LLM_Langgraph_Agents

Langgraph:

1. LangGraph is an orchestration framework for complex agentic systems and is more low-level and controllable than LangChain agents. On the other hand, LangChain provides a standard interface to interact with models and other components, useful for straight-forward chains and retrieval flows.

2. LangGraph is a stateful, orchestration framework that brings added control to agent workflows.

3. Development: Build your applications using LangChain's open-source building blocks, components, and third-party integrations. Use LangGraph to build stateful agents with first-class streaming and human-in-the-loop support.

4. Production: Use LangSmith to inspect, monitor and evaluate your chains, so that you can continuously optimize and deploy with confidence.

5. Deployment: Turn your LangGraph applications into production-ready APIs and Assistants with LangGraph Cloud.

6. https://medium.com/pythoneers/building-ai-agent-systems-with-langgraph-9d85537a6326

Langchain Acadamey

1. https://github.com/langchain-ai/langchain-academy/tree/main
2. https://github.com/langchain-ai/langgraph-101

https://medium.com/@kbdhunga/beginners-guide-to-langgraph-understanding-state-nodes-and-edges-part-1-897e6114fa48

https://medium.com/p/6e4898eb76d8

https://github.com/DhunganaKB/OpenAI-Chat/blob/main/DemoAgent/app.py