{ "version": 2, "slug": "ai-agent-framework", "category": "AI agent framework", "month": "2026-10", "checkedAt": "2026-10-09T01:30:39.213Z", "engines": [ "OPENAI", "ANTHROPIC", "PERPLEXITY", "GEMINI", "GROK", "AI_OVERVIEW" ], "runsPerPrompt": 3, "prompts": [ { "text": "What is the best framework for building AI agents?", "coverage": [ { "engine": "OPENAI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "ANTHROPIC", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "PERPLEXITY", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GEMINI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GROK", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "AI_OVERVIEW", "answered": 1, "failed": 0, "notRun": 0 } ] }, { "text": "Which AI agent framework is best for production use?", "coverage": [ { "engine": "OPENAI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "ANTHROPIC", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "PERPLEXITY", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GEMINI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GROK", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "AI_OVERVIEW", "answered": 1, "failed": 0, "notRun": 0 } ] }, { "text": "What's the best open-source framework for LLM agents?", "coverage": [ { "engine": "OPENAI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "ANTHROPIC", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "PERPLEXITY", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GEMINI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GROK", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "AI_OVERVIEW", "answered": 1, "failed": 0, "notRun": 0 } ] }, { "text": "Which framework is best for building multi-agent systems?", "coverage": [ { "engine": "OPENAI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "ANTHROPIC", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "PERPLEXITY", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GEMINI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GROK", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "AI_OVERVIEW", "answered": 1, "failed": 0, "notRun": 0 } ] }, { "text": "What's the easiest way to build an AI agent in Python?", "coverage": [ { "engine": "OPENAI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "ANTHROPIC", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "PERPLEXITY", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GEMINI", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "GROK", "answered": 3, "failed": 0, "notRun": 0 }, { "engine": "AI_OVERVIEW", "answered": 1, "failed": 0, "notRun": 0 } ] } ], "brands": [ { "name": "LangGraph", "domain": "langgraph.ai", "mentions": 71, "avgPosition": 1.92, "byEngine": { "OPENAI": 7, "ANTHROPIC": 15, "PERPLEXITY": 15, "GEMINI": 14, "GROK": 15, "AI_OVERVIEW": 5 } }, { "name": "CrewAI", "domain": "crew.ai", "mentions": 68, "avgPosition": 2.76, "byEngine": { "OPENAI": 6, "ANTHROPIC": 14, "PERPLEXITY": 14, "GEMINI": 14, "GROK": 15, "AI_OVERVIEW": 5 } }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com", "mentions": 56, "avgPosition": 4.02, "byEngine": { "OPENAI": 8, "ANTHROPIC": 11, "PERPLEXITY": 14, "GEMINI": 10, "GROK": 12, "AI_OVERVIEW": 1 } }, { "name": "Mastra", "domain": "mastra.dev", "mentions": 35, "avgPosition": 5.46, "byEngine": { "OPENAI": 1, "ANTHROPIC": 5, "PERPLEXITY": 7, "GEMINI": 10, "GROK": 8, "AI_OVERVIEW": 4 } }, { "name": "Microsoft Agent Framework", "domain": "github.com", "mentions": 33, "avgPosition": 3.52, "byEngine": { "OPENAI": 6, "ANTHROPIC": 7, "PERPLEXITY": 4, "GEMINI": 4, "GROK": 10, "AI_OVERVIEW": 2 } }, { "name": "LangChain", "domain": "langchain.com", "mentions": 31, "avgPosition": 2.81, "byEngine": { "OPENAI": 13, "ANTHROPIC": 9, "PERPLEXITY": 5, "GEMINI": 1, "GROK": 2, "AI_OVERVIEW": 1 } }, { "name": "LlamaIndex", "domain": "llamaindex.ai", "mentions": 26, "avgPosition": 5.54, "byEngine": { "OPENAI": 7, "ANTHROPIC": 5, "PERPLEXITY": 5, "GEMINI": 3, "GROK": 6 } }, { "name": "Pydantic AI", "domain": "pydantic-ai.github.io", "mentions": 25, "avgPosition": 5.04, "byEngine": { "OPENAI": 2, "ANTHROPIC": 2, "GEMINI": 6, "GROK": 12, "AI_OVERVIEW": 3 } }, { "name": "Google ADK", "domain": "google.com", "mentions": 14, "avgPosition": 5, "byEngine": { "ANTHROPIC": 1, "PERPLEXITY": 2, "GEMINI": 1, "GROK": 9, "AI_OVERVIEW": 1 } }, { "name": "Microsoft AutoGen", "domain": "microsoft.com", "mentions": 12, "avgPosition": 3.67, "byEngine": { "OPENAI": 2, "ANTHROPIC": 1, "PERPLEXITY": 8, "GEMINI": 1 } }, { "name": "Smolagents", "domain": "github.com", "mentions": 12, "avgPosition": 4.58, "byEngine": { "GEMINI": 6, "GROK": 6 } }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai", "mentions": 11, "avgPosition": 5, "byEngine": { "ANTHROPIC": 1, "PERPLEXITY": 4, "GEMINI": 3, "GROK": 2, "AI_OVERVIEW": 1 } }, { "name": "PydanticAI", "domain": "ai.pydantic.dev", "mentions": 10, "avgPosition": 3.3, "byEngine": { "PERPLEXITY": 2, "GEMINI": 6, "GROK": 2 } }, { "name": "AutoGen", "domain": "github.com", "mentions": 10, "avgPosition": 4.2, "byEngine": { "OPENAI": 4, "ANTHROPIC": 3, "AI_OVERVIEW": 3 } }, { "name": "Semantic Kernel", "domain": "microsoft.com", "mentions": 7, "avgPosition": 6, "byEngine": { "OPENAI": 1, "ANTHROPIC": 1, "PERPLEXITY": 3, "GEMINI": 1, "AI_OVERVIEW": 1 } }, { "name": "OpenAI", "domain": "openai.com", "mentions": 6, "avgPosition": 2.17, "byEngine": { "OPENAI": 1, "ANTHROPIC": 3, "GROK": 1, "AI_OVERVIEW": 1 } }, { "name": "Google Agent Development Kit (ADK)", "domain": "google.github.io", "mentions": 6, "avgPosition": 4.67, "byEngine": { "ANTHROPIC": 1, "PERPLEXITY": 3, "GEMINI": 2 } }, { "name": "Haystack", "domain": "haystack.deepset.ai", "mentions": 6, "avgPosition": 5.5, "byEngine": { "OPENAI": 3, "ANTHROPIC": 1, "PERPLEXITY": 2 } }, { "name": "Claude Agent SDK", "domain": "anthropic.com", "mentions": 5, "avgPosition": 4.4, "byEngine": { "OPENAI": 1, "ANTHROPIC": 4 } }, { "name": "Anthropic", "domain": "anthropic.com", "mentions": 4, "avgPosition": 1.5, "byEngine": { "OPENAI": 1, "ANTHROPIC": 3 } }, { "name": "AutoGen (AG2)", "domain": "github.com", "mentions": 4, "avgPosition": 3.75, "byEngine": { "ANTHROPIC": 1, "GEMINI": 3 } }, { "name": "Microsoft", "domain": "microsoft.com", "mentions": 4, "avgPosition": 3.75, "byEngine": { "OPENAI": 3, "GROK": 1 } }, { "name": "Strands Agents", "domain": "strandsagents.com", "mentions": 3, "avgPosition": 2.33, "byEngine": { "PERPLEXITY": 3 } }, { "name": "Anthropic Python SDK", "domain": "github.com", "mentions": 3, "avgPosition": 2.67, "byEngine": { "PERPLEXITY": 3 } }, { "name": "Auto-GPT", "domain": "github.com", "mentions": 3, "avgPosition": 5.33, "byEngine": { "OPENAI": 3 } }, { "name": "Ray RLlib", "domain": "docs.ray.io", "mentions": 3, "avgPosition": 5.67, "byEngine": { "OPENAI": 3 } }, { "name": "Mesa", "domain": "mesa.readthedocs.io", "mentions": 3, "avgPosition": 5.67, "byEngine": { "OPENAI": 3 } }, { "name": "Microsoft Semantic Kernel", "domain": "learn.microsoft.com", "mentions": 2, "avgPosition": 3.5, "byEngine": { "OPENAI": 2 } }, { "name": "Hugging Face", "domain": "github.com", "mentions": 2, "avgPosition": 3.5, "byEngine": { "OPENAI": 2 } }, { "name": "Microsoft AutoGen (AG2)", "domain": "github.com", "mentions": 2, "avgPosition": 4, "byEngine": { "GEMINI": 2 } }, { "name": "PettingZoo", "domain": "pettingzoo.ml", "mentions": 2, "avgPosition": 4, "byEngine": { "OPENAI": 2 } }, { "name": "Google Agent Development Kit", "domain": "google.github.io", "mentions": 2, "avgPosition": 4.5, "byEngine": { "OPENAI": 1, "PERPLEXITY": 1 } }, { "name": "Google", "domain": "google.com", "mentions": 2, "avgPosition": 5, "byEngine": { "GROK": 1, "AI_OVERVIEW": 1 } }, { "name": "JADE", "domain": "jade.tilab.com", "mentions": 2, "avgPosition": 5.5, "byEngine": { "OPENAI": 1, "PERPLEXITY": 1 } }, { "name": "Dify", "domain": "github.com", "mentions": 2, "avgPosition": 6, "byEngine": { "ANTHROPIC": 2 } }, { "name": "Ray", "domain": "docs.ray.io", "mentions": 2, "avgPosition": 6.5, "byEngine": { "OPENAI": 1, "PERPLEXITY": 1 } }, { "name": "AgentForge", "domain": "arxiv.org", "mentions": 2, "avgPosition": 6.5, "byEngine": { "OPENAI": 2 } }, { "name": "LangSmith", "domain": "smith.langchain.com", "mentions": 2, "avgPosition": 8, "byEngine": { "ANTHROPIC": 1, "AI_OVERVIEW": 1 } }, { "name": "Microsoft Agent Framework (AutoGen + Semantic Kernel)", "domain": "microsoft.github.io", "mentions": 1, "avgPosition": 2, "byEngine": { "OPENAI": 1 } }, { "name": "CrewAI Enterprise", "domain": "crewai.com", "mentions": 1, "avgPosition": 2, "byEngine": { "GEMINI": 1 } }, { "name": "OpenAI Agents SDK (Python)", "domain": "openai.github.io", "mentions": 1, "avgPosition": 2, "byEngine": { "OPENAI": 1 } }, { "name": "Deep Agents", "mentions": 1, "avgPosition": 3, "byEngine": { "ANTHROPIC": 1 } }, { "name": "Haystack (deepset)", "domain": "haystack.deepset.ai", "mentions": 1, "avgPosition": 3, "byEngine": { "OPENAI": 1 } }, { "name": "Replit", "domain": "replit.com", "mentions": 1, "avgPosition": 3, "byEngine": { "ANTHROPIC": 1 } }, { "name": "Python", "domain": "python.org", "mentions": 1, "avgPosition": 3, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "Ray Serve (Ray)", "domain": "docs.ray.io", "mentions": 1, "avgPosition": 4, "byEngine": { "OPENAI": 1 } }, { "name": "PayPal", "domain": "paypal.com", "mentions": 1, "avgPosition": 4, "byEngine": { "ANTHROPIC": 1 } }, { "name": "AG2", "domain": "ag2.ai", "mentions": 1, "avgPosition": 4, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "OpenAI Agents SDK / AgentKit", "domain": "platform.openai.com", "mentions": 1, "avgPosition": 4, "byEngine": { "OPENAI": 1 } }, { "name": "OpenAI Swarm", "mentions": 1, "avgPosition": 4, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "AutoGPT", "domain": "github.com", "mentions": 1, "avgPosition": 5, "byEngine": { "OPENAI": 1 } }, { "name": "Sanity", "domain": "sanity.io", "mentions": 1, "avgPosition": 5, "byEngine": { "ANTHROPIC": 1 } }, { "name": "Hugging Face Agents", "domain": "huggingface.co", "mentions": 1, "avgPosition": 5, "byEngine": { "OPENAI": 1 } }, { "name": "LlamaIndex Agents", "domain": "github.com", "mentions": 1, "avgPosition": 5, "byEngine": { "GEMINI": 1 } }, { "name": "NetLogo", "domain": "netlogo.org", "mentions": 1, "avgPosition": 5, "byEngine": { "OPENAI": 1 } }, { "name": "Amazon Bedrock Agents", "domain": "aws.amazon.com", "mentions": 1, "avgPosition": 5, "byEngine": { "PERPLEXITY": 1 } }, { "name": "Agents SDK", "mentions": 1, "avgPosition": 5, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "AutoGen (Microsoft)", "domain": "microsoft.github.io", "mentions": 1, "avgPosition": 6, "byEngine": { "OPENAI": 1 } }, { "name": "Google ADK (Agent Development Kit)", "domain": "github.com", "mentions": 1, "avgPosition": 6, "byEngine": { "ANTHROPIC": 1 } }, { "name": "Akka", "domain": "doc.akka.io", "mentions": 1, "avgPosition": 6, "byEngine": { "OPENAI": 1 } }, { "name": "Rasa (Open Source)", "domain": "rasa.com", "mentions": 1, "avgPosition": 6, "byEngine": { "OPENAI": 1 } }, { "name": "Vercel AI SDK", "domain": "vercel.com", "mentions": 1, "avgPosition": 7, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "Ollama", "domain": "ollama.com", "mentions": 1, "avgPosition": 7, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "Azure AI Foundry", "domain": "microsoft.com", "mentions": 1, "avgPosition": 8, "byEngine": { "ANTHROPIC": 1 } }, { "name": "Temporal", "domain": "temporal.io", "mentions": 1, "avgPosition": 8, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "Vercel", "domain": "vercel.com", "mentions": 1, "avgPosition": 10, "byEngine": { "AI_OVERVIEW": 1 } }, { "name": "Next.js", "domain": "nextjs.org", "mentions": 1, "avgPosition": 11, "byEngine": { "AI_OVERVIEW": 1 } } ], "answers": [ { "prompt": 1, "engine": "OPENAI", "run": 1, "askedAt": "2026-10-09T01:27:57.647Z", "text": "1. **LangChain** — https://www.langchain.com — Best-in-class open-source agent framework and ecosystem for chaining LLM calls, tool integrations, and deploying agent workflows (strong community, tooling, and observability). ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\n2. **Microsoft Agent Framework (AutoGen + Semantic Kernel lineage)** — https://github.com/microsoft/agent-framework — Enterprise-grade, pro-code SDK that unifies AutoGen and Semantic Kernel patterns for robust multi-agent orchestration, state management, and observability. ([github.com](https://github.com/microsoft/autogen?utm_source=openai))\n\n3. **LlamaIndex** — https://www.llamaindex.ai — Agent- and retrieval-first framework focused on building context-aware agents and RAG applications with flexible data connectors and indexing. ([llamaindex.ai](https://www.llamaindex.ai/llamaindex?utm_source=openai))\n\n4. **Haystack (deepset)** — https://haystack.deepset.ai (docs) — Production-oriented framework for building agentic apps and scalable RAG/search pipelines with strong support for evaluation and long-context scenarios. ([docs.haystack.deepset.ai](https://docs.haystack.deepset.ai/docs?utm_source=openai))\n\n5. **AutoGPT (Significant-Gravitas project)** — https://github.com/Significant-Gravitas/Auto-GPT — Popular community starter for autonomous, long-running agent experiments and rapid prototyping of autonomous workflows. ([en.wikipedia.org](https://en.wikipedia.org/wiki/AutoGPT?utm_source=openai))\n\nNotes:\n- These are ranked for typical needs: 1) fastest to prototype with broad integrations (LangChain), 2) best for enterprise/multi-agent robustness (Microsoft Agent Framework), then specialist frameworks for retrieval and production RAG (LlamaIndex, Haystack) and community autonomous examples (AutoGPT). ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\nIf you want, I can immediately: recommend which of these fits your use case (prototype vs. production vs. enterprise), or show a short example of an agent built with the top pick.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Haystack", "domain": "haystack.deepset.ai" }, { "name": "AutoGPT", "domain": "github.com" } ], "sources": [ { "url": "https://www.langchain.com/langchain?utm_source=openai", "domain": "langchain.com", "title": "LangChain: Open Source AI Agent Framework for Any Model" }, { "url": "https://github.com/microsoft/autogen?utm_source=openai", "domain": "github.com", "title": "GitHub - microsoft/autogen: A programming framework for agentic AI · GitHub" }, { "url": "https://www.llamaindex.ai/llamaindex?utm_source=openai", "domain": "llamaindex.ai", "title": "AI Agent Framework For Context-Aware Apps | LlamaIndex OSS Frameworks" }, { "url": "https://docs.haystack.deepset.ai/docs?utm_source=openai", "domain": "docs.haystack.deepset.ai", "title": "Introduction to Haystack | Haystack Documentation" }, { "url": "https://en.wikipedia.org/wiki/AutoGPT?utm_source=openai", "domain": "en.wikipedia.org", "title": "AutoGPT" } ], "searchQueries": [ "LangChain framework agents LangChain website", "Microsoft Semantic Kernel agents framework website", "AutoGen framework Microsoft AutoGen agents", "LlamaIndex agent framework website", "AutoGPT project GitHub website", "AgentVerse framework for AI agents", "Haystack agents framework", "Ray AIR agents framework" ] }, { "prompt": 1, "engine": "OPENAI", "run": 2, "askedAt": "2026-10-09T01:28:47.915Z", "text": "1. **LangChain** — https://langchain.com \n Best for general-purpose, highly extensible agent development with the largest ecosystem of tool integrations and plugins. ([openhelm.ai](https://www.openhelm.ai/blog/langchain-vs-llamaindex-vs-haystack-agent-framework-comparison?utm_source=openai))\n\n2. **LlamaIndex** — https://llamaindex.ai \n Strongest choice when retrieval-augmented agents and document/RAG workflows are the primary concern. ([ai-agentsplus.com](https://www.ai-agentsplus.com/blog/comparing-ai-agent-frameworks-2026?utm_source=openai))\n\n3. **Microsoft Semantic Kernel (Agent Framework)** — https://learn.microsoft.com/semantic-kernel \n Enterprise-grade SDK (C#/Python/Java) with an agent framework and tight Azure/Microsoft integration for production deployments. ([learn.microsoft.com](https://learn.microsoft.com/semantic-kernel/frameworks/agent/?utm_source=openai))\n\n4. **Haystack (deepset)** — https://www.deepset.ai / https://docs.haystack.deepset.ai \n Modular, production-focused orchestration and RAG pipelines with built-in agent primitives for search + action flows. ([docs.haystack.deepset.ai](https://docs.haystack.deepset.ai/docs?utm_source=openai))\n\n5. **AutoGen (actor/multi-agent frameworks)** — https://github.com/microsoft/autogen (project/GitHub) \n Designed for multi-agent conversational workflows and complex actor coordination — a go-to for multi-agent collaboration patterns. ([cordum.io](https://cordum.io/blog/ai-agent-frameworks-comparison?utm_source=openai))\n\n6. **OpenAI Agents SDK** — https://platform.openai.com/docs/guides/agents (OpenAI docs) \n Lightweight, rapidly-evolving SDK for building agent experiences that align with OpenAI model features and hosted tools. ([aiunpacking.com](https://aiunpacking.com/blog/top-ai-agent-frameworks-2026/?utm_source=openai))\n\n7. **CrewAI / LangGraph (emerging orchestration frameworks)** — https://crew.ai (CrewAI) / https://langgraph.ai (LangGraph) \n Newer graph- and role-based orchestration frameworks focused on auditable, production-scale agent workflows and human-in-the-loop checkpoints. Good when you need explicit orchestration primitives. ([aiunpacking.com](https://aiunpacking.com/blog/top-ai-agent-frameworks-2026/?utm_source=openai))\n\nNotes (quick guidance):\n- Pick by orchestration style and constraints: if you need RAG-first agents pick LlamaIndex or Haystack; for broad tool/plugin breadth pick LangChain; for enterprise/Azure alignment pick Semantic Kernel; for multi-agent conversational systems pick AutoGen or specialized multi-agent SDKs. ([cordum.io](https://cordum.io/blog/ai-agent-frameworks-comparison?utm_source=openai))\n\nIf you want, I can rank these specifically for your project constraints (programming language, hosting, need for multi-agent coordination, RAG focus, compliance/enterprise requirements) and give a one-paragraph justification for the top choice.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Microsoft Semantic Kernel", "domain": "learn.microsoft.com" }, { "name": "Haystack", "domain": "deepset.ai" }, { "name": "AutoGen", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "CrewAI", "domain": "crew.ai" }, { "name": "LangGraph", "domain": "langgraph.ai" } ], "sources": [ { "url": "https://www.openhelm.ai/blog/langchain-vs-llamaindex-vs-haystack-agent-framework-comparison?utm_source=openai", "domain": "openhelm.ai", "title": "LangChain vs LlamaIndex vs Haystack: Agent Framework Comparison 2026 | OpenHelm" }, { "url": "https://www.ai-agentsplus.com/blog/comparing-ai-agent-frameworks-2026?utm_source=openai", "domain": "ai-agentsplus.com", "title": "Comparing AI Agent Frameworks 2026: LangChain vs LlamaIndex vs AutoGPT vs Semantic Kernel" }, { "url": "https://learn.microsoft.com/semantic-kernel/frameworks/agent/?utm_source=openai", "domain": "learn.microsoft.com", "title": "Semantic Kernel Agent Framework | Microsoft Learn" }, { "url": "https://docs.haystack.deepset.ai/docs?utm_source=openai", "domain": "docs.haystack.deepset.ai", "title": "Introduction to Haystack | Haystack Documentation" }, { "url": "https://cordum.io/blog/ai-agent-frameworks-comparison?utm_source=openai", "domain": "cordum.io", "title": "AI Agent Frameworks 2026: LangGraph vs CrewAI vs AutoGen" }, { "url": "https://aiunpacking.com/blog/top-ai-agent-frameworks-2026/?utm_source=openai", "domain": "aiunpacking.com", "title": "Top AI Agent Frameworks in 2026: LangGraph, CrewAI, OpenAI Agents SDK, and More" } ], "searchQueries": [ "best AI agent frameworks 2026 LangChain LlamaIndex Semantic Kernel AutoGen Haystack comparison", "LangChain agents 2026 features website", "LlamaIndex agents 2026 website", "Meta AutoGen framework agents 2025 2026 website", "Microsoft Semantic Kernel agents 2026 website", "deepset Haystack agents framework 2026 website" ] }, { "prompt": 1, "engine": "OPENAI", "run": 3, "askedAt": "2026-10-09T01:29:40.665Z", "text": "1. **LangGraph** — https://langgraph.dev — Best general-purpose, graph-oriented agent framework for building stateful, production-grade agent workflows. ([insideaimedia.com](https://insideaimedia.com/blogs/best-ai-agent-frameworks/?utm_source=openai))\n\n2. **CrewAI** — https://crew.ai — Strong multi-agent orchestration and debugging tooling for complex, coordinated agent teams. ([insideaimedia.com](https://insideaimedia.com/blogs/best-ai-agent-frameworks/?utm_source=openai))\n\n3. **Microsoft Agent Framework** — https://learn.microsoft.com/agent-framework (or Microsoft docs) — Enterprise-ready, production-focused framework (successor to Semantic Kernel/AutoGen) with strong governance and Bedrock/Cloud integrations. ([langchain.com](https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai))\n\n4. **OpenAI Agents SDK** — https://openai.com/agents (or OpenAI platform docs) — Simple, well-integrated SDK for rapidly building agentic flows with OpenAI models and first-class tooling. ([theairankings.com](https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai))\n\n5. **LangChain** — https://langchain.com — Flexible, widely adopted agent library with many integrations and a large community/ecosystem (still a top choice for prototyping and production pipelines). ([langchain.com](https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai))\n\n6. **Pydantic AI** — https://pydantic-ai.github.io (docs) — Type-safe, structured-output-first framework that makes agents more reliable and maintainable for Python teams. ([imiel.dev](https://imiel.dev/reports/state-of-ai-agents-q2-2026.pdf?utm_source=openai))\n\n7. **Mastra** — https://mastra.dev — TypeScript-first agent application framework focused on building production custom agents for web/native stacks. ([langchain.com](https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai))\n\nNotes: there is no single universally “best” framework — the right pick depends on language preference, scale, governance needs, and which model/provider you plan to use. The items above are the most-cited, production-oriented options in recent 2026 comparisons and reviews. ([toolradar.com](https://toolradar.com/guides/best-ai-agent-frameworks?utm_source=openai))", "brands": [ { "name": "LangGraph", "domain": "langgraph.dev" }, { "name": "CrewAI", "domain": "crew.ai" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "Pydantic AI", "domain": "pydantic-ai.github.io" }, { "name": "Mastra", "domain": "mastra.dev" } ], "sources": [ { "url": "https://insideaimedia.com/blogs/best-ai-agent-frameworks/?utm_source=openai", "domain": "insideaimedia.com", "title": "10 Best AI Agent Frameworks in 2026 (for Developers) - Inside AI Media" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai", "domain": "theairankings.com", "title": "Best AI Agent Frameworks in 2026: Ranked & Compared | The AI Rankings" }, { "url": "https://imiel.dev/reports/state-of-ai-agents-q2-2026.pdf?utm_source=openai", "domain": "imiel.dev", "title": "State of AI Agents Q2 2026" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks?utm_source=openai", "domain": "toolradar.com", "title": "Best AI Agent Frameworks in 2026 | Expert Guide | Toolradar" } ], "searchQueries": [ "best frameworks for building AI agents 2026", "agent frameworks for AI developers 2024 2025 2026 LangChain Ray Agentic Frameworks", "LangChain agents vs AutoGen vs Agentic vs BabyAGI vs Microsoft Semantic Kernel agents 2026", "Open-source agent frameworks list LangChain AutoGen Vectara Microsoft Semantic Kernel AutoGPT 2026" ] }, { "prompt": 1, "engine": "ANTHROPIC", "run": 1, "askedAt": "2026-10-09T01:27:52.136Z", "text": "I'll search for current information about the best frameworks for building AI agents.\nThere's no single \"best\" framework—it depends on your specific needs. However, here are the top frameworks ranked by current popularity and enterprise adoption:\n\n1. **LangChain** - \nA flexible, open-source framework for developing autonomous AI agents powered by LLMs, with modular architecture that allows prompt chaining and seamless integration with APIs and databases\n. Best for general-purpose agent development and when you need flexibility.\n\n2. **LangGraph** - \nA specialized agent framework within the LangChain ecosystem released in 2024 with over 33,900 GitHub stars and 34.5 million monthly downloads\n. \nIt focuses on building controllable, stateful agents that maintain context throughout interactions\n. Best for complex workflows.\n\n3. **CrewAI** - \nA framework for orchestrating role-playing AI agents that allows developers to create a \"crew\" of AI agents, each with specific roles and responsibilities, to work together on complex tasks\n. Best for beginners and multi-agent teamwork.\n\n4. **Microsoft AutoGen** - \nAn open-source framework designed to build advanced AI agents and multi-agent systems, providing a flexible and powerful toolkit for creating conversational and task-completing AI applications\n. Best for enterprise multi-agent collaboration.\n\n5. **OpenAI Agents SDK** - \nA lightweight Python framework released in March 2025 that focuses on creating multi-agent workflows with tracing and guardrails\n. Best for quick prototyping with OpenAI models.\n\n6. **Semantic Kernel** - \nMicrosoft's open-source SDK for building AI agents, offering seamless integration with LLMs such as OpenAI, Azure AI, and Hugging Face\n. Best for enterprise .NET/Python applications.\n\nChoose based on: \nBeginners should use CrewAI, experienced developers should use LangChain, and enterprise developers should use Semantic Kernel\n.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft AutoGen", "domain": "microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Semantic Kernel", "domain": "microsoft.com" } ], "sources": [ { "url": "https://deepchecks.com/best-ai-agent-frameworks/", "domain": "deepchecks.com", "title": "Best 10 AI Agent Frameworks for 2025" }, { "url": "https://medium.com/@dev-infinity101/top-5-frameworks-for-building-ai-agents-in-2025-ddacc314f19f", "domain": "medium.com", "title": "Top 5 Frameworks for Building AI Agents in 2025" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.analyticsvidhya.com/blog/2024/07/ai-agent-frameworks/", "domain": "analyticsvidhya.com", "title": "Top 7 Frameworks for Building AI Agents in 2026" }, { "url": "https://www.ai21.com/knowledge/ai-agent-frameworks/", "domain": "ai21.com", "title": "Top 12 AI Agent Frameworks for Enterprises in 2025" }, { "url": "https://www.codecademy.com/article/top-ai-agent-frameworks-in-2025", "domain": "codecademy.com", "title": "Top AI Agent Frameworks in 2025" }, { "url": "https://machinelearningmastery.com/7-ai-agent-frameworks-for-machine-learning-workflows-in-2025/", "domain": "machinelearningmastery.com", "title": "7 AI Agent Frameworks for Machine Learning Workflows in 2025 - MachineLearningMastery.com" }, { "url": "https://www.secondtalent.com/resources/top-llm-frameworks-for-building-ai-agents/", "domain": "secondtalent.com", "title": "Top 8 LLM Frameworks for Building AI Agents in 2026 - Second Talent" }, { "url": "https://www.effectivesoft.com/blog/top-frameworks-for-building-ai-agents.html", "domain": "effectivesoft.com", "title": "Best AI Agent Frameworks in 2026: Features, Pros & Use Cases - EffectiveSoft" } ], "searchQueries": [ "best frameworks building AI agents 2024 2025" ] }, { "prompt": 1, "engine": "ANTHROPIC", "run": 2, "askedAt": "2026-10-09T01:28:42.450Z", "text": "I'll search for current information on the best frameworks for building AI agents.\nThere isn't a single \"best\" framework—the right choice depends on your specific needs. However, here are the top frameworks ranked by current adoption and use cases:\n\n1. **LangGraph** - https://github.com/langchain-ai/langgraph\n \nBest overall for serious developers; most likely to work correctly when your system hits real users, edge cases, and compliance reviews\n.\n\n2. **LangChain** - https://www.langchain.com/\n \nMost widely adopted open-source framework with ~134k GitHub stars and 1,000+ pre-built integrations\n.\n\n3. **CrewAI** - https://www.crewai.com/\n \nBest beginner-friendly multi-agent framework for quick role-playing task distributions\n.\n\n4. **OpenAI Agents SDK** - https://github.com/openai/agents-js\n \nLightweight design with multi-agent workflows and 100+ LLM support; good for quick prototyping\n.\n\n5. **AutoGen (AG2)** - https://github.com/ag2-ai/ag2\n \nEvent-driven architecture; GAIA benchmark leader for complex multi-agent systems\n.\n\n6. **Mastra** - https://mastra.ai/\n \nBest for TypeScript teams building production custom agents\n.\n\n**Quick decision guide:** \nFor TypeScript product teams start with Mastra; for Python teams with heavy orchestration needs, LangGraph; for OpenAI-committed teams, the Agents SDK\n.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "AutoGen (AG2)", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.lindy.ai/blog/best-ai-agent-frameworks", "domain": "lindy.ai", "title": "Top 10 AI Agent Frameworks (2026): Expert-Tested & Reviewed" }, { "url": "https://www.spaceotechnologies.com/blog/ai-agent-frameworks/", "domain": "spaceotechnologies.com", "title": "Top AI Agent Frameworks in 2026: Which One Should You Use?" }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single One)" }, { "url": "https://www.analyticsinsight.net/artificial-intelligence/best-ai-agent-frameworks-in-2026-features-pros-cons-use-cases", "domain": "analyticsinsight.net", "title": "Best AI Agent Frameworks in 2026: Features, Pros, Cons, Use Cases" }, { "url": "https://www.secondtalent.com/resources/top-llm-frameworks-for-building-ai-agents/", "domain": "secondtalent.com", "title": "Top 8 LLM Frameworks for Building AI Agents in 2026 - Second Talent" }, { "url": "https://alphacorp.ai/blog/the-8-best-ai-agent-frameworks-in-2026-a-developers-guide", "domain": "alphacorp.ai", "title": "The 8 Best AI Agent Frameworks in 2026: A Developer’s Guide" }, { "url": "https://aimlinsights.com/2026/04/13/best-ai-agent-frameworks-for-developers/", "domain": "aimlinsights.com", "title": "Best AI Agent Frameworks in 2026 for Building Real Applications » AIML Insights" } ], "searchQueries": [ "best frameworks building AI agents 2026" ] }, { "prompt": 1, "engine": "ANTHROPIC", "run": 3, "askedAt": "2026-10-09T01:29:39.115Z", "text": "I'll search for current information on the best frameworks for building AI agents.\nThere's no single \"best\" framework—the choice depends on your specific needs. However, here are the top frameworks ranked by common use cases:\n\n## General Purpose (Most Widely Adopted)\n\n\n**LangChain** is the most widely adopted open-source framework for building AI agents and LLM applications, with ~134k GitHub stars and more than 1,000 pre-built integrations\n. \nIt's best if you need an open-source framework for rapid prototyping across model providers, paired with LangGraph for stateful multi-agent orchestration, Deep Agents for long-running workflows, and LangSmith for enterprise-grade observability\n.\n\n## Production-Grade with Complex Workflows\n\n\n**LangGraph** is the best overall AI agent framework for serious developers—not the fastest to set up, but most likely to work correctly when your system hits real users, real edge cases, and real compliance reviews\n.\n\n## Quick Multi-Agent Setup\n\n\n**CrewAI** is the best beginner-friendly multi-agent framework for quick role-playing task distributions\n. \nIt's better for quick multi-agent setups with minimal code\n.\n\n## TypeScript/JavaScript Teams\n\n\nFor TypeScript product teams, start with **Mastra**\n. \nTypeScript lets full-stack teams build agents inside the same codebase as their web application, with compile-time type safety, and Mastra is one of the two leading TypeScript-first options\n.\n\n## Provider-Specific\n\n\nFor OpenAI-committed teams, the **OpenAI Agents SDK**\n is recommended. \nFor teams committed to Anthropic's models building autonomous agents, the **Claude Agent SDK**\n is available.\n\n## Document-Heavy & RAG Applications\n\n\n**LlamaIndex** remains a strong choice for document-heavy agents, retrieval-augmented generation, enterprise knowledge systems, with strength centered on data connectors, retrieval, extraction, and agent workflows\n.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Deep Agents" }, { "name": "LangSmith", "domain": "smith.langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Claude Agent SDK", "domain": "anthropic.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.lindy.ai/blog/best-ai-agent-frameworks", "domain": "lindy.ai", "title": "Top 10 AI Agent Frameworks (2026): Expert-Tested & Reviewed" }, { "url": "https://www.spaceotechnologies.com/blog/ai-agent-frameworks/", "domain": "spaceotechnologies.com", "title": "Top AI Agent Frameworks in 2026: Which One Should You Use?" }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single One)" }, { "url": "https://www.analyticsinsight.net/artificial-intelligence/best-ai-agent-frameworks-in-2026-features-pros-cons-use-cases", "domain": "analyticsinsight.net", "title": "Best AI Agent Frameworks in 2026: Features, Pros, Cons, Use Cases" }, { "url": "https://www.secondtalent.com/resources/top-llm-frameworks-for-building-ai-agents/", "domain": "secondtalent.com", "title": "Top 8 LLM Frameworks for Building AI Agents in 2026 - Second Talent" }, { "url": "https://alphacorp.ai/blog/the-8-best-ai-agent-frameworks-in-2026-a-developers-guide", "domain": "alphacorp.ai", "title": "The 8 Best AI Agent Frameworks in 2026: A Developer’s Guide" }, { "url": "https://aimlinsights.com/2026/04/13/best-ai-agent-frameworks-for-developers/", "domain": "aimlinsights.com", "title": "Best AI Agent Frameworks in 2026 for Building Real Applications » AIML Insights" } ], "searchQueries": [ "best frameworks building AI agents 2026" ] }, { "prompt": 1, "engine": "PERPLEXITY", "run": 1, "askedAt": "2026-10-09T01:27:46.990Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production agents requiring explicit state, controllable workflows, persistence, and human approval; it is widely identified as a leading choice for complex agent orchestration.[1][3]\n\n2. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for quickly building code-first agents with tools, handoffs, guardrails, and tracing in OpenAI-centric applications.\n\n3. **CrewAI** — https://www.crewai.com/ — Best for straightforward role-based multi-agent systems, with a simpler development model than graph-oriented frameworks.[2][8]\n\n4. **Google Agent Development Kit** — https://google.github.io/adk-docs/ — Best for teams building on Google Cloud and Gemini, particularly workflows that run agents sequentially, in parallel, or in loops.[10]\n\n5. **LlamaIndex** — https://www.llamaindex.ai/ — Best for document-heavy and RAG agents, with event-driven workflows available in Python and TypeScript.[3][7]\n\n6. **Mastra** — https://mastra.ai/ — Best for TypeScript teams wanting an integrated production stack covering agents, workflows, memory, RAG, evaluations, guardrails, and tracing.[4][5]\n\n7. **Microsoft Agent Framework** — https://github.com/microsoft/agent-framework — Best for Microsoft/Azure environments and developers combining enterprise orchestration with Microsoft model and cloud services.\n\n**Top pick:** **LangGraph** for the best balance of production control, flexibility, and ecosystem maturity. AutoGen is less attractive for a new project because current comparisons describe it as being in maintenance mode.[1]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Google Agent Development Kit", "domain": "google.