fix: core: Include in json output also fields set outside the constructor (#21342)

libs/core/langchain_core/load/serializable.py

@@ -12,7 +12,7 @@ from typing import (
 
 from typing_extensions import NotRequired
 
-from langchain_core.pydantic_v1 import BaseModel, PrivateAttr
+from langchain_core.pydantic_v1 import BaseModel
 
 
 class BaseSerialized(TypedDict):
@@ -114,12 +114,6 @@ class Serializable(BaseModel, ABC):
             if (k not in self.__fields__ or try_neq_default(v, k, self))
         ]
 
-    _lc_kwargs = PrivateAttr(default_factory=dict)
-
-    def __init__(self, **kwargs: Any) -> None:
-        super().__init__(**kwargs)
-        self._lc_kwargs = kwargs
-
     def to_json(self) -> Union[SerializedConstructor, SerializedNotImplemented]:
         if not self.is_lc_serializable():
             return self.to_json_not_implemented()
@@ -128,8 +122,9 @@ class Serializable(BaseModel, ABC):
         # Get latest values for kwargs if there is an attribute with same name
         lc_kwargs = {
             k: getattr(self, k, v)
-            for k, v in self._lc_kwargs.items()
+            for k, v in self
             if not (self.__exclude_fields__ or {}).get(k, False)  # type: ignore
+            and _is_field_useful(self, k, v)
         }
 
         # Merge the lc_secrets and lc_attributes from every class in the MRO
@@ -186,6 +181,23 @@ class Serializable(BaseModel, ABC):
         return to_json_not_implemented(self)
 
 
+def _is_field_useful(inst: Serializable, key: str, value: Any) -> bool:
+    """Check if a field is useful as a constructor argument.
+
+    Args:
+        inst: The instance.
+        key: The key.
+        value: The value.
+
+    Returns:
+        Whether the field is useful.
+    """
+    field = inst.__fields__.get(key)
+    if not field:
+        return False
+    return field.required is True or value or field.get_default() != value
+
+
 def _replace_secrets(
     root: Dict[Any, Any], secrets_map: Dict[str, str]
 ) -> Dict[Any, Any]:

libs/core/tests/unit_tests/conftest.py

@@ -1,9 +1,11 @@
 """Configuration for unit tests."""
 from importlib import util
 from typing import Dict, Sequence
+from uuid import UUID
 
 import pytest
 from pytest import Config, Function, Parser
+from pytest_mock import MockerFixture
 
 
 def pytest_addoption(parser: Parser) -> None:
@@ -85,3 +87,11 @@ def pytest_collection_modifyitems(config: Config, items: Sequence[Function]) ->
                 item.add_marker(
                     pytest.mark.skip(reason="Skipping not an extended test.")
                 )
+
+
+@pytest.fixture()
+def deterministic_uuids(mocker: MockerFixture) -> MockerFixture:
+    side_effect = (
+        UUID(f"00000000-0000-4000-8000-{i:012}", version=4) for i in range(10000)
+    )
+    return mocker.patch("uuid.uuid4", side_effect=side_effect)

libs/core/tests/unit_tests/messages/test_ai.py

@@ -21,6 +21,7 @@ def test_serdes_message() -> None:
         "type": "constructor",
         "id": ["langchain", "schema", "messages", "AIMessage"],
         "kwargs": {
+            "type": "ai",
             "content": [{"text": "blah", "type": "text"}],
             "tool_calls": [{"name": "foo", "args": {"bar": 1}, "id": "baz"}],
             "invalid_tool_calls": [
@@ -46,6 +47,7 @@ def test_serdes_message_chunk() -> None:
         "type": "constructor",
         "id": ["langchain", "schema", "messages", "AIMessageChunk"],
         "kwargs": {
+            "type": "AIMessageChunk",
             "content": [{"text": "blah", "type": "text"}],
             "tool_calls": [{"name": "foo", "args": {"bar": 1}, "id": "baz"}],
             "invalid_tool_calls": [

