AI Agent Deep Dive
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Deep-dive research reports on AI Agent source code — systematic analysis of mainstream AI agent framework architectures, core principles, and implementation details.
Deep-dive research reports on AI Agent source code — systematic analysis of mainstream AI agent framework architectures, core principles, and implementation details.
AutoChain is a lightweight, extensible, and testable LLM Agent framework by Forethought, providing clean abstractions for agent building with automatic tool selection, conversation history management, and automated testing workflows.
An end-to-end infrastructure for training and evaluating various LLM agents — provides a complete toolchain from data construction to model training and evaluation.
Flexible and powerful framework for managing multiple AI agents and handling complex conversations across providers like OpenAI, Anthropic, and AWS Bedrock.
A GenAI application development framework that simplifies agent interaction with structured data and chained-calls syntax, using event-driven flow for complex logic.