BaseAI is a TypeScript framework for building serverless, composable AI agents with memory and tools. It targets developers looking to create local-first, agentic applications and deploy them easily. The framework simplifies the development of AI "pipes" (custom agents) and integrates features like Retrieval-Augmented Generation (RAG).

How It Works

BaseAI utilizes a pipe-based architecture where each pipe represents a distinct AI agent. These pipes are defined in TypeScript and configured with model parameters, system prompts, memory, and tools. The framework handles the orchestration of these pipes, allowing for complex agentic workflows. Its local-first development approach, coupled with a streamlined deployment process, aims to accelerate AI application development.

Quick Start & Requirements

• Install: npx baseai@latest init
• Prerequisites: Node.js, npx, API keys for LLM providers (OpenAI, Anthropic, etc.) stored in a .env file.
• Setup: Requires creating a project, adding API keys, and defining pipes.
• Documentation: BaseAI.dev/docs, BaseAI.dev/learn

Highlighted Details

• TypeScript-first framework for AI agent development.
• Supports serverless deployment with a single command.
• Integrated memory (RAG) capabilities.
• Local-first development with a focus on rapid prototyping.
• Offers a collaborative platform (Langbase Studio) for teams.

Maintenance & Community

• Authors include Ahmad Awais, Ashar Irfan, Saqib Ameen, Saad Irfan, and Ahmad Bilal.
• Security vulnerability reporting is handled via email to security@langbase.com.
• Further learning resources are available on their website and AI course.

Licensing & Compatibility

• The README does not explicitly state the license. It mentions "BaseAI is the AI framework..." and provides links to their website and documentation, but no license file or type is specified.

Limitations & Caveats

The project's licensing is not clearly stated in the README, which could be a concern for commercial use or integration into closed-source projects. The framework relies heavily on external LLM provider API keys, requiring careful management of credentials.