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LangChain is the framework that powers most production LLM apps you've used. It's the plumbing behind the magic. What it provides: - Chains: Connect LLM calls with logic - Agents: LLMs that decide what actions to take - RAG: Retrieval-augmented generation made easy - Memory: Persistent context across conversations If you're building anything serious with LLMs, you'll probably touch LangChain. Python and JS/TS support. Huge ecosystem.
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CrewAI lets you build teams of AI agents that work together. Think of it as project management for autonomous AI. The core concept: - Define Agents with specific roles and goals - Create Tasks they need to complete - Let them collaborate and hand off work - Watch the crew get things done It's LangChain but focused entirely on multi-agent systems. When one agent isn't enough, CrewAI is how you scale. Python-first, very active development.
Phidata is a framework for building production-ready AI assistants. Think LangChain but more opinionated and batteries-included. Core features: - Built-in memory (conversations persist) - Knowledge bases (RAG out of the box) - Tool use (web search, APIs, code execution) - Structured outputs that actually work Less flexible than LangChain, more productive for common use cases. Python-first, actively maintained, strong documentation.