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When using `ProviderStrategy`, `create_agent` unnecessarily sets `strict=True` on tools for all providers. This is only needed for OpenAI / chat completions. Here we unset `strict`. For OpenAI: 1. We set it in `BaseChatOpenAI.bind_tools` (as a convenience to users calling `model.bind_tools` directly) 2. We (redundantly) special-case OpenAI in the `create_agent` factory logic so that things will not break for users who upgrade `langchain` but not `langchain-openai`. Note: payloads for OpenAI are tested here and appear unchanged: https://github.com/langchain-ai/langchain/blob/master/libs/langchain_v1/tests/unit_tests/agents/test_response_format_integration.py Quick test: ```python from langchain.agents import create_agent from langchain.agents.structured_output import ProviderStrategy from pydantic import BaseModel class Weather(BaseModel): temperature: float condition: str def weather_tool(location: str) -> str: """Get the weather at a location.""" return "Sunny and 75 degrees F." for model in [ "anthropic:claude-sonnet-4-6", "openai:gpt-5.4", "google_genai:gemini-3.5-flash", ]: agent = create_agent( model=model, tools=[weather_tool], response_format=ProviderStrategy(Weather), ) result = agent.invoke({ "messages": [{"role": "user", "content": "What's the weather in SF?"}] }) print(result["structured_response"]) ```