Agent Frameworks
Libraries to build the logic of your AI app. They handle chaining steps, memory management, and tool usage.
| Rank | Model | Price | Summary |
|---|---|---|---|
|
1
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Open Source | The Enterprise Standard. v2 cements its dominance with 'Time Travel' debugging, allowing you to rewind agent states, inspect decision forks, and replay failures with different inputs. It is the default choice for cyclic, complex production workflows. | |
|
2
|
Open Source | The Performance King. Rebranded from Phidata, Agno focuses on 'pure Python' simplicity and speed, boasting agent instantiation 5000x faster than LangGraph. Its multimodal-native architecture makes it the top choice for video/audio processing agents. | |
|
3
|
Open Source | The Data Sovereign. While LangGraph focuses on control, Workflows focuses on data. Its event-driven architecture is optimized for RAG-heavy agents, featuring a 'Context API' that maintains perfect memory across massive document retrieval tasks. | |
|
4
|
Open Source | The Type-Safe Bridge. Built by the creators of Pydantic, it brings strict type validation to agent outputs. It effectively eliminates 'malformed JSON' errors by enforcing schema compliance at the generation level, making it the safest choice for banking/fintech. | |
|
5
|
Open Source / Paid | The Orchestrator. The 'Pro' tier now features a visual drag-and-drop builder for defining agent roles (e.g., 'Researcher', 'Writer'). It remains the most accessible framework for building multi-agent 'teams' that mimic human organizational structures. | |
|
6
|
Open Source | The Event Engine. The v0.4 rewrite introduces a fully event-driven architecture, moving away from simple chat loops. It excels at massive simulations where hundreds of agents need to interact asynchronously without blocking each other. | |
|
7
|
Open Source | The Code Native. Unlike others that use JSON for tool calling, Smolagents write and execute Python code directly to perform actions. This 'CodeAgent' paradigm reduces hallucination in complex multi-step reasoning tasks by 30%. | |
|
8
|
Open Source | The Compiler. Less of an agent framework and more of an optimizer. It treats prompts as 'weights' to be trained. It is commonly used *within* other frameworks (like LangGraph) to automatically tune agent instructions for maximum accuracy. | |
|
9
|
Open Source | The Task Master. Built on the Prefect engine, it focuses on observability and 'Task' definitions rather than open-ended chat. It is the preferred choice for agents that must execute rigid business processes with zero deviation. | |
|
10
|
Open Source | The Compliant Choice. An enterprise-grade framework optimized for Llama 3 and Granite models. It features native support for sandboxed code execution and strict privacy boundaries, designed specifically for government and healthcare deployments. |
Just the Highlights
LangGraph v2
The Enterprise Standard. v2 cements its dominance with 'Time Travel' debugging, allowing you to rewind agent states, inspect decision forks, and replay failures with different inputs. It is the default choice for cyclic, complex production workflows.
Agno (formerly Phidata)
The Performance King. Rebranded from Phidata, Agno focuses on 'pure Python' simplicity and speed, boasting agent instantiation 5000x faster than LangGraph. Its multimodal-native architecture makes it the top choice for video/audio processing agents.
LlamaIndex Workflows
The Data Sovereign. While LangGraph focuses on control, Workflows focuses on data. Its event-driven architecture is optimized for RAG-heavy agents, featuring a 'Context API' that maintains perfect memory across massive document retrieval tasks.
PydanticAI
The Type-Safe Bridge. Built by the creators of Pydantic, it brings strict type validation to agent outputs. It effectively eliminates 'malformed JSON' errors by enforcing schema compliance at the generation level, making it the safest choice for banking/fintech.
CrewAI+
The Orchestrator. The 'Pro' tier now features a visual drag-and-drop builder for defining agent roles (e.g., 'Researcher', 'Writer'). It remains the most accessible framework for building multi-agent 'teams' that mimic human organizational structures.
Microsoft AutoGen 0.4
The Event Engine. The v0.4 rewrite introduces a fully event-driven architecture, moving away from simple chat loops. It excels at massive simulations where hundreds of agents need to interact asynchronously without blocking each other.
Smolagents (Hugging Face)
The Code Native. Unlike others that use JSON for tool calling, Smolagents write and execute Python code directly to perform actions. This 'CodeAgent' paradigm reduces hallucination in complex multi-step reasoning tasks by 30%.
DSPy
The Compiler. Less of an agent framework and more of an optimizer. It treats prompts as 'weights' to be trained. It is commonly used *within* other frameworks (like LangGraph) to automatically tune agent instructions for maximum accuracy.
ControlFlow (Prefect)
The Task Master. Built on the Prefect engine, it focuses on observability and 'Task' definitions rather than open-ended chat. It is the preferred choice for agents that must execute rigid business processes with zero deviation.
Bee Agent Framework (IBM)
The Compliant Choice. An enterprise-grade framework optimized for Llama 3 and Granite models. It features native support for sandboxed code execution and strict privacy boundaries, designed specifically for government and healthcare deployments.