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Microsoft Agent Framework", "domain": "github.com" } ], "sources": [ { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/", "domain": "scrimba.com", "title": "scrimba.com › articles › best-ai-agent-frameworksBest AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://www.lindy.ai/blog/ai-agent-frameworks", "domain": "lindy.ai", "title": "Best 10 AI Agent Frameworks [We've Built Them for 3 Years]" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://mastra.ai/blog/best-ai-agent-frameworks", "domain": "mastra.ai", "title": "The 6 Best AI Agent Frameworks (July 2026): Features, Tradeoffs ..." }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single ..." }, { "url": "https://www.turingpost.com/p/frameworks-sdks", "domain": "turingpost.com", "title": "13 Frameworks and SDKs for Building AI Agents" }, { "url": "https://www.dataiku.com/blog/ai-agent-frameworks", "domain": "dataiku.com", "title": "Best AI agent frameworks (2026) - Dataiku" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in ..." }, { "url": "https://www.analyticsinsight.net/amp/story/artificial-intelligence/ai-agent-frameworks-complete-guide-to-building-autonomous-ai-agents-in-2026", "domain": "analyticsinsight.net", "title": "AI Agent Frameworks: Complete Guide to Building Autonomous AI Agents in 2026" }, { "url": "https://www.chatbot.com/blog/ai-agent-frameworks/", "domain": "chatbot.com", "title": "AI Agent Frameworks: 10 Options, One Guide, Zero Fluff - ChatBot" } ], "searchQueries": "not exposed" }, { "prompt": 1, "engine": "PERPLEXITY", "run": 2, "askedAt": "2026-10-09T01:28:42.932Z", "text": "No single framework is best for every project; **LangGraph** is the strongest general-purpose choice for production agents because it provides explicit state, durable workflows, human approval, and observability.[1][3]\n\n1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for reliable, stateful, production-grade agents and complex workflows.[1][3]\n2. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for quickly building code-first agents tightly integrated with OpenAI models and tools.\n3. **CrewAI** — https://www.crewai.com/ — Best for straightforward role-based multi-agent teams and fast prototypes.[8]\n4. **Google Agent Development Kit (ADK)** — https://google.github.io/adk-docs/ — Best for Google Cloud-oriented applications with sequential, parallel, and looping agent workflows.[10]\n5. **LlamaIndex** — https://www.llamaindex.ai/ — Best for agents grounded in private documents, databases, and retrieval-heavy applications.[3][7]\n6. **Mastra** — https://mastra.ai/ — Best for TypeScript teams wanting agents, workflows, memory, RAG, evaluations, guardrails, and tracing in one stack.[4][5]\n7. **Microsoft AutoGen** — https://microsoft.github.io/autogen/ — Best for existing multi-agent prototypes, but less attractive for new projects because it is reportedly in maintenance mode.[1]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Google Agent Development Kit (ADK)", "domain": "google.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" } ], "sources": [ { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/", "domain": "scrimba.com", "title": "scrimba.com › articles › best-ai-agent-frameworksBest AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://www.lindy.ai/blog/ai-agent-frameworks", "domain": "lindy.ai", "title": "Best 10 AI Agent Frameworks [We've Built Them for 3 Years]" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://mastra.ai/blog/best-ai-agent-frameworks", "domain": "mastra.ai", "title": "The 6 Best AI Agent Frameworks (July 2026): Features, Tradeoffs ..." }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single ..." }, { "url": "https://www.turingpost.com/p/frameworks-sdks", "domain": "turingpost.com", "title": "13 Frameworks and SDKs for Building AI Agents" }, { "url": "https://www.dataiku.com/blog/ai-agent-frameworks", "domain": "dataiku.com", "title": "Best AI agent frameworks (2026) - Dataiku" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in ..." }, { "url": "https://www.analyticsinsight.net/amp/story/artificial-intelligence/ai-agent-frameworks-complete-guide-to-building-autonomous-ai-agents-in-2026", "domain": "analyticsinsight.net", "title": "AI Agent Frameworks: Complete Guide to Building Autonomous AI Agents in 2026" }, { "url": "https://www.chatbot.com/blog/ai-agent-frameworks/", "domain": "chatbot.com", "title": "AI Agent Frameworks: 10 Options, One Guide, Zero Fluff - ChatBot" } ], "searchQueries": "not exposed" }, { "prompt": 1, "engine": "PERPLEXITY", "run": 3, "askedAt": "2026-10-09T01:29:39.382Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production agents requiring explicit state, controllable workflows, persistence, and debugging; current comparisons commonly rank it first for reliability and orchestration.[1][3]\n\n2. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for quickly building tool-using agents with handoffs, tracing, and a streamlined OpenAI-native developer experience.\n\n3. **CrewAI** — https://www.crewai.com/ — Best for straightforward role-based multi-agent systems and rapid deployment without complex orchestration.[8]\n\n4. **Google Agent Development Kit (ADK)** — https://google.github.io/adk-docs/ — Best for teams building on Google Cloud or Gemini, with support for sequential, parallel, and looping agent workflows.[10]\n\n5. **LlamaIndex Workflows** — https://www.llamaindex.ai/ — Best for document-heavy agents and retrieval-augmented applications; its event-driven workflows support Python and TypeScript multi-agent systems.[3][7]\n\n6. **Mastra** — https://mastra.ai/ — Best TypeScript-first option with agents, workflows, memory, RAG, evaluations, guardrails, tracing, and a local visual studio in one stack.[4][5]\n\n7. **Microsoft AutoGen** — https://microsoft.github.io/autogen/ — Best for existing multi-agent prototypes and conversational agent experiments, but it is less attractive for new projects because current coverage describes it as being in maintenance mode.[1]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Google Agent Development Kit (ADK)", "domain": "google.github.io" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" } ], "sources": [ { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/", "domain": "scrimba.com", "title": "scrimba.com › articles › best-ai-agent-frameworksBest AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://www.lindy.ai/blog/ai-agent-frameworks", "domain": "lindy.ai", "title": "Best 10 AI Agent Frameworks [We've Built Them for 3 Years]" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://mastra.ai/blog/best-ai-agent-frameworks", "domain": "mastra.ai", "title": "The 6 Best AI Agent Frameworks (July 2026): Features, Tradeoffs ..." }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single ..." }, { "url": "https://www.turingpost.com/p/frameworks-sdks", "domain": "turingpost.com", "title": "13 Frameworks and SDKs for Building AI Agents" }, { "url": "https://www.dataiku.com/blog/ai-agent-frameworks", "domain": "dataiku.com", "title": "Best AI agent frameworks (2026) - Dataiku" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in ..." }, { "url": "https://www.analyticsinsight.net/amp/story/artificial-intelligence/ai-agent-frameworks-complete-guide-to-building-autonomous-ai-agents-in-2026", "domain": "analyticsinsight.net", "title": "AI Agent Frameworks: Complete Guide to Building Autonomous AI Agents in 2026" }, { "url": "https://www.chatbot.com/blog/ai-agent-frameworks/", "domain": "chatbot.com", "title": "AI Agent Frameworks: 10 Options, One Guide, Zero Fluff - ChatBot" } ], "searchQueries": "not exposed" }, { "prompt": 1, "engine": "GEMINI", "run": 1, "askedAt": "2026-10-09T01:27:46.822Z", "text": "The \"best\" framework depends largely on your use case, language, and production requirements (such as state management and type safety). \n\nThe top-ranked frameworks for building AI agents, categorized by their strengths, include:\n\n1. **LangGraph**\n * Website: [langchain.com/langgraph](https://www.langchain.com/langgraph)\n * The enterprise standard for complex, stateful multi-step agent graphs requiring durable execution, cyclic loops, and database check-pointing.\n\n2. **CrewAI**\n * Website: [crewai.com](https://www.crewai.com)\n * Best for setting up collaborative, role-based multi-agent teams with a fast development cycle and intuitive task delegation.\n\n3. **PydanticAI**\n * Website: [ai.pydantic.dev](https://ai.pydantic.dev)\n * A lightweight, type-safe Python framework that brings FastAPI-style dependency injection and rigorous data validation to agentic workflows.\n\n4. **OpenAI Agents SDK**\n * Website: [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python)\n * A minimalist, low-overhead option optimized for developers committed to the OpenAI ecosystem who need seamless tool calling and quick agent handoffs.\n\n5. **Mastra**\n * Website: [mastra.ai](https://mastra.ai)\n * A comprehensive TypeScript framework that packages agent execution, workflows, built-in memory, and RAG document retrieval for Node.js developers.\n\n6. **Smolagents**\n * Website: [github.com/huggingface/smolagents](https://github.com/huggingface/smolagents)\n * Hugging Face’s ultra-minimalist Python framework that keeps codebases small and transparent, allowing developers to write code-driven agents easily.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Smolagents", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFqktgPzmKHHa91p3ou3vOgpxP4MLVp99az6dLusXRgDTYYzGjKGWCxqJFJB3wvRlwpC5xyCuLneyeJY-meJbjhceAkE13guI-wrRrorL3j5b3tmvF38xWKr3jizTpcVGTlEO44QxR0pG43azs=", "domain": "browser-use.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFnTAYgIYhj8jxyxFzbNO6WXsS890x9FXelBdOyOglOMvEOShlUMr2WeR0TKbYc3azcDxgW65knAne0_VslCe9hAqkaX8Vr7miN_vvUaq62Ipw5KWhMoATshUhchZKQDjPygB_LSZUl_SreGjUM5dGxkFqp2jU=", "domain": "aiagentskit.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE1BXPbgaLHdHh6Fp1nKB8DjQGPgjbLoYqQQw80Yr0Ppeqq96Y5THVVEMAHipQOwumcJhZMYxmDmGNjTye_nlIHR5TuMmakWc0MISh2eNlHm0-xJnYLmcfPul2sR0Ey3SOHveEFnbnkQrGr_VNO039gtN-A3Dw=", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGvTlV6mMcohUwKZguqCFzVzHkST9C4KF1flOepfWRFe-oYgJ-U3JOu_vyajz_SCKe-z9DrFu9DAeogLFcgnmwD8kE-hyIn1c1Q3IHf-oNWeywlpuTdp1DDlftvhCA5-hdCeDwuzpMAAm7u77mA0_D0RWlc2TR2Jc0sUjwDICSp7AUixL3FEb7AZ2SSkvaGl-eIl3aXZEGfIWPrVNc76RahAyqm", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHXCLJK44_Aoe-l1RMzl1OMYVSUWlTYlCGciF2_S4UVzPGSeiJi2Coc1_6ALDZN4PB4b5m5Yv4LDVy-2PUNi4eNfAX4Umqamn2S2F0mP0BB4AJDLHOTIvg4tR146cxBaacIsV5su_q-qLyqrbDZaELq2M0f2EEWuO2N0DTqIehc7aXAQFk8N57l7NSo4ulc0wGJVeu2P3EbLOUwoJxhwf3zRhl8izPQMH_Ctv3e9J_JulR3czy5XiiothEpLJbR", "domain": "towardsai.net" } ], "searchQueries": [ "top AI agent frameworks python", "best framework for building AI agents 2026" ] }, { "prompt": 1, "engine": "GEMINI", "run": 2, "askedAt": "2026-10-09T01:28:46.417Z", "text": "1. **LangGraph**\n - Website: [langchain.com/langgraph](https://www.langchain.com/langgraph)\n - The enterprise standard for complex, stateful multi-step agent graphs requiring durable execution, cyclic routing, and time-travel debugging.\n\n2. **CrewAI**\n - Website: [crewai.com](https://www.crewai.com)\n - The leading framework for rapidly building collaborative, role-based multi-agent teams that tackle end-to-end tasks together.\n\n3. **PydanticAI**\n - Website: [ai.pydantic.dev](https://ai.pydantic.dev)\n - A minimalist, type-safe Python framework that brings FastAPI-style dependency injection and rigorous data validation to agent tools.\n\n4. **OpenAI Agents SDK**\n - Website: [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python)\n - A lightweight, native minimal framework optimized for fast setup of single or multi-agent handoffs directly inside the OpenAI ecosystem.\n\n5. **Mastra**\n - Website: [mastra.ai](https://mastra.ai)\n - A comprehensive open-source TypeScript framework integrating agent execution, workflows, advanced memory, and document retrieval for web stacks.\n\n6. **Smolagents**\n - Website: [github.com/huggingface/smolagents](https://github.com/huggingface/smolagents)\n - Hugging Face's ultra-minimalist Python framework where core agent loops and tool-calling code are small enough to read and modify entirely in an afternoon.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Smolagents", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEt7t0me00RfdOyS5MYPGnmkSFCYsH4bE7VreElSey1EPeaXwbPJ87Ev8PNr7GRchEYUGwPLvo7CIFf1lhx4LOJxjkre9dbSE75eMYbHbQa9PBseWsqsG1LdWHJ9kRwGzZsA0VlL0tJYt-xIKPxKIKVXgQOStA=", "domain": "aiagentskit.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGg9zduZez_QvRnn-ALj-OISLKIG2_FZdSKZNlE2BrRc5x38pJKF9mybTuE_SyaJeUR9UBByZDA8YnbxNokdpg4ztWBaXqA7mB9Kw8IFKqHpyiecQ7Z39SUALxw34QGCH7sQIBJKQHLg7ge56WQYoCE6v1dglRgtmPVadaWkUUcRO2sWTgp7zNAfjKZcKnk_bfPljX83B18qG6VSCoB5aVi7gY5", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGMaanBwLxpx8gRzIp4Zkc6wxO_Qwu41VBN8eDob-ywCMdO8YLU11UHVO722MM-0ZN-1VI4ctSFhOFVRrjx0FpwW1vwv8Qo34qoyOYl9r08SKRu0I0G8vabXsThkQojL354YyzWq5l1jBLYLZo=", "domain": "browser-use.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE2d3vgSKf6ESqdV9T1DaUut_WkHNyBbK1x08fhXhNH82VMrPA1qpECBcdRzEOgG-_4JEzzZt10EMw02ytfBN2F5KoLa6PfUAvIkQSmVY2XJ_qr156Vlicd7bCdd0xJG7NDIuhsgGrsVrt704R28gdiH1ZmBKA-l8kr9VMS1Kn7pdAb3wtEI3kS8RF6oSkL3xgnme-zYNFrBuSzAWttrReSYBNfxkHAOzlsRHIW1Kd1aYDRPr4RFD8p4stFI_1F", "domain": "towardsai.net" } ], "searchQueries": [ "top AI agent frameworks python", "best framework for building AI agents 2026" ] }, { "prompt": 1, "engine": "GEMINI", "run": 3, "askedAt": "2026-10-09T01:29:43.384Z", "text": "1. **LangGraph** \n https://www.langchain.com/langgraph \n The industry standard for complex, stateful multi-agent systems and cyclic workflows, offering fine-grained control over execution steps and state persistence.\n\n2. **CrewAI** \n https://www.crewai.com \n An intuitive framework designed for rapidly building role-based, collaborative multi-agent teams that execute end-to-end automated tasks.\n\n3. **PydanticAI** \n https://ai.pydantic.dev \n A lightweight, highly typed Python framework that brings FastAPI-style dependency injection and rigorous data validation to agentic workflows.\n\n4. **OpenAI Agents SDK** \n https://github.com/openai/openai-agents-python \n A minimalist and streamlined toolkit designed by OpenAI for seamlessly managing lightweight agent loops, handoffs, and tool execution natively.\n\n5. **Mastra** \n https://mastra.ai \n A comprehensive TypeScript framework that unifies agent execution, workflow orchestration, built-in memory, and document retrieval for web stacks.\n\n6. **Smolagents** \n https://github.com/huggingface/smolagents \n Hugging Face’s ultra-minimalist library that enables code-based agents in under a thousand lines of code, prioritizing transparency and ease of reading.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "PydanticAI", "domain": "pydantic.dev" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Smolagents", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGQBcKxoSi3ZpKZ_SnNBpJHyT6DKDhBuRplMgi9r_SnjCl4MhdRFz_i8Lqb120YCzcJCq0qVwHs8YOkFCMi-BXOFWfRawaYQzmO-_HGgJnoSTeliAMS7GVssTe_kVsaKX1wEb5cVYzRU2EjOgpYp6JRaA==", "domain": "agentmail.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGeuSbczH_sXLVuGnd8-IRRPowO6hoGtGy1k9LifysDUGXkWgv4RPXJrWqWc6x1cU_jycl4xd3kOSgH_OYIKVZSPRrIr-nLSK4Nd_qAYOwWr6IcscLwfVsK-6_foD7Ux3i3daEmqh0a8Bp4t2gS2hNFnkYAEvM=", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGQbjj5EhEBBklIKPplZOCtvC2_HE1dVQW704J_lV2Dn-KQ-GFjLXXWG6PQIOZWN8y-BLGIznBb8X8HQxWJYn8r3SVeMv2L7Fw2l5Z8Nqs_5i77M9RisLwQ_PPFkNz-cAH2GXXRNibkfPxp3o8VFEAb5Ld_5XA=", "domain": "aiagentskit.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHz9C19-MgsBpNoMsyBJW_JeLIhjZyB9LCf6a1ZHdg3RIxUnkbpGxBfYZB_NFg3v13j-55_E5GVrbmdhf8Dc5Ltw-utZauN30R4ylU0wQcf-5k9QWCf9H6yDEC-CVkbzo3KQV3UvbXc3N-gkxd51x9B8FJRsT9CR1m_5JxL5uZj6kZK0HevZ3gGqDKBCduj7E9fvix783iEsMjswGZPdaZtFG46", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQES-xSGeeVA5nv3c8MyeOmZUQQXJVAzYLDyMpphjggFx0kaSNEnPK-PLfWDezdUYesCljiFdUeXx0Ysv-ODAthcMuzrfGJA8Dw4aD9FWZ7ORhQ3JhLUNeiAeEXFE5md1I8KgiwXkesgRO9aWBU=", "domain": "browser-use.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF9JR-wfEzvaNizeGaU1cURelX7CGGAMKoNY72HyJ9L4bDaJ0aDyBdyx5JD_dyly2chuEEEKf-dUL8stv9rpErUeuxqCd30z5irgvBitDQ11dsciTnu939HbbD5O_U6qoSuIUmKLHMXc1pN-6tDZVbCqVd6ckYLuh5ftcW-YbG323ODUME8MhhyKc2hp8-iXsmhtBB88uitDaqlp-4Cn4zDAh9io1aJacoWp7szOLEKfZ_9zt-MjUmJJOBd0iIE", "domain": "towardsai.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGE8gVtlpkprTtyHCq9thP-iWwBdGrHJb4Df86zjE71BtVl9lVs25Jv_5HzsxQ9WnUSMYk76xC35iVlPOcwLX1Scq-DBHtmYL234Q-YREg-X9p-XyzGDIT8C_wBiSGChrPWyfh5Gh6rCjhO0zMovXv5hfGSM-IInStpv1N8oF0tfEe9jbDI", "domain": "kdnuggets.com" } ], "searchQueries": [ "top AI agent frameworks python", "best framework for building AI agents 2026" ] }, { "prompt": 1, "engine": "GROK", "run": 1, "askedAt": "2026-10-09T01:28:01.983Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice for complex, stateful production agents with explicit graphs, checkpointing, and human-in-the-loop support.[[1]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**2. CrewAI** \nhttps://www.crewai.com \nExcellent for rapid role-based multi-agent teams and collaborative workflows with clear task assignment.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**3. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/guides/agents \nSimplest path for lightweight, tool-using agents with handoffs and guardrails, especially OpenAI-native apps.[[3]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**4. Microsoft Agent Framework** \nhttps://learn.microsoft.com/en-us/semantic-kernel/ \nStrong enterprise option for .NET/Python teams in Azure ecosystems with graph workflows and durable execution.[[4]](https://theairankings.com/best-ai-agent-frameworks/)\n\n**5. Google ADK** \nhttps://developers.google.com/agent-development-kit \nVersatile multi-language toolkit (Python, TS, Go, Java) optimized for Gemini and Google Cloud deployments.[[3]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**6. Mastra** \nhttps://mastra.ai \nBatteries-included TypeScript framework ideal for full-stack TS teams building agents with memory and workflows.[[5]](https://blog.logrocket.com/ai-agent-frameworks-2026/)\n\n**7. Pydantic AI** \nhttps://ai.pydantic.dev \nBest for type-safe Python agents with validated outputs and easy model swapping.[[4]](https://theairankings.com/best-ai-agent-frameworks/)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "Google ADK", "domain": "google.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Pydantic AI", "domain": "pydantic.dev" } ], "sources": [ { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://theairankings.com/best-ai-agent-frameworks/", "domain": "theairankings.com" }, { "url": "https://blog.logrocket.com/ai-agent-frameworks-2026/", "domain": "blog.logrocket.com" } ], "searchQueries": [ "best AI agent frameworks 2026", "top frameworks for building AI agents", "best open source AI agent frameworks" ] }, { "prompt": 1, "engine": "GROK", "run": 2, "askedAt": "2026-10-09T01:28:57.520Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop pick for complex, stateful production agents needing branching logic, persistence, and observability.[[1]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**2. CrewAI** \nhttps://crewai.com \nBest for fast role-based multi-agent teams with clear collaboration and quick prototypes.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**3. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/agents \nSimplest path for lightweight, tool-using agents with clean handoffs in OpenAI ecosystems.[[1]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**4. Google ADK (Agent Development Kit)** \nhttps://developers.google.com \nStrong multi-language support and native integration for Gemini/Google Cloud stacks.[[3]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**5. Microsoft Agent Framework** \nhttps://microsoft.com \nEnterprise choice for .NET/Azure teams with stable workflows and governance features.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**6. Mastra** \nhttps://mastra.ai \nExcellent TypeScript-native option combining agents, workflows, memory, and evaluations.[[4]](https://browser-use.com/posts/best-ai-agent-frameworks)\n\n**7. Pydantic AI** \nhttps://docs.pydantic.dev \nIdeal for type-safe Python agents with structured outputs and validation.[[5]](https://theairankings.com/best-ai-agent-frameworks/)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI", "domain": "openai.com" }, { "name": "Google", "domain": "google.com" }, { "name": "Microsoft", "domain": "microsoft.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Pydantic AI", "domain": "pydantic.dev" } ], "sources": [ { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://browser-use.com/posts/best-ai-agent-frameworks", "domain": "browser-use.com" }, { "url": "https://theairankings.com/best-ai-agent-frameworks/", "domain": "theairankings.com" } ], "searchQueries": [ "best AI agent frameworks 2026", "top frameworks for building AI agents" ] }, { "prompt": 1, "engine": "GROK", "run": 3, "askedAt": "2026-10-09T01:29:53.556Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice in 2026 for production-grade, stateful agents with explicit graphs, checkpointing, human-in-the-loop, and observability used by enterprises like Uber and Klarna.[[1]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**2. CrewAI** \nhttps://www.crewai.com \nBest for fast role-based multi-agent teams and prototypes with simple crew/task definitions and high GitHub adoption.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**3. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/agents \nCleanest lightweight option for tool-using agents, handoffs, guardrails, and tracing with OpenAI models.[[3]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**4. Google ADK** \nhttps://developers.google.com/agent-development-kit \nStrong multi-language (Python, TS, Go, Java) support and workflows for Gemini/Google Cloud ecosystems with A2A patterns.[[4]](https://theairankings.com/best-ai-agent-frameworks/)\n\n**5. Microsoft Agent Framework** \nhttps://learn.microsoft.com/semantic-kernel \nEnterprise-ready for .NET/Azure teams with stable 1.0 release, graph workflows, and migration path from AutoGen/Semantic Kernel.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**6. Mastra** \nhttps://mastra.ai \nBatteries-included TypeScript framework ideal for agents, workflows, memory, and evaluations in JS/TS stacks.[[5]](https://browser-use.com/posts/best-ai-agent-frameworks)\n\n**7. Pydantic AI** \nhttps://ai.pydantic.dev \nExcellent type-safe Python agents with validated outputs, dependencies, and model-agnostic support.[[4]](https://theairankings.com/best-ai-agent-frameworks/)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Google ADK", "domain": "developers.google.com" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Pydantic AI", "domain": "ai.pydantic.dev" } ], "sources": [ { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://theairankings.com/best-ai-agent-frameworks/", "domain": "theairankings.com" }, { "url": "https://browser-use.com/posts/best-ai-agent-frameworks", "domain": "browser-use.com" } ], "searchQueries": [ "best AI agent frameworks 2026", "top frameworks for building AI agents", "LangChain vs CrewAI vs AutoGen vs LlamaIndex vs Semantic Kernel 2026" ] }, { "prompt": 1, "engine": "AI_OVERVIEW", "run": 1, "askedAt": "2026-10-10T15:13:34.715Z", "text": "The best AI agent framework depends on your specific goal, with **LangGraph** ranking as the top choice for complex, deterministic production systems, and **CrewAI** leading for fast, role-based multi-agent prototypes.[[1]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[2]](https://www.langchain.com/resources/ai-agent-frameworks)\n\n- **LangGraph**:\n\t- **Best for:** Production-grade, stateful, and multi-step workflows.\n\t- **Key features:** Uses a graph-based mental model (nodes and edges) for explicit state transitions, native human-in-the-loop checkpoints, and strict audit trails.[[1]](https://www.reddit.com/r/AI_Agents/comments/1kjowzp/whats_the_best_framework_for_productiongrade_ai/)[[2]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)\n- **CrewAI**:\n\t- **Best for:** Rapid prototyping of role-based teams (such as writers, researchers, and editors).\n\t- **Key features:** Intuitive setup, fast time-to-demo, and structured task delegation pipelines.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)[[2]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)\n- **Microsoft Agent Framework (AutoGen 2.0 / Semantic Kernel successor)**:\n\t- **Best for:** Enterprise .NET and Azure-native environments.\n\t- **Key features:** Async engine, conversational multi-agent dynamics, and built-in responsible AI guardrails through Azure AI Foundry.[[1]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[2]](https://www.langchain.com/resources/ai-agent-frameworks)\n- **LlamaIndex Workflows**:\n\t- **Best for:** Document-heavy, data-intensive, and RAG-centric (Retrieval-Augmented Generation) pipelines.\n\t- **Key features:** Event-driven orchestration designed to sift through thousands of PDFs, SQL databases, and local files reliably.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)[[2]](https://www.quora.com/What-are-the-best-AI-agent-frameworks-you-could-recommend)[[3]](https://www.linkedin.com/posts/shantanu-shende-17800a324_top-ai-agent-frameworks-you-should-know-activity-7362271465640992771-jscl)\n- **Google ADK (Agent Development Kit)**:\n\t- **Best for:** Google Cloud Platform (GCP) and Gemini-native applications.\n\t- **Key features:** Opinionated, batteries-included agent runtime with built-in debugging UIs.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)\n- **Mastra**:\n\t- **Best for:** TypeScript teams building custom production agents.\n\t- **Key features:** Combines workflows, persistent memory, and an integrated development Studio into a single package.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)\n\nWatch this overview of leading agentic frameworks to see how their core architectures compare in practice:\n\n![](https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQl3Ab8e-heEUvc00SoukMq_lw8urnMC0PgfDuw4eLu1FPvAx1R)\n50s\n[](https://www.youtube.com/watch?v=Tcwk7yXulYQ&t=59) Top Agentic AI Frameworks for Building AI Applications in 2026 4 days ago![](https://encrypted-tbn2.gstatic.com/faviconV2?url=https://www.youtube.com&client=AIM&size=16&type=FAVICON&fallback_opts=TYPE,SIZE,URL)\nYouTube · Ramesh Fadatare - AI, Generative AI & AI Tools\n\nTo help you pick the right one, tell me:\n\n- What is your **programming language** preference (Python, TypeScript, .NET, etc.)?\n- Are you building a **quick prototype** or a **mission-critical production app**?", "brands": [ { "name": "LangGraph" }, { "name": "CrewAI" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Google ADK", "domain": "google.com" }, { "name": "Mastra" } ], "sources": [ { "url": "https://www.reddit.com/r/AI_Agents/comments/1kjowzp/whats_the_best_framework_for_productiongrade_ai/", "domain": "reddit.com", "title": "What's the best framework for production‑grade AI agents right ..." }, { "url": "https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d", "domain": "pub.towardsai.net", "title": "Top AI Agent Frameworks in 2026: A Production-Ready Comparison | by Pratik K Rupareliya | Towards AI" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.quora.com/What-are-the-best-AI-agent-frameworks-you-could-recommend", "domain": "quora.com", "title": "What are the best AI agent frameworks you could recommend? - Quora" }, { "url": "https://www.linkedin.com/posts/shantanu-shende-17800a324_top-ai-agent-frameworks-you-should-know-activity-7362271465640992771-jscl", "domain": "linkedin.com", "title": "Top AI Agent Frameworks: LangChain, AutoGen, CrewAI, LlamaIndex ..." } ], "searchQueries": "not exposed" }, { "prompt": 2, "engine": "OPENAI", "run": 1, "askedAt": "2026-10-09T01:28:02.344Z", "text": "1. **LangChain** — https://langchain.com \n Fast-to-prototype, widely adopted agent + orchestration SDK with commercial tooling (LangSmith) and many production case studies. ([langchain.com](https://www.langchain.com/?trk=public_post_comment-text&utm_source=openai))\n\n2. **Microsoft Agent Framework (AutoGen + Semantic Kernel)** — https://microsoft.github.io/autogen/ (AutoGen) / https://learn.microsoft.com/semantic-kernel/overview/ (Semantic Kernel) \n Microsoft’s production-focused agent stack combining AutoGen’s multi-agent patterns with Semantic Kernel’s enterprise features and integrations. ([github.com](https://github.com/microsoft/autogen?utm_source=openai))\n\n3. **Haystack (deepset)** — https://haystack.deepset.ai / https://www.deepset.ai/solutions/enterprise \n Open-source AI orchestration framework built for RAG/agents and enterprise production deployments with deployment guides and enterprise support. ([docs.haystack.deepset.ai](https://docs.haystack.deepset.ai/docs?utm_source=openai))\n\n4. **Ray Serve (Ray)** — https://docs.ray.io/en/latest/serve/ \n Framework-agnostic, highly scalable serving/orchestration layer ideal for running multi-model, autoscaling agent pipelines in production. ([docs.ray.io](https://docs.ray.io/en/master/serve/?utm_source=openai))\n\n5. **Semantic Kernel** — https://learn.microsoft.com/semantic-kernel/overview/ \n Lightweight SDK for building production agents with first-class support for state, middleware, and language-model integrations (works in C#, Python, Java). ([learn.microsoft.com](https://learn.microsoft.com/semantic-kernel/overview/?utm_source=openai))\n\n6. **AutoGen (Microsoft)** — https://microsoft.github.io/autogen/ \n Research-driven, code-first multi-agent framework for orchestrating agent conversations and tool use at scale (now integrated into Microsoft’s agent efforts). ([github.com](https://github.com/microsoft/autogen?utm_source=openai))\n\nNotes (brief): I ranked by typical production-readiness, ecosystem/maturity, and scalability: LangChain for fastest path to production and ecosystem; Microsoft’s stack for enterprise/scale and vendor support; Haystack for data-grounded RAG/agents in enterprise settings; Ray Serve as the serving/scale layer; Semantic Kernel / AutoGen for tighter enterprise integration and advanced agent patterns. If you want, I can produce the same list filtered for a specific language (Python/TypeScript/C#), cloud provider (AWS/Azure/GCP), or if you prefer fully open-source vs. commercial offerings.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework (AutoGen + Semantic Kernel)", "domain": "microsoft.github.io" }, { "name": "Haystack (deepset)", "domain": "haystack.deepset.ai" }, { "name": "Ray Serve (Ray)", "domain": "docs.ray.io" }, { "name": "Semantic Kernel", "domain": "learn.microsoft.com" }, { "name": "AutoGen (Microsoft)", "domain": "microsoft.github.io" } ], "sources": [ { "url": "https://www.langchain.com/?trk=public_post_comment-text&utm_source=openai", "domain": "langchain.com", "title": "LangChain: the open agent platform to own your intelligence" }, { "url": "https://github.com/microsoft/autogen?utm_source=openai", "domain": "github.com", "title": "GitHub - microsoft/autogen: A programming framework for agentic AI · GitHub" }, { "url": "https://docs.haystack.deepset.ai/docs?utm_source=openai", "domain": "docs.haystack.deepset.ai", "title": "Introduction to Haystack | Haystack Documentation" }, { "url": "https://docs.ray.io/en/master/serve/?utm_source=openai", "domain": "docs.ray.io", "title": "Ray Serve: Scalable and Programmable Serving — Ray 3.0.0.dev0" }, { "url": "https://learn.microsoft.com/semantic-kernel/overview/?utm_source=openai", "domain": "learn.microsoft.com", "title": "Introduction to Semantic Kernel | Microsoft Learn" } ], "searchQueries": [ "LangChain production use LangChain framework website", "Microsoft Semantic Kernel production use website", "Autogen AI framework Microsoft Autogen GitHub Autogen framework website", "Ray Serve Ray AI agent framework production use website Ray Serve", "deepset Haystack framework production use website Haystack deepset", "LlamaIndex (formerly GPT Index) production use website LlamaIndex" ] }, { "prompt": 2, "engine": "OPENAI", "run": 2, "askedAt": "2026-10-09T01:28:59.941Z", "text": "1. **LangChain (LangChain Agents)** — https://www.langchain.com — Mature, extensible Python/TypeScript framework with broad ecosystem (connectors, tooling, community) and many production deployments. ([langchain.com](https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai))\n\n2. **OpenAI Agents SDK** — https://platform.openai.com/docs/agents — First‑party SDK that gives the shortest path to production on OpenAI models with deep native tooling, managed runtimes, and model‑vendor optimizations. ([theairankings.com](https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai))\n\n3. **Anthropic / Claude Agent SDK** — https://www.anthropic.com (Claude Agents docs) — Vendor SDK tailored for Claude family models; good if you’ve standardized on Anthropic for safety, steerability, and enterprise integrations. ([theairankings.com](https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai))\n\n4. **Microsoft Agent Framework / Semantic Kernel** — https://learn.microsoft.com/semantic-kernel and https://github.com/microsoft/semantic-kernel — Strong enterprise story (Azure integration, .NET and Python support) and production features for state, orchestration, and governance. ([makeanapplike.com](https://www.makeanapplike.com/article/list/ai-agent-frameworks-compared-langchain-llamaindex-autogen-crewai-smolagents-mastra?utm_source=openai))\n\n5. **AutoGen** — https://github.com/microsoft/autogen (open‑source) — Code‑first multi‑agent collaboration framework focused on robust agent workflows and fine‑grained control for complex production scenarios. ([lindy.ai](https://www.lindy.ai/blog/langchain-alternatives?utm_source=openai))\n\n6. **CrewAI** — https://crew.ai (CrewAI / CrewAI Enterprise) — Enterprise‑oriented agent orchestration with multi‑agent coordination, observability, and governance layers for production teams. ([agentframeworkhub.com](https://www.agentframeworkhub.com/blog/langchain-alternatives-2026?utm_source=openai))\n\n7. **LlamaIndex (formerly GPT Index)** — https://www.llamaindex.ai — Best when retrieval and vector‑indexing are core to your product; pairs well with agent frameworks for production RAG systems. ([agentframeworkhub.com](https://www.agentframeworkhub.com/blog/langchain-alternatives-2026?utm_source=openai))\n\nNotes (short): pick the one that matches your stack and constraints — use a vendor SDK (OpenAI / Anthropic / Microsoft) if you want the fastest, lowest‑risk path to production on that model family; pick LangChain or AutoGen/CrewAI if you need multi‑model portability, richer orchestration, or heavy customization; choose LlamaIndex when retrieval is the dominant workload. For production, also evaluate observability, retry/failure semantics, cost/token overhead, security/sandboxing, and whether the framework’s abstractions let you escape them when needed. ([langchain.com](https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai))", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Anthropic", "domain": "anthropic.com" }, { "name": "Microsoft", "domain": "learn.microsoft.com" }, { "name": "AutoGen", "domain": "github.com" }, { "name": "CrewAI", "domain": "crew.ai" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://www.langchain.com/resources/ai-agent-frameworks?utm_source=openai", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai", "domain": "theairankings.com", "title": "Best AI Agent Frameworks in 2026: Ranked & Compared | The AI Rankings" }, { "url": "https://www.makeanapplike.com/article/list/ai-agent-frameworks-compared-langchain-llamaindex-autogen-crewai-smolagents-mastra?utm_source=openai", "domain": "makeanapplike.com", "title": "AI Agent Frameworks Compared (2026): LangChain vs Alternatives" }, { "url": "https://www.lindy.ai/blog/langchain-alternatives?utm_source=openai", "domain": "lindy.ai", "title": "7 LangChain Alternatives to Try in 2026 (Tested and Reviewed) | Lindy" }, { "url": "https://www.agentframeworkhub.com/blog/langchain-alternatives-2026?utm_source=openai", "domain": "agentframeworkhub.com", "title": "7 Best LangChain Alternatives in 2026 (Compare... | MintSquare" } ], "searchQueries": [ "best AI agent frameworks production 2026", "LangChain alternatives 2026 production agent frameworks", "Autonomous agents frameworks for production 2026 'agent framework' 'production' '2026'", "Hugging Face 'agents' framework 2026 production" ] }, { "prompt": 2, "engine": "OPENAI", "run": 3, "askedAt": "2026-10-09T01:29:52.471Z", "text": "1. **Microsoft Agent Framework (Microsoft / Azure)** — https://learn.microsoft.com/ (Microsoft Agent Framework docs). \n Why: Enterprise-grade, Azure-native agent framework now positioned for GA production with deep integrations to Semantic Kernel and Azure tooling (best for Microsoft/enterprise shops). ([github.com](https://github.com/microsoft/semantic-kernel/discussions/13521?utm_source=openai))\n\n2. **OpenAI Agents SDK (OpenAI Agents / OpenAI)** — https://openai.com (OpenAI Agents SDK pages). \n Why: First‑party SDK tightly integrated with OpenAI models, optimized developer experience and short path to production if you’re committed to OpenAI’s model stack. ([theairankings.com](https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai))\n\n3. **Claude Agent SDK / Claude Managed Agents (Anthropic)** — https://claude.com (Anthropic Claude agent resources). \n Why: Anthropic’s managed agents provide a production-focused runtime, tooling and safety harness built from their agent research (used in real products). ([claude.com](https://claude.com/resources/articles/building-with-claude-managed-agents?utm_source=openai))\n\n4. **LangChain (agent tooling and integrations)** — https://langchain.com (State of agent engineering / LangChain). \n Why: Widely adopted, strong ecosystem of integrations and orchestrators — often the fastest path from prototype to production when you need flexibility across models and data stores. ([langchain.com](https://www.langchain.com/state-of-agent-engineering?trk=article-ssr-frontend-pulse_little-text-block&utm_source=openai))\n\n5. **LangGraph (open-source agent orchestration)** — https://langgraph.io (LangGraph resources / comparisons). \n Why: Rising open-source framework focused on deterministic orchestration, state management and production patterns — good for teams needing control and observability. ([scrimba.com](https://scrimba.com/articles/best-ai-agent-frameworks/?utm_source=openai))\n\nNotes:\n- “Best” depends on your constraints (cloud/provider lock‑in, language, scale, safety/observability, cost). The list above ranks frameworks that reporters, vendors and practitioner benchmarks cite most often for production use in 2026. ([pharosproduction.com](https://pharosproduction.com/insights/engineering/ai-agent-frameworks-comparison-2026/?utm_source=openai))\n- If you want, I can give a short decision tree mapping your stack (cloud, language, need for model‑native SDK vs. neutral orchestrator, multi‑agent vs. flow) to the best pick and implementation checklist.", "brands": [ { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Claude Agent SDK", "domain": "claude.