mirror of
https://github.com/hwchase17/langchain
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be9371ca8f
Mirror PR for https://github.com/hwchase17/langchainjs/pull/1696 Secrets passed via environment variables should be present in the serialised chain
143 lines
4.1 KiB
Python
143 lines
4.1 KiB
Python
"""Test for Serializable base class"""
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from typing import Any, Dict
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import pytest
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from langchain.callbacks.tracers.langchain import LangChainTracer
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from langchain.chains.llm import LLMChain
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from langchain.chat_models.openai import ChatOpenAI
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from langchain.llms.openai import OpenAI
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from langchain.load.dump import dumps
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from langchain.load.serializable import Serializable
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from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
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from langchain.prompts.prompt import PromptTemplate
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class Person(Serializable):
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secret: str
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you_can_see_me: str = "hello"
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@property
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def lc_serializable(self) -> bool:
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return True
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@property
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def lc_secrets(self) -> Dict[str, str]:
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return {"secret": "SECRET"}
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@property
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def lc_attributes(self) -> Dict[str, str]:
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return {"you_can_see_me": self.you_can_see_me}
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class SpecialPerson(Person):
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another_secret: str
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another_visible: str = "bye"
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# Gets merged with parent class's secrets
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@property
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def lc_secrets(self) -> Dict[str, str]:
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return {"another_secret": "ANOTHER_SECRET"}
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# Gets merged with parent class's attributes
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@property
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def lc_attributes(self) -> Dict[str, str]:
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return {"another_visible": self.another_visible}
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class NotSerializable:
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pass
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def test_person(snapshot: Any) -> None:
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p = Person(secret="hello")
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assert dumps(p, pretty=True) == snapshot
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sp = SpecialPerson(another_secret="Wooo", secret="Hmm")
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assert dumps(sp, pretty=True) == snapshot
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@pytest.mark.requires("openai")
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def test_serialize_openai_llm(snapshot: Any) -> None:
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llm = OpenAI(
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model="davinci",
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temperature=0.5,
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openai_api_key="hello",
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# This is excluded from serialization
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callbacks=[LangChainTracer()],
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)
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llm.temperature = 0.7 # this is reflected in serialization
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assert dumps(llm, pretty=True) == snapshot
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@pytest.mark.requires("openai")
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def test_serialize_llmchain(snapshot: Any) -> None:
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llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
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prompt = PromptTemplate.from_template("hello {name}!")
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chain = LLMChain(llm=llm, prompt=prompt)
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assert dumps(chain, pretty=True) == snapshot
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@pytest.mark.requires("openai")
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def test_serialize_llmchain_env() -> None:
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llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
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prompt = PromptTemplate.from_template("hello {name}!")
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chain = LLMChain(llm=llm, prompt=prompt)
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import os
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has_env = "OPENAI_API_KEY" in os.environ
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if not has_env:
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os.environ["OPENAI_API_KEY"] = "env_variable"
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llm_2 = OpenAI(model="davinci", temperature=0.5)
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prompt_2 = PromptTemplate.from_template("hello {name}!")
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chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
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assert dumps(chain_2, pretty=True) == dumps(chain, pretty=True)
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if not has_env:
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del os.environ["OPENAI_API_KEY"]
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@pytest.mark.requires("openai")
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def test_serialize_llmchain_chat(snapshot: Any) -> None:
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llm = ChatOpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
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prompt = ChatPromptTemplate.from_messages(
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[HumanMessagePromptTemplate.from_template("hello {name}!")]
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)
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chain = LLMChain(llm=llm, prompt=prompt)
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assert dumps(chain, pretty=True) == snapshot
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import os
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has_env = "OPENAI_API_KEY" in os.environ
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if not has_env:
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os.environ["OPENAI_API_KEY"] = "env_variable"
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llm_2 = ChatOpenAI(model="davinci", temperature=0.5)
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prompt_2 = ChatPromptTemplate.from_messages(
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[HumanMessagePromptTemplate.from_template("hello {name}!")]
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)
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chain_2 = LLMChain(llm=llm_2, prompt=prompt_2)
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assert dumps(chain_2, pretty=True) == dumps(chain, pretty=True)
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if not has_env:
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del os.environ["OPENAI_API_KEY"]
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@pytest.mark.requires("openai")
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def test_serialize_llmchain_with_non_serializable_arg(snapshot: Any) -> None:
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llm = OpenAI(
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model="davinci",
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temperature=0.5,
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openai_api_key="hello",
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client=NotSerializable,
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)
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prompt = PromptTemplate.from_template("hello {name}!")
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chain = LLMChain(llm=llm, prompt=prompt)
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assert dumps(chain, pretty=True) == snapshot
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