LLM data framework for connecting custom data sources to language models. Best-in-class RAG, data connectors, and query engines. Python and TypeScript.
LlamaIndex is the go-to framework for connecting your own data to large language models. It provides data connectors (LlamaHub) for ingesting from PDFs, databases, APIs, Notion, Slack, and hundreds of other sources. The indexing layer chunks, embeds, and stores your data in any vector database. Query engines handle retrieval-augmented generation with support for recursive retrieval, sub-question decomposition, and multi-document synthesis. It also includes an agent framework with tool use and multi-step reasoning. Available in both Python and TypeScript (LlamaIndex.TS). If your use case is primarily about making LLMs smarter with your own data rather than building autonomous agents, LlamaIndex is more focused and mature than LangChain for that specific problem.
Most popular LLM framework. 100K+ GitHub stars. Chains, RAG, vector stores, tool use. LangGraph adds stateful multi-agent workflows with cycles and persistence.
TypeScript-first AI agent framework. Agents, tools, memory, workflows, RAG, evals, tracing, MCP, and production deployment for Node.js apps.
Structured data extraction from any LLM using Pydantic models. Automatic retries, validation, and streaming. 3M+ monthly downloads. Available in Python, TypeScript, Go, Ruby, and Rust.
Open-source AI orchestration framework by deepset. Modular pipelines for RAG, agents, semantic search, and multimodal apps. Pipeline-as-graph architecture with explicit control.
LLM data framework for connecting custom data sources to language models. Best-in-class RAG, data connectors, and query engines. Python and TypeScript.
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Subscribe FreeThe TypeScript toolkit for building AI apps. Unified API across OpenAI, Anthropic, Google. Streaming, tool calling, structured output, multi-step agents. 50K+ GitHub stars.
Frontend stack for agent-native apps. React hooks, prebuilt copilot UI, AG-UI runtime, frontend tools, shared state, and human-in-the-loop flows.
Anthropic's Python SDK for building production agent systems. Tool use, guardrails, agent handoffs, and orchestration. Released alongside Claude 4.
Step-by-step guide to building an MCP server in TypeScript - from project setup to tool definitions, resource handling, testing, and deployment.
AI AgentsDeep comparison of the top AI agent frameworks - LangGraph, CrewAI, Mastra, CopilotKit, AutoGen, and Claude Code.
AI AgentsInstall the dd CLI and scaffold your first AI-powered app in under a minute.
Getting Started
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