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langgraph.io" } ], "sources": [ { "url": "https://github.com/microsoft/semantic-kernel/discussions/13521?utm_source=openai", "domain": "github.com", "title": "Production Strategy: Should we start with Semantic Kernel and migrate to Agent Framework post-GA · microsoft semantic-kernel · Discussion #13521 · GitHub" }, { "url": "https://theairankings.com/best-ai-agent-frameworks/?utm_source=openai", "domain": "theairankings.com", "title": "Best AI Agent Frameworks in 2026: Ranked & Compared | The AI Rankings" }, { "url": "https://claude.com/resources/articles/building-with-claude-managed-agents?utm_source=openai", "domain": "claude.com", "title": "The evolution of agentic surfaces: building with Claude Managed Agents | Claude by Anthropic" }, { "url": "https://www.langchain.com/state-of-agent-engineering?trk=article-ssr-frontend-pulse_little-text-block&utm_source=openai", "domain": "langchain.com", "title": "State of AI Agents" }, { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/?utm_source=openai", "domain": "scrimba.com", "title": "Best AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://pharosproduction.com/insights/engineering/ai-agent-frameworks-comparison-2026/?utm_source=openai", "domain": "pharosproduction.com", "title": "AI Agent Frameworks Comparison 2026 | Pharos Production" } ], "searchQueries": [ "best AI agent framework for production 2026", "LangChain production readiness 2026", "AutoGen agent framework production 2026", "Microsoft Semantic Kernel production use 2026", "Anthropic's Claude agents framework toolkits 2026", "Hugging Face AutoTrain agents frameworks 2026", "Grid AI Agents framework production 2026" ] }, { "prompt": 2, "engine": "ANTHROPIC", "run": 1, "askedAt": "2026-10-09T01:28:00.080Z", "text": "I'll search for current information on AI agent frameworks suitable for production use.\nBased on current 2026 research, here are the top AI agent frameworks ranked for production use:\n\n1. **LangGraph** | https://www.langgraph.dev | \nBest multi-agent framework for production with stateful graphs, durable execution, and human-in-the-loop checkpoints, used by Anthropic, Replit, LinkedIn, and Uber\n.\n\n2. **Mastra** | https://mastra.ai | \nTypeScript framework bundling the whole production stack (agents, workflows, memory, RAG, evals, guardrails, tracing) with production users including Replit, PayPal, and Sanity\n.\n\n3. **Microsoft Agent Framework** | https://learn.microsoft.com/en-us/ai/agents | \nUnified successor to AutoGen and Semantic Kernel with graph-based workflows and responsible AI guardrails through Azure AI Foundry\n.\n\n4. **OpenAI Agents SDK** | https://platform.openai.com/docs/agents | \nWell-suited to linear handoff chains where one agent transfers control to another\n.\n\n5. **CrewAI** | https://www.crewai.com | \nFastest path to a working crew of role-based agents\n.\n\n6. **LlamaIndex** | https://www.llamaindex.ai | \nFits retrieval-heavy agents for reasoning over enterprise documents like contracts, regulatory filings, and technical manuals\n.\n\nThe best choice depends on your tech stack and needs: \nwhether your application needs explicit graph state, role-based collaboration, linear handoffs, TypeScript-native workflows, or retrieval-heavy reasoning\n.", "brands": [ { "name": "LangGraph", "domain": "langgraph.dev" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.braintrust.dev/articles/best-ai-agent-frameworks-2026", "domain": "braintrust.dev", "title": "Best AI agent frameworks (2026): How to choose one and add evals - Articles - Braintrust" }, { "url": "https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/", "domain": "blog.jetbrains.com", "title": "Top Agentic Frameworks for Building Applications 2026 - The JetBrains Blog" }, { "url": "https://pickaxe.co/post/top-ai-agent-frameworks", "domain": "pickaxe.co", "title": "Top 15 AI Agent Frameworks in 2026" }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single One)" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://hostkey.com/blog/195-best-ai-agent-frameworks-in-2026-a-practical-guide-for-developers-and-infrastructure-teams/", "domain": "hostkey.com", "title": "Best Agentic AI Frameworks in 2026: How to Choose for Production" }, { "url": "https://alphacorp.ai/blog/the-8-best-ai-agent-frameworks-in-2026-a-developers-guide", "domain": "alphacorp.ai", "title": "The 8 Best AI Agent Frameworks in 2026: A Developer’s Guide" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" } ], "searchQueries": [ "best AI agent framework production 2026" ] }, { "prompt": 2, "engine": "ANTHROPIC", "run": 2, "askedAt": "2026-10-09T01:28:54.722Z", "text": "I'll search for current information about the best AI agent frameworks for production use.\nBased on current information, here are the best AI agent frameworks for production use, ranked:\n\n1. **LangGraph** - https://www.langchain.com/langgraph\n \nThe production default for complex AI agent workflows, having surpassed CrewAI in adoption during early 2026 largely driven by enterprise teams needing state persistence, conditional routing, and rollback capabilities\n.\n\n2. **Mastra** - https://www.mastra.ai\n \nBest full-stack framework for TypeScript teams shipping production agents, with production users including Replit, PayPal, and Sanity\n.\n\n3. **Microsoft Agent Framework** - https://github.com/microsoft/agent-framework\n \nThe unified successor to AutoGen and Semantic Kernel for Microsoft stack users, with graph-based workflows, responsible AI guardrails, and Python + .NET runtimes at 1.0 GA\n.\n\n4. **CrewAI** - https://www.crewai.com\n \nBest if you need role-based multi-agent prototypes up and running quickly with an intuitive mental model\n.\n\n5. **OpenAI Agents SDK** - https://github.com/openai/agents-api\n \nWell-suited to linear handoff chains where one agent transfers control to another\n.\n\n6. **LlamaIndex** - https://www.llamaindex.ai\n \nFits retrieval-heavy agents where reasoning over enterprise documents is needed, and is strongest when retrieval quality, citation handling, and document processing shape the agent's output\n.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.braintrust.dev/articles/best-ai-agent-frameworks-2026", "domain": "braintrust.dev", "title": "Best AI agent frameworks (2026): How to choose one and add evals - Articles - Braintrust" }, { "url": "https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/", "domain": "blog.jetbrains.com", "title": "Top Agentic Frameworks for Building Applications 2026 - The JetBrains Blog" }, { "url": "https://pickaxe.co/post/top-ai-agent-frameworks", "domain": "pickaxe.co", "title": "Top 15 AI Agent Frameworks in 2026" }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single One)" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://hostkey.com/blog/195-best-ai-agent-frameworks-in-2026-a-practical-guide-for-developers-and-infrastructure-teams/", "domain": "hostkey.com", "title": "Best Agentic AI Frameworks in 2026: How to Choose for Production" }, { "url": "https://alphacorp.ai/blog/the-8-best-ai-agent-frameworks-in-2026-a-developers-guide", "domain": "alphacorp.ai", "title": "The 8 Best AI Agent Frameworks in 2026: A Developer’s Guide" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" } ], "searchQueries": [ "best AI agent framework production 2026" ] }, { "prompt": 2, "engine": "ANTHROPIC", "run": 3, "askedAt": "2026-10-09T01:29:51.723Z", "text": "I'll search for current information about AI agent frameworks suitable for production use.\nBased on current information about AI agent frameworks for production use, here's the ranked list:\n\n1. **LangGraph**, https://www.langgraph.dev/ — \nThe best multi-agent framework for production in 2026\n, with \ncheckpointing and time-travel debugging for when your system hits real users and edge cases\n.\n\n2. **Mastra**, https://www.mastra.ai/ — \nBest full-stack framework for TypeScript teams shipping production agents\n, \nwith production users including Replit, PayPal, and Sanity\n.\n\n3. **Microsoft Agent Framework**, https://learn.microsoft.com/en-us/dotnet/api/microsoft.autogen — \nThe unified successor to AutoGen with graph-based workflows and responsible AI guardrails through Azure AI Foundry\n.\n\n4. **CrewAI**, https://www.crewai.com/ — \nChoose CrewAI if you need role-based multi-agent prototypes up and running quickly with an intuitive mental model\n.\n\n5. **OpenAI Agents SDK**, https://platform.openai.com/docs/guides/agents — \nWell-suited to linear handoff chains where one agent transfers control to another\n.\n\n6. **LlamaIndex**, https://www.llamaindex.ai/ — \nFits retrieval-heavy agents where the main problem is reasoning over enterprise documents, strongest when retrieval quality and citation handling shape output\n.", "brands": [ { "name": "LangGraph", "domain": "langgraph.dev" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Replit", "domain": "replit.com" }, { "name": "PayPal", "domain": "paypal.com" }, { "name": "Sanity", "domain": "sanity.io" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "AutoGen", "domain": "microsoft.com" }, { "name": "Azure AI Foundry", "domain": "microsoft.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.braintrust.dev/articles/best-ai-agent-frameworks-2026", "domain": "braintrust.dev", "title": "Best AI agent frameworks (2026): How to choose one and add evals - Articles - Braintrust" }, { "url": "https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/", "domain": "blog.jetbrains.com", "title": "Top Agentic Frameworks for Building Applications 2026 - The JetBrains Blog" }, { "url": "https://pickaxe.co/post/top-ai-agent-frameworks", "domain": "pickaxe.co", "title": "Top 15 AI Agent Frameworks in 2026" }, { "url": "https://www.agentmail.to/blog/best-ai-agent-frameworks-2026", "domain": "agentmail.to", "title": "The 9 Best AI Agent Frameworks in 2026 (We Tested Every Single One)" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://hostkey.com/blog/195-best-ai-agent-frameworks-in-2026-a-practical-guide-for-developers-and-infrastructure-teams/", "domain": "hostkey.com", "title": "Best Agentic AI Frameworks in 2026: How to Choose for Production" }, { "url": "https://alphacorp.ai/blog/the-8-best-ai-agent-frameworks-in-2026-a-developers-guide", "domain": "alphacorp.ai", "title": "The 8 Best AI Agent Frameworks in 2026: A Developer’s Guide" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" } ], "searchQueries": [ "best AI agent framework production 2026", "production AI agent frameworks comparison" ] }, { "prompt": 2, "engine": "PERPLEXITY", "run": 1, "askedAt": "2026-10-09T01:28:01.588Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph \n Best overall for production: explicit state machines, durable execution, persistence, branching workflows, and human approval paths.[1][4]\n\n2. **Microsoft Agent Framework** — https://github.com/microsoft/agent-framework \n Best for Microsoft-oriented enterprises needing enterprise adoption, governance, and integration with Azure ecosystems.[8]\n\n3. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ \n Best for teams building quickly around OpenAI models with tools, handoffs, and a relatively simple production architecture.[10]\n\n4. **CrewAI** — https://www.crewai.com/ \n Best for rapidly assembling role-based multi-agent systems, especially when developer productivity matters more than highly customized orchestration.[1][10]\n\n5. **LlamaIndex Workflows** — https://www.llamaindex.ai/ \n Best for production agents centered on document data, retrieval, knowledge bases, and structured data workflows.[7][10]\n\n6. **Mastra** — https://mastra.ai/ \n Best TypeScript-first option for teams wanting agents, workflows, memory, evaluations, and observability in one developer-oriented stack.[6][10]\n\n**Recommendation:** Choose **LangGraph** for the safest general-purpose production default; choose **Microsoft Agent Framework** for Microsoft/Azure enterprises and **LlamaIndex** for retrieval-heavy applications. AutoGen is less attractive for new production projects because recent comparisons describe it as being in maintenance mode.[3]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://www.workflowbuilder.io/blog/best-ai-agent-frameworks", "domain": "workflowbuilder.io", "title": "Best AI agent frameworks in 2026: a comparison for production teams" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/", "domain": "scrimba.com", "title": "scrimba.com › articles › best-ai-agent-frameworksBest AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://kestra.io/resources/ai/ai-agent-orchestration-frameworks", "domain": "kestra.io", "title": "Top AI Agent Orchestration Frameworks & Platforms (2026) | Kestra" }, { "url": "https://www.openlayer.com/blog/best-ai-agent-frameworks-production-teams", "domain": "openlayer.com", "title": "The 10 best AI agent frameworks for production teams ..." }, { "url": "https://www.daytona.io/dotfiles/best-ai-agent-frameworks", "domain": "daytona.io", "title": "The 7 Best AI Agent Frameworks: Features and Tradeoffs - Daytona" }, { "url": "https://www.intuz.com/blog/top-5-ai-agent-frameworks-2025/", "domain": "intuz.com", "title": "Best AI Agent Frameworks: Tested in 100+ Production ..." }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://www.hostinger.com/in/tutorials/agentic-ai-frameworks/", "domain": "hostinger.com", "title": "10 best agentic AI frameworks to build intelligent AI agents" }, { "url": "https://www.braintrust.dev/articles/best-ai-agent-frameworks-2026", "domain": "braintrust.dev", "title": "Best AI agent frameworks (2026): How to choose one and add evals" } ], "searchQueries": "not exposed" }, { "prompt": 2, "engine": "PERPLEXITY", "run": 2, "askedAt": "2026-10-09T01:28:51.889Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production: durable, stateful workflows with explicit control, persistence, branching, and human approval paths.[1][4]\n\n2. **Microsoft Agent Framework** — https://learn.microsoft.com/en-us/agent-framework/ — Best for enterprise Microsoft environments, especially teams needing governed deployment and deep Azure integration.[8]\n\n3. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for teams standardizing on OpenAI models and wanting a relatively simple production path with tools, handoffs, and tracing.[10]\n\n4. **CrewAI** — https://www.crewai.com/ — Best for rapidly building role-based multi-agent systems, with accessible abstractions for teams that prioritize development speed.[1][10]\n\n5. **LlamaIndex Workflows** — https://www.llamaindex.ai/ — Best for document- and retrieval-heavy agents that need strong data connectors and workflow orchestration.[7][10]\n\n6. **Mastra** — https://mastra.ai/ — Best TypeScript-native option for teams wanting agents, workflows, memory, evaluations, and observability in one ecosystem.[6][10]\n\n**Overall pick: LangGraph.** It offers the strongest balance of production control, recoverability, state management, and framework flexibility; choose Microsoft Agent Framework instead when Azure and enterprise governance are decisive.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://www.workflowbuilder.io/blog/best-ai-agent-frameworks", "domain": "workflowbuilder.io", "title": "Best AI agent frameworks in 2026: a comparison for production teams" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/", "domain": "scrimba.com", "title": "scrimba.com › articles › best-ai-agent-frameworksBest AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://kestra.io/resources/ai/ai-agent-orchestration-frameworks", "domain": "kestra.io", "title": "Top AI Agent Orchestration Frameworks & Platforms (2026) | Kestra" }, { "url": "https://www.openlayer.com/blog/best-ai-agent-frameworks-production-teams", "domain": "openlayer.com", "title": "The 10 best AI agent frameworks for production teams ..." }, { "url": "https://www.daytona.io/dotfiles/best-ai-agent-frameworks", "domain": "daytona.io", "title": "The 7 Best AI Agent Frameworks: Features and Tradeoffs - Daytona" }, { "url": "https://www.intuz.com/blog/top-5-ai-agent-frameworks-2025/", "domain": "intuz.com", "title": "Best AI Agent Frameworks: Tested in 100+ Production ..." }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://www.hostinger.com/in/tutorials/agentic-ai-frameworks/", "domain": "hostinger.com", "title": "10 best agentic AI frameworks to build intelligent AI agents" }, { "url": "https://www.braintrust.dev/articles/best-ai-agent-frameworks-2026", "domain": "braintrust.dev", "title": "Best AI agent frameworks (2026): How to choose one and add evals" } ], "searchQueries": "not exposed" }, { "prompt": 2, "engine": "PERPLEXITY", "run": 3, "askedAt": "2026-10-09T01:29:47.856Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production: durable, stateful workflows with explicit control, persistence, branching, and recovery.[1][4]\n\n2. **Microsoft Agent Framework** — https://github.com/microsoft/agent-framework — Strongest enterprise option for organizations invested in Microsoft, with production-oriented orchestration and governance.[8]\n\n3. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for teams standardizing on OpenAI models and wanting a relatively streamlined agent, tool, handoff, and tracing stack.[10]\n\n4. **LlamaIndex Workflows** — https://www.llamaindex.ai — Best for retrieval-heavy agents that need to connect documents, knowledge bases, and data sources to multi-step workflows.[7][10]\n\n5. **CrewAI** — https://www.crewai.com — Best for quickly building role-based multi-agent systems, though deterministic flows should control critical production paths.[1][10]\n\n6. **Mastra** — https://mastra.ai — Strong TypeScript choice for teams seeking an integrated framework for agents, workflows, memory, evaluations, and observability.[6][10]\n\n**Top recommendation:** Choose **LangGraph** for most production systems; choose **Microsoft Agent Framework** for Microsoft-centric enterprises and **OpenAI Agents SDK** for an OpenAI-first stack.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://www.workflowbuilder.io/blog/best-ai-agent-frameworks", "domain": "workflowbuilder.io", "title": "Best AI agent frameworks in 2026: a comparison for production teams" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://scrimba.com/articles/best-ai-agent-frameworks/", "domain": "scrimba.com", "title": "scrimba.com › articles › best-ai-agent-frameworksBest AI Agent Frameworks [2026]: LangGraph, CrewAI, AutoGen" }, { "url": "https://kestra.io/resources/ai/ai-agent-orchestration-frameworks", "domain": "kestra.io", "title": "Top AI Agent Orchestration Frameworks & Platforms (2026) | Kestra" }, { "url": "https://www.openlayer.com/blog/best-ai-agent-frameworks-production-teams", "domain": "openlayer.com", "title": "The 10 best AI agent frameworks for production teams ..." }, { "url": "https://www.daytona.io/dotfiles/best-ai-agent-frameworks", "domain": "daytona.io", "title": "The 7 Best AI Agent Frameworks: Features and Tradeoffs - Daytona" }, { "url": "https://www.intuz.com/blog/top-5-ai-agent-frameworks-2025/", "domain": "intuz.com", "title": "Best AI Agent Frameworks: Tested in 100+ Production ..." }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://www.hostinger.com/in/tutorials/agentic-ai-frameworks/", "domain": "hostinger.com", "title": "10 best agentic AI frameworks to build intelligent AI agents" }, { "url": "https://www.braintrust.dev/articles/best-ai-agent-frameworks-2026", "domain": "braintrust.dev", "title": "Best AI agent frameworks (2026): How to choose one and add evals" } ], "searchQueries": "not exposed" }, { "prompt": 2, "engine": "GEMINI", "run": 1, "askedAt": "2026-10-09T01:28:03.879Z", "text": "1. **LangGraph** — [langchain.com/langgraph](https://www.langchain.com/langgraph) \n Widely considered the industry standard for production-grade agent systems, offering fine-grained control via explicit stateful graphs, durable execution, and built-in human-in-the-loop checkpoints.\n\n2. **CrewAI** — [crewai.com](https://www.crewai.com) \n The leading choice for role-based multi-agent orchestration, allowing teams to quickly spin up collaborative autonomous agents with structured task delegation.\n\n3. **PydanticAI** — [ai.pydantic.dev](https://ai.pydantic.dev) \n A production-focused Python framework that brings strict type safety, dependency injection, and robust Pydantic validation to agent outputs and tool calling.\n\n4. **Microsoft Agent Framework** — [github.com/microsoft/semantic-kernel](https://github.com/microsoft/semantic-kernel) \n The go-to enterprise framework for .NET and Azure-backed architectures, combining robust governance, explicit orchestration, and middleware support.\n\n5. **Mastra** — [mastra.ai](https://mastra.ai) \n An all-in-one, TypeScript-first framework built for full-stack web teams needing to tightly integrate persistent agents, workflows, and memory into Node.js or Next.js applications.\n\n6. **OpenAI Agents SDK** — [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python) \n A lightweight, developer-friendly orchestration SDK by OpenAI optimized for low-latency tool execution, seamless model handoffs, and GPT-native applications.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "OpenAI Agents SDK", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFOsmQIjJ41MdOi2RXSYYIEo6PYAT2_Lo6tEBsRX2ed4aHldSetChAG-2iw-_ZGDFEyPFp1XZMVwTCorqoa_1tBY8qyILpayB4TWQNTiIcGozzwEPxztFHS8CQqdFzpLw8c8eySOKP13KbcGRM8Ie2WSUa7Vy4B", "domain": "redlinesoft.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGQZIXqWrIscabjC2xBlWzKZn4YN0ju7TnrsPwiAFT0Ulw88fhWp9zg-DbiXc1UY6o1hHR7GOvvKFmE6Om-OdHdCQP4D4IJsPOq4baN7Z2oh8qjbhOl-_vVq51CYHL5pLo4KbtdAOKq7QAeqaNrxjNCKQ==", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEr47zNqMj6xASZrvXCH4fW_5D9ZLxN_geSTOMTPffsaF_WNwQ9nlUAbIWfBQzejq2Jry4HVP3hmpuvGNbMV0jGwX3EHfWNOVKGigmV1zQn3zz-5ouIIXSNF7a_ugBzPcmJWkj3K4hczyvpCpLy7RyRdmx7UHQAJxgnw5udJ8Ylw7Z8w32J6F5h5a9-EdVJ811Vs4Tj_0pWnuDe", "domain": "towardsai.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGwWt6W0WHOIDpJvym34G9oDwdz_0YpHhTAcWBEce7_eCDAlcPETq8ehpYQSF1T__qmh_ovCzZZNs92p7O6sZs7LRXZYL5tXK_IE3dj1kF-ksKmvpfQMkwG2Er-P07VMwR5KFGMvJLM1YJfygUfaIyLf4fYCgSPfYEABJ4buz2MpGMS8SIi5CK8MbJjviXXsnHiXbi3A1DxMip72AEJcTCh81XI", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEs-LQRmPGAYzQxbJhkhI9TLR1pVwa7sWn7XRCMVuBKyxvSvpyiz7jqLY8DEZ2vhr2Mc5xRt-jAt-BBZuGZut-ATEdXdMzqF4v7ZAt8FBqDQ9u3I7jrwlqcvXXwSBGwObEy67eqwAjHro-h1_8=", "domain": "kimi.ai" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH318reMTVbmPFgjdvs4Qy49RZBV9d_gNoJOyL3Gci7_jamTmHsrTAJnwWGZClxdQyyhOmT53nYaXoSbNmPBuLzYeMiykcGvWlIrksYTAPSZkMY3-tOea-XXM3TpNVL-HUmJS2oKb5HvkbznW5x6-_1FAH6o08q8bzsPMD-pJcd--X2E-wpHWX2RQ1PagNDBBF5QLkH9QazOgj3JnEMNfBPlo4pD6lQo-eh", "domain": "medium.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG9wIozlpQjCX6T-q7ZykTD2gW5U4MdIC0bupRmuCD2ZkdDPq2we8PWagr6saKTQjim66sv1NXBg5qX23_KRvY4K9CitVWEg_HmPW8so6ZCHQAJIIWp9TxoQL4XwS6_2Qo4mW4=", "domain": "lindy.ai" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGLSiTbA-yaBneLdfw_sf9X7F3FPanemXDRqHzoGZ7fBq8KxPRbLJdJUMoTn8MmW_vVlZIvGwPSMAfdn9ZiHzMQExSNUZ6rU5sRCxqKFNqLQ1y7LajGKOQKUhRIQBwsD1l-Z7NHQipXR-u_dymIAZC1WIc-WEjtWHNl4UP0i-IIfZSwyo0wVCLxKR5k4bXAfTD4hP15PXsExWyUFS6mVTwnt9VjFfhZmt7HY7gmQhE=", "domain": "hostkey.com" } ], "searchQueries": [ "top production ready AI agent frameworks", "best AI agent frameworks for production use 2025 2026" ] }, { "prompt": 2, "engine": "GEMINI", "run": 2, "askedAt": "2026-10-09T01:28:55.514Z", "text": "1. **LangGraph** \n [https://www.langchain.com/langgraph](https://www.langchain.com/langgraph) \n The most production-hardened framework for complex, stateful multi-agent architectures, featuring native support for durable execution, persistence, and human-in-the-loop checkpoints.\n\n2. **PydanticAI** \n [https://ai.pydantic.dev](https://ai.pydantic.dev) \n A streamlined, type-safe Python framework designed to bring production-grade reliability to agent application logic through rigorous data validation and structured outputs.\n\n3. **CrewAI** \n [https://www.crewai.com](https://www.crewai.com) \n An opinionated multi-agent framework tailored for role-based collaborative workflows, widely deployed for business process automation and research tasks.\n\n4. **Microsoft AutoGen** (or **Microsoft Agent Framework**) \n [https://github.com/microsoft/autogen](https://github.com/microsoft/autogen) \n An enterprise-grade asynchronous engine ideal for building complex conversational systems and multi-agent distributed conversations, deeply integrated with the Azure ecosystem.\n\n5. **OpenAI Agents SDK** \n [https://github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python) \n A lightweight and performant native framework optimized specifically for managing handoffs, guardrails, and tool execution loops across OpenAI's model lineup.\n\n6. **Mastra** \n [https://mastra.ai](https://mastra.ai) \n A comprehensive TypeScript framework built for production web stacks, combining agent execution, advanced memory, document retrieval, and workflows into a unified developer experience.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft AutoGen", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFJ3G6J56mKvd6YvmF0BhD8HcJQozpQlmPmtWpKdiU64z9m6gvOC6fvViIAwd__vb3XAxFMen9HaxKC2CdCDQa7jT0Sb-y9BKea7BhVcjh3oTarT-S6fQEzKOAKxgJWhCNBf3cACq4YqVzjw66auu8BAg==", "domain": "agentmail.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG0aMMtY3F1EyeKENnPlEQt9iomiVcTXjhM5s6czIucr4kQFv_sKeahVLBNV4BPfIkyZdGC_-cyVj4r2C44z7t2Fl_ESruTaWdv4qmppGSpZmqXAszJ29PVqsVqLovjdIheUGRp3B3OQbF-qDmsTy0wZf1Y6AYaxU_QCNR75-28qsxTAfTE911AYeRhD52iki9pCScfxVmzPrv1vN4J-fZnJAUR", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHed4OsV16Qy52UxX0M-ssaMpZuzS7ngMLrOQOEk8gN6H6w79ANkkSXk3LEwmy6WKN5tTEt1JTa65P0enz4cItMr_Rr0cC0aiN2x4eVX2aPO9RVdDsBjDU1WV_JaxVA6r5t", "domain": "youtube.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHzbSD46194Od4UNMs2jS9gajqEBDfllaXuaHraYahiQnL6iVClbFjcgeI3c5-krSVPKY-S6ftjIhGdO1RmvCRuq4Mu5ZudZYEVi7pfrLTSOEMPDLGsq0ru4ccGPLh-Kr_zzTkPnfvhluwmcUF-QoGgUmhNfSlkbSRNYmE71VBF-YgP5w0XobbCL1olkwxpKqBpZmiAi9-Hm4SN", "domain": "towardsai.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGrnQJ7QCuu3DdEPYE6glip9U-Sg9pIZ3jVLkJ3bXX1k3K3k0zV6FL9tvFIEGGJyjc5Gg6LHK9Ev7I3zc6TYANhy1OCh7Thnabbbb6XPfGj0OHOfWbdCacpxXEu2GuwyHxoNI0=", "domain": "rasa.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGRPIqQFlRZ0zjPmtz-gSDVaVnGGfz07kyreMbkq4POuIGJGS6PnLvy3WtJwmDPadbUAB7eqj_LKh8-qaXcuc7mbVpbv4zK2s7jRRDpFW20nAYamdGB9WrXpfVJPPpecY0Oszd4orUYqZbin68=", "domain": "browser-use.com" } ], "searchQueries": [ "top enterprise AI agent frameworks", "best AI agent frameworks for production 2026" ] }, { "prompt": 2, "engine": "GEMINI", "run": 3, "askedAt": "2026-10-09T01:29:51.990Z", "text": "Choosing the best AI agent framework for production depends heavily on your requirements for state management, human-in-the-loop controls, and multi-agent orchestration. \n\n1. **LangGraph** — [langchain.com/langgraph](https://www.langchain.com/langgraph) \n Widely regarded as the industry standard for complex, stateful production workflows, offering explicit graph-based control over loops, durable checkpointing, and robust human-in-the-loop capabilities.\n\n2. **CrewAI Enterprise** — [crewai.com](https://www.crewai.com) \n The leading choice for role-based, multi-agent collaborative workflows, providing a streamlined developer experience coupled with production support and telemetry features.\n\n3. **OpenAI Agents SDK** — [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python) \n A lightweight, low-overhead framework optimized for native OpenAI model features, agent handoffs, and fast tool execution.\n\n4. **Pydantic AI** — [ai.pydantic.dev](https://ai.pydantic.dev) \n An exceptional choice for type-safe Python applications, leveraging Pydantic validation to ensure structured, predictable inputs and outputs across agent steps.\n\n5. **Microsoft AutoGen (AG2)** — [github.com/ag2ai/ag2](https://github.com/ag2ai/ag2) \n A robust, enterprise-async engine tailored for complex conversational programming and distributed multi-agent conversation patterns.\n\n6. **Mastra** — [mastra.ai](https://mastra.ai) \n A full-stack TypeScript framework designed for web developers looking to embed reliable agents, RAG, and workflow steps natively into Node-based architectures.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI Enterprise", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "ai.pydantic.dev" }, { "name": "Microsoft AutoGen (AG2)", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHQtZ-bwB4Z-ns8FhG1R3uYUL0qVnSaMhMOG0uI03YgjbYuiODjRvc_GqKwYko_QyoHOizCzp_bGaL6HEhnDjKaoDj5Q9RnfxpXjx9C-pdahGEwLtIlFkNarqsIlo3gNHw=", "domain": "youtube.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGordyjVG0tKC83iFHicbUK8-2sMDCmDKInZu-lW9ZDgfqTLMVI9wm6K76xpqZXMiLe8HO-TWcbZy_v17qfk48uvJrksKgMkU2HH7-rALpwpcdgGhp0hV0MUGl8Lk-uAxIuW52x3NGAt4jTVWiAcsWbPbCXIIfKVeo8qormFjaD2bcCGL52423TZ-gwIUcevhNB", "domain": "zimaspace.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGZ_f0q3x25zSdVPq0YR8PlzEbTDXW1GQym0IdOsohdXboPJB2jiTXjww-mup59QvVwRh5Whugy9wc_fdzQHUmxAiM6J3KVl_t7eFVqfkE026KWrET2mHyJjgcYHhdKGUI0pjREISbtl_sYS5oqym89ZwsUa4rTnLm-Gz49EANs6B5yvfA-yZv8qlVPdOTZYfWYVsCvHsIHoL0=", "domain": "reddit.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGMb2cHfLHxICxUyC4xWTEnOUCKKJCNlJ8lrukhVMyZe1e68hxuWHK-JooeErmonT8rx4A8ELt2W4eLt5pbXyGamr7D-1lmk17ZtqbCDY1Ak7uCe6OzTK0UVzJDiv4HyTlJKRe6N53x9EvPL21hm1Ye", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFqk50KqdZVJ3-rtD1VlkGLSKWl_yNFb3e3yIXChtVUEhU7nWj_1vOIVPaZ9FQUKOBt1sawq96HQEqOc9rs3COu_rQ2D97DOY8oENWdcC80UtI1N2JL3tMiA2_FEejZYFsfZy2rEZ6RW-OwSOQAL9qzXCqECBadK-_U6NIC4OPqbE3j_pgkBK5ehrjAvph3ysZwUUhFcaLBx4k=", "domain": "towardsai.net" } ], "searchQueries": [ "production ready AI agent frameworks", "best AI agent framework for production 2026" ] }, { "prompt": 2, "engine": "GROK", "run": 1, "askedAt": "2026-10-09T01:28:20.906Z", "text": "**1. LangGraph** https://www.langchain.com/langgraph \nMost battle-tested for complex stateful production agents with checkpoints, human-in-the-loop, and observability.[[1]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**2. Microsoft Agent Framework** https://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview \nStable 1.0 enterprise option with graph workflows, strong Azure/.NET support, and LTS commitment.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**3. CrewAI** https://crewai.com/ \nFastest path to role-based multi-agent production systems with high GitHub stars and Fortune 500 adoption.[[1]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**4. OpenAI Agents SDK** https://openai.github.io/openai-agents-python/ \nLightweight, minimal-overhead choice for OpenAI-native production agents with built-in guardrails and sessions.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**5. Google ADK** https://adk.dev/ \nStrong for Gemini-first or polyglot production agents with native graph workflows and multi-language support.[[3]](https://www.ayautomate.com/blog/best-multi-agent-frameworks)\n\n**6. Pydantic AI** (inferred from comparisons) https://github.com/pydantic/pydantic-ai \nType-safe Python agents ideal for reliable, model-agnostic production use with durable execution options.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Google ADK", "domain": "adk.dev" }, { "name": "Pydantic AI", "domain": "github.com" } ], "sources": [ { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com" } ], "searchQueries": [ "best AI agent frameworks for production use 2026", "top AI agent frameworks comparison production LangChain CrewAI AutoGen", "recommended AI agent frameworks enterprise production", "LangGraph official website", "CrewAI official website", "Microsoft Agent Framework official site", "OpenAI Agents SDK website", "Google ADK agent framework website" ] }, { "prompt": 2, "engine": "GROK", "run": 2, "askedAt": "2026-10-09T01:29:10.502Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice for production with explicit graph-based state control, checkpointing, human-in-the-loop, and proven enterprise deployments at Uber, LinkedIn, and Klarna.