docs/build/snippets/python/code-samples/agent-invocation-thread-id-py.mdx

<CodeGroup>
    ```python Google
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="google_genai:gemini-3.6-flash",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```

    ```python OpenAI
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="openai:gpt-5.5",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```

    ```python Anthropic
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="anthropic:claude-sonnet-4-6",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```

    ```python OpenRouter
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="openrouter:z-ai/glm-5.2",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```

    ```python Fireworks
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="fireworks:accounts/fireworks/models/glm-5p2",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```

    ```python Baseten
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="baseten:zai-org/GLM-5.2",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```

    ```python Ollama
    from langchain.agents import create_agent
    from langchain_core.utils.uuid import uuid7
    from langgraph.checkpoint.memory import InMemorySaver
    
    agent = create_agent(
        model="ollama:north-mini-code-1.0",
        tools=[],
        checkpointer=InMemorySaver(),
    )
    
    config = {"configurable": {"thread_id": str(uuid7())}}
    
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What's the weather in San Francisco?"}]},
        config=config,
    )
    
    # A follow-up turn on the same conversation: reuse the same thread_id to keep history
    result = agent.invoke(
        {"messages": [{"role": "user", "content": "What about tomorrow?"}]},
        config=config,
    )
    ```
</CodeGroup>