libs/core/tests/unit_tests/runnables/__snapshots__/test_fallbacks.ambr

@@ -74,7 +74,6 @@
           ]
         }
       },
-      "middle": [],
       "last": {
         "lc": 1,
         "type": "constructor",
@@ -109,8 +108,7 @@
                     "buz"
                   ],
                   "template": "what did baz say to {buz}",
-                  "template_format": "f-string",
+                  "template_format": "f-string"
-                  "partial_variables": {}
                 },
                 "name": "PromptTemplate",
                 "graph": {
@@ -151,7 +149,6 @@
                   ]
                 }
               },
-              "middle": [],
               "last": {
                 "lc": 1,
                 "type": "not_implemented",
@@ -200,8 +197,7 @@
                     }
                   ]
                 }
-              },
+              }
-              "name": null
             },
             "name": "RunnableSequence",
             "graph": {
@@ -284,8 +280,7 @@
                       "buz"
                     ],
                     "template": "what did baz say to {buz}",
-                    "template_format": "f-string",
+                    "template_format": "f-string"
-                    "partial_variables": {}
                   },
                   "name": "PromptTemplate",
                   "graph": {
@@ -326,7 +321,6 @@
                     ]
                   }
                 },
-                "middle": [],
                 "last": {
                   "lc": 1,
                   "type": "not_implemented",
@@ -375,8 +369,7 @@
                       }
                     ]
                   }
-                },
+                }
-                "name": null
               },
               "name": "RunnableSequence",
               "graph": {
@@ -445,8 +438,7 @@
               ],
               "repr": "<class 'Exception'>"
             }
-          ],
+          ]
-          "exception_key": null
         },
         "name": "RunnableWithFallbacks",
         "graph": {
@@ -486,8 +478,7 @@
             }
           ]
         }
-      },
+      }
-      "name": null
     },
     "name": "RunnableSequence",
     "graph": {
@@ -579,11 +570,7 @@
                 "runnable",
                 "RunnablePassthrough"
               ],
-              "kwargs": {
+              "kwargs": {},
-                "func": null,
-                "afunc": null,
-                "input_type": null
-              },
               "name": "RunnablePassthrough",
               "graph": {
                 "nodes": [
@@ -664,7 +651,6 @@
           ]
         }
       },
-      "middle": [],
       "last": {
         "lc": 1,
         "type": "constructor",
@@ -750,8 +736,7 @@
             }
           ]
         }
-      },
+      }
-      "name": null
     },
     "name": "RunnableSequence",
     "graph": {
@@ -933,8 +918,7 @@
           ],
           "repr": "<class 'Exception'>"
         }
-      ],
+      ]
-      "exception_key": null
     },
     "name": "RunnableWithFallbacks",
     "graph": {
@@ -1148,8 +1132,7 @@
           ],
           "repr": "<class 'Exception'>"
         }
-      ],
+      ]
-      "exception_key": null
     },
     "name": "RunnableWithFallbacks",
     "graph": {

libs/core/tests/unit_tests/runnables/test_runnable.py

@@ -48,6 +48,8 @@ from langchain_core.output_parsers import (
     CommaSeparatedListOutputParser,
     StrOutputParser,
 )
+from langchain_core.outputs.chat_generation import ChatGeneration
+from langchain_core.outputs.llm_result import LLMResult
 from langchain_core.prompt_values import ChatPromptValue, StringPromptValue
 from langchain_core.prompts import (
     ChatPromptTemplate,
@@ -111,7 +113,19 @@ class FakeTracer(BaseTracer):
 
     def _replace_message_id(self, maybe_message: Any) -> Any:
         if isinstance(maybe_message, BaseMessage):
-            maybe_message.id = AnyStr()
+            maybe_message.id = str(next(self.uuids_generator))
+        if isinstance(maybe_message, ChatGeneration):
+            maybe_message.message.id = str(next(self.uuids_generator))
+        if isinstance(maybe_message, LLMResult):
+            for i, gen_list in enumerate(maybe_message.generations):
+                for j, gen in enumerate(gen_list):
+                    maybe_message.generations[i][j] = self._replace_message_id(gen)
+        if isinstance(maybe_message, dict):
+            for k, v in maybe_message.items():
+                maybe_message[k] = self._replace_message_id(v)
+        if isinstance(maybe_message, list):
+            for i, v in enumerate(maybe_message):
+                maybe_message[i] = self._replace_message_id(v)
 
         return maybe_message
 
@@ -136,16 +150,8 @@ class FakeTracer(BaseTracer):
                 "child_runs": [self._copy_run(child) for child in run.child_runs],
                 "trace_id": self._replace_uuid(run.trace_id) if run.trace_id else None,
                 "dotted_order": new_dotted_order,
-                "inputs": (
+                "inputs": self._replace_message_id(run.inputs),
-                    {k: self._replace_message_id(v) for k, v in run.inputs.items()}
+                "outputs": self._replace_message_id(run.outputs),
-                    if isinstance(run.inputs, dict)
-                    else run.inputs
-                ),
-                "outputs": (
-                    {k: self._replace_message_id(v) for k, v in run.outputs.items()}
-                    if isinstance(run.outputs, dict)
-                    else run.outputs
-                ),
             }
         )
 