[[1]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**2. Microsoft Agent Framework** \nhttps://www.microsoft.com/en-us/ai \nStable 1.0 release with long-term support, graph workflows, and strong fit for .NET/Azure enterprises as AutoGen successor.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**3. CrewAI** \nhttps://crewai.com \nFastest path to role-based multi-agent crews with high GitHub popularity and production monitoring options for quick workflows.[[1]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**4. OpenAI Agents SDK** \nhttps://openai.com \nLightweight, minimal-overhead framework optimized for OpenAI models with built-in guardrails, handoffs, and sessions.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**5. Google ADK** \nhttps://cloud.google.com \nGemini-native toolkit with multi-language support (Python, TS, Go, Java), graph workflows, and strong GCP integration.[[3]](https://www.ayautomate.com/blog/best-multi-agent-frameworks)\n\n**6. LlamaIndex Workflows** \nhttps://www.llamaindex.ai \nSpecialized for RAG-heavy and document-centric agents with reliable retrieval pipelines and production-grade indexing.[[4]](https://uvik.net/blog/agentic-ai-frameworks/)\n\n**7. Pydantic AI** \nhttps://docs.pydantic.dev \nType-safe Python framework emphasizing validated outputs, testability, and durable execution integrations for reliable agents.[[5]](https://theexpertranking.com/developers/best-ai-agent-frameworks/)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Google ADK", "domain": "cloud.google.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Pydantic AI", "domain": "docs.pydantic.dev" } ], "sources": [ { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com" }, { "url": "https://uvik.net/blog/agentic-ai-frameworks/", "domain": "uvik.net" }, { "url": "https://theexpertranking.com/developers/best-ai-agent-frameworks/", "domain": "theexpertranking.com" } ], "searchQueries": [ "best AI agent frameworks for production use 2026", "top AI agent frameworks comparison production deployment", "LangChain vs CrewAI vs AutoGen vs LlamaIndex production 2026" ] }, { "prompt": 2, "engine": "GROK", "run": 3, "askedAt": "2026-10-09T01:30:06.601Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice for production due to explicit graph-based state management, native checkpoints, human-in-the-loop support, and proven enterprise deployments at companies like Uber, LinkedIn, and Klarna.[[1]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**2. Microsoft Agent Framework** \nhttps://learn.microsoft.com/semantic-kernel \nStable 1.0 release with long-term support, built-in orchestration patterns, and strong fit for .NET/Azure enterprise environments.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**3. CrewAI** \nhttps://www.crewai.com \nExcellent for rapid role-based multi-agent production systems with simple APIs, high GitHub popularity, and enterprise monitoring options.[[3]](https://www.ayautomate.com/blog/best-multi-agent-frameworks)\n\n**4. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/agents \nLightweight, model-flexible option ideal for OpenAI-centric production agents with clean handoffs, guardrails, and minimal overhead.[[1]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**5. Google ADK** \nhttps://developers.google.com/vertex-ai/generative-ai/docs/agent-development-kit \nStrong for Gemini-native or polyglot teams needing graph workflows, native MCP support, and multi-language production deployment.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**6. Pydantic AI** \nhttps://docs.pydantic.dev \nBest-in-class type safety and structured outputs for reliable Python production agents with any model provider.[[4]](https://theexpertranking.com/developers/best-ai-agent-frameworks/)\n\n**7. LlamaIndex Workflows** \nhttps://www.llamaindex.ai \nOptimized for RAG-heavy and data-intensive production agents with strong retrieval, indexing, and event-driven orchestration.[[5]](https://rtslabs.com/best-agentic-ai-frameworks)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Google ADK", "domain": "developers.google.com" }, { "name": "Pydantic AI", "domain": "docs.pydantic.dev" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com" }, { "url": "https://theexpertranking.com/developers/best-ai-agent-frameworks/", "domain": "theexpertranking.com" }, { "url": "https://rtslabs.com/best-agentic-ai-frameworks", "domain": "rtslabs.com" } ], "searchQueries": [ "best AI agent frameworks for production use 2026", "top production-ready AI agent frameworks comparison", "LangChain vs CrewAI vs AutoGen vs LlamaIndex production" ] }, { "prompt": 2, "engine": "AI_OVERVIEW", "run": 1, "askedAt": "2026-10-10T15:13:40.814Z", "text": "**LangGraph** is widely considered the top choice for complex, deterministic, stateful production use cases, while other frameworks fit specific technology stacks or architecture styles.[[1]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[2]](https://www.langchain.com/resources/ai-agent-frameworks)[[3]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n\n### Top Frameworks by Production Scenario\n\n- **LangGraph (Python / TypeScript)** \n\t- **Best for:** Complex, stateful, multi-step workflows requiring exact control, branching state machines, human-in-the-loop approvals, and checkpointing.\n\t- **Why it wins in production:** Built on top of LangChain , it treats agent workflows as explicit graphs rather than loose magic loops, making error recovery and state tracking predictable.[[1]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)[[2]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[3]](https://www.youtube.com/watch?v=vVZ5bEdv61w&t=300)\n- **CrewAI (Python)** \n\t- **Best for:** Rapid prototyping and role-based multi-agent teams (e.g., distinct researcher, writer, and reviewer roles).\n\t- **Why it fits:** It provides clean, intuitive abstractions when your business logic naturally breaks down into collaborative human-style team handoffs.[[1]](https://www.instagram.com/reel/DVVvMiBiGrK/)[[2]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n- **Microsoft Agent Framework (Python / .NET)** \n\t- **Best for:** Enterprise, Azure-heavy, or mixed .NET/Python environments.\n\t- **Why it fits:** It unifies the legacy AutoGen and Semantic Kernel approaches into a standardized multi-agent and tool-routing runtime with built-in enterprise governance.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)[[2]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n- **OpenAI Agents SDK (Python / TypeScript)** \n\t- **Best for:** Lightweight, tool-driven, and handoff-focused loops tied closely to native model APIs.\n\t- **Why it fits:** It strips away heavy abstractions, making it ideal if you prefer pairing minimalist agent logic with durable external orchestrators like Temporal.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)[[2]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n- **Mastra (TypeScript)** \n\t- **Best for:** JavaScript and TypeScript-native production stacks.\n\t- **Why it fits:** It offers built-in developer tooling, native suspend/resume workflows, and tight integration with Vercel or Next.js.[[1]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n\n\n\n---\n\n### What Actually Matters in Production\nReal-world deployments rely far less on the marketing hype of an agent \"brain\" and much more on the surrounding infrastructure:[[1]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[2]](https://www.moxo.com/blog/agentic-ai-framework-comparison)\n\n- **State Management & Persistence:** Ability to pause, save, and resume long-running sessions across server restarts.[[1]](https://www.splunk.com/en_us/blog/learn/agent-frameworks.html)[[2]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[3]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n- **Observability & Evaluation:** Tracing and debugging tools like [LangSmith](https://www.langchain.com/resources/ai-agent-frameworks) or dedicated evaluation layers to catch infinite loops and hallucinations before users see them.[[1]](https://www.openlayer.com/blog/best-ai-agent-frameworks-production-teams)[[2]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[3]](https://www.langchain.com/resources/ai-agent-frameworks)\n- **Human-in-the-Loop (HITL):** Built-in safe pauses to let a human operator inspect or approve actions (like financial transactions or data writes).[[1]](https://www.instaclustr.com/education/agentic-ai/agentic-ai-frameworks-top-10-options-in-2026/)[[2]](https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d)[[3]](https://www.workflowbuilder.io/blog/best-ai-agent-frameworks)\n\nIf you share your **primary programming language** (Python or TypeScript), the **type of task** (e.g., customer support, data pipelines, coding agent), and whether you need **multi-agent collaboration** , I can recommend the exact framework and setup for your stack.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "AutoGen", "domain": "microsoft.com" }, { "name": "Semantic Kernel", "domain": "microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Temporal", "domain": "temporal.io" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Vercel", "domain": "vercel.com" }, { "name": "Next.js", "domain": "nextjs.org" }, { "name": "LangSmith", "domain": "smith.langchain.com" } ], "sources": [ { "url": "https://pub.towardsai.net/top-ai-agent-frameworks-in-2026-a-production-ready-comparison-7ba5e39ad56d", "domain": "pub.towardsai.net", "title": "Top AI Agent Frameworks in 2026: A Production-Ready Comparison | by Pratik K Rupareliya | Towards AI" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.instaclustr.com/education/agentic-ai/agentic-ai-frameworks-top-10-options-in-2026/", "domain": "instaclustr.com", "title": "Agentic AI Frameworks: Top 8 Options in 2026" }, { "url": "https://www.workflowbuilder.io/blog/best-ai-agent-frameworks", "domain": "workflowbuilder.io", "title": "Best AI agent frameworks in 2026: a comparison for production teams" }, { "url": "https://www.openlayer.com/blog/best-ai-agent-frameworks-production-teams", "domain": "openlayer.com", "title": "The 10 best AI agent frameworks for production teams (updated ..." }, { "url": "https://www.splunk.com/en_us/blog/learn/agent-frameworks.html", "domain": "splunk.com", "title": "Top Agent Frameworks To Use in 2026: A Comparison - Splunk" }, { "url": "https://www.instagram.com/reel/DVVvMiBiGrK/", "domain": "instagram.com", "title": "Here are 5 AI agent frameworks that are worth building with in ..." }, { "url": "https://www.youtube.com/watch?v=vVZ5bEdv61w&t=300", "domain": "youtube.com", "title": "Which AI Agent Framework Should You Choose? | Uplatz" }, { "url": "https://www.moxo.com/blog/agentic-ai-framework-comparison", "domain": "moxo.com", "title": "Complete guide to agentic AI frameworks: Comparison ..." } ], "searchQueries": "not exposed" }, { "prompt": 3, "engine": "OPENAI", "run": 1, "askedAt": "2026-10-09T01:28:14.313Z", "text": "1. **LangChain (Deep Agents / Agent Builder)** — https://www.langchain.com. \n Why: Widest ecosystem, mature agent tools (Deep Agents, Agent Builder) and a large community/hosted tooling for production agent workflows. ([langchain.com](https://www.langchain.com/blog/new-in-agent-builder-all-new-agent-chat-file-uploads-tool-registry?utm_source=openai))\n\n2. **Microsoft Agent Framework (successor to AutoGen + Semantic Kernel / Foundry)** — https://www.microsoft.com/devblogs (Microsoft Foundry / Agent Framework). \n Why: Enterprise-grade, opinionated open-source framework that unifies Semantic Kernel and AutoGen approaches for stateful, scalable multi-agent systems. ([devblogs.microsoft.com](https://devblogs.microsoft.com/foundry/agent-service-build2026/?utm_source=openai))\n\n3. **AutoGen (Microsoft Research)** — https://github.com/microsoft/autogen (project pages / docs). \n Why: Designed for conversation-driven multi-agent orchestration and research-to-production multi-agent dialogue patterns. ([microsoft.com](https://www.microsoft.com/en-us/research/wp-content/uploads/2025/01/WEF-2025_Leave-Behind_AutoGen.pdf?utm_source=openai))\n\n4. **OpenAI Agents SDK** — https://platform.openai.com (OpenAI Agents SDK docs / repo). \n Why: Provider-agnostic, minimalist SDK focused on reliable agent primitives and interoperability with many LLM providers. ([aiagentrank.io](https://aiagentrank.io/blog/best-open-source-ai-agent-frameworks-2026?utm_source=openai))\n\n5. **LangGraph (LangChain-related graph-first framework)** — https://github.com/langchain-ai/langgraph (project page). \n Why: Graph-based orchestration for complex, stateful flows—good when you need explicit flow structure and observability. ([alicelabs.ai](https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026?utm_source=openai))\n\n6. **LlamaIndex (Workflows / retrieval + agent integration)** — https://gpt-index.readthedocs.io (LlamaIndex docs). \n Why: Strong retrieval-as-a-service and RAG + workflow integrations for agents that need grounded access to private data. ([alicelabs.ai](https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026?utm_source=openai))\n\n7. **Haystack (deepset) Agent / Pipelines** — https://haystack.deepset.ai. \n Why: Production-ready retrieval + pipeline tooling with built-in support for RAG and agent-like orchestration in document-heavy applications. ([github.com](https://github.com/prayagupa/agent-frameworks?utm_source=openai))\n\nNotes: The agent ecosystem is fast-moving and several projects (AutoGen, Semantic Kernel, LangChain, LangGraph, OpenAI Agents SDK, etc.) continue to evolve; the items above are ranked for 2026-era tradeoffs (ecosystem, production-readiness, multi-agent features, retrieval support). If you want a narrower ranking (e.g., best for multi-agent research, best for enterprise, best for retrieval/RAG, or best TypeScript-first), tell me which use case and I’ll return a 1–3 recommendation shortlist for that use case.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "AutoGen", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "LangGraph", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "gpt-index.readthedocs.io" }, { "name": "Haystack", "domain": "haystack.deepset.ai" } ], "sources": [ { "url": "https://www.langchain.com/blog/new-in-agent-builder-all-new-agent-chat-file-uploads-tool-registry?utm_source=openai", "domain": "langchain.com", "title": "New in Agent Builder: all new agent chat, file uploads + tool registry" }, { "url": "https://devblogs.microsoft.com/foundry/agent-service-build2026/?utm_source=openai", "domain": "devblogs.microsoft.com", "title": "Build and run agents at scale with Microsoft Foundry at Build 2026 | Microsoft Foundry Blog" }, { "url": "https://www.microsoft.com/en-us/research/wp-content/uploads/2025/01/WEF-2025_Leave-Behind_AutoGen.pdf?utm_source=openai", "domain": "microsoft.com", "title": "AutoGen \nMicrosoft Research \nJanuary 2025\n\n## In" }, { "url": "https://aiagentrank.io/blog/best-open-source-ai-agent-frameworks-2026?utm_source=openai", "domain": "aiagentrank.io", "title": "Best Open-Source AI Agent Frameworks 2026: Ranked" }, { "url": "https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026?utm_source=openai", "domain": "alicelabs.ai", "title": "Open Source AI Agent Frameworks Comparison 2026" }, { "url": "https://github.com/prayagupa/agent-frameworks?utm_source=openai", "domain": "github.com", "title": "GitHub - prayagupa/agent-frameworks: agent frameworks · GitHub" } ], "searchQueries": [ "best open-source framework for LLM agents 2026 comparison LangChain AutoGen Microsoft Semantic Kernel AutoGen Reflexion", "LangChain agents 2026 features", "AutoGen by Microsoft Agents framework 2026", "LlamaIndex agents 2026", "MetaGPT agents framework 2026", "Open-source agent frameworks list 2026 LangChain, Microsoft Semantic Kernel, AutoGen, BabyAGI, Haystack, AgentVerse" ] }, { "prompt": 3, "engine": "OPENAI", "run": 2, "askedAt": "2026-10-09T01:29:05.745Z", "text": "1. **LangChain (including LangGraph / Deep Agents)** — https://www.langchain.com — Best general-purpose, production-ready open-source agent stack with wide tooling, observability, and model/provider flexibility. ([langchain.com](https://www.langchain.com/oss-overview?utm_source=openai))\n\n2. **OpenAI Agents SDK** — https://platform.openai.com/docs/agents (OpenAI Agents docs) — Provider-native SDK that’s simple to adopt if you already use OpenAI (good for single-agent flows and tight provider integration). ([thefrontierwire.com](https://thefrontierwire.com/articles/best-agent-orchestration-frameworks/?utm_source=openai))\n\n3. **Microsoft AutoGen / Microsoft Agent Framework** — https://github.com/microsoft or Microsoft Agent docs — Strong multi-agent conversation primitives and enterprise-grade features; useful for multi-actor workflows and teams invested in Microsoft stack. ([arxiv.org](https://arxiv.org/abs/2308.08155?utm_source=openai))\n\n4. **LangGraph** — https://www.langchain.com/oss-overview or LangGraph repo/docs — Graph-oriented agent framework focused on explicit state, branching, persistence, and recovery (favored for complex, production orchestration). ([langchain.com](https://www.langchain.com/oss-overview?utm_source=openai))\n\n5. **Hugging Face Agents / smolagents** — https://huggingface.co/docs/hub/main/agents — Lightweight, Hub-integrated agent tooling that’s provider-agnostic and neat for experiments or self-hosted stacks. ([huggingface.co](https://huggingface.co/docs/hub/main/agents?utm_source=openai))\n\n6. **Pydantic AI (PydanticAI agent tooling)** — https://pydantic-docs or PydanticAI repo — Type-safe, developer-friendly agent framework that integrates well into Python apps and emphasizes schema/contract safety. ([raw.githubusercontent.com](https://raw.githubusercontent.com/vasilyevdm/ai-agent-handbook/main/COMPREHENSIVE_AGENT_ENGINEERING_GUIDE_2026.pdf?utm_source=openai))\n\n7. **CrewAI** — https://github.com/CrewAI or CrewAI project page — Purpose-built for multi-agent collaboration (crews), a solid choice when you want structured multi-role agents out of the box. ([aiflowpost.com](https://aiflowpost.com/self-hosted/best-open-source-ai-agent-frameworks/?utm_source=openai))\n\nNotes: I ranked these by general applicability, production features (state, observability, persistence), and community/industry traction in 2026. If you want a narrower recommendation (e.g., “best for single-node self-hosted,” “best TypeScript/web-first,” or “best for multi-agent research”), tell me which constraint and I’ll re-rank accordingly.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Microsoft AutoGen", "domain": "github.com" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Hugging Face Agents", "domain": "huggingface.co" }, { "name": "Pydantic AI", "domain": "pydantic-docs" }, { "name": "CrewAI", "domain": "github.com" } ], "sources": [ { "url": "https://www.langchain.com/oss-overview?utm_source=openai", "domain": "langchain.com", "title": "Open Source Agent Stack | LangChain OSS Overview" }, { "url": "https://thefrontierwire.com/articles/best-agent-orchestration-frameworks/?utm_source=openai", "domain": "thefrontierwire.com", "title": "Best AI agent frameworks 2026: 10 open-source compared | The Frontier Wire" }, { "url": "https://arxiv.org/abs/2308.08155?utm_source=openai", "domain": "arxiv.org", "title": "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation" }, { "url": "https://huggingface.co/docs/hub/main/agents?utm_source=openai", "domain": "huggingface.co", "title": "Agents · Hugging Face" }, { "url": "https://raw.githubusercontent.com/vasilyevdm/ai-agent-handbook/main/COMPREHENSIVE_AGENT_ENGINEERING_GUIDE_2026.pdf?utm_source=openai", "domain": "raw.githubusercontent.com", "title": "The Comprehensive Guide to AI Agent Engineering (March 2026)" }, { "url": "https://aiflowpost.com/self-hosted/best-open-source-ai-agent-frameworks/?utm_source=openai", "domain": "aiflowpost.com", "title": "Best Open Source AI Agent Frameworks (2026) | AIFlowPost" } ], "searchQueries": [ "best open-source framework for LLM agents 2026 comparison", "LangChain open-source LLM agents 2026", "LlamaIndex agents 2026", "AutoGen open-source LLM agents 2026", "Hugging Face agents framework 2026 \"agents\" toolkit", "BabyAGI open-source agent frameworks 2026" ] }, { "prompt": 3, "engine": "OPENAI", "run": 3, "askedAt": "2026-10-09T01:30:03.982Z", "text": "1. **LangChain** — https://www.langchain.com — The most mature, widely-adopted open-source agent/agent-ecosystem with rich tooling, multi-model support, and many production-ready integrations. ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\n2. **Hugging Face — smolagents** — https://github.com/huggingface/smolagents — A compact, open-source agent library from Hugging Face focused on lightweight ReAct/code-agent patterns and easy local-model use. ([github.com](https://github.com/huggingface/smolagents?utm_source=openai))\n\n3. **Microsoft Semantic Kernel (Agent Framework)** — https://github.com/microsoft/semantic-kernel / docs.microsoft.com semantic-kernel — A production-oriented agent framework with explicit agent abstractions, orchestration, and SDKs (C#/Python) for enterprise scenarios. ([github.com](https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/GettingStartedWithAgents/README.md?utm_source=openai))\n\n4. **Auto-GPT (Significant-Gravitas)** — https://github.com/Significant-Gravitas/Auto-GPT — An experiment-driven open-source autonomous agent project and community ecosystem for goal-directed multi-step automation. ([github.com](https://github.com/Centaurioun/Auto-GPT?utm_source=openai))\n\n5. **Hugging Face Agents (Agents docs / MCP & Skills)** — https://huggingface.co/docs/hub/main/agents — HF’s integrated “Agents” tooling (Skills/MCP) for tying models, datasets, and community tools into agentic workflows, especially for open models. ([huggingface.co](https://huggingface.co/docs/hub/main/agents?utm_source=openai))\n\n6. **Ray (for scaling/production of agents)** — https://docs.ray.io — Not an agent DSL itself but the standard open-source platform to scale, orchestrate, and serve multi-agent/LLM workloads (Ray Serve, Ray AIR). Use with LangChain/others for production. ([docs.ray.io](https://docs.ray.io/en/latest/index.html?utm_source=openai))\n\n7. **AgentForge (open-source research framework)** — (GitHub / arXiv paper) — A lightweight modular framework aiming to simplify building LLM-driven autonomous agents (research + prototype focused). ([arxiv.org](https://arxiv.org/abs/2601.13383?utm_source=openai))\n\nIf you want, I can (without asking questions): (A) pick the single best choice for a given use case (research, production, local-only, multi-agent), or (B) give quick pros/cons and example starter repos/CLI commands for the top 3. Which would you like me to produce next?", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "Hugging Face", "domain": "github.com" }, { "name": "Microsoft", "domain": "github.com" }, { "name": "Auto-GPT", "domain": "github.com" }, { "name": "Hugging Face", "domain": "huggingface.co" }, { "name": "Ray", "domain": "docs.ray.io" }, { "name": "AgentForge", "domain": "arxiv.org" } ], "sources": [ { "url": "https://www.langchain.com/langchain?utm_source=openai", "domain": "langchain.com", "title": "LangChain: Open Source AI Agent Framework for Any Model" }, { "url": "https://github.com/huggingface/smolagents?utm_source=openai", "domain": "github.com", "title": "GitHub - huggingface/smolagents: 🤗 smolagents: a barebones library for agents that think in code. · GitHub" }, { "url": "https://github.com/microsoft/semantic-kernel/blob/main/dotnet/samples/GettingStartedWithAgents/README.md?utm_source=openai", "domain": "github.com", "title": "semantic-kernel/dotnet/samples/GettingStartedWithAgents/README.md at main · microsoft/semantic-kernel · GitHub" }, { "url": "https://github.com/Centaurioun/Auto-GPT?utm_source=openai", "domain": "github.com", "title": "GitHub - Centaurioun/Auto-GPT: An experimental open-source attempt to make GPT-4 fully autonomous. · GitHub" }, { "url": "https://huggingface.co/docs/hub/main/agents?utm_source=openai", "domain": "huggingface.co", "title": "Agents · Hugging Face" }, { "url": "https://docs.ray.io/en/latest/index.html?utm_source=openai", "domain": "docs.ray.io", "title": "Welcome to Ray! — Ray 2.59.0" }, { "url": "https://arxiv.org/abs/2601.13383?utm_source=openai", "domain": "arxiv.org", "title": "A Lightweight Modular Framework for Constructing Autonomous Agents Driven by Large Language Models: Design, Implementation, and Applications in AgentForge" } ], "searchQueries": [ "LangChain open-source agent framework LangChain agents GitHub", "Microsoft Semantic Kernel agents open source GitHub", "Auto-GPT open source agent framework GitHub Auto-GPT", "Hugging Face Agents framework 'agents' open source", "Ray AI agents framework 'Ray RLlib' 'Ray Serve' agents LLM" ] }, { "prompt": 3, "engine": "ANTHROPIC", "run": 1, "askedAt": "2026-10-09T01:28:10.967Z", "text": "I'll search for current information on the best open-source frameworks for LLM agents.\nBased on the latest 2026 data, here are the top open-source frameworks for LLM agents:\n\n1. **LangGraph** — https://github.com/langchain-ai/langgraph\n \nStrongest pick for production agents that need state, retries, and human approval steps\n.\n\n2. **CrewAI** — https://github.com/crewAIInc/crewAI\n \nFast role-based multi-agent prototypes with a gentle learning curve\n.\n\n3. **Claude Agent SDK** — https://github.com/anthropics/anthropic-sdk-python\n \nBest Anthropic-native primitives\n for building agents with Claude models.\n\n4. **LlamaIndex (Workflows)** — https://github.com/run-llama/llama_index\n \nLeads for document-heavy\n agent applications with RAG capabilities.\n\n5. **Pydantic AI** — https://github.com/pydantic/pydantic-ai\n \nBest type-safe Python\n agents with validated outputs and model flexibility.\n\n6. **Google ADK** — https://github.com/google-cloud-python/google-cloud-python\n \nBest for .NET / Python enterprise stacks\n with cloud integration.\n\n7. **OpenAI Agents SDK** — https://github.com/openai/openai-python\n \nBest for traced, guarded agents with few primitives\n.\n\n\nLangGraph 1.0 is ranked best overall for stateful production workflows\n, while CrewAI offers the fastest path to prototyping multi-agent systems.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "github.com" }, { "name": "Claude Agent SDK", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "github.com" }, { "name": "Google ADK", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" } ], "sources": [ { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://pickaxe.co/post/top-ai-agent-frameworks", "domain": "pickaxe.co", "title": "Top 15 AI Agent Frameworks in 2026" }, { "url": "https://tinycommand.com/ai-agents/open-source-ai-agent-frameworks", "domain": "tinycommand.com", "title": "Best Open Source AI Agent Frameworks in 2026 (Compared) · TinyCommand" }, { "url": "https://dev.to/sonotommy/8-open-source-frameworks-for-building-ai-agents-that-actually-work-in-2026-1hhm", "domain": "dev.to", "title": "8 Open-Source Frameworks for Building AI Agents That Actually Work in 2026 - DEV Community" }, { "url": "https://contabo.com/blog/best-open-source-ai-agent-frameworks/", "domain": "contabo.com", "title": "Best Open-Source AI Agent Frameworks to Self-Host in 2026" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Open-Source AI Agent Frameworks on GitHub (2026)" }, { "url": "https://dev.to/ialijr/top-10-most-starred-ai-agent-frameworks-on-github-2026-3d4o", "domain": "dev.to", "title": "top 10 most starred ai agent frameworks on github 2026 3d4o" } ], "searchQueries": [ "best open-source LLM agent frameworks 2026" ] }, { "prompt": 3, "engine": "ANTHROPIC", "run": 2, "askedAt": "2026-10-09T01:29:06.660Z", "text": "I'll search for current information about the best open-source frameworks for LLM agents.\nBased on current information, here are the top open-source frameworks for LLM agents, ranked by production readiness and adoption:\n\n1. **LangGraph**, https://github.com/langchain-ai/langgraph\n \nProduction-grade agent framework that reached 1.0 in October 2025 after powering agents at Uber, LinkedIn, and Klarna\n.\n\n2. **CrewAI**, https://github.com/joaomdmoura/crewai\n \nMulti-agent framework where each agent gets a role and goal, and it's cited as the fastest to go from zero to a working prototype with a large community\n.\n\n3. **LangChain**, https://github.com/langchain-ai/langchain\n \nThe most widely adopted open-source framework with ~134k GitHub stars and more than 1,000 pre-built integrations\n.\n\n4. **Dify**, https://github.com/langgenius/dify\n \nLow-code platform with over 144,000 GitHub stars and a visual interface accessible to non-technical users\n.\n\n5. **Haystack**, https://github.com/deepset-ai/haystack\n \nTop open-source framework for production-ready LLM apps, described as an AI orchestration framework well-suited for RAG, autonomous agents, and multimodal applications\n.\n\n6. **Google ADK (Agent Development Kit)**, https://github.com/google/adk-python\n \nGoogle's agent development framework with Apache 2.0 license and 19k GitHub stars\n.\n\nThe best choice depends on your needs: \nLangGraph for enterprise apps needing state management, CrewAI for quick multi-agent setups, and Dify for teams preferring visual, low-code development\n.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "github.com" }, { "name": "LangChain", "domain": "github.com" }, { "name": "Dify", "domain": "github.com" }, { "name": "Haystack", "domain": "github.com" }, { "name": "Google ADK (Agent Development Kit)", "domain": "github.com" } ], "sources": [ { "url": "https://redwerk.com/blog/top-llm-frameworks/", "domain": "redwerk.com", "title": "Top 7 LLM Frameworks 2026" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.gumloop.com/blog/open-source-ai-agents", "domain": "gumloop.com", "title": "5 best open source AI agents I'm using in 2026" }, { "url": "https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/", "domain": "blog.jetbrains.com", "title": "Top Agentic Frameworks for Building Applications 2026 - The JetBrains Blog" }, { "url": "https://tinycommand.com/ai-agents/open-source-ai-agent-frameworks", "domain": "tinycommand.com", "title": "Best Open Source AI Agent Frameworks in 2026 (Compared) · TinyCommand" }, { "url": "https://evermind.ai/blogs/best-open-source-agent-memory-frameworks-2026", "domain": "evermind.ai", "title": "Best Open Source Agent Memory Frameworks 2026 - EverMind AI Long-Term Memory System Updates & Breakthroughs" }, { "url": "https://contabo.com/blog/best-open-source-ai-agent-frameworks/", "domain": "contabo.com", "title": "Best Open-Source AI Agent Frameworks to Self-Host in 2026" }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Open-Source AI Agent Frameworks on GitHub (2026)" } ], "searchQueries": [ "best open-source framework LLM agents 2026", "top LLM agent frameworks open source comparison" ] }, { "prompt": 3, "engine": "ANTHROPIC", "run": 3, "askedAt": "2026-10-09T01:30:00.975Z", "text": "I'll search for current information on open-source LLM agent frameworks.\nBased on the current landscape, here are the top open-source LLM agent frameworks:\n\n1. **LangGraph**, https://github.com/langchain-ai/langgraph - \nBest overall for stateful production workflows\n; ideal for enterprise applications requiring state management and human-in-the-loop control.\n\n2. **CrewAI**, https://github.com/crewAIInc/crewAI - \nFastest path to a role-based multi-agent prototype\n; great for quickly building collaborative multi-agent systems.\n\n3. **Claude Agent SDK**, https://github.com/anthropics/anthropic-sdk-python - \nBest Anthropic-native primitives\n; optimized for Anthropic's Claude models with safety-focused design.\n\n4. **LlamaIndex Workflows**, https://github.com/run-llama/llama_index - \nBest RAG-grounded agents\n; excellent for document-heavy and retrieval-augmented applications.\n\n5. **Pydantic AI**, https://github.com/pydantic/pydantic-ai - \nBest type-safe Python\n; focuses on validated outputs and type safety for Python developers.\n\n6. **Microsoft Agent Framework**, https://github.com/microsoft/autogen - \nBest for .NET / Python enterprise stacks\n; supports multiple languages and enterprise deployments.\n\n7. **OpenAI Agents SDK**, https://github.com/openai/swarm - \nBest for traced, guarded agents with few primitives; keeps the concept count low\n.\n\n8. **Dify**, https://github.com/langgenius/dify - \nBest for LLM App + Agent Hybrid; full LLM application platform with visual workflow editor and production RAG pipeline\n.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "github.com" }, { "name": "Claude Agent SDK", "domain": "github.com" }, { "name": "LlamaIndex Workflows", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "github.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "Dify", "domain": "github.com" } ], "sources": [ { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://pickaxe.co/post/top-ai-agent-frameworks", "domain": "pickaxe.co", "title": "Top 15 AI Agent Frameworks in 2026" }, { "url": "https://tinycommand.com/ai-agents/open-source-ai-agent-frameworks", "domain": "tinycommand.com", "title": "Best Open Source AI Agent Frameworks in 2026 (Compared) · TinyCommand" }, { "url": "https://dev.to/sonotommy/8-open-source-frameworks-for-building-ai-agents-that-actually-work-in-2026-1hhm", "domain": "dev.to", "title": "8 Open-Source Frameworks for Building AI Agents That Actually Work in 2026 - DEV Community" }, { "url": "https://contabo.com/blog/best-open-source-ai-agent-frameworks/", "domain": "contabo.com", "title": "Best Open-Source AI Agent Frameworks to Self-Host in 2026" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Open-Source AI Agent Frameworks on GitHub (2026)" }, { "url": "https://dev.to/ialijr/top-10-most-starred-ai-agent-frameworks-on-github-2026-3d4o", "domain": "dev.to", "title": "top 10 most starred ai agent frameworks on github 2026 3d4o" } ], "searchQueries": [ "best open-source LLM agent frameworks 2026" ] }, { "prompt": 3, "engine": "PERPLEXITY", "run": 1, "askedAt": "2026-10-09T01:28:07.858Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production agents because its graph-based design supports durable state, branching, human approval, retries, and complex workflows; it is widely recommended as the safest default for stateful agents.[1][4][6]\n\n2. **Microsoft AutoGen** — https://github.com/microsoft/autogen — Best for conversational multi-agent systems, with MIT-licensed code and strong support for agents that collaborate through messages.[2]\n\n3. **CrewAI** — https://www.crewai.com/ — Best for quickly assembling role-based teams of agents; its task-and-crew abstraction is easier to learn than lower-level orchestration frameworks.[1][3]\n\n4. **LangChain** — https://www.langchain.com/ — Best for broad integrations and rapid prototyping, offering extensive model, API, database, and tool connectivity.[5][9]\n\n5. **OpenAI Agents SDK** — https://github.com/openai/openai-agents-python — Best for Python developers building tool-using agents with handoffs, guardrails, and tracing in a relatively streamlined SDK.\n\n6. **LlamaIndex** — https://www.llamaindex.ai/ — Best for agents centered on private or enterprise data, especially retrieval, document search, and data-connected workflows.