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

256 lines
8.0 KiB
Python

"""Test for Serializable base class"""
import json
import os
from typing import Any, Dict, List
from unittest.mock import patch
import pytest
from langchain.chains.llm import LLMChain
from langchain_core.load.dump import dumps
from langchain_core.load.serializable import Serializable
from langchain_core.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.pydantic_v1 import Field, root_validator
from langchain_core.tracers.langchain import LangChainTracer
class Person(Serializable):
secret: str
you_can_see_me: str = "hello"
@classmethod
def is_lc_serializable(cls) -> bool:
return True
@property
def lc_secrets(self) -> Dict[str, str]:
return {"secret": "SECRET"}
@property
def lc_attributes(self) -> Dict[str, str]:
return {"you_can_see_me": self.you_can_see_me}
class SpecialPerson(Person):
another_secret: str
another_visible: str = "bye"
@classmethod
def get_lc_namespace(cls) -> List[str]:
return ["my", "special", "namespace"]
# Gets merged with parent class's secrets
@property
def lc_secrets(self) -> Dict[str, str]:
return {"another_secret": "ANOTHER_SECRET"}
# Gets merged with parent class's attributes
@property
def lc_attributes(self) -> Dict[str, str]:
return {"another_visible": self.another_visible}
class NotSerializable:
pass
def test_person(snapshot: Any) -> None:
p = Person(secret="hello")
assert dumps(p, pretty=True) == snapshot
sp = SpecialPerson(another_secret="Wooo", secret="Hmm")
assert dumps(sp, pretty=True) == snapshot
assert Person.lc_id() == ["tests", "unit_tests", "load", "test_dump", "Person"]
assert SpecialPerson.lc_id() == ["my", "special", "namespace", "SpecialPerson"]
def test_typeerror() -> None:
assert (
dumps({(1, 2): 3})
== """{"lc": 1, "type": "not_implemented", "id": ["builtins", "dict"], "repr": "{(1, 2): 3}"}""" # noqa: E501
)
@pytest.mark.requires("openai")
def test_serialize_openai_llm(snapshot: Any) -> None:
from langchain_community.llms.openai import OpenAI
with patch.dict(os.environ, {"LANGCHAIN_API_KEY": "test-api-key"}):
llm = OpenAI( # type: ignore[call-arg]
model="davinci",
temperature=0.5,
openai_api_key="hello",
# This is excluded from serialization
callbacks=[LangChainTracer()],
)
llm.temperature = 0.7 # this is reflected in serialization
assert dumps(llm, pretty=True) == snapshot
@pytest.mark.requires("openai")
def test_serialize_llmchain(snapshot: Any) -> None:
from langchain_community.llms.openai import OpenAI
llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello") # type: ignore[call-arg]
prompt = PromptTemplate.from_template("hello {name}!")
chain = LLMChain(llm=llm, prompt=prompt)
assert dumps(chain, pretty=True) == snapshot
@pytest.mark.requires("openai")
def test_serialize_llmchain_env() -> None:
from langchain_community.llms.openai import OpenAI
llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello") # type: ignore[call-arg]
prompt = PromptTemplate.from_template("hello {name}!")
chain = LLMChain(llm=llm, prompt=prompt)
import os
has_env = "OPENAI_API_KEY" in os.environ
if not has_env:
os.environ["OPENAI_API_KEY"] = "env_variable"
llm_2 = OpenAI(model="davinci", temperature=0.5) # type: ignore[call-arg]
prompt_2 = PromptTemplate.from_template("hello {name}!")
chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
assert dumps(chain_2, pretty=True) == dumps(chain, pretty=True)
if not has_env:
del os.environ["OPENAI_API_KEY"]
@pytest.mark.requires("openai")
def test_serialize_llmchain_chat(snapshot: Any) -> None:
from langchain_community.chat_models.openai import ChatOpenAI
llm = ChatOpenAI(model="davinci", temperature=0.5, openai_api_key="hello") # type: ignore[call-arg]
prompt = ChatPromptTemplate.from_messages(
[HumanMessagePromptTemplate.from_template("hello {name}!")]
