mirror of
https://github.com/Mintplex-Labs/langchain-python.git
synced 2026-08-26 16:55:38 -04:00
Harrison Chase
d82cbf5e76
Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: Erick Friis <erick@langchain.dev>
144 lines
4.4 KiB
Python
144 lines
4.4 KiB
Python
"""Test for Serializable base class"""
|
|
|
|
import pytest
|
|
from langchain_core.load.dump import dumpd, dumps
|
|
from langchain_core.load.load import load, loads
|
|
from langchain_core.prompts.prompt import PromptTemplate
|
|
|
|
from langchain.chains.llm import LLMChain
|
|
from langchain.llms.openai import OpenAI
|
|
|
|
|
|
class NotSerializable:
|
|
pass
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_loads_openai_llm() -> None:
|
|
llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
|
|
llm_string = dumps(llm)
|
|
llm2 = loads(llm_string, secrets_map={"OPENAI_API_KEY": "hello"})
|
|
|
|
assert llm2 == llm
|
|
assert dumps(llm2) == llm_string
|
|
assert isinstance(llm2, OpenAI)
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_loads_llmchain() -> None:
|
|
llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
|
|
prompt = PromptTemplate.from_template("hello {name}!")
|
|
chain = LLMChain(llm=llm, prompt=prompt)
|
|
chain_string = dumps(chain)
|
|
chain2 = loads(chain_string, secrets_map={"OPENAI_API_KEY": "hello"})
|
|
|
|
assert chain2 == chain
|
|
assert dumps(chain2) == chain_string
|
|
assert isinstance(chain2, LLMChain)
|
|
assert isinstance(chain2.llm, OpenAI)
|
|
assert isinstance(chain2.prompt, PromptTemplate)
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_loads_llmchain_env() -> None:
|
|
import os
|
|
|
|
has_env = "OPENAI_API_KEY" in os.environ
|
|
if not has_env:
|
|
os.environ["OPENAI_API_KEY"] = "env_variable"
|
|
|
|
llm = OpenAI(model="davinci", temperature=0.5)
|
|
prompt = PromptTemplate.from_template("hello {name}!")
|
|
chain = LLMChain(llm=llm, prompt=prompt)
|
|
chain_string = dumps(chain)
|
|
chain2 = loads(chain_string)
|
|
|
|
assert chain2 == chain
|
|
assert dumps(chain2) == chain_string
|
|
assert isinstance(chain2, LLMChain)
|
|
assert isinstance(chain2.llm, OpenAI)
|
|
assert isinstance(chain2.prompt, PromptTemplate)
|
|
|
|
if not has_env:
|
|
del os.environ["OPENAI_API_KEY"]
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_loads_llmchain_with_non_serializable_arg() -> None:
|
|
llm = OpenAI(
|
|
model="davinci",
|
|
temperature=0.5,
|
|
openai_api_key="hello",
|
|
http_client=NotSerializable,
|
|
)
|
|
prompt = PromptTemplate.from_template("hello {name}!")
|
|
chain = LLMChain(llm=llm, prompt=prompt)
|
|
chain_string = dumps(chain, pretty=True)
|
|
with pytest.raises(NotImplementedError):
|
|
loads(chain_string, secrets_map={"OPENAI_API_KEY": "hello"})
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_load_openai_llm() -> None:
|
|
llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
|
|
llm_obj = dumpd(llm)
|
|
llm2 = load(llm_obj, secrets_map={"OPENAI_API_KEY": "hello"})
|
|
|
|
assert llm2 == llm
|
|
assert dumpd(llm2) == llm_obj
|
|
assert isinstance(llm2, OpenAI)
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_load_llmchain() -> None:
|
|
llm = OpenAI(model="davinci", temperature=0.5, openai_api_key="hello")
|
|
prompt = PromptTemplate.from_template("hello {name}!")
|
|
chain = LLMChain(llm=llm, prompt=prompt)
|
|
chain_obj = dumpd(chain)
|
|
chain2 = load(chain_obj, secrets_map={"OPENAI_API_KEY": "hello"})
|
|
|
|
assert chain2 == chain
|
|
assert dumpd(chain2) == chain_obj
|
|
assert isinstance(chain2, LLMChain)
|
|
assert isinstance(chain2.llm, OpenAI)
|
|
assert isinstance(chain2.prompt, PromptTemplate)
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_load_llmchain_env() -> None:
|
|
import os
|
|
|
|
has_env = "OPENAI_API_KEY" in os.environ
|
|
if not has_env:
|
|
os.environ["OPENAI_API_KEY"] = "env_variable"
|
|
|
|
llm = OpenAI(model="davinci", temperature=0.5)
|
|
prompt = PromptTemplate.from_template("hello {name}!")
|
|
chain = LLMChain(llm=llm, prompt=prompt)
|
|
chain_obj = dumpd(chain)
|
|
chain2 = load(chain_obj)
|
|
|
|
assert chain2 == chain
|
|
assert dumpd(chain2) == chain_obj
|
|
assert isinstance(chain2, LLMChain)
|
|
assert isinstance(chain2.llm, OpenAI)
|
|
assert isinstance(chain2.prompt, PromptTemplate)
|
|
|
|
if not has_env:
|
|
del os.environ["OPENAI_API_KEY"]
|
|
|
|
|
|
@pytest.mark.requires("openai")
|
|
def test_load_llmchain_with_non_serializable_arg() -> None:
|
|
llm = OpenAI(
|
|
model="davinci",
|
|
temperature=0.5,
|
|
openai_api_key="hello",
|
|
http_client=NotSerializable,
|
|
)
|
|
prompt = PromptTemplate.from_template("hello {name}!")
|
|
chain = LLMChain(llm=llm, prompt=prompt)
|
|
chain_obj = dumpd(chain)
|
|
with pytest.raises(NotImplementedError):
|
|
load(chain_obj, secrets_map={"OPENAI_API_KEY": "hello"})
|