[7]\n\n**Best single choice:** **LangGraph**—particularly if the agent must be reliable, observable, stateful, or deployed in production.[1][4][6]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft AutoGen", "domain": "github.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026", "domain": "alicelabs.ai", "title": "Open Source AI Agent Frameworks Comparison 2026" }, { "url": "https://resources.rework.com/tools/ai-agents/best-open-source-ai-agent-frameworks-2026", "domain": "resources.rework.com", "title": "Best Open-Source AI Agent Frameworks in 2026: 15 Frameworks ..." }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Open-Source AI Agent Frameworks on GitHub (2026)" }, { "url": "https://kestra.io/resources/ai/ai-agent-orchestration-frameworks", "domain": "kestra.io", "title": "Top AI Agent Orchestration Frameworks & Platforms (2026) | Kestra" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://futureagi.com/blog/oss-agent-frameworks-2026/", "domain": "futureagi.com", "title": "Comparing Open-Source AI Agent Frameworks in 2026" }, { "url": "https://zapier.com/blog/ai-agent-frameworks/", "domain": "zapier.com", "title": "AI Agent Frameworks: Definition, Comparison + Guide - Zapier" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://winder.ai/comparison-open-source-llm-frameworks-pipelining/", "domain": "winder.ai", "title": "Overview of Low-Code LLM..." }, { "url": "https://botpress.com/blog/llm-agent-framework", "domain": "botpress.com", "title": "Choosing the Right LLM Agent Framework in 2026" } ], "searchQueries": "not exposed" }, { "prompt": 3, "engine": "PERPLEXITY", "run": 2, "askedAt": "2026-10-09T01:29:04.765Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — **Best overall** for reliable, stateful, multi-step agents; its graph model supports durable execution, human approval, memory, and transparent control flow.[1][4][6]\n\n2. **Microsoft AutoGen** — https://microsoft.github.io/autogen/ — Best for multi-agent conversations and collaborative agent teams; its code is MIT-licensed and openly available.[2]\n\n3. **CrewAI** — https://www.crewai.com/ — Best for quickly assembling role-based agent teams and workflows with a relatively approachable Python API.[1][3]\n\n4. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for lightweight Python or TypeScript agents with tools, handoffs, guardrails, and tracing.[3]\n\n5. **LlamaIndex** — https://www.llamaindex.ai/ — Best for agents grounded in private data, documents, vector stores, and retrieval pipelines.[7][9]\n\n6. **Haystack** — https://haystack.deepset.ai/ — Best for production RAG and search-heavy agents where explicit pipelines and components matter.[3]\n\n7. **Semantic Kernel** — https://learn.microsoft.com/en-us/semantic-kernel/ — Best for Microsoft/.NET-oriented teams that want an open-source SDK integrating agents, plugins, memory, and enterprise services.[2][8]\n\n**Bottom line:** Choose **LangGraph** unless the primary need is rapid role-based collaboration (**CrewAI**), multi-agent experimentation (**AutoGen**), or retrieval-heavy applications (**LlamaIndex**). LangGraph is the strongest general-purpose default because it combines broad ecosystem adoption with explicit, inspectable stateful workflows.[1][4][5]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Haystack", "domain": "haystack.deepset.ai" }, { "name": "Semantic Kernel", "domain": "learn.microsoft.com" } ], "sources": [ { "url": "https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026", "domain": "alicelabs.ai", "title": "Open Source AI Agent Frameworks Comparison 2026" }, { "url": "https://resources.rework.com/tools/ai-agents/best-open-source-ai-agent-frameworks-2026", "domain": "resources.rework.com", "title": "Best Open-Source AI Agent Frameworks in 2026: 15 Frameworks ..." }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Open-Source AI Agent Frameworks on GitHub (2026)" }, { "url": "https://kestra.io/resources/ai/ai-agent-orchestration-frameworks", "domain": "kestra.io", "title": "Top AI Agent Orchestration Frameworks & Platforms (2026) | Kestra" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://futureagi.com/blog/oss-agent-frameworks-2026/", "domain": "futureagi.com", "title": "Comparing Open-Source AI Agent Frameworks in 2026" }, { "url": "https://zapier.com/blog/ai-agent-frameworks/", "domain": "zapier.com", "title": "AI Agent Frameworks: Definition, Comparison + Guide - Zapier" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://winder.ai/comparison-open-source-llm-frameworks-pipelining/", "domain": "winder.ai", "title": "Overview of Low-Code LLM..." }, { "url": "https://botpress.com/blog/llm-agent-framework", "domain": "botpress.com", "title": "Choosing the Right LLM Agent Framework in 2026" } ], "searchQueries": "not exposed" }, { "prompt": 3, "engine": "PERPLEXITY", "run": 3, "askedAt": "2026-10-09T01:29:57.502Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — **Best overall** for reliable, stateful, multi-step agents; its graph model makes workflows easier to control, test, and resume.[1][4][6]\n\n2. **CrewAI** — https://www.crewai.com — Best for quickly building role-based teams of collaborating agents, especially in Python.[1][3]\n\n3. **Microsoft AutoGen** — https://microsoft.github.io/autogen/ — Best for conversational multi-agent systems and flexible agent-to-agent collaboration; its code is MIT-licensed.[2][3]\n\n4. **PydanticAI** — https://ai.pydantic.dev — Best for Python teams that want strongly typed outputs, validation, and clean production-oriented code.[3]\n\n5. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for lightweight agent applications using tools, handoffs, guardrails, and tracing with minimal framework overhead.[3]\n\n6. **LlamaIndex** — https://www.llamaindex.ai — Best for agents that need to retrieve, search, and reason over private documents or structured data.[3][7]\n\n7. **LangChain** — https://www.langchain.com — Best for broad model, API, database, and vector-store integrations, with a large ecosystem and more than 1,000 integrations.[5]\n\n**Pick LangGraph** unless the priority is rapid multi-agent prototyping, in which case CrewAI is the simpler starting point.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "LangChain", "domain": "langchain.com" } ], "sources": [ { "url": "https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026", "domain": "alicelabs.ai", "title": "Open Source AI Agent Frameworks Comparison 2026" }, { "url": "https://resources.rework.com/tools/ai-agents/best-open-source-ai-agent-frameworks-2026", "domain": "resources.rework.com", "title": "Best Open-Source AI Agent Frameworks in 2026: 15 Frameworks ..." }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Open-Source AI Agent Frameworks on GitHub (2026)" }, { "url": "https://kestra.io/resources/ai/ai-agent-orchestration-frameworks", "domain": "kestra.io", "title": "Top AI Agent Orchestration Frameworks & Platforms (2026) | Kestra" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://futureagi.com/blog/oss-agent-frameworks-2026/", "domain": "futureagi.com", "title": "Comparing Open-Source AI Agent Frameworks in 2026" }, { "url": "https://zapier.com/blog/ai-agent-frameworks/", "domain": "zapier.com", "title": "AI Agent Frameworks: Definition, Comparison + Guide - Zapier" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://winder.ai/comparison-open-source-llm-frameworks-pipelining/", "domain": "winder.ai", "title": "Overview of Low-Code LLM..." }, { "url": "https://botpress.com/blog/llm-agent-framework", "domain": "botpress.com", "title": "Choosing the Right LLM Agent Framework in 2026" } ], "searchQueries": "not exposed" }, { "prompt": 3, "engine": "GEMINI", "run": 1, "askedAt": "2026-10-09T01:28:11.557Z", "text": "1. **LangGraph**\n - Website: [github.com/langchain-ai/langgraph](https://github.com/langchain-ai/langgraph)\n - The go-to open-source framework for building stateful, production-grade, multi-agent applications using graph-based control flows and native checkpointing.\n\n2. **CrewAI**\n - Website: [github.com/crewAIInc/crewAI](https://github.com/crewAIInc/crewAI)\n - A popular framework designed for orchestrating role-playing autonomous agent teams that collaborate to tackle complex, multi-step workflows.\n\n3. **AutoGen (AG2)**\n - Website: [github.com/microsoft/autogen](https://github.com/microsoft/autogen)\n - Microsoft’s foundational multi-agent conversation framework, allowing diverse agents to interact seamlessly through customizable message exchanges.\n\n4. **Smolagents**\n - Website: [github.com/huggingface/smolagents](https://github.com/huggingface/smolagents)\n - Hugging Face's lightweight, highly minimalist framework built around the concept of letting LLMs write and execute code actions directly.\n\n5. **Pydantic AI**\n - Website: [github.com/pydantic/pydantic-ai](https://github.com/pydantic/pydantic-ai)\n - A modern, type-safe Python framework that leverages Pydantic schemas to ensure reliable, structured, and validated outputs from agent loops.\n\n6. **Mastra**\n - Website: [github.com/mastra-ai/mastra](https://github.com/mastra-ai/mastra)\n - A TypeScript-native framework equipped with built-in workflows, robust RAG integrations, and comprehensive observability tools for web developers.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "github.com" }, { "name": "AutoGen (AG2)", "domain": "github.com" }, { "name": "Smolagents", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "github.com" }, { "name": "Mastra", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGAycM-o_J9qlFHU40XAAcqYmo0TNHMg211zNMzssCuSdosjXAont2YSEePs6Ncqp_lS00__WJzfz2FctD87EeL93pnYzGZqHm6seizCdehZ6GlD8IraZxXlrkbfPz3pKBT5i6xzk-nlR-M8GuEkyAT7JEKSEHOiD79-rdSCrEnGMc6Pu6pgxz59W90fudywqb3OnO7kl_Xgx8v9mESBg==", "domain": "dev.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE5mEdzz-hgPd-6nLKok_rnc-4aHp0GIXcjnK84aiuKCrp_e3RmWG1tD2NIXW-NJWeYQhYJK9Cd2eNchfj2aNERAvXBTviaQiyrpQN91CIl_SwrHEzAY3s7hbyGnnjT47A2hTb4NMOrJx8pnTr_glGnJ4pq6BHDCdxdg9ABfA==", "domain": "ranksquire.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHj1qe_9vISHzxoQ-uuuqI4nlVIJAUJfcN--phu2aKJ8j7aPjXN-6jdJgzpeiPZ4huK9xQwkJuFakTUDJp0099wXJfQO-ZC0O0MJ586n2vTpmuK7pnqFT60rZYS9Cm9RsXLoe89jDySd5ugHHYvG7s=", "domain": "gurusup.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHKn9D_hqtrn-5IfeXpjQ6iRvmaN8BE4-b4oWQslAxoxWyT4vs0nD6yfSiYMrUJRpyXMdv6zZ9bamGXVwGIHgjLFY-zqZlCJfKUogxRn6F4rv5dKEN-75ViuS7LH3CjvgtprU8vDujF4lUuk37LV3bV4x-ol7YUF5fXOfPGceDhlDtpfmEO-GhRuFqDYtsdL8l0WOOR4N_CKnku6Zk=", "domain": "medium.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEssD0RKFWcGHXOQvU1_G0vwAnp5aofqHoQrJ2JlGVprG58UtpUHiRDM7k-foONSZtxqN5iRgLLOPzfL94XYR__urinpbUaASKvEpIC5ADkS8xYX7HXMh7fR4GSfnvuxSYt2psyY7I=", "domain": "github.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHxNdV0PxtE_MlNT4SaqfsNoLCh4a3-oAauyTEtkfcIY35EiNJsbGG75-xcjrNKYgJs2pFL6U7QgKZcJbCx3y3XLguTdKLaQ66AoNIdtjxerls1uE2XA-DbP2VBVUKZBofBqVexME8jCkGMWAbopCJpYaGGsQgqzKsN6mo=", "domain": "agentailor.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG1Ks2Ylhwm5Ua3RbAUM3UJmnaaUyN2gaYGzwXA1nMowJwI-rPTv4QfZSHXhrNOTtjS1H_TKVXsDyG-EScYm54FqLBUXtYCqvqVHdVIWHmVyVoEvFtOQFzX6lYe_K2Y3aeeQJF6xeujrTjc3h69rZhlANAPzDTa", "domain": "firecrawl.dev" } ], "searchQueries": [ "top open source agent frameworks llm github stars", "best open source framework for LLM agents 2025 2026" ] }, { "prompt": 3, "engine": "GEMINI", "run": 2, "askedAt": "2026-10-09T01:29:09.149Z", "text": "1. **LangGraph** \n https://github.com/langchain-ai/langgraph \n The leading standard for production-grade, stateful agent workflows, offering precise control via graph-based state machines and built-in human-in-the-loop checkpoints.\n\n2. **CrewAI** \n https://github.com/crewai/crewAI \n An intuitive, role-based framework designed for rapidly spinning up multi-agent teams that coordinate collaboratively to achieve complex goals.\n\n3. **Microsoft AutoGen (AG2)** \n https://github.com/microsoft/autogen \n A powerful programming framework enabling complex multi-agent conversation patterns, customizable agent interactions, and flexible execution environments.\n\n4. **Pydantic AI** \n https://github.com/pydantic/pydantic-ai \n A type-safe, highly structured Python framework that leverages Pydantic schemas to build robust, predictable, and production-ready agents.\n\n5. **LlamaIndex Agents** \n https://github.com/run-llama/llama_index \n An exceptional choice for data-heavy and retrieval-augmented generation (RAG) agent workflows that require deep integration with external documents and vector stores.\n\n6. **Mastra** \n https://github.com/mastra-ai/mastra \n A TypeScript-native framework built for web developers looking to construct autonomous agents, workflows, and RAG pipelines seamlessly inside JavaScript stacks.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "github.com" }, { "name": "Microsoft AutoGen (AG2)", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "github.com" }, { "name": "LlamaIndex Agents", "domain": "github.com" }, { "name": "Mastra", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF3H5CgaoscnHx8OIOdel-Ef4SyplPwUKD3jSUBX1YCyKHXm2iwOPwgfiKFD5LOm74JoFRG1sOQNMvZGBaKT3Pqbhdl8tc_ecJfB9si2vaHu5J5dFlIrDQPs95U0E3KR21xyA==", "domain": "vdf.ai" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGn719LVzvOu_J8HBjTbr6n96rOboeGPPHxArOLVRmokQXVjiXwtIW3jhoqXCCo3Td-uL6MET-I9Bv4uQPDGaWpKtuWVtEz2XpQok-OMFRvN8DcVJoXrhiAN0QC2YG9YM638pcHlkWz62IIhYj0IOeUDZpI7SwElkipXcO9eCjteMhvW08OL6Zi-0Gdfj6igoNfG7I9c54=", "domain": "jetbrains.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEDgXoEzmJ2cPaCEbkqJnaQ1TX4CD8m0xv56NdsRyuvgubfWHWNO4DdErqK7i9jsZZM-NebfOT3PkUJ2XXt5Fh3-1dTwdtuzzbo9glGArLtbQT1oA1OqCwuecqlwuu-dJINL7aw1sypUf4TDnk-4hVQ03wWOWUXIfg8Jghp", "domain": "ranksquire.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGL4GlUpKfzOI3BKEcGjgsQBqKWBazJZR5HSWFVcZGace1rqGQJ5vfGPepEh8npgNa6T-v7zdlt5-BaWATgNqYRe5plP8QqSoAIOpQDNpW2E7ntPBmvXBr10dTK1X0JwbqoG-BP7NPacC2QAeecXTo5qUi9", "domain": "contabo.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGLBs7P5zozsOYxSnk17XddpGYjsDUMK5tF-aapV8iYHyhIb_h11hQwabDq98hRwTCwAN8a6KHCAhC47oWYNn6tVpD8gJjZiJCfq6pIO_2t4c-6fv9v747cWBYu-NZdN2FzEX9Xr9sZ7sbIMWYqy7HUzeNxianQ", "domain": "tinycommand.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGlq3MN3eG9VkYkj0e5jYsKXpneWsvzJP5p2HPwsuxigx6xS82TQs6wnkWFOCujImyoGB7guVpQMnPWx79Y2v56u3mstasZEu23sCNGhDU-8UmS5CJs_SvmZvXSAgivZYEv2oHWmZpdN2jOg9-vjxVNlwaJjfh1ysca_GUChTkr80R91gylo7C-Y4quRMuFNw8n", "domain": "towardsai.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHgLKOfLj1sN2-GgbbiTHSLXErfBG4fIv6R58HL-xCKXBakzIFabln8Agp-MZRLBuulUqDbpARSyCMcXO1IEBkCwqldYIGI66IRvC1erVnYiirDCBkfLIitlzc9eRbN5tMGybug9D8YPMCPb5A7x9iQuLgc9ejt", "domain": "braintrust.dev" } ], "searchQueries": [ "best open source framework for LLM agents 2026", "top open source LLM agent frameworks" ] }, { "prompt": 3, "engine": "GEMINI", "run": 3, "askedAt": "2026-10-09T01:30:01.410Z", "text": "1. **LangGraph** \n [github.com/langchain-ai/langchain](https://github.com/langchain-ai/langchain) \n A graph-based orchestration framework built for stateful, multi-step agents requiring fine-grained control flow and native persistence.\n\n2. **CrewAI** \n [github.com/crewai/crewai](https://github.com/crewai/crewai) \n A role-based multi-agent framework that simplifies organizing collaborative agent teams using intuitive structural definitions.\n\n3. **Pydantic AI** \n [github.com/pydantic/pydantic-ai](https://github.com/pydantic/pydantic-ai) \n A type-safe, production-ready framework built around Pydantic schema validation for robust and predictable agent outputs.\n\n4. **AutoGen (AG2)** \n [github.com/ag2ai/ag2](https://github.com/ag2ai/ag2) \n A powerful multi-agent conversation framework enabling complex, autonomous agent-to-agent interactions and workflow automations.\n\n5. **Google ADK** \n [github.com/google/adk-py](https://github.com/google/adk-py) \n A code-first agent development kit by Google designed for seamless multi-agent orchestration and deployment on Google Cloud.\n\n6. **Semantic Kernel** \n [github.com/microsoft/semantic-kernel](https://github.com/microsoft/semantic-kernel) \n An enterprise-grade Microsoft framework integrating AI plugins seamlessly with traditional programming languages like C# and Python.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "github.com" }, { "name": "AutoGen (AG2)", "domain": "github.com" }, { "name": "Google ADK", "domain": "github.com" }, { "name": "Semantic Kernel", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGSIThlGaeA0NiYoIQouCXdWLKWtv6VcB1JFgtLhiri837V1UlFZnASgCAJM8mZDURVzh5bWnAw9zRq9ehDGA4_Q6_zrYwZABXwYRP1vBvI6bus-VW8nnnWoSvx-10qdZ0fJWcMawvYa4Q6N9ZM5B8Ia-qejw7T-6kI0RAgOA==", "domain": "ranksquire.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH7dTGrSEXoqFsSCyhv262c9axBEc7q2WtCppAq4Gcq7WZpOiJbi1DFPx-e3IzeueCdaSiVd76AyhhjYgIW11WyiIn4zWa0TtpvRVuAh5q8uGLJysXrbCfu4SiKCTSr99uVTtV7cllqYNJ9KrsS", "domain": "langchain.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEKS35jo54ssdLFF2Qo6Pi9xJ4q4dt0R6A1-csaCvF0xuv3L_wfOaUXPqADA7rx1c24qqFYKdB5236ApDN1Jko0TI7HeLcmhOSfMDIuHUiFAAE43yPaX55XqWb42sKHAEkXeUmkfq4AVsJUedMVWxsepmp-_ZCyxrrf6nyv2yZK5AgbNieNEyPnlv7OcBAsfWsTi38T7Tdg0geOE3mTJA==", "domain": "dev.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQELPxJsf5JjPAkaNLf-6bZHSIptmcu9-LL8eJXYvFWhNIKo6_dlZM5GedDl9VYsk6IzLMe_td3yxLDrZWc3TaE93dXhhTnTXgRrQSGmmoj-FeNaURqHVUNa9L3eQZQzrSgI0sOlvDs=", "domain": "github.com" } ], "searchQueries": [ "best open source framework for LLM agents 2025 2026" ] }, { "prompt": 3, "engine": "GROK", "run": 1, "askedAt": "2026-10-09T01:28:22.931Z", "text": "**1. LangGraph** https://www.langchain.com/langgraph \nTop choice for production-grade, stateful multi-step agent workflows with explicit control, persistence, and human-in-the-loop.\n\n**2. CrewAI** https://crewai.com \nBest for rapid multi-agent role-based teams and quick prototypes with intuitive collaboration primitives.\n\n**3. Pydantic AI** https://docs.pydantic.dev \nStrong pick for type-safe, testable Python agents with validated outputs and dependency injection.\n\n**4. Mastra** https://mastra.ai \nLeading TypeScript framework for full-stack agents combining execution, RAG, memory, and observability.\n\n**5. smolagents** https://huggingface.co/docs/smolagents \nMinimalist Hugging Face library ideal for lightweight, code-first agents that emphasize simplicity and local models.\n\n**6. LlamaIndex** https://www.llamaindex.ai \nExcellent for document-centric and RAG-heavy agents with strong data connectors and retrieval integration.\n\n**7. OpenAI Agents SDK** https://platform.openai.com/docs/agents \nLean official option for straightforward multi-agent handoffs, guardrails, and tracing within the OpenAI ecosystem.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Pydantic AI", "domain": "pydantic.dev" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "smolagents", "domain": "huggingface.co" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" } ], "sources": [ { "url": "https://futureagi.com/blog/oss-agent-frameworks-2026/", "domain": "futureagi.com" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev" }, { "url": "https://blog.sandbase.ai/best-open-source-ai-agent-frameworks-2026/", "domain": "blog.sandbase.ai" }, { "url": "https://buildagentic.ai/frameworks", "domain": "buildagentic.ai" }, { "url": "https://www.swfte.com/blog/open-source-ai-agent-frameworks", "domain": "swfte.com" }, { "url": "https://thefrontierwire.com/articles/best-agent-orchestration-frameworks/", "domain": "thefrontierwire.com" }, { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://langfuse.com/blog/2025-03-19-ai-agent-comparison?ref=blog.sparrow.so", "domain": "langfuse.com" }, { "url": "https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/", "domain": "mefmobile.org" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://intelligenttools.co/blog/best-ai-agents", "domain": "intelligenttools.co" }, { "url": "https://gravity.fast/blog/open-source-ai-agent-frameworks/", "domain": "gravity.fast" }, { "url": "https://alicelabs.ai/en/insights/open-source-ai-agent-frameworks-comparison-2026", "domain": "alicelabs.ai" }, { "url": "https://openalternative.co/blog/best-open-source-ai-agents", "domain": "openalternative.co" }, { "url": "https://www.ayautomate.com/blog/best-open-source-ai-agent-frameworks", "domain": "ayautomate.com" }, { "url": "https://tinycommand.com/ai-agents/open-source-ai-agent-frameworks", "domain": "tinycommand.com" }, { "url": "https://raw.githubusercontent.com/kaushikb11/awesome-llm-agents/main/README.md", "domain": "raw.githubusercontent.com" }, { "url": "https://langfuse.com/blog/2025-03-19-ai-agent-comparison", "domain": "langfuse.com" }, { "url": "https://browser-use.com/posts/best-ai-agent-frameworks", "domain": "browser-use.com" } ], "searchQueries": [ "best open-source LLM agent frameworks 2026", "top open source frameworks for LLM agents comparison" ] }, { "prompt": 3, "engine": "GROK", "run": 2, "askedAt": "2026-10-09T01:29:20.208Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice for complex, stateful production agents with explicit graph control, persistence, and human-in-the-loop features.[[1]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)\n\n**2. CrewAI** \nhttps://crewai.com \nFastest path to role-based multi-agent teams and collaborative workflows with high-level abstractions.[[1]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)\n\n**3. Pydantic AI** \nhttps://ai.pydantic.dev \nExcellent for type-safe, testable Python agents with structured outputs and runtime validation.[[1]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)\n\n**4. Mastra** \nhttps://mastra.ai \nLeading TypeScript-native framework combining agents, workflows, RAG, and observability.[[2]](https://buildagentic.ai/frameworks)\n\n**5. Microsoft Agent Framework** \nhttps://learn.microsoft.com/semantic-kernel \nStrong enterprise option for .NET/Python with graph workflows, checkpointing, and Azure integration.[[1]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)\n\n**6. smolagents** \nhttps://huggingface.co/docs/smolagents \nLightweight, code-first Python framework from Hugging Face ideal for quick experimentation and minimal agents.[[2]](https://buildagentic.ai/frameworks)\n\n**7. LlamaIndex** \nhttps://www.llamaindex.ai \nBest for document-heavy and retrieval-augmented agent applications with strong data connectors.[[1]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Pydantic AI", "domain": "ai.pydantic.dev" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "smolagents", "domain": "huggingface.co" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/", "domain": "mefmobile.org" }, { "url": "https://buildagentic.ai/frameworks", "domain": "buildagentic.ai" } ], "searchQueries": [ "top open-source frameworks for LLM agents 2026", "best open source LLM agent frameworks" ] }, { "prompt": 3, "engine": "GROK", "run": 3, "askedAt": "2026-10-09T01:30:16.195Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice for stateful, production-grade agent workflows with explicit graphs, persistence, and human-in-the-loop control.[[1]](https://buildagentic.ai/frameworks)\n\n**2. CrewAI** \nhttps://crewai.com \nFastest path to role-based multi-agent teams with simple orchestration and collaboration primitives.[[2]](https://intelligenttools.co/blog/best-ai-agents)\n\n**3. Pydantic AI** \nhttps://ai.pydantic.dev \nExcellent for type-safe, validated Python agents with structured outputs and dependency injection.[[3]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)\n\n**4. Mastra** \nhttps://mastra.ai \nStrong TypeScript framework combining agents, workflows, memory, RAG, and observability in one stack.[[2]](https://intelligenttools.co/blog/best-ai-agents)\n\n**5. LlamaIndex** \nhttps://www.llamaindex.ai \nBest-in-class for RAG-heavy agents with deep document indexing, retrieval, and data connectors.[[3]](https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/)\n\n**6. Smolagents** \nhttps://huggingface.co/docs/smolagents \nMinimal, code-first agents from Hugging Face ideal for lightweight tool use and experimentation.[[4]](https://www.swfte.com/blog/open-source-ai-agent-frameworks)\n\n**7. Microsoft Agent Framework** \nhttps://github.com/microsoft/agent-framework \nEnterprise-friendly graph-based multi-agent orchestration with strong .NET and Azure integration.[[4]](https://www.swfte.com/blog/open-source-ai-agent-frameworks)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Pydantic AI", "domain": "ai.pydantic.dev" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Smolagents", "domain": "huggingface.co" }, { "name": "Microsoft Agent Framework", "domain": "github.com" } ], "sources": [ { "url": "https://buildagentic.ai/frameworks", "domain": "buildagentic.ai" }, { "url": "https://intelligenttools.co/blog/best-ai-agents", "domain": "intelligenttools.co" }, { "url": "https://mefmobile.org/best-open-source-ai-agent-frameworks-ranked-for-2026/", "domain": "mefmobile.org" }, { "url": "https://www.swfte.com/blog/open-source-ai-agent-frameworks", "domain": "swfte.com" } ], "searchQueries": [ "best open source LLM agent frameworks 2026", "top open-source frameworks for building LLM agents", "LangChain vs CrewAI vs AutoGen vs LlamaIndex for agents" ] }, { "prompt": 3, "engine": "AI_OVERVIEW", "run": 1, "askedAt": "2026-10-10T15:13:35.980Z", "text": "`There is no single \"best\" open-source framework for LLM agents` ; the right choice depends on your specific use case, team structure, and code complexity.[[1]](https://langfuse.com/blog/2025-03-19-ai-agent-comparison)[[2]](https://pub.towardsai.net/the-4-best-open-source-multi-agent-ai-frameworks-2026-9da389f9407a)The top open-source frameworks stand out for different scenarios:\n\n### Top Open-Source LLM Agent Frameworks\n\n- **[LangGraph](https://www.langchain.com/resources/ai-agent-frameworks)** \n\t- **Best for:** Complex, stateful, and cyclic multi-agent workflows where you need explicit, code-enforced control over every step.\n\t- **Pros:** Deep integration with the LangChain ecosystem, fine-grained control over state/memory, and strong caching support.\n\t- **Cons:** Steeper learning curve and requires writing more custom code than higher-level wrappers.[[1]](https://www.langchain.com/resources/ai-agent-frameworks)[[2]](https://langfuse.com/blog/2025-03-19-ai-agent-comparison)[[3]](https://www.instaclustr.com/education/agentic-ai/agentic-ai-frameworks-top-10-options-in-2026/)[[4]](https://www.youtube.com/watch?v=t4272x9x1NY&t=661)\n- **CrewAI** \n\t- **Best for:** Role-based multi-agent collaboration and fast time-to-production on linear or team-oriented workflows.\n\t- **Pros:** Easy to set up role-based agents, clean readable logs, and built-in human-in-the-loop pause options.\n\t- **Cons:** Can generate higher token usage and fresh model calls outside of standard caches.[[1]](https://pub.towardsai.net/the-4-best-open-source-multi-agent-ai-frameworks-2026-9da389f9407a)[[2]](https://www.langchain.com/resources/ai-agent-frameworks)[[3]](https://getstream.io/blog/multiagent-ai-frameworks/)[[4]](https://www.youtube.com/watch?v=t4272x9x1NY&t=661)\n- **AutoGen / AG2** \n\t- **Best for:** Conversational multi-agent simulations and chat-centric automation.\n\t- **Pros:** Flexible multi-agent conversation patterns and active open-source community backing (via AG2).\n\t- **Cons:** Can feel low-code or abstract, making debugging complex state harder as systems scale.[[1]](https://github.com/kaushikb11/awesome-llm-agents)[[2]](https://pub.towardsai.net/the-4-best-open-source-multi-agent-ai-frameworks-2026-9da389f9407a)[[3]](https://getstream.io/blog/multiagent-ai-frameworks/)[[4]](https://botpress.com/blog/llm-agent-framework)[[5]](https://www.instaclustr.com/education/agentic-ai/agentic-ai-frameworks-top-10-options-in-2026/)\n- **Pydantic AI** \n\t- **Best for:** Python developers who prioritize strict type safety and structured outputs.\n\t- **Pros:** Built cleanly on Pydantic, making tool-calling and validation reliable and predictable.\n\t- **Cons:** Less focused out-of-the-box on massive multi-agent orchestration.[[1]](https://github.com/kaushikb11/awesome-llm-agents)[[2]](https://langfuse.com/blog/2025-03-19-ai-agent-comparison)\n- **Mastra / Vercel AI SDK** \n\t- **Best for:** TypeScript and JavaScript production environments.\n\t- **Pros:** Brings native agentic workflows and streaming capabilities directly to the JS/TS web stack.[[1]](https://langfuse.com/blog/2025-03-19-ai-agent-comparison)[[2]](https://www.langchain.com/resources/ai-agent-frameworks)\n\n\n\n---\n\nTo narrow this down to the right choice for you:\n\n- What **programming language** are you working with (Python, TypeScript/JS, etc.)?\n- Are you building a **single assistant** or a **multi-agent team**?\n- Is this for a **quick prototype** or a **production app**?", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "AutoGen", "domain": "microsoft.github.io" }, { "name": "AG2", "domain": "ag2.ai" }, { "name": "Pydantic AI", "domain": "pydantic.dev" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Vercel AI SDK", "domain": "vercel.com" } ], "sources": [ { "url": "https://github.com/kaushikb11/awesome-llm-agents", "domain": "github.com", "title": "A curated list of awesome LLM agents frameworks." }, { "url": "https://langfuse.com/blog/2025-03-19-ai-agent-comparison", "domain": "langfuse.com", "title": "Comparing Open-Source AI Agent Frameworks - Langfuse" }, { "url": "https://pub.towardsai.net/the-4-best-open-source-multi-agent-ai-frameworks-2026-9da389f9407a", "domain": "pub.towardsai.net", "title": "The 4 Best Open Source Multi" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026" }, { "url": "https://getstream.io/blog/multiagent-ai-frameworks/", "domain": "getstream.io", "title": "Best 5 Frameworks To Build Multi" }, { "url": "https://botpress.com/blog/llm-agent-framework", "domain": "botpress.com", "title": "Choosing the Right LLM Agent Framework in 2026" }, { "url": "https://www.instaclustr.com/education/agentic-ai/agentic-ai-frameworks-top-10-options-in-2026/", "domain": "instaclustr.com", "title": "Agentic AI Frameworks: Top 10 Options in 2026 - Instaclustr" }, { "url": "https://www.youtube.com/watch?v=t4272x9x1NY&t=661", "domain": "youtube.com", "title": "AI Agent Frameworks 2026: Which One Should You Pick?" } ], "searchQueries": "not exposed" }, { "prompt": 4, "engine": "OPENAI", "run": 1, "askedAt": "2026-10-09T01:28:26.031Z", "text": "1. **LangGraph** — https://langgraph.ai (coverage and ecosystem articles). \n Why: Designed as an orchestration-first multi-agent framework with built-in supervisor/swarm patterns and strong production tooling for tracing and persistence. ([resources.rework.com](https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai))\n\n2. **CrewAI** — https://crew.ai (product pages and reviews). \n Why: Fast path to role-based crews — good developer DX and quick prototyping of coordinated agent teams. ([resources.rework.com](https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai))\n\n3. **Microsoft Agent Framework (successor to AutoGen / Semantic Kernel)** — https://learn.microsoft.com (Microsoft Agent/AutoGen docs and announcements). \n Why: Broad built-in orchestration patterns (sequential, concurrent, handoff, group) and enterprise integrations — strong for Windows/.NET shops and large-scale production. ([resources.rework.com](https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai))\n\n4. **OpenAI Agents SDK / AgentKit** — https://platform.openai.com/docs/guides/agents (OpenAI Agents docs and AgentKit announcement). \n Why: Tight integration with OpenAI APIs, ready-made multi-agent orchestration primitives and tracing; good for teams using OpenAI models. ([developers.openai.com](https://developers.openai.com/api/docs/guides/agents-api/multi-agent?utm_source=openai))\n\n5. **Ray RLlib (multi-agent support)** — https://docs.ray.io (Ray RLlib multi-agent docs). \n Why: Mature, scalable runtime for multi-agent reinforcement learning and distributed execution — ideal when agents learn via RL or need high-throughput simulation. ([docs.ray.io](https://docs.ray.io/en/latest/rllib/multi-agent-envs.html?utm_source=openai))\n\n6. **PettingZoo** — https://www.pettingzoo.ml (paper and library resources). \n Why: Standardized API and many multi-agent environments for MARL research — the de facto interoperability layer for multi-agent RL experiments. ([papers.nips.cc](https://papers.nips.cc/paper/2021/file/7ed2d3454c5eea71148b11d0c25104ff-Paper.pdf?utm_source=openai))\n\n7. **Mesa (Python agent-based modeling)** — https://mesa.readthedocs.io (Mesa docs). \n Why: Lightweight, Python-native agent-based modeling framework with visualization and notebook-friendly tooling — great for simulations, ABM prototyping, and social-science style multi-agent work. ([mesa.readthedocs.io](https://mesa.readthedocs.io/stable/index.html?utm_source=openai))\n\nNotes to pick the best one for you:\n- If you want production-grade orchestration, observability, and enterprise integrations: prefer LangGraph or Microsoft Agent Framework. ([resources.rework.com](https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai)) \n- If you’re building research or RL-based agents: use Ray RLlib + PettingZoo (environments). ([docs.ray.io](https://docs.ray.io/en/latest/rllib/multi-agent-envs.html?utm_source=openai)) \n- If you want quick developer experience with OpenAI models: OpenAI Agents SDK / AgentKit or CrewAI can be fastest. ([developers.openai.com](https://developers.openai.com/api/docs/guides/agents-api/multi-agent?utm_source=openai))\n\nIf you want, I can: (a) pick the single best fit based on whether your project is production vs research vs prototyping, or (b) provide links to quick-start examples for any of the frameworks above.", "brands": [ { "name": "LangGraph", "domain": "langgraph.ai" }, { "name": "CrewAI", "domain": "crew.ai" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK / AgentKit", "domain": "platform.openai.com" }, { "name": "Ray RLlib", "domain": "docs.ray.io" }, { "name": "PettingZoo", "domain": "pettingzoo.ml" }, { "name": "Mesa", "domain": "mesa.readthedocs.io" } ], "sources": [ { "url": "https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai", "domain": "resources.rework.com", "title": "\"Best Multi-Agent Frameworks in 2026: 11 Frameworks for Orchestrating Agents That Hand Off Work\"" }, { "url": "https://developers.openai.com/api/docs/guides/agents-api/multi-agent?utm_source=openai", "domain": "developers.openai.com", "title": "Multi-agent | OpenAI API" }, { "url": "https://docs.ray.io/en/latest/rllib/multi-agent-envs.html?utm_source=openai", "domain": "docs.ray.io", "title": "Multi-Agent Environments — Ray 2.58.0" }, { "url": "https://papers.nips.cc/paper/2021/file/7ed2d3454c5eea71148b11d0c25104ff-Paper.pdf?utm_source=openai", "domain": "papers.nips.cc", "title": "PettingZoo: A Standard API for Multi-Agent" }, { "url": "https://mesa.readthedocs.io/stable/index.html?utm_source=openai", "domain": "mesa.readthedocs.io", "title": "Mesa: Agent-based modeling in Python — Mesa .1 documentation" } ], "searchQueries": [ "best frameworks for multi-agent systems 2026", "multi-agent system frameworks list JADE SPADE Mesa Ray RLlib PettingZoo 2026", "JADE multi-agent framework website", "SPADE multi-agent framework website", "Mesa agent-based modeling Python website", "Ray RLlib multi-agent framework website", "PettingZoo multi-agent library website", "Microsoft Bonsai multi-agent framework 2026", "OpenAI multi-agent frameworks or tools 2026" ] }, { "prompt": 4, "engine": "OPENAI", "run": 2, "askedAt": "2026-10-09T01:29:18.165Z", "text": "1. **LangGraph** — https://langgraph.dev \n Best overall for production multi‑agent systems today: graph-based orchestration, checkpointing and strong tooling for large distributed agent teams. ([ayautomate.com](https://www.ayautomate.com/blog/best-multi-agent-frameworks?utm_source=openai))\n\n2. **CrewAI** — https://crew.ai \n Built from the ground up for multi‑agent \"crew\" workflows (role-based agents, manager patterns) and fast to prototype multi‑role collaborations. ([multimodal.dev](https://www.multimodal.dev/post/best-multi-agent-ai-frameworks?utm_source=openai))\n\n3. **Microsoft Agent Framework (successor to AutoGen / Semantic Kernel)** — https://docs.microsoft.com/agent-framework (or Microsoft docs) \n Enterprise-grade, .NET/Python SDK with native orchestration patterns, streaming, checkpointing and Microsoft platform integrations (GA April 3, 2026). ([resources.rework.com](https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai))\n\n4. **OpenAI Agents SDK** — https://platform.openai.com/agents \n Lightweight, well‑instrumented SDK for building agent workflows on the OpenAI stack; excellent tracing, tool integrations and quick dev loop if you use OpenAI models. ([firecrawl.dev](https://www.firecrawl.dev/blog/best-ai-agent-frameworks?utm_source=openai))\n\n5. **Google Agent Development Kit (ADK) / Vertex AI Agent Engine** — https://cloud.google.com/vertex-ai/agents or Google ADK pages \n Strong for hierarchical/parent‑child agent topologies and seamless deployment to Vertex AI for scale and managed hosting. ([multimodal.dev](https://www.multimodal.dev/post/best-multi-agent-ai-frameworks?utm_source=openai))\n\n6. **Ray RLlib (multi-agent / MARL support)** — https://www.ray.io/rllib \n Best choice when you need scalable multi‑agent reinforcement‑learning environments and production RL training at scale. ([docs.ray.io](https://docs.ray.io/en/latest/rllib/multi-agent-envs.html?utm_source=openai))\n\n7. **Mesa (Python agent‑based modeling)** — https://mesa.readthedocs.io / https://github.com/mesa/mesa \n Mature open‑source library for agent‑based simulation and research (good for modeling, prototyping and academic MAS use). ([github.com](https://github.com/mesa/mesa?utm_source=openai))\n\nNotes: frameworks split into two common use cases — (A) production orchestration of LLM agents (LangGraph, CrewAI, Microsoft, OpenAI, Google ADK) and (B) research/simulation or MARL (Mesa, Ray RLlib, PettingZoo). If you tell me which use case you care about (production orchestration, research/simulation, MARL, or specific cloud/model stack), I can give a shorter recommendation and implementation starter code for the top pick.", "brands": [ { "name": "LangGraph", "domain": "langgraph.dev" }, { "name": "CrewAI", "domain": "crew.ai" }, { "name": "Microsoft Agent Framework", "domain": "docs.