)
chain = LLMChain(llm=llm, prompt=prompt)
assert dumps(chain, pretty=True) == snapshot
import os
has_env = "OPENAI_API_KEY" in os.environ
if not has_env:
os.environ["OPENAI_API_KEY"] = "env_variable"
llm_2 = ChatOpenAI(model="davinci", temperature=0.5) # type: ignore[call-arg]
prompt_2 = ChatPromptTemplate.from_messages(
[HumanMessagePromptTemplate.from_template("hello {name}!")]
)
chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
assert dumps(chain_2, pretty=True) == dumps(chain, pretty=True)
if not has_env:
del os.environ["OPENAI_API_KEY"]
@pytest.mark.requires("openai")
def test_serialize_llmchain_with_non_serializable_arg(snapshot: Any) -> None:
from langchain_community.llms.openai import OpenAI
llm = OpenAI( # type: ignore[call-arg]
model="davinci",
temperature=0.5,
openai_api_key="hello",
client=NotSerializable,
)
prompt = PromptTemplate.from_template("hello {name}!")
chain = LLMChain(llm=llm, prompt=prompt)
assert dumps(chain, pretty=True) == snapshot
def test_person_with_kwargs(snapshot: Any) -> None:
person = Person(secret="hello")
assert dumps(person, separators=(",", ":")) == snapshot
def test_person_with_invalid_kwargs() -> None:
person = Person(secret="hello")
with pytest.raises(TypeError):
dumps(person, invalid_kwarg="hello")
class TestClass(Serializable):
my_favorite_secret: str = Field(alias="my_favorite_secret_alias")
my_other_secret: str = Field()
class Config:
"""Configuration for this pydantic object."""
allow_population_by_field_name = True
@root_validator(pre=True)
def get_from_env(cls, values: Dict) -> Dict:
"""Get the values from the environment."""
if "my_favorite_secret" not in values:
values["my_favorite_secret"] = os.getenv("MY_FAVORITE_SECRET")
if "my_other_secret" not in values:
values["my_other_secret"] = os.getenv("MY_OTHER_SECRET")
return values
@classmethod
def is_lc_serializable(cls) -> bool:
return True
@classmethod
def get_lc_namespace(cls) -> List[str]:
return ["my", "special", "namespace"]
@property
def lc_secrets(self) -> Dict[str, str]:
return {
"my_favorite_secret": "MY_FAVORITE_SECRET",
"my_other_secret": "MY_OTHER_SECRET",
}
def test_aliases_hidden() -> None:
test_class = TestClass(my_favorite_secret="hello", my_other_secret="world") # type: ignore[call-arg]
dumped = json.loads(dumps(test_class, pretty=True))
expected_dump = {
"lc": 1,
"type": "constructor",
"id": ["my", "special", "namespace", "TestClass"],
"kwargs": {
"my_favorite_secret": {
"lc": 1,
"type": "secret",
"id": ["MY_FAVORITE_SECRET"],
},
"my_other_secret": {"lc": 1, "type": "secret", "id": ["MY_OTHER_SECRET"]},
},
}
assert dumped == expected_dump
# Check while patching the os environment
with patch.dict(
os.environ, {"MY_FAVORITE_SECRET": "hello", "MY_OTHER_SECRET": "world"}
):
test_class = TestClass() # type: ignore[call-arg]
dumped = json.loads(dumps(test_class, pretty=True))
# Check by alias
test_class = TestClass(my_favorite_secret_alias="hello", my_other_secret="world") # type: ignore[call-arg]
dumped = json.loads(dumps(test_class, pretty=True))
expected_dump = {
"lc": 1,
"type": "constructor",
"id": ["my", "special", "namespace", "TestClass"],
"kwargs": {
"my_favorite_secret": {
"lc": 1,
"type": "secret",
"id": ["MY_FAVORITE_SECRET"],
},
"my_other_secret": {"lc": 1, "type": "secret", "id": ["MY_OTHER_SECRET"]},
},
}
assert dumped == expected_dump