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Lang Graph – Syllabus
Lang Graph Syllabus (1) Lang Graph Overview (2) Get Started Installation Quickstart Local Servers Changelog Thinking In LangGraph Workflows + Agents (3) Capabilities Persistence Checkpointers Stores Fault Tolerance Event Streaming Streaming Interrupts Time Travell Memory Subgraphs (4) Production Application Structure Test Backward Compatibility LangSmith Studio Agent Chat UI Deployment LangSmith Observability (5) Frontend Overview Graph Execution Custom Stream Channels (6) LangGraph APIs Graph API Functional API Studio
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Python Library: “os”
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Python Library : “getpass”
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Agentic AI Use Case -1: How to integrate LangGraph (functional API) with AutoGen, CrewAI, and other frameworks .
How to integrate LangGraph (functional API) with AutoGen, CrewAI, and other frameworks . %pip install autogen langgraph import getpass import os def _set_env(var: str): if not os.environ.get(var): os.environ[var] = getpass.getpass(f"{var}") _set_env("OPENAI_API_KEY") import autogen import os config_list =[{"model": "gpt-40", "api_key": os.environ["OPENAI_API_KEY"]}] llm_config = { "timeout": 600, "cache_seed":42, "config_list":config_list, "temperature": 0 } autogen_agent = autogen.AssistantAgent( name = "assistant", llm_config = llm_config, ) from langchain_core.messages import convert_t0_openai_message, BaseMessage from langgrapg.func import entrypoint , task from langgraph.graph import add_messages from langgraph.checkpoint.memory import InMemorySaver @task def call_autogen_agent(messages: list[BaseMessage]): # Convert To An openai-style Messages messages = convert_to_openai_messages(messages) response = user_proxy.initiate_chat( autogen_agent, message = messages[-1], #
