INTPYTHON-680 Use random seed when testing ChatOpenAI (#171)

Author: blink1073

libs/langchain-mongodb/tests/integration_tests/test_agent_toolkit.py

@@ -55,9 +55,9 @@ def test_toolkit_response(db):
         CONNECTION_STRING, database=DB_NAME
     )
     if "AZURE_OPENAI_ENDPOINT" in os.environ:
-        llm = AzureChatOpenAI(model="gpt-4o-mini", timeout=60)
+        llm = AzureChatOpenAI(model="gpt-4o-mini", timeout=60, seed=12345)
     else:
-        llm = ChatOpenAI(model="gpt-4o-mini", timeout=60)
+        llm = ChatOpenAI(model="gpt-4o-mini", timeout=60, seed=12345)
 
     toolkit = MongoDBDatabaseToolkit(db=db_wrapper, llm=llm)
 

libs/langchain-mongodb/tests/integration_tests/test_chain_example.py

@@ -122,9 +122,9 @@ def test_chain(
     prompt = ChatPromptTemplate.from_template(template)
 
     if "AZURE_OPENAI_ENDPOINT" in os.environ:
-        model: BaseChatOpenAI = AzureChatOpenAI(model="o4-mini")
+        model: BaseChatOpenAI = AzureChatOpenAI(model="o4-mini", seed=12345)
     else:
-        model = ChatOpenAI()
+        model = ChatOpenAI(seed=12345)
 
     chain = (
         {"context": retriever, "question": RunnablePassthrough()}  # type: ignore

libs/langchain-mongodb/tests/integration_tests/test_graphrag.py

@@ -7,7 +7,7 @@
 from langchain_core.documents import Document
 from langchain_core.language_models.chat_models import BaseChatModel
 from langchain_core.messages import AIMessage
-from langchain_openai import ChatOpenAI
+from langchain_openai import AzureChatOpenAI, ChatOpenAI
 from pymongo import MongoClient
 from pymongo.collection import Collection
 from pymongo.results import BulkWriteResult
@@ -40,7 +40,11 @@ def collection() -> Generator[Collection]:
 def entity_extraction_model() -> BaseChatModel | None:
     """LLM for converting documents into Graph of Entities and Relationships"""
     try:
-        return ChatOpenAI(model="gpt-4o", temperature=0.0, cache=False)
+        if "AZURE_OPENAI_ENDPOINT" in os.environ:
+            return AzureChatOpenAI(
+                model="gpt-4o", temperature=0.0, cache=False, seed=12345
+            )
+        return ChatOpenAI(model="gpt-4o", temperature=0.0, cache=False, seed=12345)
     except Exception:
         pass
     return None

libs/langchain-mongodb/tests/integration_tests/test_retriever_selfquerying.py

@@ -165,8 +165,8 @@ def vectorstore(
 def llm() -> BaseChatOpenAI:
     """Model used for interpreting query."""
     if "AZURE_OPENAI_ENDPOINT" in os.environ:
-        return AzureChatOpenAI(model="gpt-4o", temperature=0.0, cache=False)
-    return ChatOpenAI(model="gpt-4o", temperature=0.0, cache=False)
+        return AzureChatOpenAI(model="gpt-4o", temperature=0.0, cache=False, seed=12345)
+    return ChatOpenAI(model="gpt-4o", temperature=0.0, cache=False, seed=1235)
 
 
 @pytest.fixture

libs/langchain-mongodb/tests/integration_tests/test_retrievers.py

@@ -2,6 +2,7 @@
 from typing import Generator, List
 
 import pytest
+from flaky import flaky  # type:ignore[import-untyped]
 from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from pymongo import MongoClient
@@ -202,6 +203,7 @@ def test_hybrid_retriever_deprecated_top_k(
     assert "New Orleans" in results[0].page_content
 
 
+@flaky(max_runs=5, min_passes=4)
 def test_hybrid_retriever_nested(
     indexed_nested_vectorstore: PatchedMongoDBAtlasVectorSearch,
 ) -> None:

libs/langchain-mongodb/tests/utils.py

@@ -47,10 +47,10 @@ def create_database() -> MongoDBDatabase:
 
 def create_llm() -> BaseChatModel:
     if os.environ.get("AZURE_OPENAI_ENDPOINT"):
-        return AzureChatOpenAI(model="o4-mini", timeout=60, cache=False)
+        return AzureChatOpenAI(model="o4-mini", timeout=60, cache=False, seed=12345)
     if os.environ.get("OPENAI_API_KEY"):
-        return ChatOpenAI(model="gpt-4o-mini", timeout=60, cache=False)
-    return ChatOllama(model="llama3:8b", cache=False)
+        return ChatOpenAI(model="gpt-4o-mini", timeout=60, cache=False, seed=12345)
+    return ChatOllama(model="llama3:8b", cache=False, seed=12345)
 
 
 class PatchedMongoDBAtlasVectorSearch(MongoDBAtlasVectorSearch):