langchain[patch]: Update unit tests to workaround a pydantic 2 issue (#24886)

This will allow our unit tests to pass when using AnyID() with our pydantic models.

libs/langchain/tests/unit_tests/llms/test_fake_chat_model.py

@@ -9,7 +9,7 @@ from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
 from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
 
 from tests.unit_tests.llms.fake_chat_model import GenericFakeChatModel
-from tests.unit_tests.stubs import AnyStr
+from tests.unit_tests.stubs import AnyStr, _AnyIdAIMessage, _AnyIdAIMessageChunk
 
 
 def test_generic_fake_chat_model_invoke() -> None:
@@ -17,11 +17,11 @@ def test_generic_fake_chat_model_invoke() -> None:
     infinite_cycle = cycle([AIMessage(content="hello"), AIMessage(content="goodbye")])
     model = GenericFakeChatModel(messages=infinite_cycle)
     response = model.invoke("meow")
-    assert response == AIMessage(content="hello", id=AnyStr())
+    assert response == _AnyIdAIMessage(content="hello")
     response = model.invoke("kitty")
-    assert response == AIMessage(content="goodbye", id=AnyStr())
+    assert response == _AnyIdAIMessage(content="goodbye")
     response = model.invoke("meow")
-    assert response == AIMessage(content="hello", id=AnyStr())
+    assert response == _AnyIdAIMessage(content="hello")
 
 
 async def test_generic_fake_chat_model_ainvoke() -> None:
@@ -29,11 +29,11 @@ async def test_generic_fake_chat_model_ainvoke() -> None:
     infinite_cycle = cycle([AIMessage(content="hello"), AIMessage(content="goodbye")])
     model = GenericFakeChatModel(messages=infinite_cycle)
     response = await model.ainvoke("meow")
-    assert response == AIMessage(content="hello", id=AnyStr())
+    assert response == _AnyIdAIMessage(content="hello")
     response = await model.ainvoke("kitty")
-    assert response == AIMessage(content="goodbye", id=AnyStr())
+    assert response == _AnyIdAIMessage(content="goodbye")
     response = await model.ainvoke("meow")
-    assert response == AIMessage(content="hello", id=AnyStr())
+    assert response == _AnyIdAIMessage(content="hello")
 
 
 async def test_generic_fake_chat_model_stream() -> None:
@@ -46,16 +46,16 @@ async def test_generic_fake_chat_model_stream() -> None:
     model = GenericFakeChatModel(messages=infinite_cycle)
     chunks = [chunk async for chunk in model.astream("meow")]
     assert chunks == [
-        AIMessageChunk(content="hello", id=AnyStr()),
-        AIMessageChunk(content=" ", id=AnyStr()),
-        AIMessageChunk(content="goodbye", id=AnyStr()),
+        _AnyIdAIMessageChunk(content="hello"),
+        _AnyIdAIMessageChunk(content=" "),
+        _AnyIdAIMessageChunk(content="goodbye"),
     ]
 
     chunks = [chunk for chunk in model.stream("meow")]
     assert chunks == [
-        AIMessageChunk(content="hello", id=AnyStr()),
-        AIMessageChunk(content=" ", id=AnyStr()),
-        AIMessageChunk(content="goodbye", id=AnyStr()),
+        _AnyIdAIMessageChunk(content="hello"),
+        _AnyIdAIMessageChunk(content=" "),
+        _AnyIdAIMessageChunk(content="goodbye"),
     ]
 
     # Test streaming of additional kwargs.
@@ -136,9 +136,9 @@ async def test_generic_fake_chat_model_astream_log() -> None:
     ]
     final = log_patches[-1]
     assert final.state["streamed_output"] == [
-        AIMessageChunk(content="hello", id=AnyStr()),
-        AIMessageChunk(content=" ", id=AnyStr()),
-        AIMessageChunk(content="goodbye", id=AnyStr()),
+        _AnyIdAIMessageChunk(content="hello"),
+        _AnyIdAIMessageChunk(content=" "),
+        _AnyIdAIMessageChunk(content="goodbye"),
     ]
 
 
@@ -186,8 +186,8 @@ async def test_callback_handlers() -> None:
     # New model
     results = list(model.stream("meow", {"callbacks": [MyCustomAsyncHandler(tokens)]}))
     assert results == [
-        AIMessageChunk(content="hello", id=AnyStr()),
-        AIMessageChunk(content=" ", id=AnyStr()),
-        AIMessageChunk(content="goodbye", id=AnyStr()),
+        _AnyIdAIMessageChunk(content="hello"),
+        _AnyIdAIMessageChunk(content=" "),
+        _AnyIdAIMessageChunk(content="goodbye"),
     ]
     assert tokens == ["hello", " ", "goodbye"]

libs/langchain/tests/unit_tests/stubs.py

@@ -1,6 +1,44 @@
 from typing import Any
 
+from langchain_core.documents import Document
+from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage
+
 
 class AnyStr(str):
     def __eq__(self, other: Any) -> bool:
         return isinstance(other, str)
+
+
+# The code below creates version of pydantic models
+# that will work in unit tests with AnyStr as id field
+# Please note that the `id` field is assigned AFTER the model is created
+# to workaround an issue with pydantic ignoring the __eq__ method on
+# subclassed strings.
+
+
+def _AnyIdDocument(**kwargs: Any) -> Document:
+    """Create a document with an id field."""
+    message = Document(**kwargs)
+    message.id = AnyStr()
+    return message
+
+
+def _AnyIdAIMessage(**kwargs: Any) -> AIMessage:
+    """Create ai message with an any id field."""
+    message = AIMessage(**kwargs)
+    message.id = AnyStr()
+    return message
+
+
+def _AnyIdAIMessageChunk(**kwargs: Any) -> AIMessageChunk:
+    """Create ai message with an any id field."""
+    message = AIMessageChunk(**kwargs)
+    message.id = AnyStr()
+    return message
+
+
+def _AnyIdHumanMessage(**kwargs: Any) -> HumanMessage:
+    """Create a human with an any id field."""
+    message = HumanMessage(**kwargs)
+    message.id = AnyStr()
+    return message