Top AI Repos — open-source AI, indexed and scored
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
The collaborative spreadsheet for AI. Chain cells into powerful pipelines, experiment with prompts and models, and evaluate LLM responses in real-time. Work together seamlessly to build and iterate on AI applications.
| Date | Stars |
|---|---|
| 2026-07-24 | 1103 |
| 2026-07-25 | 1104 |
| 2026-07-28 | 1104 |
| 2026-07-30 | 1103 |
| 2026-08-06 | 1104 |
Today
+1 stars today
This week
+1 stars this week
This month
— stars this month
Momentum
5.0
growth rate 0.09%/day
# JamAI Base  <!-- prettier-ignore-start -->   > [!TIP] > [Explore our docs](#explore-the-documentation) <!-- prettier-ignore-end --> ## Overview JamAI Base is an open-source RAG (Retrieval-Augmented Generation) backend platform that integrates an embedded database (SQLite) and an embedded vector database (LanceDB) with managed memory and RAG capabilities. It features built-in LLM, vector embeddings, and reranker orchestration and management, all accessible through a convenient, intuitive, spreadsheet-like UI and a simple REST API.  ## Migration Guide from v1 to v2 Refer to [Migration Guide](./MIGRATION_GUIDE.md) ## Key Features - Embedded database (SQLite) and vector database (LanceDB) - Managed memory and RAG capabilities - Built-in LLM, vector embeddings, and reranker orchestration - Intuitive spreadsheet-like UI - Simple REST API ### Generative Tables Transform static database tables into dynamic, AI-enhanced entities. - **Dynamic Data Generation**: Automatically populate columns with relevant data generated by LLMs. - **Built-in REST API Endpoint**: Streamline the process of integrating AI capabilities into applications. ### Action Tables Facilitate real-time interactions between the application frontend and the LLM backend. - **Real-Time Responsiveness**: Provide a responsive AI interaction layer for applications. - **Automated Backend Management**: Eliminate the need for manual backend management of user inputs and outputs. - **Complex Workflow Orchestration**: Enable the creation of sophisticated LLM workflows. ### Knowledge Tables Act as repositories for structured data and documents, enhancing the LLM’s contextual understanding. - **Rich Contextual Backdrop**: Provide a rich contextual backdrop for LLM operations. - **Enhanced Data Retrieval**: Support other generative tables by supplying detailed, structured contextual information. - **Efficient Document Management**: Enable uploading and synchronization of documents and data. ### Chat Tables Simplify the creation and management of intelligent chatbot applications. - **Intelligent Chatbot Development**: Simplify the development and operational management of chatbots. - **Context-Aware Interactions**: Enhance user engagement through intelligent and context-aware interactions. - **Seamless Integration**: Integrate with Retrieval-Augmented Generation (RAG) to utilize content from any Knowledge Table. ### LanceDB Integration Efficient management and querying of large-scale multi-modal data. - **Optimized Data Handling**: Store, manage, query, and retrieve embeddings on large-scale multi-modal data efficiently. - **Scalability**: Ensure optimal performance and seamless scalability. ### Declarative Paradigm Focus on defining "what" you want to achieve rather than "how" to achieve it. - **Simplified Development**: Allow users to define relationships and desired outcomes. - **Non-Procedural Approach**: Eliminate the need to write procedures. - **Functional Flexibility**: Support functional programming through LLMs. ## Key Benefits ### Ease of Use - **Interface**: Simple, intuitive spreadsheet-like interface. - **Focus**: Define data requirements through natural language prompts. ### Scalability - **Foundation**: Built on LanceDB, an open-source vector database designed for AI workloads. - **Performance**: Serverless design ensures optimal performance and seamless scalability. ### Flexibility - **LLM Support**: Supports any LLMs, including OpenAI GPT-4, Anthropic Claude 3, and Meta Llama3. - **Capabilities**: Leverage state-of-the-art AI capabilities effortlessly. ### Declarative Paradigm - **Approach**: Define the "what" rather than the "how." - **Simplification**: Simplifies complex data operat
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Ikko Eltociear Ashimine · Japan
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Michael Feil · @basetenlabs · United States
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:578e4862d53cefb0, topic:rag, topic:retrieval-augmented-generation, readme:retrieval-augmented generation
matched fp:578e4862d53cefb0, topic:serverless
matched fp:578e4862d53cefb0, topic:chatbot, topic:chatgpt, readme:chatbot
matched fp:578e4862d53cefb0, topic:workflow, topic:orchestration