories or GitHub issues using a GitHub token.
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