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langchain/libs/standard-tests/langchain_standard_tests/integration_tests/chat_models.py

118 lines
4.0 KiB
Python

from abc import ABC, abstractmethod
from typing import Type
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_core.messages import AIMessage, AIMessageChunk
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import tool
class Person(BaseModel):
name: str = Field(..., description="The name of the person.")
age: int = Field(..., description="The age of the person.")
@tool
def my_adder_tool(a: int, b: int) -> int:
"""Takes two integers, a and b, and returns their sum."""
return a + b
class ChatModelIntegrationTests(ABC):
@abstractmethod
@pytest.fixture
def chat_model_class(self) -> Type[BaseChatModel]:
...
@pytest.fixture
def chat_model_params(self) -> dict:
return {}
@pytest.fixture
def chat_model_has_tool_calling(
self, chat_model_class: Type[BaseChatModel]
) -> bool:
return chat_model_class.bind_tools is not BaseChatModel.bind_tools
@pytest.fixture
def chat_model_has_structured_output(
self, chat_model_class: Type[BaseChatModel]
) -> bool:
return (
chat_model_class.with_structured_output
is not BaseChatModel.with_structured_output
)
def test_invoke(
self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
) -> None:
model = chat_model_class(**chat_model_params)
result = model.invoke("Hello")
assert result is not None
assert isinstance(result, AIMessage)
assert isinstance(result.content, str)
assert len(result.content) > 0
async def test_ainvoke(
self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
) -> None:
model = chat_model_class(**chat_model_params)
result = await model.ainvoke("Hello")
assert result is not None
assert isinstance(result, AIMessage)
assert isinstance(result.content, str)
assert len(result.content) > 0
def test_stream(
self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
) -> None:
model = chat_model_class(**chat_model_params)
num_tokens = 0
for token in model.stream("Hello"):
assert token is not None
assert isinstance(token, AIMessageChunk)
assert isinstance(token.content, str)
num_tokens += len(token.content)
assert num_tokens > 0
async def test_astream(
self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
) -> None:
model = chat_model_class(**chat_model_params)
num_tokens = 0
async for token in model.astream("Hello"):
assert token is not None
assert isinstance(token, AIMessageChunk)
assert isinstance(token.content, str)
num_tokens += len(token.content)
assert num_tokens > 0
def test_batch(
self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
) -> None:
model = chat_model_class(**chat_model_params)
batch_results = model.batch(["Hello", "Hey"])
assert batch_results is not None
assert isinstance(batch_results, list)
assert len(batch_results) == 2
for result in batch_results:
assert result is not None
assert isinstance(result, AIMessage)
assert isinstance(result.content, str)
assert len(result.content) > 0
async def test_abatch(
self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
) -> None:
model = chat_model_class(**chat_model_params)
batch_results = await model.abatch(["Hello", "Hey"])
assert batch_results is not None
assert isinstance(batch_results, list)
assert len(batch_results) == 2
for result in batch_results:
assert result is not None
assert isinstance(result, AIMessage)
assert isinstance(result.content, str)
assert len(result.content) > 0