@@ -1939,7 +1945,9 @@ async def test_with_listeners_async(mocker: MockerFixture) -> None:
 
 @freeze_time("2023-01-01")
 def test_prompt_with_chat_model(
-    mocker: MockerFixture, snapshot: SnapshotAssertion
+    mocker: MockerFixture,
+    snapshot: SnapshotAssertion,
+    deterministic_uuids: MockerFixture,
 ) -> None:
     prompt = (
         SystemMessagePromptTemplate.from_template("You are a nice assistant.")
@@ -2043,7 +2051,9 @@ def test_prompt_with_chat_model(
 
 @freeze_time("2023-01-01")
 async def test_prompt_with_chat_model_async(
-    mocker: MockerFixture, snapshot: SnapshotAssertion
+    mocker: MockerFixture,
+    snapshot: SnapshotAssertion,
+    deterministic_uuids: MockerFixture,
 ) -> None:
     prompt = (
         SystemMessagePromptTemplate.from_template("You are a nice assistant.")
@@ -2770,7 +2780,9 @@ async def test_prompt_with_llm_and_async_lambda(
 
 @freeze_time("2023-01-01")
 def test_prompt_with_chat_model_and_parser(
-    mocker: MockerFixture, snapshot: SnapshotAssertion
+    mocker: MockerFixture,
+    snapshot: SnapshotAssertion,
+    deterministic_uuids: MockerFixture,
 ) -> None:
     prompt = (
         SystemMessagePromptTemplate.from_template("You are a nice assistant.")
@@ -2809,7 +2821,9 @@ def test_prompt_with_chat_model_and_parser(
 
 @freeze_time("2023-01-01")
 def test_combining_sequences(
-    mocker: MockerFixture, snapshot: SnapshotAssertion
+    mocker: MockerFixture,
+    snapshot: SnapshotAssertion,
+    deterministic_uuids: MockerFixture,
 ) -> None:
     prompt = (
         SystemMessagePromptTemplate.from_template("You are a nice assistant.")

