AI Agents in Python

🚀 AI Agents in Python

Agentic frameworks are accelerating how we design and deploy autonomous systems.

🤖 What are these AI agent frameworks for? Imagine you want to create an “intelligent agent”:

• a program that thinks, decides, and acts on its own to help you perform tasks.
• These frameworks are toolboxes that make it easier to build these types of agents without having to program everything from scratch.

🧠 In summary: These frameworks allow you to create programs that think and act on their own, such as:

• An assistant that reads documents and summarizes everything for you
• A bot that writes code and tests it
• An agent that searches for information and answers you
• A team of agents that divide tasks among themselves Without these tools, you would have to program everything from scratch… and it would take forever.

Some examples

• LangChain – Broad integrations and agent module https://github.com/langchain-ai/langchain
• Microsoft AutoGen – Multi-agent collaboration and dynamic flows https://github.com/microsoft/autogen
• CrewAI – Lightweight, fast, and oriented towards collaborative intelligence https://github.com/crewAIInc/crewAI
• Haystack (Deepset) – Ideal for RAG and production applications https://github.com/deepset-ai/haystack
• SmolAgents (Hugging Face) – Minimalist and efficient for code agents https://github.com/huggingface/smolagents
• LangGraph – Orchestration of long-running agents https://github.com/langchain-ai/langgraph
• OpenAI Agents SDK – Multi-agent workflows with traceability https://github.com/openai/openai-agents-python

More information at the link 👇

Top 7 Python Frameworks for AI Agents - KDnuggets

Design, test, and deploy multi-agent systems in hours using the powerful agentic frameworks.

www.kdnuggets.com ↗