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Google Agent Development Kit", "domain": "cloud.google.com" }, { "name": "Ray RLlib", "domain": "ray.io" }, { "name": "Mesa", "domain": "mesa.readthedocs.io" } ], "sources": [ { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks?utm_source=openai", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" }, { "url": "https://www.multimodal.dev/post/best-multi-agent-ai-frameworks?utm_source=openai", "domain": "multimodal.dev", "title": "Best Multi-Agent AI Frameworks in 2026 (Compared)" }, { "url": "https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026?utm_source=openai", "domain": "resources.rework.com", "title": "\"Best Multi-Agent Frameworks in 2026: 11 Frameworks for Orchestrating Agents That Hand Off Work\"" }, { "url": "https://www.firecrawl.dev/blog/best-ai-agent-frameworks?utm_source=openai", "domain": "firecrawl.dev", "title": "Best AI Agent Frameworks of 2026" }, { "url": "https://docs.ray.io/en/latest/rllib/multi-agent-envs.html?utm_source=openai", "domain": "docs.ray.io", "title": "Multi-Agent Environments — Ray 2.58.0" }, { "url": "https://github.com/mesa/mesa?utm_source=openai", "domain": "github.com", "title": "GitHub - mesa/mesa: Mesa is an open-source Python library for agent-based modeling, ideal for simulating complex systems and exploring emergent behaviors. · GitHub" } ], "searchQueries": [ "best frameworks for multi-agent systems 2026 list", "multi-agent systems frameworks JADE 2026", "Ray RLlib multi-agent framework 2026", "Microsoft Bonsai multi-agent 2026", "OpenAI multi-agent frameworks PettingZoo, MA-Env, Gym-MA 2026", "Mesa agent-based modeling python 2026" ] }, { "prompt": 4, "engine": "OPENAI", "run": 3, "askedAt": "2026-10-09T01:30:16.328Z", "text": "1. **LangChain** — https://www.langchain.com — Best for building modern LLM-driven multi‑agent applications with ready agent primitives, integrations and an agent engineering platform. ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\n2. **PettingZoo** — https://www.farama.org/pettingzoo (GitHub: Farama-Foundation/PettingZoo) — De facto standard API and suite of benchmark environments for multi‑agent reinforcement learning research and tooling. ([github.com](https://github.com/Farama-Foundation/PettingZoo?utm_source=openai))\n\n3. **Mesa** — https://mesa.readthedocs.io — Python agent‑based modeling framework focused on simulation, analysis and visualization (great for research and prototyping multi‑agent simulations). ([mesa.readthedocs.io](https://mesa.readthedocs.io/stable/index.html?utm_source=openai))\n\n4. **JADE (Java Agent DEvelopment Framework)** — https://jade.tilab.com — Longstanding, production‑grade Java framework for building distributed multi‑agent systems with messaging, yellow‑pages and lifecycle support. ([jade.tilab.com](https://jade.tilab.com/?utm_source=openai))\n\n5. **NetLogo** — https://www.netlogo.org — Easy‑to‑use environment for teaching and rapid prototyping of multi‑agent models and interactive simulations. ([netlogo.org](https://www.netlogo.org/?utm_source=openai))\n\n6. **Akka (Actors / agent patterns)** — https://doc.akka.io — Actor‑based toolkit for highly concurrent, distributed agent‑style systems (good when you need scalable, fault‑tolerant messaging and orchestration). ([doc.akka.io](https://doc.akka.io/akka-agents.html?utm_source=openai))\n\nIf you want, I can (without asking questions) pick the single best fit from the list for a specific use case (research MARL, LLM agents, simulation/teaching, or production distributed services) and justify that choice with a short plan for starting a prototype.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "PettingZoo", "domain": "farama.org" }, { "name": "Mesa", "domain": "mesa.readthedocs.io" }, { "name": "JADE", "domain": "jade.tilab.com" }, { "name": "NetLogo", "domain": "netlogo.org" }, { "name": "Akka", "domain": "doc.akka.io" } ], "sources": [ { "url": "https://www.langchain.com/langchain?utm_source=openai", "domain": "langchain.com", "title": "LangChain: Open Source AI Agent Framework for Any Model" }, { "url": "https://github.com/Farama-Foundation/PettingZoo?utm_source=openai", "domain": "github.com", "title": "GitHub - Farama-Foundation/PettingZoo: A standard API for multi-agent reinforcement learning environments, with popular reference environments and related utilities · GitHub" }, { "url": "https://mesa.readthedocs.io/stable/index.html?utm_source=openai", "domain": "mesa.readthedocs.io", "title": "Mesa: Agent-based modeling in Python — Mesa .1 documentation" }, { "url": "https://jade.tilab.com/?utm_source=openai", "domain": "jade.tilab.com", "title": "Jade Site | Java Agent DEvelopment Framework" }, { "url": "https://www.netlogo.org/?utm_source=openai", "domain": "netlogo.org", "title": "NetLogo Home" }, { "url": "https://doc.akka.io/akka-agents.html?utm_source=openai", "domain": "doc.akka.io", "title": "Agents :: Akka Documentation" } ], "searchQueries": [ "best frameworks for multi-agent systems JADE SPADE Mesa Ray LangChain PettingZoo comparison 2024 2025", "JADE framework multi-agent system website", "SPADE multi agent framework website", "Mesa agent-based modeling framework website", "Ray RLlib multi-agent support multi-agent framework website", "LangChain agents multi-agent framework website", "PettingZoo multi-agent RL environments website", "Akka actors multi-agent systems website", "NetLogo multi-agent modeling website" ] }, { "prompt": 4, "engine": "ANTHROPIC", "run": 1, "askedAt": "2026-10-09T01:28:23.957Z", "text": "I'll search for current information on the best frameworks for building multi-agent systems.\nBased on current research, there isn't a single \"best\" framework—it depends on your specific needs. However, here are the top frameworks ranked by overall popularity and use cases for multi-agent systems:\n\n1. **\nLangGraph\n** - https://www.langchain.com/langgraph\n \nBest for production-grade stateful agent graphs with human-in-the-loop checkpoints, used by Anthropic, Replit, LinkedIn, Uber.\n\n\n2. **\nCrewAI\n** - https://www.crewai.com\n \nBest for role-based agent crews with the lowest barrier to entry; the fastest path from idea to working swarm.\n\n\n3. **\nAutoGen\n** - https://microsoft.github.io/autogen/\n \nDeveloped by Microsoft Research, is a cutting-edge framework for multi-agent AI systems that orchestrates seamless collaboration among autonomous agents. It supports both synchronous and asynchronous interactions.\n\n\n4. **\nLangChain\n** - https://www.langchain.com\n \nWith its tool-calling and multi-agent orchestration capabilities, allows developers to design advanced agents for automation, decision-making, and seamless system integration.\n\n\n5. **\nMicrosoft Agent Framework\n** - https://github.com/microsoft/semantic-kernel\n \nBest for Azure and .NET teams that want graph workflows with sequential, concurrent, handoff, group chat, and manager-led patterns built in.\n\n\n6. **\nOpenAI Agents SDK\n** - https://platform.openai.com/docs/guides/agents\n \nA deliberately minimal framework for multi-agent workflows on OpenAI's model APIs. Its design philosophy favors a small API surface over comprehensive abstraction — handoffs and tool-calling are easy to reason about.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "AutoGen", "domain": "microsoft.github.io" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" } ], "sources": [ { "url": "https://deepchecks.com/best-ai-agent-frameworks/", "domain": "deepchecks.com", "title": "Best 10 AI Agent Frameworks for 2025" }, { "url": "https://www.ai21.com/knowledge/ai-agent-frameworks/", "domain": "ai21.com", "title": "Top 12 AI Agent Frameworks for Enterprises in 2025" }, { "url": "https://medium.com/@simplenight/top-frameworks-empowering-multi-agent-llm-development-in-2025-ecc7931d18b6", "domain": "medium.com", "title": "Top Frameworks Empowering Multi-Agent LLM Development in 2025" }, { "url": "https://futureagi.com/blog/multi-agent-systems-2025/", "domain": "futureagi.com", "title": "Multi-Agent AI Systems in 2026: Frameworks, Patterns, Production" }, { "url": "https://www.secondtalent.com/resources/top-llm-frameworks-for-building-ai-agents/", "domain": "secondtalent.com", "title": "Top 8 LLM Frameworks for Building AI Agents in 2026 - Second Talent" }, { "url": "https://www.intuz.com/blog/top-5-ai-agent-frameworks-2025/", "domain": "intuz.com", "title": "Best AI Agent Frameworks: Tested in 100+ Production Deployments" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" }, { "url": "https://davepatten.substack.com/p/choosing-your-ai-stack-a-deep-dive", "domain": "davepatten.substack.com", "title": "Choosing Your AI Stack: A Deep Dive into Top Agent Frameworks (2025)" }, { "url": "https://dev.to/yeahiasarker/the-best-agentic-ai-framework-options-for-building-multi-agent-systems-in-2025-3l9l", "domain": "dev.to", "title": "DEV Community" } ], "searchQueries": [ "best frameworks building multi-agent systems 2024 2025" ] }, { "prompt": 4, "engine": "ANTHROPIC", "run": 2, "askedAt": "2026-10-09T01:29:17.246Z", "text": "I'll search for current information on the best frameworks for building multi-agent systems.\nBased on the latest information, there's no single \"best\" framework—the choice depends on your specific needs. However, here are the top frameworks ranked by overall adoption and capabilities:\n\n1. **LangGraph** | https://www.langgraph.dev/\n \nBest for production-grade stateful agent graphs with human-in-the-loop checkpoints, used by Anthropic, Replit, LinkedIn, Uber\n.\n\n2. **CrewAI** | https://www.crewai.com/\n \nBest for role-based agent crews with the lowest barrier to entry; the fastest path from idea to working swarm\n.\n\n3. **AutoGen** | https://microsoft.github.io/autogen/\n \nDeveloped by Microsoft Research, is a cutting-edge framework for multi-agent AI systems that orchestrates seamless collaboration among autonomous agents, supporting both synchronous and asynchronous interactions\n.\n\n4. **LangChain** | https://www.langchain.com/\n \nHas quickly become one of the most popular frameworks for building multi-agent applications, known for its ease of use and extensive library of pre-built components, simplifying the orchestration of multiple agents\n.\n\n5. **Microsoft Agent Framework** | https://learn.microsoft.com/en-us/azure/ai-services/\n \nBest for Azure and .NET teams that want graph workflows with sequential, concurrent, handoff, group chat, and manager-led patterns built in\n.\n\n6. **OpenAI Agents SDK** | https://platform.openai.com/\n \nBest for teams already deep in the OpenAI ecosystem who want lightweight handoffs\n.", "brands": [ { "name": "LangGraph", "domain": "langgraph.dev" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "AutoGen", "domain": "microsoft.github.io" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" } ], "sources": [ { "url": "https://deepchecks.com/best-ai-agent-frameworks/", "domain": "deepchecks.com", "title": "Best 10 AI Agent Frameworks for 2025" }, { "url": "https://medium.com/@simplenight/top-frameworks-empowering-multi-agent-llm-development-in-2025-ecc7931d18b6", "domain": "medium.com", "title": "Top Frameworks Empowering Multi-Agent LLM Development in 2025" }, { "url": "https://www.ai21.com/knowledge/ai-agent-frameworks/", "domain": "ai21.com", "title": "Top 12 AI Agent Frameworks for Enterprises in 2025" }, { "url": "https://www.codecademy.com/article/top-ai-agent-frameworks-in-2025", "domain": "codecademy.com", "title": "Top AI Agent Frameworks in 2025" }, { "url": "https://futureagi.com/blog/multi-agent-systems-2025/", "domain": "futureagi.com", "title": "Multi-Agent AI Systems in 2026: Frameworks, Patterns, Production" }, { "url": "https://www.intuz.com/blog/top-5-ai-agent-frameworks-2025/", "domain": "intuz.com", "title": "Best AI Agent Frameworks: Tested in 100+ Production Deployments" }, { "url": "https://www.secondtalent.com/resources/top-llm-frameworks-for-building-ai-agents/", "domain": "secondtalent.com", "title": "Top 8 LLM Frameworks for Building AI Agents in 2026 - Second Talent" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" }, { "url": "https://davepatten.substack.com/p/choosing-your-ai-stack-a-deep-dive", "domain": "davepatten.substack.com", "title": "Choosing Your AI Stack: A Deep Dive into Top Agent Frameworks (2025)" } ], "searchQueries": [ "best frameworks multi-agent systems 2024 2025" ] }, { "prompt": 4, "engine": "ANTHROPIC", "run": 3, "askedAt": "2026-10-09T01:30:12.107Z", "text": "I'll search for current information on the best frameworks for building multi-agent systems.\nThere's no single \"best\" framework—the choice depends on your specific needs. Here are the top options ranked by current popularity and use cases:\n\n1. **LangGraph** - https://www.langchain.com/langgraph\n \nDe facto standard for serious multi-agent systems\n, best for \ncomplex, stateful workflows requiring explicit control over execution, state, branching, persistence, and human approval\n.\n\n2. **CrewAI** - https://www.crewai.com\n \nFastest path to a working crew of role-based agents\n, with \nmulti-agent systems with defined roles requiring the least boilerplate\n.\n\n3. **Microsoft Agent Framework** - https://github.com/microsoft/autogen\n \nReached 1.0 GA in April 2026 with .NET and Python support\n, best for \nAzure and .NET teams that want graph workflows with sequential, concurrent, handoff, group chat, and manager-led patterns built in\n.\n\n4. **OpenAI Agents SDK** - https://platform.openai.com/docs/agents\n \nBest for rapid prototyping and moderate-complexity production\n, ideal for \nteams already deep in the OpenAI ecosystem who want lightweight handoffs\n.\n\n5. **Google Agent Development Kit (ADK)** - https://cloud.google.com/vertex-ai/generative-ai/docs/agent-builder/adk\n \nBest for Google Cloud environments building hierarchical agent systems\n.\n\n\nLangGraph suits deterministic workflows, CrewAI fits role-based business processes, AutoGen or AG2 supports reasoning-heavy work, Google ADK fits Google Cloud environments, and OpenAI Agents SDK works well when OpenAI is confirmed\n.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Google Agent Development Kit (ADK)", "domain": "cloud.google.com" } ], "sources": [ { "url": "https://www.truefoundry.com/blog/multi-agent-orchestration-frameworks", "domain": "truefoundry.com", "title": "Best Multi-agent Orchestration Frameworks in 2026" }, { "url": "https://www.firecrawl.dev/blog/best-open-source-agent-frameworks", "domain": "firecrawl.dev", "title": "The best open source frameworks for building AI agents in 2026" }, { "url": "https://www.gumloop.com/blog/ai-agent-frameworks", "domain": "gumloop.com", "title": "6 best AI agent frameworks (and how I picked one) in 2026" }, { "url": "https://www.multimodal.dev/post/best-multi-agent-ai-frameworks", "domain": "multimodal.dev", "title": "Best Multi-Agent AI Frameworks in 2026 (Compared)" }, { "url": "https://www.analyticsinsight.net/artificial-intelligence/best-ai-agent-frameworks-in-2026-features-pros-cons-use-cases", "domain": "analyticsinsight.net", "title": "Best AI Agent Frameworks in 2026: Features, Pros, Cons, Use Cases" }, { "url": "https://resources.rework.com/tools/ai-agents/best-multi-agent-frameworks-2026", "domain": "resources.rework.com", "title": "\"Best Multi-Agent Frameworks in 2026: 11 Frameworks for Orchestrating Agents That Hand Off Work\"" }, { "url": "https://alicelabs.ai/en/insights/best-ai-agent-frameworks-2026", "domain": "alicelabs.ai", "title": "Best AI Agent Frameworks 2026: Alice Labs Top 10 Ranked" }, { "url": "https://is4.ai/blog/our-blog-1/top-12-multi-agent-ai-frameworks-2026-335", "domain": "is4.ai", "title": "Top 12 Multi-Agent AI Frameworks for Developers in 2026" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "Best Multi-Agent Frameworks 2026: 12 Ranked for Production" } ], "searchQueries": [ "best frameworks multi-agent systems 2026" ] }, { "prompt": 4, "engine": "PERPLEXITY", "run": 1, "askedAt": "2026-10-09T01:28:25.138Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production multi-agent systems requiring explicit workflows, persistent state, branching, checkpoints, and granular execution control.[1][2][6]\n\n2. **CrewAI** — https://www.crewai.com — Best for quickly creating role-based teams of specialized agents that collaborate on complex tasks.[3][4]\n\n3. **Microsoft AutoGen** — https://microsoft.github.io/autogen/ — Best for conversational multi-agent applications and Microsoft-supported event-driven agent architectures.[4][8]\n\n4. **Google Agent Development Kit (ADK)** — https://google.github.io/adk-docs/ — Best for teams building agent systems closely integrated with Google Cloud and Gemini.\n\n5. **Amazon Bedrock Agents** — https://aws.amazon.com/bedrock/agents/ — Best for AWS-native deployments requiring managed agents, enterprise tools, permissions, and cloud integration.\n\n6. **Semantic Kernel** — https://learn.microsoft.com/semantic-kernel/ — Best for .NET or Microsoft-focused applications that need agent orchestration alongside existing enterprise software.\n\n7. **JADE** — https://jade.tilab.com — Best for traditional distributed multi-agent systems built in Java, rather than primarily LLM-based agent workflows.[7]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" }, { "name": "Google Agent Development Kit (ADK)", "domain": "google.github.io" }, { "name": "Amazon Bedrock Agents", "domain": "aws.amazon.com" }, { "name": "Semantic Kernel", "domain": "learn.microsoft.com" }, { "name": "JADE", "domain": "jade.tilab.com" } ], "sources": [ { "url": "https://arize.com/ai-agents/agent-frameworks/", "domain": "arize.com", "title": "AI agent frameworks compared: LangGraph, CrewAI, ..." }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Multi-Agent Frameworks for Production in 2026 - AY Automate" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://mastra.ai/articles/best-ai-agents", "domain": "mastra.ai", "title": "Best AI Agents in 2026: Tested, Compared, and Ranked" }, { "url": "https://www.chatbot.com/blog/ai-agent-frameworks/", "domain": "chatbot.com", "title": "AI Agent Frameworks: 10 Options, One Guide, Zero Fluff - ChatBot" }, { "url": "https://www.sim.ai/library/best-multi-agent-frameworks-2026", "domain": "sim.ai", "title": "Best Multi-Agent Frameworks for Production in 2026 - Sim AI" }, { "url": "https://milvus.io/ai-quick-reference/what-are-popular-frameworks-for-building-multiagent-systems", "domain": "milvus.io", "title": "What are popular frameworks for building multi-agent systems? - Milvus" }, { "url": "https://www.dataiku.com/blog/ai-agent-frameworks", "domain": "dataiku.com", "title": "Best AI agent frameworks (2026) - Dataiku" }, { "url": "https://ones.com/blog/solution-guide/best-multi-agent-frameworks-2026/", "domain": "ones.com", "title": "7 Best Multi-Agent Frameworks in 2026 - ones.com" }, { "url": "https://mastra.ai/blog/best-ai-agent-frameworks", "domain": "mastra.ai", "title": "The 6 Best AI Agent Frameworks (July 2026): Features, Tradeoffs ..." } ], "searchQueries": "not exposed" }, { "prompt": 4, "engine": "PERPLEXITY", "run": 2, "askedAt": "2026-10-09T01:29:14.528Z", "text": "1. **LangGraph** — https://langchain.com/langgraph — Best overall for production multi-agent systems requiring explicit workflows, persistent state, conditional routing, human approval, and durable execution.[1][2]\n\n2. **CrewAI** — https://crewai.com — Best for quickly building role-based teams of specialized agents with straightforward Python orchestration.[3][4]\n\n3. **Microsoft AutoGen** — https://microsoft.github.io/autogen — Best for conversational multi-agent applications and Microsoft-oriented development stacks.[4][8]\n\n4. **Google ADK** — https://google.github.io/adk-docs — Best for teams building agent systems around Google Cloud and Gemini services.\n\n5. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python — Best for lightweight code-first systems using OpenAI models, tools, handoffs, and tracing.\n\n6. **Mastra** — https://mastra.ai — Best for TypeScript teams that want agent workflows, tools, memory, and observability in a modern web-development stack.[4][10]\n\n7. **Ray** — https://ray.io — Best for large-scale, distributed multi-agent workloads where Python-native parallelism and cluster execution matter.[7]\n\n**Bottom line:** Choose **LangGraph** for the strongest general-purpose, production-oriented option; choose **CrewAI** when ease of setup and role-based collaboration matter more than fine-grained execution control.[1][4][6]", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" }, { "name": "Google ADK", "domain": "google.github.io" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Ray", "domain": "ray.io" } ], "sources": [ { "url": "https://arize.com/ai-agents/agent-frameworks/", "domain": "arize.com", "title": "AI agent frameworks compared: LangGraph, CrewAI, ..." }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Multi-Agent Frameworks for Production in 2026 - AY Automate" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://mastra.ai/articles/best-ai-agents", "domain": "mastra.ai", "title": "Best AI Agents in 2026: Tested, Compared, and Ranked" }, { "url": "https://www.chatbot.com/blog/ai-agent-frameworks/", "domain": "chatbot.com", "title": "AI Agent Frameworks: 10 Options, One Guide, Zero Fluff - ChatBot" }, { "url": "https://www.sim.ai/library/best-multi-agent-frameworks-2026", "domain": "sim.ai", "title": "Best Multi-Agent Frameworks for Production in 2026 - Sim AI" }, { "url": "https://milvus.io/ai-quick-reference/what-are-popular-frameworks-for-building-multiagent-systems", "domain": "milvus.io", "title": "What are popular frameworks for building multi-agent systems? - Milvus" }, { "url": "https://www.dataiku.com/blog/ai-agent-frameworks", "domain": "dataiku.com", "title": "Best AI agent frameworks (2026) - Dataiku" }, { "url": "https://ones.com/blog/solution-guide/best-multi-agent-frameworks-2026/", "domain": "ones.com", "title": "7 Best Multi-Agent Frameworks in 2026 - ones.com" }, { "url": "https://mastra.ai/blog/best-ai-agent-frameworks", "domain": "mastra.ai", "title": "The 6 Best AI Agent Frameworks (July 2026): Features, Tradeoffs ..." } ], "searchQueries": "not exposed" }, { "prompt": 4, "engine": "PERPLEXITY", "run": 3, "askedAt": "2026-10-09T01:30:14.844Z", "text": "1. **LangGraph** — https://www.langchain.com/langgraph — Best overall for production multi-agent systems requiring explicit workflows, persistent state, conditional routing, human approval, and durable execution.[1][2]\n\n2. **CrewAI** — https://www.crewai.com — Best for quickly creating role-based teams of specialized agents that collaborate on complex tasks.[3][4]\n\n3. **Microsoft AutoGen** — https://microsoft.github.io/autogen/ — Best for conversational multi-agent applications and flexible agent-to-agent messaging, with Microsoft-backed tooling.[4][8]\n\n4. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best for Python teams building OpenAI-centered agent applications with tools, handoffs, tracing, and guardrails.\n\n5. **Google ADK** — https://google.github.io/adk-docs/ — Best for teams building agents around Google models, services, and cloud deployment.\n\n6. **Semantic Kernel** — https://learn.microsoft.com/semantic-kernel/ — Best for .NET or Azure-focused enterprise applications that need structured agent orchestration and integration with existing Microsoft systems.\n\n7. **Haystack** — https://haystack.deepset.ai — Best for retrieval-heavy multi-agent systems, especially applications combining agents with search, document processing, and RAG pipelines.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft AutoGen", "domain": "microsoft.github.io" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Google ADK", "domain": "google.github.io" }, { "name": "Semantic Kernel", "domain": "learn.microsoft.com" }, { "name": "Haystack", "domain": "haystack.deepset.ai" } ], "sources": [ { "url": "https://arize.com/ai-agents/agent-frameworks/", "domain": "arize.com", "title": "AI agent frameworks compared: LangGraph, CrewAI, ..." }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com", "title": "12 Best Multi-Agent Frameworks for Production in 2026 - AY Automate" }, { "url": "https://www.langchain.com/resources/ai-agent-frameworks", "domain": "langchain.com", "title": "The best AI agent frameworks in 2026 - LangChain" }, { "url": "https://mastra.ai/articles/best-ai-agents", "domain": "mastra.ai", "title": "Best AI Agents in 2026: Tested, Compared, and Ranked" }, { "url": "https://www.chatbot.com/blog/ai-agent-frameworks/", "domain": "chatbot.com", "title": "AI Agent Frameworks: 10 Options, One Guide, Zero Fluff - ChatBot" }, { "url": "https://www.sim.ai/library/best-multi-agent-frameworks-2026", "domain": "sim.ai", "title": "Best Multi-Agent Frameworks for Production in 2026 - Sim AI" }, { "url": "https://milvus.io/ai-quick-reference/what-are-popular-frameworks-for-building-multiagent-systems", "domain": "milvus.io", "title": "What are popular frameworks for building multi-agent systems? - Milvus" }, { "url": "https://www.dataiku.com/blog/ai-agent-frameworks", "domain": "dataiku.com", "title": "Best AI agent frameworks (2026) - Dataiku" }, { "url": "https://ones.com/blog/solution-guide/best-multi-agent-frameworks-2026/", "domain": "ones.com", "title": "7 Best Multi-Agent Frameworks in 2026 - ones.com" }, { "url": "https://mastra.ai/blog/best-ai-agent-frameworks", "domain": "mastra.ai", "title": "The 6 Best AI Agent Frameworks (July 2026): Features, Tradeoffs ..." } ], "searchQueries": "not exposed" }, { "prompt": 4, "engine": "GEMINI", "run": 1, "askedAt": "2026-10-09T01:28:26.351Z", "text": "1. **LangGraph**\n - Website: [langchain.com/langgraph](https://www.langchain.com/langgraph)\n - The industry standard for complex, production-grade multi-agent systems requiring stateful orchestration, cyclical graphs, persistence, and human-in-the-loop checkpoints.\n\n2. **CrewAI**\n - Website: [crewai.com](https://www.crewai.com)\n - The fastest path for prototyping and deploying role-based collaborative multi-agent workflows with sequential or hierarchical task execution.\n\n3. **Microsoft Agent Framework**\n - Website: [microsoft.com](https://microsoft.com)\n - A robust framework optimized for enterprise environments, combining Azure integrations, .NET/Python support, and robust governance pathways.\n\n4. **Mastra**\n - Website: [mastra.ai](https://mastra.ai)\n - A comprehensive TypeScript/JavaScript framework that integrates multi-agent orchestration, workflow branching, vector retrieval, and local developer studios.\n\n5. **OpenAI Agents SDK**\n - Website: [openai.com](https://openai.com)\n - A lightweight, developer-friendly toolkit engineered for seamless handoffs, guardrails, and multi-step tool execution natively within the OpenAI ecosystem.\n\n6. **LlamaIndex Workflows**\n - Website: [llamaindex.ai](https://www.llamaindex.ai)\n - An event-driven framework that excels at tying heavy data retrieval and document processing pipelines together with multi-step agent coordination.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH1GKQyD2E3DpkRfDs7BfKIsCn0zryX_sTvs2N2P56JWGiUUDJUVNYtnbCkYjQFqIbN7k-IPhzZ6mPu9IOLY4cvwkubZgCQa3UmReafndFrwAOL_gsOm__Jzl-UzFUVNgB7ydDEfba-k9zOkUpf179wqg==", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGaOT8v5G1P82khbQmtAED1dzFwIHG9m7BcIBt1Ewc5PxtWdZmmnp98IWmOI4pFA51a17yi4oK_PgYLNCV3uTgXPb2da0qiMMMU4M0mdu_NSFWCzAw52b1OS8x2AVVV8XynlbPW66zVZnGfyM7a", "domain": "langchain.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGdmXg35_bccfZHumoZ0L6B9CaHA_XmqNfcwu6IeuuCHXSYH3s0bGeRqyz9q7ifEeUZvbqUzyViwtjsm3urCq7sThsBXKDsr6CzBZHwuGG8a6qqhHbDGTngFO_NH0EeAr4PDVpGdvTOTj14uFlWrAM11aR_Jrql1C3uaFtMdG9oUy_O5vkaSAc3VoeItJ6tGJuWDMPg2z-cWBZ0cg==", "domain": "reddit.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHwWbRhTTKLf_584G_SE8AzH5G6oxx1J16RqxHw5HyyZCWyjOKJzgS6aoLTIs4JzXb6v41YvObJcy9O0zzJ5T5rvbJN8yq0eIdKXJDBrCr-iOF-KErY7JVhbhUXpcOWAwAJmDX74OVCa0wdncaqMMBZU8IzHCluhHc-ECHx713jVk6r8_8h5e_jNpq6ubUVizC39HiSv_vLGIwKq-fJ8A2oEbrvJBjw20zp", "domain": "medium.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHv_iGkNzs7na7eCYO1YOrBFpvh1KIqPZIWOjOpyvvC9KTQNOCPo7kXiCJxeHDVCTuzP4FFR-RC_uDdYmAu1oe8134LLVbqk4P1u8v5SJMuk5ruL7aYRAgv5DXNAVdWiuCa0inW9tkda5HrslCUxLVLrg==", "domain": "microsoft.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQH5XjAYDs8Gdsxk0ZWStAE22N0ydupD_seIdcxktiIh2eSIUfzbRFB6sCVqT6m4cicKvOtYcNUwPFzANSS6BeqmzKCI9txcNovY7VJ5O8WZ_asOiT_pCjov9UAAcRD8l221pH7OKvafQlvkjTY=", "domain": "browser-use.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFpOUxDqOlqxhPR844n3MOVvXur9O6pezlv7N5eWTobXcrHKABfwtFGm4ZEsEIKhDclG_P1kQfE7JAhczn68LrJehQHyt2UN2-0yD-Zvc53aoUbbd4Vr6JYHppy3edEGsLA026MzXwd8oedLlgGQDtRlTjYkz2k3x0W12OWkOReURBAhMQAolZ8OQwWr1p_fRG2LlUJqLhjK0Dqsb1rp_XUIgxx", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHmAXbL0T5lKCnNP9SQmCSgrXenP6tMOiFWroFcACHJ2YtAg9Trh6vU05XuUgxzz_J7tvx8wFoN2p2yStmQX5xcv_TodSs4Y9q6ug5x_CAkAkJR0SyLCdgrNFYpDXMMCXrne_q6GutxWlX92qavh3UNusG80rHuRCMt10HDyYX2sdedE8SxQqRkC2JeLgc3wF4GCgEtSLc-iTxD", "domain": "towardsai.net" } ], "searchQueries": [ "best frameworks for building multi agent systems 2026", "multi agent frameworks ai agents" ] }, { "prompt": 4, "engine": "GEMINI", "run": 2, "askedAt": "2026-10-09T01:29:19.837Z", "text": "1. **LangGraph**\n - Website: [github.com/langchain-ai/langgraph](https://github.com/langchain-ai/langgraph)\n - Widely considered the leading framework for production-grade multi-agent systems, offering explicit, graph-based control over state, cyclic workflows, and deterministic branching logic.\n\n2. **CrewAI**\n - Website: [crewai.com](https://crewai.com)\n - Excellent for rapid prototyping and role-based agent collaboration, letting developers easily assign roles, goals, and tools to a crew of cooperative agents.\n\n3. **AutoGen (AG2)**\n - Website: [microsoft.github.io/autogen](https://microsoft.github.io/autogen)\n - A robust framework pioneered by Microsoft Research that excels at conversation-driven, asynchronous multi-agent interaction, code generation, and automated multi-agent debates.\n\n4. **Microsoft Agent Framework**\n - Website: [github.com/microsoft/agent-framework](https://github.com/microsoft/agent-framework)\n - The unified successor framework combining AutoGen and Semantic Kernel, optimized for enterprise-grade .NET and Python stacks requiring strict type safety, telemetry, and session-based state management.\n\n5. **LlamaIndex Workflows**\n - Website: [llamaindex.ai](https://www.llamaindex.ai)\n - Best-in-class for document-heavy and RAG-centric architectures, providing an event-driven workflow engine to compose clean, parallel multi-agent systems in plain Python or TypeScript.\n\n6. **Google Agent Development Kit (ADK)**\n - Website: [cloud.google.com](https://cloud.google.com)\n - Google’s code-first orchestration toolkit built for GCP-native teams, offering structured support for sessions, memory, multi-agent evaluation patterns, and scalable deployment.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "AutoGen (AG2)", "domain": "microsoft.github.io" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Google Agent Development Kit (ADK)", "domain": "cloud.google.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHB-RGBYUCvs8_YTV67JTm3Ef1IKCl12FBJeZzFzSIfSziFIrtEkFmjsEnEyxOuKANQkeC5IvxlSGeUgmffOKfsVJDznmWiGpxsO5ThKxXEKG73i_ZLwIbLLvQUwfTdxOaajZDEbX7dO6iwh1oxMuV0M8wk5P8=", "domain": "redlinesoft.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEFrnoQ4TThDeUGroJzELlJ_EQ5-PIMK2-eZPIcZul-V6Xs8cl4NPy6CGGHDM3kUyoUA4hyRrpC2YaG6ANl4WuZ79RRxNbNGvNqOyXBuv0b_H8XKxT-krQROuTdcagUw291Ams0-TzBoZinv6ruHJqqgVH8yydn_A1NSCm-68qjtEQYs_DA4iXJ5M0fAdA=", "domain": "dev.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHboEonVMJmX6FHLfP1UBXETIhgB6lcWYHmZYPEcL0Y-77qnyyMTE6U5TGMorGeNuGlYrphj4QwYCr2qYNjyff75XS4WY92c5kLEVFII6p2MLCJv9f2K-HJaY5eJo2jZYAGx47woTMQgAc54iDgWxak", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGKUE4nu0yYBFJyNxHOaTPAbCerqYiwPdyNmENdzDDO_UBXKyZ5228DQKZ302Vl2bDGgFftO9eaTgmMx0LcI6GzY3m07GUtuST-eCJ9YGYAQndd3dAwf8F-qvoJRgWrzfRUH3zVjrsWAgshsZg=", "domain": "langchain.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEA5aawWFWvf8fjK3F7KhthHiKeojnQw3Rd784GfPylqyeACIPj4rIo1pW8_Yjyfmo5E6Q4Mpb-AIgsH2jGWCHJy5cFS0fA7wvRz9HVcsmE-SoOYzcxs4tjkPmMZ6LvA0FVxJcggs5eZO5nahWc70EuclQA6a-j0KaMraap", "domain": "towardsdatascience.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGwRnp4LXmwDKZ3OCMOPMlWvWj96bTh_9H3Qfdhajm2VzUdDky1HDjLAxA_Xv-BlHpC32Xk7M2Tps1Aq6u4wgcMbilz7D4bcIjl9dyX9XgmsNsZJDua4eJxI238eODzeHDrK-cvqVp1jVP3cwbC6ex-3yPfcCb_kWWazsCpxK_et7Bu1yWmA-hNitK1mXmD31I4t9HO_8k1DdI=", "domain": "towardsai.