ca00f5aed9
## Description Fixes #33453 `ModelResponse` was defined in `types.py` and included in its `__all__` list, but was not exported from the middleware package's `__init__.py`. This caused `ImportError` when attempting to import it directly from `langchain.agents.middleware`, despite being documented as a public export. ## Changes - Added `ModelResponse` to the import statement in `langchain/agents/middleware/__init__.py` - Added `ModelResponse` to the `__all__` list in `langchain/agents/middleware/__init__.py` - Added comprehensive unit tests in `test_imports.py` to verify the import works correctly ## Issue The original issue reported that the following import failed: ```python from langchain.agents.middleware import ModelResponse # ImportError: cannot import name 'ModelResponse' from 'langchain.agents.middleware' The workaround was to import from the submodule: from langchain.agents.middleware.types import ModelResponse # Workaround Solution After this fix, ModelResponse can be imported directly as documented: from langchain.agents.middleware import ModelResponse # Now works! Testing - ✅ Added 3 unit tests in tests/unit_tests/agents/middleware/test_imports.py - ✅ All tests pass locally: make format, make lint, make test - ✅ Verified ModelResponse is properly exported and importable - ✅ Verified ModelResponse appears in __all__ list Dependencies None. This is a simple export fix with no new dependencies. --------- Co-authored-by: Eugene Yurtsev <eugene@langchain.dev> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
The platform for reliable agents.
LangChain is a framework for building LLM-powered applications. It helps you chain together interoperable components and third-party integrations to simplify AI application development — all while future-proofing decisions as the underlying technology evolves.
pip install langchain
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If you're looking for more advanced customization or agent orchestration, check out LangGraph, our framework for building controllable agent workflows.
Note
Looking for the JS/TS library? Check out LangChain.js.
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LangChain helps developers build applications powered by LLMs through a standard interface for models, embeddings, vector stores, and more.
Use LangChain for:
- Real-time data augmentation. Easily connect LLMs to diverse data sources and external/internal systems, drawing from LangChain’s vast library of integrations with model providers, tools, vector stores, retrievers, and more.
- Model interoperability. Swap models in and out as your engineering team experiments to find the best choice for your application’s needs. As the industry frontier evolves, adapt quickly — LangChain’s abstractions keep you moving without losing momentum.
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While the LangChain framework can be used standalone, it also integrates seamlessly with any LangChain product, giving developers a full suite of tools when building LLM applications.
To improve your LLM application development, pair LangChain with:
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