libs/langchain/tests/unit_tests/load/__snapshots__/test_dump.ambr

@@ -36,13 +36,6 @@
       "SpecialPerson"
     ],
     "kwargs": {
-      "another_secret": {
-        "lc": 1,
-        "type": "secret",
-        "id": [
-          "ANOTHER_SECRET"
-        ]
-      },
       "secret": {
         "lc": 1,
         "type": "secret",
@@ -50,8 +43,15 @@
           "SECRET"
         ]
       },
-      "another_visible": "bye",
+      "you_can_see_me": "hello",
-      "you_can_see_me": "hello"
+      "another_secret": {
+        "lc": 1,
+        "type": "secret",
+        "id": [
+          "ANOTHER_SECRET"
+        ]
+      },
+      "another_visible": "bye"
     }
   }
   '''
@@ -71,6 +71,61 @@
       "LLMChain"
     ],
     "kwargs": {
+      "prompt": {
+        "lc": 1,
+        "type": "constructor",
+        "id": [
+          "langchain",
+          "prompts",
+          "prompt",
+          "PromptTemplate"
+        ],
+        "kwargs": {
+          "input_variables": [
+            "name"
+          ],
+          "template": "hello {name}!",
+          "template_format": "f-string"
+        },
+        "name": "PromptTemplate",
+        "graph": {
+          "nodes": [
+            {
+              "id": 0,
+              "type": "schema",
+              "data": "PromptInput"
+            },
+            {
+              "id": 1,
+              "type": "runnable",
+              "data": {
+                "id": [
+                  "langchain",
+                  "prompts",
+                  "prompt",
+                  "PromptTemplate"
+                ],
+                "name": "PromptTemplate"
+              }
+            },
+            {
+              "id": 2,
+              "type": "schema",
+              "data": "PromptTemplateOutput"
+            }
+          ],
+          "edges": [
+            {
+              "source": 0,
+              "target": 1
+            },
+            {
+              "source": 1,
+              "target": 2
+            }
+          ]
+        }
+      },
       "llm": {
         "lc": 1,
         "type": "constructor",
@@ -81,15 +136,23 @@
           "OpenAI"
         ],
         "kwargs": {
-          "model": "davinci",
+          "model_name": "davinci",
           "temperature": 0.5,
+          "max_tokens": 256,
+          "top_p": 1,
+          "n": 1,
+          "best_of": 1,
           "openai_api_key": {
             "lc": 1,
             "type": "secret",
             "id": [
               "OPENAI_API_KEY"
             ]
-          }
+          },
+          "openai_proxy": "",
+          "batch_size": 20,
+          "max_retries": 2,
+          "disallowed_special": "all"
         },
         "name": "OpenAI",
         "graph": {
@@ -130,30 +193,24 @@
           ]
         }
       },
-      "prompt": {
+      "output_key": "text",
+      "output_parser": {
         "lc": 1,
         "type": "constructor",
         "id": [
           "langchain",
-          "prompts",
+          "schema",
-          "prompt",
+          "output_parser",
-          "PromptTemplate"
+          "StrOutputParser"
         ],
-        "kwargs": {
+        "kwargs": {},
-          "input_variables": [
+        "name": "StrOutputParser",
-            "name"
-          ],
-          "template": "hello {name}!",
-          "template_format": "f-string",
-          "partial_variables": {}
-        },
-        "name": "PromptTemplate",
         "graph": {
           "nodes": [
             {
               "id": 0,
               "type": "schema",
-              "data": "PromptInput"
+              "data": "StrOutputParserInput"
             },
             {
               "id": 1,
@@ -161,17 +218,17 @@
               "data": {
                 "id": [
                   "langchain",
-                  "prompts",
+                  "schema",
-                  "prompt",
+                  "output_parser",
-                  "PromptTemplate"
+                  "StrOutputParser"
                 ],
-                "name": "PromptTemplate"
+                "name": "StrOutputParser"
               }
             },
             {
               "id": 2,
               "type": "schema",
-              "data": "PromptTemplateOutput"
+              "data": "StrOutputParserOutput"
             }
           ],
           "edges": [
@@ -185,7 +242,8 @@
             }
           ]
         }
-      }
+      },
+      "return_final_only": true
     },
     "name": "LLMChain",
     "graph": {
@@ -240,65 +298,6 @@
       "LLMChain"
     ],
     "kwargs": {
-      "llm": {
-        "lc": 1,
-        "type": "constructor",
-        "id": [
-          "langchain",
-          "chat_models",
-          "openai",
-          "ChatOpenAI"
-        ],
-        "kwargs": {
-          "model": "davinci",
-          "temperature": 0.5,
-          "openai_api_key": {
-            "lc": 1,
-            "type": "secret",
-            "id": [
-              "OPENAI_API_KEY"
-            ]
-          }
-        },
-        "name": "ChatOpenAI",
-        "graph": {
-          "nodes": [
-            {
-              "id": 0,
-              "type": "schema",
-              "data": "ChatOpenAIInput"
-            },
-            {
-              "id": 1,
-              "type": "runnable",
-              "data": {
-                "id": [
-                  "langchain",
-                  "chat_models",
-                  "openai",
-                  "ChatOpenAI"
-                ],
-                "name": "ChatOpenAI"
-              }
-            },
-            {
-              "id": 2,
-              "type": "schema",
-              "data": "ChatOpenAIOutput"
-            }
-          ],
-          "edges": [
-            {
-              "source": 0,
-              "target": 1
-            },
-            {
-              "source": 1,
-              "target": 2
-            }
-          ]
-        }
-      },
       "prompt": {
         "lc": 1,
         "type": "constructor",
@@ -337,8 +336,7 @@
                       "name"
                     ],
                     "template": "hello {name}!",
-                    "template_format": "f-string",
+                    "template_format": "f-string"
-                    "partial_variables": {}
                   },
                   "name": "PromptTemplate",
                   "graph": {
@@ -381,8 +379,7 @@
                 }
               }
             }
-          ],
+          ]
-          "partial_variables": {}
         },
         "name": "ChatPromptTemplate",
         "graph": {
@@ -422,7 +419,120 @@
             }
           ]
         }
-      }
+      },
+      "llm": {
+        "lc": 1,
+        "type": "constructor",
+        "id": [
+          "langchain",
+          "chat_models",
+          "openai",
+          "ChatOpenAI"
+        ],
+        "kwargs": {