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGLHKGMufBt5kS4rNs2iYuM77gtIjww1eA41MLFev5-_8SI6FEsMsbu2CVS9icj0YGlkDLIGLIxts78ESkWrjOIsRnpyDlbAi6EJgw9ibKeps1iIMz8jNH0rtQD0S0A_GEfk_dy4Cu8CM4QP49T7Rw0pfWVo2p2x_29Q4E=", "domain": "cybic.ai" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHmeI2-vyaQdZHhUhp2ZKI0KaBHBF18SHOSbht-IPyBWuR1ZCa9tyHFWI3iMG7_DBGQmNkQgF9fU2zYXFRuFCBzGIpdN-wLyusWR7gkAtDBKvXlzcoWNJBSZ0T_Ua_IxafqeeNJPnKLlVmH_36-N8DdblPMnr0njhii7Dlsoru9Uv8chOK_8SkyhkLJuT_vuBaETz6BL5S5xRBA-jvTIzRyj-iSSpaxXIk=", "domain": "medium.com" } ], "searchQueries": [ "best multi agent frameworks ai 2025 2026", "multi agent systems frameworks python" ] }, { "prompt": 4, "engine": "GEMINI", "run": 3, "askedAt": "2026-10-09T01:30:15.842Z", "text": "1. **LangGraph**\n * Website: [github.com/langchain-ai/langgraph](https://github.com/langchain-ai/langgraph)\n * Widely regarded as the industry standard for production-grade multi-agent systems, offering deterministic, graph-based control over agent state and transitions.\n\n2. **CrewAI**\n * Website: [crewai.com](https://www.crewai.com)\n * Excellent for rapid prototyping of role-based teams where agents collaborate autonomously to achieve a shared objective.\n\n3. **Microsoft Agent Framework**\n * Website: [github.com/microsoft/agent-framework](https://github.com/microsoft/agent-framework)\n * Microsoft's unified enterprise orchestration SDK (combining AutoGen and Semantic Kernel features) built for secure, type-safe, and scalable multi-agent systems.\n\n4. **LlamaIndex Workflows**\n * Website: [llamaindex.ai](https://www.llamaindex.ai)\n * Ideal for data-heavy and document-centric multi-agent architectures leveraging an event-driven model in plain Python or TypeScript.\n\n5. **Google Agent Development Kit (ADK)**\n * Website: [github.com/google/agent-development-kit](https://github.com/google/agent-development-kit)\n * A code-first, Google-native toolkit designed for building structured agent teams, handling session management, and deploying multi-agent workflows.\n\n6. **Mastra**\n * Website: [mastra.ai](https://mastra.ai)\n * A comprehensive TypeScript/JavaScript-focused framework providing robust orchestration, memory, and tooling for building production-ready agent networks.", "brands": [ { "name": "LangGraph", "domain": "github.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft Agent Framework", "domain": "github.com" }, { "name": "LlamaIndex Workflows", "domain": "llamaindex.ai" }, { "name": "Google Agent Development Kit (ADK)", "domain": "github.com" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQG5uMoeqHYZvCjIygdovbGYvxDc7iCa0fzdrjHfeyxVG8RumscR3MZcVAdjgVQv9DI-AvHJJTqU0KkEMxCAMfK--juzoYHAHAVc6vrm1Acp47rw4aMSHvDrYJG_4DjqFXeE94sQXP_F9lhkiFNx4J9JmHL8K-aW", "domain": "redlinesoft.net" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQF_H5wAj4yMvwt-fT5bi-2kDDnvP5pC5ungOklZjdM3ZC7ktES_O7yPSeWe9wAt1B4Yo_J5JAhJzJqcU0cltbYOZ-c6DSTYk-iekQ9UVVI5z3YnLB2xhtIoQ-AS8LyqkVaRPzIsJ694pJ52OLZl", "domain": "langchain.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFzzVfr4HXLU-NV8FCRVMgK4IDFzPWTelavnESkoG8SUM-yDb_ZOt9dnDRQcGoLk3RJnUmNMRKKtYbFTt2IuPZ71UUN-QLK_eS1TRDaj2rRDiKjWdg1myQnpmvYyqcn2iByReDq_vdNxT68n1pbpHMEB4IdfFt3DK04h9mJpE6MjqoVTvEDZduQ97jLHaHMg0cXpJCz8Ua2KluUMAXxwruV9VJ7yYvjHEVV", "domain": "medium.com" } ], "searchQueries": [ "multi agent systems frameworks python", "best multi agent frameworks ai 2025 2026" ] }, { "prompt": 4, "engine": "GROK", "run": 1, "askedAt": "2026-10-09T01:28:39.349Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nBest overall for production multi-agent systems with explicit stateful graphs, checkpointing, human-in-the-loop, and strong enterprise adoption.[[1]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**2. CrewAI** \nhttps://crewai.com \nFastest for role-based multi-agent crews and prototypes, with intuitive agent/task/crew model and highest GitHub stars.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**3. Microsoft Agent Framework** \nhttps://learn.microsoft.com/en-us/semantic-kernel/ \nTop choice for Azure/.NET teams with built-in orchestration patterns (sequential, handoff, group chat) as the AutoGen successor.[[3]](https://www.ayautomate.com/blog/best-multi-agent-frameworks)\n\n**4. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/guides/agents \nCleanest lightweight option for OpenAI-centric agents with handoffs, guardrails, and minimal overhead.[[4]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**5. Google ADK** \nhttps://google.github.io/adk-docs/ \nStrong for Gemini-native and multi-language (Python, TS, Go, etc.) production agents with graph workflows and A2A support.[[1]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**6. Mastra** \nhttps://mastra.ai \nExcellent TypeScript-native framework for full-stack agent apps with workflows, memory, and observability.[[4]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**7. Pydantic AI** \nhttps://ai.pydantic.dev/ \nBest for type-safe, model-agnostic Python agents with validated outputs and durable execution options.[[5]](https://theexpertranking.com/developers/best-ai-agent-frameworks/)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft Agent Framework", "domain": "learn.microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Google ADK", "domain": "google.github.io" }, { "name": "Mastra", "domain": "mastra.ai" }, { "name": "Pydantic AI", "domain": "ai.pydantic.dev" } ], "sources": [ { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://theexpertranking.com/developers/best-ai-agent-frameworks/", "domain": "theexpertranking.com" } ], "searchQueries": [ "top frameworks for building multi-agent AI systems 2026", "best multi-agent frameworks LangGraph AutoGen CrewAI" ] }, { "prompt": 4, "engine": "GROK", "run": 2, "askedAt": "2026-10-09T01:29:35.416Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice for production multi-agent systems due to explicit stateful graphs, checkpointing, human-in-the-loop, and proven enterprise use at scale.[[1]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**2. CrewAI** \nhttps://crewai.com/ \nBest for fast role-based multi-agent crews with simple role/task/crew abstractions ideal for quick prototypes and collaborative workflows.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**3. Microsoft Agent Framework** \nhttps://learn.microsoft.com/en-us/agent-framework/overview/agent-framework-overview \nStrong for .NET/Python/Azure teams with built-in orchestration patterns, graph workflows, and unified successor to AutoGen/Semantic Kernel.[[3]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**4. OpenAI Agents SDK** \nhttps://openai.github.io/openai-agents-python/ \nLightweight and clean for OpenAI-centric apps with native handoffs, guardrails, sessions, and minimal overhead for tool-using agents.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**5. Google ADK** \nhttps://adk.dev/ \nExcellent for Gemini-native or polyglot multi-agent setups with graph workflows, multi-language support, and strong Google Cloud deployment options.[[1]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**6. Mastra** \nhttps://mastra.ai/ \nTop TypeScript option for full-stack teams needing batteries-included workflows, memory, and observability in multi-agent applications.[[2]](https://toolradar.com/guides/best-ai-agent-frameworks)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Google ADK", "domain": "adk.dev" }, { "name": "Mastra", "domain": "mastra.ai" } ], "sources": [ { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" } ], "searchQueries": [ "best frameworks for multi-agent AI systems 2026", "top multi-agent frameworks LangGraph CrewAI AutoGen 2026", "best multi-agent orchestration frameworks comparison", "LangGraph official website", "CrewAI official website", "Microsoft Agent Framework official site", "OpenAI Agents SDK website", "Google ADK agent framework website" ] }, { "prompt": 4, "engine": "GROK", "run": 3, "askedAt": "2026-10-09T01:30:30.934Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nBest overall for production-grade stateful multi-agent systems with explicit graph control, checkpointing, and human-in-the-loop.[[1]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**2. CrewAI** \nhttps://www.crewai.com \nTop choice for fast role-based multi-agent prototypes and collaborative crews with simple mental models.[[2]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**3. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/agents \nIdeal lightweight framework for clean tool-using agents and handoffs in OpenAI-centric apps.[[3]](https://toolradar.com/guides/best-ai-agent-frameworks)\n\n**4. Microsoft Agent Framework** \nhttps://learn.microsoft.com/en-us/semantic-kernel/ \nStrong for .NET/Azure teams with built-in orchestration patterns like sequential, concurrent, and group chat.[[4]](https://www.ayautomate.com/blog/best-multi-agent-frameworks)\n\n**5. Google ADK** \nhttps://developers.google.com/vertex-ai \nExcellent polyglot option for Gemini-native agents with multi-agent patterns and broad language support.[[1]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**6. Pydantic AI** \nhttps://ai.pydantic.dev \nBest for type-safe Python agents with strong validation and model-agnostic flexibility.", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.com" }, { "name": "Microsoft Agent Framework", "domain": "microsoft.com" }, { "name": "Google ADK", "domain": "google.com" }, { "name": "Pydantic AI", "domain": "pydantic.dev" } ], "sources": [ { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://toolradar.com/guides/best-ai-agent-frameworks", "domain": "toolradar.com" }, { "url": "https://www.ayautomate.com/blog/best-multi-agent-frameworks", "domain": "ayautomate.com" } ], "searchQueries": [ "best frameworks for building multi-agent AI systems 2026", "top multi-agent frameworks comparison CrewAI AutoGen LangGraph" ] }, { "prompt": 4, "engine": "AI_OVERVIEW", "run": 1, "askedAt": "2026-10-10T15:13:35.223Z", "text": "`There is no single \"best\" framework for multi-agent systems` ; the right choice depends on your production needs, architecture style, and team background:[[1]](https://arize.com/ai-agents/agent-frameworks/)\n\n### Top Frameworks by Use Case\n\n- **LangGraph:** Best for **production and deterministic control** . It uses graph-based state machines, offers fast latency, handles explicit state management, and remains a trusted standard for scalable enterprise deployments.[[1]](https://www.reddit.com/r/AI_Agents/comments/1swylbg/the_new_gen_multi_agent_frameworks_who_are_they/)[[2]](https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/)[[3]](https://www.decipherzone.com/blog-detail/best-ai-agent-frameworks)[[4]](https://aimultiple.com/agentic-frameworks)[[5]](https://medium.com/online-inference/best-practices-for-building-effective-ai-agents-and-multi-agent-systems-2c7fe11c9605)\n- **CrewAI:** Best for **role-based and collaborative team setups** . It models agents like a corporate team with specific roles, managers, and delegated tasks, though it can run higher in token consumption and latency.[[1]](https://aimultiple.com/agentic-frameworks)[[2]](https://www.bitcot.com/ai-agent-frameworks/)[[3]](https://arize.com/ai-agents/agent-frameworks/)\n- **AutoGen (Microsoft):** Best for **conversational and actor-model multi-agent loops** . It excels at unstructured data handling and autonomous peer-to-peer or group chat interactions.[[1]](https://www.openlayer.com/blog/multi-agent-system-architecture-guide)[[2]](https://www.bitcot.com/ai-agent-frameworks/)[[3]](https://aimultiple.com/agentic-frameworks)\n- **OpenAI Swarm / Agents SDK:** Best for **lightweight, experimental, or hosted workflows** . It focuses on routine-based handoffs with minimal overhead.[[1]](https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/)[[2]](https://aimultiple.com/agentic-frameworks)\n- **Pydantic AI / Mastra:** Best for **type-safe or TypeScript/Python developer ecosystems** requiring strict data validation and modular design.[[1]](https://arize.com/ai-agents/agent-frameworks/)\n\n### How to Choose\n\n- Choose **LangGraph** if you need high reliability, strict state graphs, and predictable enterprise control.\n- Choose **CrewAI** if you want an intuitive, high-level abstraction for multi-agent role delegation.\n- Choose **AutoGen** if your system relies on conversational agent-to-agent negotiations.[[1]](https://www.reddit.com/r/AI_Agents/comments/1swylbg/the_new_gen_multi_agent_frameworks_who_are_they/)[[2]](https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/)[[3]](https://aimultiple.com/agentic-frameworks)[[4]](https://www.bitcot.com/ai-agent-frameworks/)", "brands": [ { "name": "LangGraph" }, { "name": "CrewAI" }, { "name": "AutoGen", "domain": "microsoft.com" }, { "name": "OpenAI Swarm" }, { "name": "Agents SDK" }, { "name": "Pydantic AI" }, { "name": "Mastra" } ], "sources": [ { "url": "https://www.reddit.com/r/AI_Agents/comments/1swylbg/the_new_gen_multi_agent_frameworks_who_are_they/", "domain": "reddit.com", "title": "The New gen multi agent frameworks. Who are they targetted ..." }, { "url": "https://blog.jetbrains.com/pycharm/2026/06/top-agentic-frameworks-for-building-applications-2026/", "domain": "blog.jetbrains.com", "title": "Top Agentic Frameworks for Building Applications 2026 - The JetBrains Blog" }, { "url": "https://www.openlayer.com/blog/multi-agent-system-architecture-guide", "domain": "openlayer.com", "title": "Multi-agent system architecture: a comparison guide + best practices (March 2026) | Openlayer" }, { "url": "https://medium.com/online-inference/best-practices-for-building-effective-ai-agents-and-multi-agent-systems-2c7fe11c9605", "domain": "medium.com", "title": "Medium" }, { "url": "https://aimultiple.com/agentic-frameworks", "domain": "aimultiple.com", "title": "Top 5 Open-Source Agentic AI Frameworks" }, { "url": "https://arize.com/ai-agents/agent-frameworks/", "domain": "arize.com", "title": "AI agent frameworks compared: LangGraph, CrewAI, AutoGen, and ..." }, { "url": "https://www.decipherzone.com/blog-detail/best-ai-agent-frameworks", "domain": "decipherzone.com", "title": "Top 12 Best Frameworks for Building AI Agents in 2026" }, { "url": "https://www.bitcot.com/ai-agent-frameworks/", "domain": "bitcot.com", "title": "Top 10 AI Agent Frameworks to Build Multi-Agent Enterprise Apps in 2025" } ], "searchQueries": "not exposed" }, { "prompt": 5, "engine": "OPENAI", "run": 1, "askedAt": "2026-10-09T01:28:34.609Z", "text": "1. **LangChain (Python)** — https://www.langchain.com/langchain \n Easiest for rapid agent prototyping with many built-in agent patterns, tool integrations, and tutorials. ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\n2. **OpenAI Agents SDK (Python)** — https://openai.github.io/openai-agents-python/ \n Very simple code-first agent primitives, automatic function-tool wiring, and official SDK support for running tool-using agents. ([openai.github.io](https://openai.github.io/openai-agents-python/?utm_source=openai))\n\n3. **Microsoft Semantic Kernel (Python)** — https://github.com/microsoft/semantic-kernel (docs: learn.microsoft.com/semantic-kernel) \n Provides a lightweight Agent/Assistant abstraction with plug-in “skills” and examples for quick Python agent builds (good enterprise integrations). ([github.com](https://github.com/microsoft/semantic-kernel/blob/main/python/samples/getting_started_with_agents/README.md?utm_source=openai))\n\n4. **LlamaIndex (Python)** — https://developers.llamaindex.ai/ \n Focused on data-indexed agents (LLM + retrieval); easy to turn indexed data into callable tools and agent workflows. ([developers.llamaindex.ai](https://developers.llamaindex.ai/python/framework/module_guides/deploying/agents/?utm_source=openai))\n\n5. **AutoGen (Meta) / AutoGen Studio (Python API + tools)** — (paper / project pages: arXiv and project repo) \n Designed for multi-agent conversations and debugging; good if you want declarative multi-agent setups and a higher-level orchestration layer. ([arxiv.org](https://arxiv.org/abs/2308.08155?utm_source=openai))\n\n6. **AgentForge (open-source framework/research)** — (research paper / GitHub if available) \n Lightweight modular Python framework promising fast development of autonomous agents with simple modular APIs (useful if you want minimal boilerplate). ([arxiv.org](https://arxiv.org/abs/2601.13383?utm_source=openai))\n\nNotes: these are ranked from easiest/most commonly used first (LangChain, OpenAI Agents SDK) to more specialized frameworks. If you want a single-sentence starter recommendation: use LangChain or the OpenAI Agents SDK and follow their Python quickstart examples — both provide ready-made agent patterns and tool wiring so you can have a working agent in minutes.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "OpenAI", "domain": "openai.github.io" }, { "name": "Microsoft", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "developers.llamaindex.ai" }, { "name": "AutoGen", "domain": "arxiv.org" }, { "name": "AgentForge", "domain": "arxiv.org" } ], "sources": [ { "url": "https://www.langchain.com/langchain?utm_source=openai", "domain": "langchain.com", "title": "LangChain: Open Source AI Agent Framework for Any Model" }, { "url": "https://openai.github.io/openai-agents-python/?utm_source=openai", "domain": "openai.github.io", "title": "OpenAI Agents SDK" }, { "url": "https://github.com/microsoft/semantic-kernel/blob/main/python/samples/getting_started_with_agents/README.md?utm_source=openai", "domain": "github.com", "title": "semantic-kernel/python/samples/getting_started_with_agents/README.md at main · microsoft/semantic-kernel · GitHub" }, { "url": "https://developers.llamaindex.ai/python/framework/module_guides/deploying/agents/?utm_source=openai", "domain": "developers.llamaindex.ai", "title": "Agents | Developer Documentation" }, { "url": "https://arxiv.org/abs/2308.08155?utm_source=openai", "domain": "arxiv.org", "title": "AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation" }, { "url": "https://arxiv.org/abs/2601.13383?utm_source=openai", "domain": "arxiv.org", "title": "A Lightweight Modular Framework for Constructing Autonomous Agents Driven by Large Language Models: Design, Implementation, and Applications in AgentForge" } ], "searchQueries": [ "LangChain Python agents library website", "OpenAI Python SDK function calling agents guide", "LlamaIndex (now called LlamaIndex) website python agent", "Microsoft Semantic Kernel python agents website", "Meta AutoGen python agents website", "Hugging Face AutoTrain/Agentic? 'agentic' library python agents Hugging Face" ] }, { "prompt": 5, "engine": "OPENAI", "run": 2, "askedAt": "2026-10-09T01:29:29.230Z", "text": "1. **LangChain** — https://www.langchain.com/langchain \n Easiest way to glue LLMs, tools, and prompts into an agent-style workflow with rich Python examples and many integrations. ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\n2. **OpenAI Agents SDK (Python)** — https://openai.github.io/openai-agents-python/ \n High-level managed SDK for building agents with tools, function-tool wrapping, sessions, and runners directly in Python. ([openai.github.io](https://openai.github.io/openai-agents-python/?utm_source=openai))\n\n3. **LlamaIndex (formerly GPT-Index)** — https://llamaindex.openml.io/ \n Fast way to build data-backed agents that index, query, and reason over your documents from Python with simple APIs. ([llamaindex.openml.io](https://llamaindex.openml.io/?utm_source=openai))\n\n4. **Microsoft Semantic Kernel** — https://github.com/microsoft/semantic-kernel (docs: learn.microsoft.com) \n Opinionated agent framework with plugins/skills, a Kernel abstraction, and Python samples for building multi-step assistants. ([github.com](https://github.com/microsoft/semantic-kernel/blob/main/python/samples/getting_started_with_agents/README.md?utm_source=openai))\n\n5. **Auto-GPT (community project)** — https://github.com/Significant-Gravitas/Auto-GPT \n Ready-made autonomous agent example to experiment with multi-step goal-directed behavior in Python (good for prototyping). ([en.wikipedia.org](https://en.wikipedia.org/wiki/AutoGPT?utm_source=openai))\n\n6. **Rasa (Open Source)** — https://rasa.com/ (quickstart: opensource.rasa.com/quickstart) \n If you need conversational/dialogue agents with state tracking and custom Python actions, Rasa provides a proven open-source stack. ([opensource.rasa.com](https://opensource.rasa.com/quickstart/?utm_source=openai))\n\nIf you want a single recommendation to start immediately: use LangChain for general-purpose LLM agents or the OpenAI Agents SDK if you prefer a tightly integrated, supported runtime for OpenAI models.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK (Python)", "domain": "openai.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.openml.io" }, { "name": "Microsoft Semantic Kernel", "domain": "github.com" }, { "name": "Auto-GPT", "domain": "github.com" }, { "name": "Rasa (Open Source)", "domain": "rasa.com" } ], "sources": [ { "url": "https://www.langchain.com/langchain?utm_source=openai", "domain": "langchain.com", "title": "LangChain: Open Source AI Agent Framework for Any Model" }, { "url": "https://openai.github.io/openai-agents-python/?utm_source=openai", "domain": "openai.github.io", "title": "OpenAI Agents SDK" }, { "url": "https://llamaindex.openml.io/?utm_source=openai", "domain": "llamaindex.openml.io", "title": "Welcome to LlamaIndex 🦙 ! | LlamaIndex Python Documentation" }, { "url": "https://github.com/microsoft/semantic-kernel/blob/main/python/samples/getting_started_with_agents/README.md?utm_source=openai", "domain": "github.com", "title": "semantic-kernel/python/samples/getting_started_with_agents/README.md at main · microsoft/semantic-kernel · GitHub" }, { "url": "https://en.wikipedia.org/wiki/AutoGPT?utm_source=openai", "domain": "en.wikipedia.org", "title": "AutoGPT" }, { "url": "https://opensource.rasa.com/quickstart/?utm_source=openai", "domain": "opensource.rasa.com", "title": "Build your first Rasa agent · Rasa Community" } ], "searchQueries": [ "LangChain Python agents library website", "LlamaIndex agents Python website", "OpenAI Python SDK agents function calling documentation", "Microsoft Semantic Kernel Python agents website", "Auto-GPT GitHub Python agent", "Hugging Face Transformers agents python examples", "Rasa open source conversational AI python", "Ray Serve for building agents in python" ] }, { "prompt": 5, "engine": "OPENAI", "run": 3, "askedAt": "2026-10-09T01:30:29.879Z", "text": "1. **LangChain (Python)** — https://langchain.com \n Easiest for building tool-using LLM agents with lots of ready-made agent templates, memory, and integrations. ([langchain.com](https://www.langchain.com/langchain?utm_source=openai))\n\n2. **OpenAI Agents SDK (Python)** — https://openai.github.io/openai-agents-python/ \n A very straightforward, maintained SDK for turning Python functions into tools and running managed agent workflows (quickstarts and function-tool decorators). ([openai.github.io](https://openai.github.io/openai-agents-python/?utm_source=openai))\n\n3. **Microsoft AutoGen / Agent Framework** — https://github.com/microsoft/autogen \n High-level multi-agent framework (and AutoGen Studio) for quickly composing agents that coordinate, call tools, and run multi-agent conversations. ([github.com](https://github.com/microsoft/autogen?utm_source=openai))\n\n4. **LlamaIndex (formerly GPT-Index)** — https://llamaindex.ai \n Easiest way to add retrieval-augmented context and document tooling to an agent (indexing, vector retrieval, RAG workflows). ([gpt-index.readthedocs.io](https://gpt-index.readthedocs.io/_/downloads/en/v0.6.0/pdf/?utm_source=openai))\n\n5. **Hugging Face (Transformers + Accelerate)** — https://huggingface.co/docs/transformers / https://huggingface.co/docs/accelerate \n Best if you want to run local or open models in Python and integrate them into agent loops with model/acceleration tooling. ([huggingface.co](https://huggingface.co/docs/accelerate/main/basic_tutorials/install?utm_source=openai))\n\n6. **Ray RLlib** — https://www.ray.io/rllib \n Easiest when your definition of “agent” is a reinforcement-learning agent (training, distributed execution, multi-agent RL support). ([assets.ctfassets.net](https://assets.ctfassets.net/xjan103pcp94/6hZjf3wmEKtDsipspotPXL/06a435863fed9729dc9e6ceb06400e36/RL.pdf?utm_source=openai))\n\n7. **Auto-GPT / Open-source agent projects (examples on GitHub)** — (search GitHub for Auto-GPT / agent templates) \n Quick demos and boilerplate projects you can run locally to understand agent loops (task planning, tools, memory) and iterate fast. ([cdn.openai.com](https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf?utm_source=openai))\n\nQuick recommendation: if you want the absolute easiest path for typical LLM-based assistants that call Python tools, start with LangChain or the OpenAI Agents SDK (both have short Python quickstarts and built-in tool/function wrappers). If you want multi-agent orchestration or no-code studio features, try Microsoft AutoGen / Agent Framework.", "brands": [ { "name": "LangChain", "domain": "langchain.com" }, { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Microsoft AutoGen", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "Hugging Face", "domain": "huggingface.co" }, { "name": "Ray RLlib", "domain": "ray.io" }, { "name": "Auto-GPT", "domain": "github.com" } ], "sources": [ { "url": "https://www.langchain.com/langchain?utm_source=openai", "domain": "langchain.com", "title": "LangChain: Open Source AI Agent Framework for Any Model" }, { "url": "https://openai.github.io/openai-agents-python/?utm_source=openai", "domain": "openai.github.io", "title": "OpenAI Agents SDK" }, { "url": "https://github.com/microsoft/autogen?utm_source=openai", "domain": "github.com", "title": "GitHub - microsoft/autogen: A programming framework for agentic AI · GitHub" }, { "url": "https://gpt-index.readthedocs.io/_/downloads/en/v0.6.0/pdf/?utm_source=openai", "domain": "gpt-index.readthedocs.io", "title": "LlamaIndex 🦙" }, { "url": "https://huggingface.co/docs/accelerate/main/basic_tutorials/install?utm_source=openai", "domain": "huggingface.co", "title": "Installation · Hugging Face" }, { "url": "https://assets.ctfassets.net/xjan103pcp94/6hZjf3wmEKtDsipspotPXL/06a435863fed9729dc9e6ceb06400e36/RL.pdf?utm_source=openai", "domain": "assets.ctfassets.net", "title": "RAY\nReinforcement Learning\nML library for reinforc" }, { "url": "https://cdn.openai.com/business-guides-and-resources/a-practical-guide-to-building-agents.pdf?utm_source=openai", "domain": "cdn.openai.com", "title": "For example, here’s how you would equip the agent defined above with a series of tools when using the Agents SDK:" } ], "searchQueries": [ "LangChain Python agents LangChain agents library website", "Microsoft AutoGen GitHub AutoGen python conversational agents", "OpenAI function calling Python SDK agents", "LlamaIndex (now GPT Index) python retrieval augmented generation website", "Hugging Face Accelerate and Transformers building agents python", "Ray RLlib python reinforcement learning library agents website" ] }, { "prompt": 5, "engine": "ANTHROPIC", "run": 1, "askedAt": "2026-10-09T01:28:33.845Z", "text": "I'll search for current best practices on building AI agents in Python.\nBased on current 2026 guidance, here's the easiest way to build an AI agent in Python:\n\n## Core Approach\n\n\nThe fastest way is to pick a task with a clear success condition, use the Anthropic Claude API or OpenAI API with tool use enabled, define 2–3 tools, and wrap it in a loop that feeds the model's output back as input until it says it's done. The whole skeleton fits in under 100 lines of Python.\n\n\n## Why This Works\n\n\nAn AI agent is a loop, not a magic product: the model reads the conversation, decides whether to call a tool, your code runs that tool, and the result goes back to the model until it can answer.\n\n\n## Getting Started\n\n1. **Start with raw Python**: \nBuild your first agent in 60 lines of raw Python with a while loop and the Anthropic SDK.\n \nSkip LangChain for your first agent—LangChain's abstractions hide the exact mechanics a learner needs to see.\n\n\n2. **The basic structure**:\n - Install the Anthropic SDK: `pip install anthropic`\n - Define your tools with JSON schemas\n - Write a loop that calls the model and executes any requested tools\n - Return results back to the model until it completes\n\n3. **When to use frameworks**: \nThe leading frameworks in 2026 are LangChain (broad ecosystem, mature tooling), LangGraph (graph-based multi-step workflows), and the Claude Agent SDK.\n But start simple—master the loop first.\n\nThe key insight: \nEvery framework is just a wrapper around this loop.", "brands": [ { "name": "Anthropic", "domain": "anthropic.com" }, { "name": "OpenAI", "domain": "openai.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Claude Agent SDK", "domain": "anthropic.com" } ], "sources": [ { "url": "https://www.eicta.iitk.ac.in/knowledge-hub/artificial-intelligence/how-to-build-ai-agent-from-scratch", "domain": "eicta.iitk.ac.in", "title": "How to Build an AI Agent From Scratch in 2026: Step-by-Step Beginner Guide With Python Code" }, { "url": "https://www.aibuilderclub.com/blog/ai-agents", "domain": "aibuilderclub.com", "title": "AI Agents in 2026: Build, Deploy, and Scale (Full Guide)" }, { "url": "https://newsletter.aiengineer.co/p/the-simplest-way-to-build-ai-agents", "domain": "newsletter.aiengineer.co", "title": "The simplest way to build AI agents in 2026" }, { "url": "https://www.crazehq.com/ai-agent/how-to-build-an-ai-agent", "domain": "crazehq.com", "title": "How to Build an AI Agent: Step-by-Step Guide (2026) - Craze" }, { "url": "https://www.uselearnai.com/blog/how-to-build-ai-agents-beginners-guide-2026", "domain": "uselearnai.com", "title": "How to Build AI Agents in 2026: A Beginner's Complete Tutorial" }, { "url": "https://www.genericode.com/blogs/how-to-build-an-ai-agent-in-2026-a-simple-beginners-guide/", "domain": "genericode.com", "title": "How to Build an AI Agent in 2026: A Simple Beginner’s Guide" }, { "url": "https://cloudsoftsol.com/blog/build-your-first-ai-agent", "domain": "cloudsoftsol.com", "title": "Build an AI Agent in Python: Step-by-Step Tutorial 2026 — Cloud Soft Solutions" }, { "url": "https://precisionaiacademy.com/blog/how-to-build-ai-agent-python-2026", "domain": "precisionaiacademy.com", "title": "How to Build an AI Agent with Python in 2026 — Complete Step-by-Step Guide" }, { "url": "https://precisionaiacademy.com/blog/how-to-build-ai-agent-2026", "domain": "precisionaiacademy.com", "title": "How to Build an AI Agent from Scratch [2026] (Step-by-Step)" } ], "searchQueries": [ "easiest way build AI agent Python 2026" ] }, { "prompt": 5, "engine": "ANTHROPIC", "run": 2, "askedAt": "2026-10-09T01:29:28.795Z", "text": "I can help you with that! Let me search for the current best approaches and tools for building AI agents in Python.\nBased on current best practices, here are the easiest approaches to build an AI agent in Python:\n\n## **Simplest Approach: Raw Python with an LLM API**\n\n\nThe fastest way is to pick a task with a clear success condition, use the Anthropic Claude API or OpenAI API with tool use enabled, define 2–3 tools, and wrap it in a loop that feeds the model's output back as input until it says it's done—the whole skeleton fits in under 100 lines of Python.\n\n\n\nBuild your first agent in 60 lines of raw Python with a while loop and the Anthropic SDK.\n You only need one dependency: `pip install anthropic`\n\n## **Framework-Based Approaches**\n\nIf you want more structure:\n\n- **\nCrewAI is the easiest to learn—if your workflow is naturally multi-role, it gets you to a working prototype faster than anything else.\n**\n\n- **\nOpenAI Agents SDK is the simplest option if you're already using OpenAI models, with less flexibility than LangGraph but faster to start.\n**\n\n- **\nLangChain is a popular framework for building agents with tools, memory, and the ReAct pattern.\n**\n\n## **Core Concept**\n\n\nAn AI agent is a loop: the model reads the conversation, decides whether to call a tool, your code runs that tool, and the result goes back to the model until it can answer. Define a few safe tools with clear JSON schemas, write a loop that calls the model, executes any requested tool and returns the result, and wrap that loop with a step limit, error handling, and logging.\n\n\nFor beginners, starting with raw Python and the Anthropic SDK gives you the most control and understanding of how agents actually work.", "brands": [ { "name": "Anthropic", "domain": "anthropic.com" }, { "name": "OpenAI", "domain": "openai.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "LangChain", "domain": "langchain.com" } ], "sources": [ { "url": "https://www.eicta.iitk.ac.in/knowledge-hub/artificial-intelligence/how-to-build-ai-agent-from-scratch", "domain": "eicta.iitk.ac.in", "title": "How to Build an AI Agent From Scratch in 2026: Step-by-Step Beginner Guide With Python Code" }, { "url": "https://www.aibuilderclub.com/blog/ai-agents", "domain": "aibuilderclub.com", "title": "AI Agents in 2026: Build, Deploy, and Scale (Full Guide)" }, { "url": "https://www.crazehq.com/ai-agent/how-to-build-an-ai-agent", "domain": "crazehq.com", "title": "How to Build an AI Agent: Step-by-Step Guide (2026) - Craze" }, { "url": "https://newsletter.aiengineer.co/p/the-simplest-way-to-build-ai-agents", "domain": "newsletter.aiengineer.co", "title": "The simplest way to build AI agents in 2026" }, { "url": "https://www.uselearnai.com/blog/how-to-build-ai-agents-beginners-guide-2026", "domain": "uselearnai.com", "title": "How to Build AI Agents in 2026: A Beginner's Complete Tutorial" }, { "url": "https://www.genericode.com/blogs/how-to-build-an-ai-agent-in-2026-a-simple-beginners-guide/", "domain": "genericode.com", "title": "How to Build an AI Agent in 2026: A Simple Beginner’s Guide" }, { "url": "https://cloudsoftsol.com/blog/build-your-first-ai-agent", "domain": "cloudsoftsol.com", "title": "Build an AI Agent in Python: Step-by-Step Tutorial 2026 — Cloud Soft Solutions" }, { "url": "https://precisionaiacademy.com/blog/how-to-build-ai-agent-python-2026", "domain": "precisionaiacademy.com", "title": "How to Build an AI Agent with Python in 2026 — Complete Step-by-Step Guide" }, { "url": "https://precisionaiacademy.com/blog/how-to-build-ai-agent-2026", "domain": "precisionaiacademy.com", "title": "How to Build an AI Agent from Scratch [2026] (Step-by-Step)" } ], "searchQueries": [ "easiest way build AI agent Python 2026" ] }, { "prompt": 5, "engine": "ANTHROPIC", "run": 3, "askedAt": "2026-10-09T01:30:23.963Z", "text": "I'll search for current information on the easiest ways to build AI agents in Python.\nBased on current information, here are the easiest ways to build an AI agent in Python:\n\n## The Simplest Approach (No Framework)\n\n\nThe fastest way is to pick a task with a clear success condition, use the Anthropic Claude API or OpenAI API with tool use enabled, define 2-3 tools, and wrap it in a loop that feeds the model's output back as input until it says it's done—the whole skeleton fits in under 100 lines of Python.\n\n\n\nBuild your first agent in 60 lines of raw Python with a while loop and the Anthropic SDK.\n \nAt minimum you need an LLM SDK — the Anthropic Python SDK (anthropic) for Claude or openai for GPT models.\n\n\n## With Frameworks\n\n\nIf you want more control, use a Python framework like CrewAI or LangChain.\n \nThe leading frameworks in 2026 are LangChain (broad ecosystem, mature tooling), LangGraph (graph-based multi-step workflows), the Claude Agent SDK.