+          "model_name": "davinci",
+          "temperature": 0.5,
+          "openai_api_key": {
+            "lc": 1,
+            "type": "secret",
+            "id": [
+              "OPENAI_API_KEY"
+            ]
+          },
+          "openai_proxy": "",
+          "max_retries": 2,
+          "n": 1
+        },
+        "name": "ChatOpenAI",
+        "graph": {
+          "nodes": [
+            {
+              "id": 0,
+              "type": "schema",
+              "data": "ChatOpenAIInput"
+            },
+            {
+              "id": 1,
+              "type": "runnable",
+              "data": {
+                "id": [
+                  "langchain",
+                  "chat_models",
+                  "openai",
+                  "ChatOpenAI"
+                ],
+                "name": "ChatOpenAI"
+              }
+            },
+            {
+              "id": 2,
+              "type": "schema",
+              "data": "ChatOpenAIOutput"
+            }
+          ],
+          "edges": [
+            {
+              "source": 0,
+              "target": 1
+            },
+            {
+              "source": 1,
+              "target": 2
+            }
+          ]
+        }
+      },
+      "output_key": "text",
+      "output_parser": {
+        "lc": 1,
+        "type": "constructor",
+        "id": [
+          "langchain",
+          "schema",
+          "output_parser",
+          "StrOutputParser"
+        ],
+        "kwargs": {},
+        "name": "StrOutputParser",
+        "graph": {
+          "nodes": [
+            {
+              "id": 0,
+              "type": "schema",
+              "data": "StrOutputParserInput"
+            },
+            {
+              "id": 1,
+              "type": "runnable",
+              "data": {
+                "id": [
+                  "langchain",
+                  "schema",
+                  "output_parser",
+                  "StrOutputParser"
+                ],
+                "name": "StrOutputParser"
+              }
+            },
+            {
+              "id": 2,
+              "type": "schema",
+              "data": "StrOutputParserOutput"
+            }
+          ],
+          "edges": [
+            {
+              "source": 0,
+              "target": 1
+            },
+            {
+              "source": 1,
+              "target": 2
+            }
+          ]
+        }
+      },
+      "return_final_only": true
     },
     "name": "LLMChain",
     "graph": {
@@ -477,6 +587,61 @@
       "LLMChain"
     ],
     "kwargs": {
+      "prompt": {
+        "lc": 1,
+        "type": "constructor",
+        "id": [
+          "langchain",
+          "prompts",
+          "prompt",
+          "PromptTemplate"
+        ],
+        "kwargs": {
+          "input_variables": [
+            "name"
+          ],
+          "template": "hello {name}!",
+          "template_format": "f-string"
+        },
+        "name": "PromptTemplate",
+        "graph": {
+          "nodes": [
+            {
+              "id": 0,
+              "type": "schema",
+              "data": "PromptInput"
+            },
+            {
+              "id": 1,
+              "type": "runnable",
+              "data": {
+                "id": [
+                  "langchain",
+                  "prompts",
+                  "prompt",
+                  "PromptTemplate"
+                ],
+                "name": "PromptTemplate"
+              }
+            },
+            {
+              "id": 2,
+              "type": "schema",
+              "data": "PromptTemplateOutput"
+            }
+          ],
+          "edges": [
+            {
+              "source": 0,
+              "target": 1
+            },
+            {
+              "source": 1,
+              "target": 2
+            }
+          ]
+        }
+      },
       "llm": {
         "lc": 1,
         "type": "constructor",
@@ -487,15 +652,23 @@
           "OpenAI"
         ],
         "kwargs": {
-          "model": "davinci",
+          "model_name": "davinci",
           "temperature": 0.5,
+          "max_tokens": 256,
+          "top_p": 1,
+          "n": 1,
+          "best_of": 1,
           "openai_api_key": {
             "lc": 1,
             "type": "secret",
             "id": [
               "OPENAI_API_KEY"
             ]
-          }
+          },
+          "openai_proxy": "",
+          "batch_size": 20,
+          "max_retries": 2,
+          "disallowed_special": "all"
         },
         "name": "OpenAI",
         "graph": {
@@ -536,30 +709,24 @@
           ]
         }
       },
-      "prompt": {
+      "output_key": "text",
+      "output_parser": {
         "lc": 1,
         "type": "constructor",
         "id": [
           "langchain",
-          "prompts",
+          "schema",
-          "prompt",
+          "output_parser",
-          "PromptTemplate"
+          "StrOutputParser"
         ],
-        "kwargs": {
+        "kwargs": {},
-          "input_variables": [
+        "name": "StrOutputParser",
-            "name"
-          ],
-          "template": "hello {name}!",
-          "template_format": "f-string",
-          "partial_variables": {}
-        },
-        "name": "PromptTemplate",
         "graph": {
           "nodes": [
             {
               "id": 0,
               "type": "schema",
-              "data": "PromptInput"
+              "data": "StrOutputParserInput"
             },
             {
               "id": 1,
@@ -567,17 +734,17 @@
               "data": {
                 "id": [
                   "langchain",
-                  "prompts",
+                  "schema",
-                  "prompt",
+                  "output_parser",
-                  "PromptTemplate"
+                  "StrOutputParser"
                 ],
-                "name": "PromptTemplate"
+                "name": "StrOutputParser"
               }
             },
             {
               "id": 2,
               "type": "schema",
-              "data": "PromptTemplateOutput"
+              "data": "StrOutputParserOutput"
             }
           ],
           "edges": [
@@ -591,7 +758,8 @@
             }
           ]
         }
-      }
+      },
+      "return_final_only": true
     },
     "name": "LLMChain",
     "graph": {
@@ -646,15 +814,23 @@
       "OpenAI"
     ],
     "kwargs": {
-      "model": "davinci",
+      "model_name": "davinci",
       "temperature": 0.7,
+      "max_tokens": 256,
+      "top_p": 1,
+      "n": 1,
+      "best_of": 1,
       "openai_api_key": {
         "lc": 1,
         "type": "secret",
         "id": [
           "OPENAI_API_KEY"
         ]
-      }
+      },
+      "openai_proxy": "",
+      "batch_size": 20,
+      "max_retries": 2,
+      "disallowed_special": "all"
     },
     "name": "OpenAI",
     "graph": {

libs/langchain/tests/unit_tests/load/test_dump.py

@@ -242,11 +242,6 @@ def test_aliases_hidden() -> None:
                 "type": "secret",
                 "id": ["MY_FAVORITE_SECRET"],
             },
-            "my_favorite_secret_alias": {
-                "lc": 1,
-                "type": "secret",
-                "id": ["MY_FAVORITE_SECRET"],
-            },
             "my_other_secret": {"lc": 1, "type": "secret", "id": ["MY_OTHER_SECRET"]},
         },
     }

libs/langchain/tests/unit_tests/load/test_load.py

@@ -17,7 +17,9 @@ class NotSerializable:
 def test_loads_openai_llm() -> None:
     from langchain_openai import OpenAI
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
+    llm = CommunityOpenAI(
+        model="davinci", temperature=0.5, openai_api_key="hello", top_p=0.8
+    )  # type: ignore[call-arg]
     llm_string = dumps(llm)
     llm2 = loads(llm_string, secrets_map={"OPENAI_API_KEY": "hello"})
 
@@ -31,7 +33,9 @@ def test_loads_openai_llm() -> None:
 def test_loads_llmchain() -> None:
     from langchain_openai import OpenAI
 
-    llm = CommunityOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")  # type: ignore[call-arg]
+    llm = CommunityOpenAI(
+        model="davinci", temperature=0.5, openai_api_key="hello", top_p=0.8
+    )  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     chain_string = dumps(chain)
@@ -54,7 +58,7 @@ def test_loads_llmchain_env() -> None:
     if not has_env:
         os.environ["OPENAI_API_KEY"] = "env_variable"
 
-    llm = OpenAI(model="davinci", temperature=0.5)  # type: ignore[call-arg]
+    llm = OpenAI(model="davinci", temperature=0.5, top_p=0.8)  # type: ignore[call-arg]
     prompt = PromptTemplate.from_template("hello {name}!")
     chain = LLMChain(llm=llm, prompt=prompt)
     chain_string = dumps(chain)