\n\n\n## Key Components\n\n\nTo build an AI agent in Python, you define a few safe tools with clear JSON schemas, write a loop that calls the model, executes any requested tool and returns the result, and wrap that loop with a step limit, error handling, logging and a small evaluation set.\n\n\n**Recommendation:** \nStart with the direct SDK\n rather than frameworks if you're new to agent building. This teaches you the core mechanics that frameworks abstract away.", "brands": [ { "name": "Anthropic", "domain": "anthropic.com" }, { "name": "OpenAI", "domain": "openai.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langchain.com" } ], "sources": [ { "url": "https://www.eicta.iitk.ac.in/knowledge-hub/artificial-intelligence/how-to-build-ai-agent-from-scratch", "domain": "eicta.iitk.ac.in", "title": "How to Build an AI Agent From Scratch in 2026: Step-by-Step Beginner Guide With Python Code" }, { "url": "https://www.aibuilderclub.com/blog/ai-agents", "domain": "aibuilderclub.com", "title": "AI Agents in 2026: Build, Deploy, and Scale (Full Guide)" }, { "url": "https://newsletter.aiengineer.co/p/the-simplest-way-to-build-ai-agents", "domain": "newsletter.aiengineer.co", "title": "The simplest way to build AI agents in 2026" }, { "url": "https://www.crazehq.com/ai-agent/how-to-build-an-ai-agent", "domain": "crazehq.com", "title": "How to Build an AI Agent: Step-by-Step Guide (2026) - Craze" }, { "url": "https://www.uselearnai.com/blog/how-to-build-ai-agents-beginners-guide-2026", "domain": "uselearnai.com", "title": "How to Build AI Agents in 2026: A Beginner's Complete Tutorial" }, { "url": "https://www.genericode.com/blogs/how-to-build-an-ai-agent-in-2026-a-simple-beginners-guide/", "domain": "genericode.com", "title": "How to Build an AI Agent in 2026: A Simple Beginner’s Guide" }, { "url": "https://cloudsoftsol.com/blog/build-your-first-ai-agent", "domain": "cloudsoftsol.com", "title": "Build an AI Agent in Python: Step-by-Step Tutorial 2026 — Cloud Soft Solutions" }, { "url": "https://precisionaiacademy.com/blog/how-to-build-ai-agent-python-2026", "domain": "precisionaiacademy.com", "title": "How to Build an AI Agent with Python in 2026 — Complete Step-by-Step Guide" }, { "url": "https://precisionaiacademy.com/blog/how-to-build-ai-agent-2026", "domain": "precisionaiacademy.com", "title": "How to Build an AI Agent from Scratch [2026] (Step-by-Step)" } ], "searchQueries": [ "easiest way build AI agent Python 2026" ] }, { "prompt": 5, "engine": "PERPLEXITY", "run": 1, "askedAt": "2026-10-09T01:28:30.299Z", "text": "1. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ \n Easiest overall for a first Python agent: define a model, instructions, and tools while the SDK handles the agent loop and handoffs.[1][2]\n\n2. **Anthropic Python SDK** — https://github.com/anthropics/anthropic-sdk-python \n Best for a minimal, framework-free implementation using ordinary Python functions plus a short tool-calling loop.[4]\n\n3. **Strands Agents** — https://strandsagents.com/ \n A concise SDK that lets the model orchestrate tool calls and conversation state with very little workflow code.[2]\n\n4. **LangChain** — https://www.langchain.com/ \n A beginner-friendly higher-level framework with ready-made agent creation, provider integrations, tools, and memory options.[6]\n\n5. **PydanticAI** — https://ai.pydantic.dev/ \n A strong choice when you want simple Python syntax combined with typed, validated tool inputs and structured outputs.[9]\n\n6. **LangGraph** — https://www.langchain.com/langgraph \n Choose it when the agent needs explicit state, branching, retries, or multi-step workflows rather than the smallest possible prototype.[8][9]\n\nFor the easiest first project, start with **OpenAI Agents SDK**: give the agent one narrowly defined goal, add one read-only tool, and test successful, failed, and unsafe requests before expanding it.[3]", "brands": [ { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Anthropic Python SDK", "domain": "github.com" }, { "name": "Strands Agents", "domain": "strandsagents.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "LangGraph", "domain": "langchain.com" } ], "sources": [ { "url": "https://www.oreilly.com/radar/how-to-build-a-general-purpose-ai-agent-in-131-lines-of-python/", "domain": "oreilly.com", "title": "How to Build a General-Purpose AI Agent in 131 Lines of Python" }, { "url": "https://dev.to/aws/ai-agents-dont-need-complex-workflows-build-one-in-python-in-10-minutes-2m5d", "domain": "dev.to", "title": "AI Agents Don't Need Complex Workflows. Build One in ..." }, { "url": "https://www.itechguides.com/how-to-build-your-first-ai-agent-a-step-by-step-tutorial/", "domain": "itechguides.com", "title": "How to Build Your First AI Agent in Python: Step-by-Step - iTechGuides" }, { "url": "https://www.aibuilderclub.com/blog/how-to-build-ai-agent-from-scratch", "domain": "aibuilderclub.com", "title": "www.aibuilderclub.com › blog › how-to-build-ai-agentHow to Build an AI Agent from Scratch in Python (2026)" }, { "url": "https://lilys.ai/en/notes/separate-dividend-taxation-20251112/build-ai-agents-python", "domain": "lilys.ai", "title": "How to Build AI Agents in Python" }, { "url": "https://freeacademy.ai/blog/build-first-ai-agent-python-30-minutes", "domain": "freeacademy.ai", "title": "freeacademy.ai › blog › build-first-ai-agent-pythonBuild Your First AI Agent in 30 Minutes (Python + LangChain ..." }, { "url": "https://fast.io/resources/build-ai-agent-python/", "domain": "fast.io", "title": "How to Build an AI Agent in Python: Complete G | Fastio" }, { "url": "https://www.udacity.com/blog/how-to-build-an-ai-agent-step-by-step-with-python/", "domain": "udacity.com", "title": "www.udacity.com · blog · how-to-build-an-ai-agent-step-by-stepHow to Build an AI Agent: Step-by-Step with Python - Udacity" }, { "url": "https://www.ema.ai/additional-blogs/addition-blogs/building-ai-agents-python-guide", "domain": "ema.ai", "title": "How to Build AI Agents Using Python: A Step-by-Step Guide - Ema AI" }, { "url": "https://www.gsdcouncil.org/blogs/python-developer-guide-agentic-ai-ai-agents", "domain": "gsdcouncil.org", "title": "The Python Developer's Guide to Agentic AI and AI Agents" } ], "searchQueries": "not exposed" }, { "prompt": 5, "engine": "PERPLEXITY", "run": 2, "askedAt": "2026-10-09T01:29:24.296Z", "text": "1. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Best overall starting point: define a model, instructions, and tools, while the SDK handles the agent loop and handoffs.[1][2]\n\n2. **Strands Agents** — https://strandsagents.com/ — Very fast to prototype because the model can orchestrate tool calls with minimal workflow code.[2]\n\n3. **Anthropic Python SDK** — https://github.com/anthropics/anthropic-sdk-python — Easiest lightweight, framework-free option: add Python functions, then implement a small tool-use loop.[4]\n\n4. **LangChain** — https://www.langchain.com/ — Beginner-friendly ecosystem with prebuilt agent functions, model integrations, tools, and memory support.[6]\n\n5. **LangGraph** — https://www.langchain.com/langgraph — Best when the simple agent must become a reliable, stateful workflow with explicit steps and control.[8][9]\n\n6. **CrewAI** — https://www.crewai.com/ — Convenient for coordinating multiple specialized agents, though more complexity than needed for a first single-agent prototype.[10]\n\nFor the easiest first build, use **OpenAI Agents SDK**: create one agent with one narrowly scoped, read-only tool, test it without tools first, then add validation and a hard step limit.[3][10]", "brands": [ { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Strands Agents", "domain": "strandsagents.com" }, { "name": "Anthropic Python SDK", "domain": "github.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" } ], "sources": [ { "url": "https://www.oreilly.com/radar/how-to-build-a-general-purpose-ai-agent-in-131-lines-of-python/", "domain": "oreilly.com", "title": "How to Build a General-Purpose AI Agent in 131 Lines of Python" }, { "url": "https://dev.to/aws/ai-agents-dont-need-complex-workflows-build-one-in-python-in-10-minutes-2m5d", "domain": "dev.to", "title": "AI Agents Don't Need Complex Workflows. Build One in ..." }, { "url": "https://www.itechguides.com/how-to-build-your-first-ai-agent-a-step-by-step-tutorial/", "domain": "itechguides.com", "title": "How to Build Your First AI Agent in Python: Step-by-Step - iTechGuides" }, { "url": "https://www.aibuilderclub.com/blog/how-to-build-ai-agent-from-scratch", "domain": "aibuilderclub.com", "title": "www.aibuilderclub.com › blog › how-to-build-ai-agentHow to Build an AI Agent from Scratch in Python (2026)" }, { "url": "https://lilys.ai/en/notes/separate-dividend-taxation-20251112/build-ai-agents-python", "domain": "lilys.ai", "title": "How to Build AI Agents in Python" }, { "url": "https://freeacademy.ai/blog/build-first-ai-agent-python-30-minutes", "domain": "freeacademy.ai", "title": "freeacademy.ai › blog › build-first-ai-agent-pythonBuild Your First AI Agent in 30 Minutes (Python + LangChain ..." }, { "url": "https://fast.io/resources/build-ai-agent-python/", "domain": "fast.io", "title": "How to Build an AI Agent in Python: Complete G | Fastio" }, { "url": "https://www.udacity.com/blog/how-to-build-an-ai-agent-step-by-step-with-python/", "domain": "udacity.com", "title": "www.udacity.com · blog · how-to-build-an-ai-agent-step-by-stepHow to Build an AI Agent: Step-by-Step with Python - Udacity" }, { "url": "https://www.ema.ai/additional-blogs/addition-blogs/building-ai-agents-python-guide", "domain": "ema.ai", "title": "How to Build AI Agents Using Python: A Step-by-Step Guide - Ema AI" }, { "url": "https://www.gsdcouncil.org/blogs/python-developer-guide-agentic-ai-ai-agents", "domain": "gsdcouncil.org", "title": "The Python Developer's Guide to Agentic AI and AI Agents" } ], "searchQueries": "not exposed" }, { "prompt": 5, "engine": "PERPLEXITY", "run": 3, "askedAt": "2026-10-09T01:30:19.916Z", "text": "1. **OpenAI Agents SDK** — https://openai.github.io/openai-agents-python/ — Easiest overall for a first Python agent: define instructions and tools, then let the SDK manage the agent loop and handoffs.[1][2]\n2. **Strands Agents** — https://strandsagents.com/ — Minimal code-first option that lets the model choose among Python tools while the SDK handles execution and conversation state.[2]\n3. **Anthropic Python SDK** — https://github.com/anthropics/anthropic-sdk-python — Best for maximum simplicity and control: combine Claude tool use with a short Python `while` loop.[4]\n4. **LangChain** — https://www.langchain.com/ — Beginner-friendly framework with integrations, memory, and prebuilt agent patterns such as ReAct.[6]\n5. **LangGraph** — https://langchain-ai.github.io/langgraph/ — Strong choice when the agent needs explicit state, branching, retries, or multi-step workflows rather than a simple loop.[8][9]\n6. **CrewAI** — https://www.crewai.com/ — Convenient for coordinating multiple specialized agents, though more complexity than necessary for a first single-agent project.[9]", "brands": [ { "name": "OpenAI Agents SDK", "domain": "openai.github.io" }, { "name": "Strands Agents", "domain": "strandsagents.com" }, { "name": "Anthropic Python SDK", "domain": "github.com" }, { "name": "LangChain", "domain": "langchain.com" }, { "name": "LangGraph", "domain": "langchain-ai.github.io" }, { "name": "CrewAI", "domain": "crewai.com" } ], "sources": [ { "url": "https://www.oreilly.com/radar/how-to-build-a-general-purpose-ai-agent-in-131-lines-of-python/", "domain": "oreilly.com", "title": "How to Build a General-Purpose AI Agent in 131 Lines of Python" }, { "url": "https://dev.to/aws/ai-agents-dont-need-complex-workflows-build-one-in-python-in-10-minutes-2m5d", "domain": "dev.to", "title": "AI Agents Don't Need Complex Workflows. Build One in ..." }, { "url": "https://www.itechguides.com/how-to-build-your-first-ai-agent-a-step-by-step-tutorial/", "domain": "itechguides.com", "title": "How to Build Your First AI Agent in Python: Step-by-Step - iTechGuides" }, { "url": "https://www.aibuilderclub.com/blog/how-to-build-ai-agent-from-scratch", "domain": "aibuilderclub.com", "title": "www.aibuilderclub.com › blog › how-to-build-ai-agentHow to Build an AI Agent from Scratch in Python (2026)" }, { "url": "https://lilys.ai/en/notes/separate-dividend-taxation-20251112/build-ai-agents-python", "domain": "lilys.ai", "title": "How to Build AI Agents in Python" }, { "url": "https://freeacademy.ai/blog/build-first-ai-agent-python-30-minutes", "domain": "freeacademy.ai", "title": "freeacademy.ai › blog › build-first-ai-agent-pythonBuild Your First AI Agent in 30 Minutes (Python + LangChain ..." }, { "url": "https://fast.io/resources/build-ai-agent-python/", "domain": "fast.io", "title": "How to Build an AI Agent in Python: Complete G | Fastio" }, { "url": "https://www.udacity.com/blog/how-to-build-an-ai-agent-step-by-step-with-python/", "domain": "udacity.com", "title": "www.udacity.com · blog · how-to-build-an-ai-agent-step-by-stepHow to Build an AI Agent: Step-by-Step with Python - Udacity" }, { "url": "https://www.ema.ai/additional-blogs/addition-blogs/building-ai-agents-python-guide", "domain": "ema.ai", "title": "How to Build AI Agents Using Python: A Step-by-Step Guide - Ema AI" }, { "url": "https://www.gsdcouncil.org/blogs/python-developer-guide-agentic-ai-ai-agents", "domain": "gsdcouncil.org", "title": "The Python Developer's Guide to Agentic AI and AI Agents" } ], "searchQueries": "not exposed" }, { "prompt": 5, "engine": "GEMINI", "run": 1, "askedAt": "2026-10-09T01:28:33.826Z", "text": "1. **CrewAI**\n - Website: [crewai.com](https://www.crewai.com)\n - One of the easiest frameworks for setting up role-based multi-agent systems where tasks are divided among specialized AI personas.\n\n2. **Smolagents**\n - Website: [github.com/huggingface/smolagents](https://github.com/huggingface/smolagents)\n - A lightweight library by Hugging Face that lets you build code-driven agents in just a few lines of plain Python.\n\n3. **Pydantic AI**\n - Website: [ai.pydantic.dev](https://ai.pydantic.dev)\n - Perfect for Python developers who want type-safe, robust agents driven by Pydantic data validation and clean dependency injection.\n\n4. **LangGraph**\n - Website: [langchain-ai.github.io/langgraph](https://langchain-ai.github.io/langgraph)\n - Best for moving beyond simple loops into stateful, graph-based agent workflows with built-in persistence and human-in-the-loop controls.\n\n5. **LlamaIndex**\n - Website: [llamaindex.ai](https://www.llamaindex.ai)\n - The go-to framework if your agent's primary task is querying, reasoning over, and interacting with heavy document stores and enterprise data.\n\n6. **OpenAI Agents SDK**\n - Website: [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python)\n - A lightweight, official SDK designed for fast agent-to-agent handoffs and native tool execution inside the OpenAI ecosystem.", "brands": [ { "name": "CrewAI", "domain": "crewai.com" }, { "name": "Smolagents", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "ai.pydantic.dev" }, { "name": "LangGraph", "domain": "langchain-ai.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "OpenAI Agents SDK", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFEEiW-sZP_pvvlTPUS_tfAjdixM3LKVC-tUOLE8s3l3NBpqqaRBoVff1gj97bvaMwFPIRZ_pKEpaQd804wIbJ0PcBaBqGrF1-4ZNvfO3jVh9TbUcoNe0b-J_5Bm3vwRYucORbKBlCYWbzHMjN6o1QuPUktg7ECpp3dTPNOCnOP9DER7uQ6nHQgN2RNEDI=", "domain": "dev.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEttKoUxv9DX43PDStBTpWqdLilm_ps5XvnIo9TjcCSZDWpgPU7Rsz20ZA2kkgVYBK-BJkCrP4vm_96drh8crIJ3V9z6J-ezsDr4j5WJXks1RVseiCH3MTOVaGyC4aNfqS9fTnuLw845HN28Q==", "domain": "browser-use.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGmlzK8toE6Zkz7D9mjmoP1_P7lAoNVI6HLQmk6BpiviqMJCYQfga4q4ABZqG4UFHB-lpmnyO4hWbTow1HWl_UOzEALi1xZUltuhsAOBuqihOK1eWNGn75jamOv6FFvv0cibg5g46yDPRmcGvXpkuCyzDgbK4Lgx7eSDw==", "domain": "kdnuggets.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHyWPXHiEOFExh_cylc0fKkmLGvrqt_Go9fTNqnkDxezrT8n9mQQImiHabAaH2T_O7mg5U2DKOB3HOv2xQEqavLDbZF5AivE3ZQuc2Zu0eIU0-thjy8hsqkDwAu_zk8XFsx_-2M1iqU2EyhHfcV5f_BcdNdGnN2uvNo494wcnJXozijDExxFNjEqbKi052BsN2-Vv2FFcisMagbCQmVpPlG719XqCDy1kH6R5DfivZBS63ikF7eERZu", "domain": "medium.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQFA4HyUJIYKQ1bJ8S2Om7agrokoVJft-kCVKhNg_5TkshCSER2mKcRh1h0TutLED4nqLJThJwOFZ2T0KgivTAmAO0-E0S20-tjNCXAF4njjtsM_f4yAxYP7xRgPhmikq3LosO6umyk7CNhquiAoZ1x9sCgKqw==", "domain": "ayautomate.com" } ], "searchQueries": [ "easiest python frameworks to build ai agents", "python libraries for ai agents 2025 2026" ] }, { "prompt": 5, "engine": "GEMINI", "run": 2, "askedAt": "2026-10-09T01:29:27.439Z", "text": "Here are 5 of the easiest and most popular Python tools and frameworks for building AI agents, ranked by ease of use and development speed:\n\n1. **CrewAI**\n * [github.com/crewaiinc/crewai](https://github.com/crewaiinc/crewai)\n * The absolute fastest way to spin up role-based, multi-agent prototypes using simple configuration classes.\n\n2. **PydanticAI**\n * [ai.pydantic.dev](https://ai.pydantic.dev)\n * Best for Python developers who want type-safe, predictable agent logic with minimal abstraction and seamless data validation.\n\n3. **LangChain**\n * [github.com/langchain-ai/langchain](https://github.com/langchain-ai/langchain)\n * The most widely adopted framework for quick prototypes, offering thousands of pre-built integrations for tools, models, and memory.\n\n4. **OpenAI Agents SDK**\n * [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python)\n * A lightweight, minimalist toolkit for building agents centered around OpenAI models with native handoffs and guardrails.\n\n5. **LlamaIndex**\n * [github.com/run-llama/llama_index](https://github.com/run-llama/llama_index)\n * Ideal if your agent needs to easily ingest, search, and reason over heavy document stores and unstructured enterprise data.", "brands": [ { "name": "CrewAI", "domain": "github.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "LangChain", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHPBiaZJmc4tF5DhclgZvBAlf-dhgtyf1KdbRnfFCBVJwDybTaLnT8jBkYz5sPzx8CpS03ggoVnKknHGXB1tCnDYT4EtXmp_gdhp8gx8tOlM-Q56QJzQXGeZYj073Q8zZ7Um_9udVo7wkSzKu3cSn_7CbOpMQwogoCORN9kliZtq4cH_8-YFUevDwbQEO0=", "domain": "dev.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQE-Zu1Eue4Ki9fyc6--lcPTWqCJVClqcX6dad28dq63zo6xaBwS0BPLV9A2FMzoXzxKGbk1444-WNHpr-TIzyRL87IvlikLoz5jaMdEWoPnlC9-RixwGPL_J5Oyd1iHSpRMZwMXwf5DzSIVhQFF2GHs", "domain": "agentmail.to" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHeWUell7XUzAD8AA6J0FGMYMQyGn90j-iO9GoOYtER-QYort-s6EkyJO3_QbM5jhSHVmGws52I4Cg2YkOKMxr0vOjO3yCdP3A0zgWz-tU8BJNKaau2ZyDiiwZHsq_BguCeRVCqIURs9YM1s8m4XHpl7B9Hp53kt-apLtqf9Dr0iIbyT1AD794uy_B1JA1vsKNULBuWrFA8v_7h6U-dOhSVoXo=", "domain": "machinelearningmastery.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEE1rmcTINOPA0xxCuZgh6mhcQi5sYUIAwx8_jB11evOC7sqOg7EFd09oLJrfPL_chy-V7J13Xn_X9_2f320HVdbHhd8f3V2OVTil8pXFVqp-wHvs3mXSWy2DxuKv6Sz_SMS0ZnvTtA9JQRprc=", "domain": "langchain.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEkXYZCGXcDuERu2p-hitAJiW_hjxTpFH2fiWOyunefL-Cu48Mn8YHMC8wJMkM25uGiBeXO_9ZT2xyo-OTGFnjCmntx_Q5JLzgJjEq3Z14fM7Mfd33G-We2CfsA-GOsuO8Hs79VG4HE0psy7VQrvV_3b_RQ7A==", "domain": "ayautomate.com" } ], "searchQueries": [ "easiest python frameworks to build AI agents", "best python AI agent frameworks 2026" ] }, { "prompt": 5, "engine": "GEMINI", "run": 3, "askedAt": "2026-10-09T01:30:23.887Z", "text": "1. **CrewAI** \n [github.com/joaomdmoura/crewai](https://github.com/joaomdmoura/crewai) \n The easiest framework to set up if your project maps naturally to a team of specialized, role-based agents working sequentially or collaboratively.\n\n2. **OpenAI Agents SDK** \n [github.com/openai/openai-agents-python](https://github.com/openai/openai-agents-python) \n A lightweight, minimal framework officially designed for seamless agent handoffs, guardrails, and tool execution using OpenAI models.\n\n3. **smolagents** \n [github.com/huggingface/smolagents](https://github.com/huggingface/smolagents) \n Hugging Face’s ultra-minimal library that cuts out complex prompt chains by having the LLM write and execute simple Python code directly.\n\n4. **Pydantic AI** \n [github.com/pydantic/pydantic-ai](https://github.com/pydantic/pydantic-ai) \n An agent framework built around type safety, making it exceptionally easy to build production-ready agents driven by validated Pydantic types and dependencies.\n\n5. **LlamaIndex** \n [github.com/run-llama/llama_index](https://github.com/run-llama/llama_index) \n The best option if your agent needs to ingest, search, and reason over heavy document stores, PDFs, or unstructured enterprise data using its native Workflows API.\n\n6. **LangGraph** \n [github.com/langchain-ai/langgraph](https://github.com/langchain-ai/langgraph) \n The industry standard for total orchestration control, giving developers explicit power over state, loops, and human-in-the-loop approvals in complex workflows.", "brands": [ { "name": "CrewAI", "domain": "github.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "smolagents", "domain": "github.com" }, { "name": "Pydantic AI", "domain": "github.com" }, { "name": "LlamaIndex", "domain": "github.com" }, { "name": "LangGraph", "domain": "github.com" } ], "sources": [ { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQHLRXSPChM1a2nTV0_OwHdWG_4-Vka15ycwOhMfJCYbX4q2kMH6LJw-lrrGHX37e3eFVA5h15zrOIpOhjWYlMxnkE6FJZ25BGLvJTlpgI9t00X-U0X4-rSiolywZ_Lm8uB-t9FB6OrAqtOXPKstsaJupvhvzSdDDIFcPxUIHhWD-YefHZRjbbgK8_Lsv1_fR0FVkQ==", "domain": "zimaspace.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQEPrK3s7VhYTPl4n41bec4GkZszcGbl2Vk0mZSxtzzQAzL_grlBo-0IP1yrc0KIMavNQ4MNK6xR0FyYnH_ibw5nneFNt98GCTf_Z0HyVI9qKbdH2yqaFCtLHTP_dauBDRPKg7ouQnr4DPLHQtM=", "domain": "browser-use.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQETWG6acsm49PcaGfT1ofVl6t_TBk655WPYNEq-uitd3JO4aN1ctNjl-2j_R-C_PgZuF-ZAkL4Xls9stEPcz4BVcChGAOriHzD1AO_hku-SD3IX51GaicFCwjALZ_SdfLCMR6PFmLLp3v72Dqzsp9AvYXbFvwk=", "domain": "ayautomate.com" }, { "url": "https://vertexaisearch.cloud.google.com/grounding-api-redirect/AUZIYQGqQ4_8VdHeZH46Lvzu92oJyPI0SJE5rsz5HvfXT61p_xVffh-Pbwd5yBia1uUUvYbB9VOvGLPLZWl_ezUpRP7RwQ3RX5JrvKTKHCCgzUcXCkeVMAIOxv7lqZuWxibHY6Mu9L5rBSSFIZG2a3MgdwB6n6Oz0519", "domain": "firecrawl.dev" } ], "searchQueries": [ "easiest python frameworks to build AI agents 2025 2026", "best python AI agent libraries" ] }, { "prompt": 5, "engine": "GROK", "run": 1, "askedAt": "2026-10-09T01:28:46.387Z", "text": "**1. CrewAI**, https://crewai.com, Role-based multi-agent teams with minimal code for fastest beginner results. \n**2. OpenAI Agents SDK**, https://platform.openai.com/docs/guides/agents, Fewest abstractions and three simple building blocks for quick OpenAI agents. \n**3. smolagents**, https://github.com/huggingface/smolagents, Lightweight Hugging Face library with tiny core code that's easy to read and run. \n**4. PydanticAI**, https://ai.pydantic.dev, Clean typed Python with validated tools and outputs for reliable simple agents. \n**5. LangChain**, https://python.langchain.com, Massive ecosystem of ready integrations and quick agent prototypes. \n**6. LlamaIndex**, https://www.llamaindex.ai, Simple agents focused on document search and retrieval tasks. \n**7. LangGraph**, https://langchain-ai.github.io/langgraph/, Stateful graphs that stay manageable for growing from easy starts.", "brands": [ { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "smolagents", "domain": "github.com" }, { "name": "PydanticAI", "domain": "ai.pydantic.dev" }, { "name": "LangChain", "domain": "python.langchain.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "LangGraph", "domain": "langchain-ai.github.io" } ], "sources": [ { "url": "https://www.swfte.com/blog/open-source-ai-agent-frameworks", "domain": "swfte.com" }, { "url": "https://fast.io/resources/best-ai-agent-frameworks-for-python/", "domain": "fast.io" }, { "url": "https://buildagentic.ai/frameworks", "domain": "buildagentic.ai" }, { "url": "https://blog.sandbase.ai/best-open-source-ai-agent-frameworks-2026/", "domain": "blog.sandbase.ai" }, { "url": "https://awesome-python.com/categories/ai-and-agents/orchestration/", "domain": "awesome-python.com" }, { "url": "https://www.ayautomate.com/blog/best-python-ai-agent-frameworks", "domain": "ayautomate.com" }, { "url": "https://uvik.net/blog/python-ai-agent-frameworks/", "domain": "uvik.net" }, { "url": "https://theexpertranking.com/developers/best-ai-agent-frameworks/", "domain": "theexpertranking.com" }, { "url": "https://forfrontend.com/best-ai-agent-framework-for-python/", "domain": "forfrontend.com" }, { "url": "https://www.analyticsinsight.net/artificial-intelligence/top-python-frameworks-for-building-autonomous-ai-agents-in-2026", "domain": "analyticsinsight.net" }, { "url": "https://awesome-python.com/categories/ai-and-agents/", "domain": "awesome-python.com" }, { "url": "https://www.kdnuggets.com/7-python-frameworks-for-orchestrating-local-ai-agents", "domain": "kdnuggets.com" }, { "url": "https://intelligenttools.co/blog/best-ai-agents", "domain": "intelligenttools.co" }, { "url": "https://forfrontend.com/best-ai-agent-frameworks/", "domain": "forfrontend.com" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://agentspan.ai/blogs/best-ai-agent-frameworks-2026/", "domain": "agentspan.ai" }, { "url": "https://dev.to/thedailyagent/7-best-python-frameworks-for-building-ai-agents-in-2026-21b", "domain": "dev.to" }, { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" } ], "searchQueries": [ "easiest Python libraries frameworks for building AI agents 2026", "best Python tools for AI agents October 2026" ] }, { "prompt": 5, "engine": "GROK", "run": 2, "askedAt": "2026-10-09T01:29:43.762Z", "text": "**1. LangGraph** \nhttps://www.langchain.com/langgraph \nTop choice in 2026 for stateful, production-grade AI agents with persistence, branching, and human-in-the-loop support.[[1]](https://buildagentic.ai/frameworks)\n\n**2. CrewAI** \nhttps://crewai.com \nFastest way to prototype role-based multi-agent teams with minimal code and high-level abstractions.[[2]](https://uvik.net/blog/python-ai-agent-frameworks/)\n\n**3. OpenAI Agents SDK** \nhttps://platform.openai.com/docs/guides/agents \nSimplest starting point for OpenAI-centric agents with built-in tool calling, handoffs, and sessions.[[3]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**4. Pydantic AI** \nhttps://docs.pydantic.dev/ \nExcellent type-safe Python experience with validated tools, structured outputs, and any model provider.[[4]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**5. smolagents** \nhttps://huggingface.co/docs/smolagents \nLightweight Hugging Face framework ideal for minimal-code, code-writing agents that run in sandboxes.[[4]](https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026)\n\n**6. Google ADK** \nhttps://developers.google.com/vertex-ai/generative-ai/docs/agent-builder \nStrong polyglot option optimized for Gemini with workflow and graph-based agent orchestration.[[3]](https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026)\n\n**7. LlamaIndex** \nhttps://www.llamaindex.ai \nBest for retrieval-augmented agents that need strong document indexing, RAG, and data connectors.[[1]](https://buildagentic.ai/frameworks)", "brands": [ { "name": "LangGraph", "domain": "langchain.com" }, { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "platform.openai.com" }, { "name": "Pydantic AI", "domain": "docs.pydantic.dev" }, { "name": "smolagents", "domain": "huggingface.co" }, { "name": "Google ADK", "domain": "developers.google.com" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" } ], "sources": [ { "url": "https://buildagentic.ai/frameworks", "domain": "buildagentic.ai" }, { "url": "https://uvik.net/blog/python-ai-agent-frameworks/", "domain": "uvik.net" }, { "url": "https://aitecharchive.com/articles/agentic-ai-frameworks-compared-2026", "domain": "aitecharchive.com" }, { "url": "https://www.kdnuggets.com/10-agentic-ai-frameworks-you-should-know-in-2026", "domain": "kdnuggets.com" } ], "searchQueries": [ "top Python libraries frameworks for building AI agents 2026", "easiest way to build AI agent in Python tools libraries" ] }, { "prompt": 5, "engine": "GROK", "run": 3, "askedAt": "2026-10-09T01:30:39.195Z", "text": "**1. CrewAI** \nhttps://crewai.com \nBest for beginners with role-based multi-agent teams that run in minutes via simple Python code.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)\n\n**2. OpenAI Agents SDK** \nhttps://github.com/openai/openai-agents \nLeast code required for OpenAI-powered agents with built-in handoffs and guardrails.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)\n\n**3. smolagents** \nhttps://github.com/huggingface/smolagents \nLightweight Hugging Face framework ideal for quick code-first agents and easy inspection.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)\n\n**4. PydanticAI** \nhttps://github.com/pydantic/pydantic-ai \nClean, type-safe Python agents with validated tools and outputs for reliable development.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)\n\n**5. LangGraph** \nhttps://langchain-ai.github.io/langgraph/ \nStateful graph-based workflows from LangChain for controllable, production-ready agents.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)\n\n**6. LlamaIndex** \nhttps://www.llamaindex.ai \nStrong for document-aware agents with built-in retrieval and indexing capabilities.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)\n\n**7. LangChain** \nhttps://www.langchain.com \nExtensive ecosystem of integrations for rapid prototyping of agent tools and chains.[[1]](https://forfrontend.com/best-ai-agent-framework-for-python/)", "brands": [ { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI Agents SDK", "domain": "github.com" }, { "name": "smolagents", "domain": "github.com" }, { "name": "PydanticAI", "domain": "github.com" }, { "name": "LangGraph", "domain": "langchain-ai.github.io" }, { "name": "LlamaIndex", "domain": "llamaindex.ai" }, { "name": "LangChain", "domain": "langchain.com" } ], "sources": [ { "url": "https://forfrontend.com/best-ai-agent-framework-for-python/", "domain": "forfrontend.com" } ], "searchQueries": [ "easiest Python libraries frameworks for building AI agents 2026", "best Python tools for AI agents LangChain alternatives" ] }, { "prompt": 5, "engine": "AI_OVERVIEW", "run": 1, "askedAt": "2026-10-10T15:13:43.114Z", "text": "The easiest and most beginner-friendly way to build a functional AI agent in Python is by using **CrewAI** . Unlike complex orchestration frameworks or writing loops from scratch, CrewAI allows you to define an agent's role, goals, and backstory using **plain natural language**.[[1]](https://www.youtube.com/watch?v=-RTgK6qX6A8)Here is a step-by-step guide to building your first AI agent in under 5 minutes.\n\n---\n\n### Step 1: Install the Dependencies\nMake sure you have Python installed. Open your terminal and install the `crewai` library. We will also use standard OpenAI models, so ensure you have your API key handy.bash```\npip install crewai\n``` \nUse code with caution.\n\n### Step 2: Set Your API Key\nSet your OpenAI API key as an environment variable so the framework can connect to the model backend.[[1]](https://www.youtube.com/watch?v=-RTgK6qX6A8)**On Mac/Linux:** bash```\nexport OPENAI_API_KEY=\"your-api-key-here\"\n``` \nUse code with caution.**On Windows (Command Prompt):** cmd```\nset OPENAI_API_KEY=\"your-api-key-here\"\n``` \nUse code with caution.\n\n### Step 3: Write the Python Code\nCreate a file named `agent.py` and add the following code. This script sets up a researcher agent, gives it a specific task, and executes the agentic loop.python```\nfrom crewai import Agent, Task, Crew, Process\n\n# 1. Define the Agent with natural language instructions\nresearcher = Agent(\n role='Senior Tech Researcher',\n goal='Uncover groundbreaking advancements in AI technology',\n backstory='You are a curious tech enthusiast who loves analyzing future trends.',\n verbose=True,\n allow_delegation=False\n)\n\n# 2. Define the Task you want the agent to accomplish\nresearch_task = Task(\n description='Analyze the top 3 trends in AI agents for 2026. Write a summary report.',\n expected_output='A 3-paragraph bulletin article highlighting key trends.',\n agent=researcher\n)\n\n# 3. Form the Crew and execute the loop\ntech_crew = Crew(\n agents=[researcher],\n tasks=[research_task],\n process=Process.sequential\n)\n\n# Kick off the execution\nresult = tech_crew.kickoff()\nprint(\"\\n######################\")\nprint(\"RESULT OF THE AGENT:\")\nprint(######################\\n\")\nprint(result)\n``` \nUse code with caution.\n\n### Step 4: Run Your Agent\nExecute the script from your terminal:bash```\npython agent.py\n``` \nUse code with caution.The agent will automatically read its backstory, understand its objective, handle the prompting internally, and output a clean, formatted report.[[1]](https://www.youtube.com/watch?v=-RTgK6qX6A8)\n\n---\n\n### Alternative Frameworks (Depending on Your Use Case)\nIf your project grows and CrewAI becomes too rigid, consider these popular options based on your goals:[[1]](https://www.youtube.com/watch?v=zOFxHmjIhvY&vl=en-US&t=335)[[2]](https://www.youtube.com/watch?v=-RTgK6qX6A8)| Framework | Best For | Complexity | Why Choose It? |\n|---|---|---|---|\n| **CrewAI** | **Beginners & Multi-Agent Teams** | 🟢 Low | Out-of-the-box prompting structure using natural language. |\n| **Pydantic AI** | **Production-grade Structured Data** | 🟡 Medium | Ensures the agent's responses perfectly match your data models. |\n| **LangGraph** | **Complex, Custom Agent Loops** | 🔴 High | Gives you absolute control over the agent's logic using state machines. |\n\nIf you want to customize this further, let me know:\n\n- What **specific task** do you want your agent to perform?\n- Do you want the agent to **connect to external tools** (like searching Google or writing local files)?\n- Do you prefer using a **free/local model** (like Ollama) instead of paid OpenAI keys?[[1]](https://www.youtube.com/watch?v=bTMPwUgLZf0&t=1600)[[2]](https://www.youtube.com/watch?v=-RTgK6qX6A8)[[3]](https://www.youtube.com/watch?v=ByWCsa8DbF8)[[4]](https://www.youtube.com/watch?v=E4l91XKQSgw)", "brands": [ { "name": "CrewAI", "domain": "crewai.com" }, { "name": "OpenAI", "domain": "openai.com" }, { "name": "Python", "domain": "python.org" }, { "name": "Pydantic AI", "domain": "pydantic.dev" }, { "name": "LangGraph", "domain": "langchain.com" }, { "name": "Google", "domain": "google.com" }, { "name": "Ollama", "domain": "ollama.com" } ], "sources": [ { "url": "https://www.youtube.com/watch?v=bTMPwUgLZf0&t=1600", "domain": "youtube.com", "title": "Build an AI Agent From Scratch in Python - Tutorial for Beginners" }, { "url": "https://www.youtube.com/watch?v=zOFxHmjIhvY&vl=en-US&t=335", "domain": "youtube.com", "title": "Building Your First AI Agent in Python - A Crash Course" }, { "url": "https://www.youtube.com/watch?v=E4l91XKQSgw", "domain": "youtube.com", "title": "How to Build a Local AI Agent With Python (Ollama, LangChain & ..." }, { "url": "https://www.youtube.com/watch?v=-RTgK6qX6A8", "domain": "youtube.com", "title": "How to Build AI Agents in Python - 3 Ways" }, { "url": "https://www.youtube.com/watch?v=ByWCsa8DbF8", "domain": "youtube.com", "title": "Build a Local AI Agent in 10 Minutes using Python" }, { "url": "https://machinelearningmastery.com/building-ai-agents-in-python-with-pydantic-ai/", "domain": "machinelearningmastery.com", "title": "Building AI Agents in Python with Pydantic AI" } ], "searchQueries": "not exposed" } ], "engineCheckedAt": { "AI_OVERVIEW": "2026-10-10T15:13:43.114Z" } }