standard-tests[patch]: add tests for runnables as tools and streaming usage metadata (#24153)

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ccurme 2024-07-11 18:30:05 -04:00 committed by GitHub
parent d002fa902f
commit cb95198398
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5 changed files with 49 additions and 4 deletions

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@ -33,14 +33,18 @@ class TestAI21J2(BaseTestAI21):
"model": "j2-ultra",
}
@pytest.mark.xfail(reason="Emits AIMessage instead of AIMessageChunk.")
@pytest.mark.xfail(reason="Streaming is not supported for Jurassic models.")
def test_stream(self, model: BaseChatModel) -> None:
super().test_stream(model)
@pytest.mark.xfail(reason="Emits AIMessage instead of AIMessageChunk.")
@pytest.mark.xfail(reason="Streaming is not supported for Jurassic models.")
async def test_astream(self, model: BaseChatModel) -> None:
await super().test_astream(model)
@pytest.mark.xfail(reason="Streaming is not supported for Jurassic models.")
def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
super().test_usage_metadata_streaming(model)
class TestAI21Jamba(BaseTestAI21):
@property

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@ -3,6 +3,7 @@
import os
from typing import Type
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_standard_tests.integration_tests import ChatModelIntegrationTests
@ -30,3 +31,7 @@ class TestOpenAIStandard(ChatModelIntegrationTests):
"azure_endpoint": OPENAI_API_BASE,
"api_key": OPENAI_API_KEY,
}
@pytest.mark.xfail(reason="Not yet supported.")
def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
super().test_usage_metadata_streaming(model)

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@ -18,7 +18,7 @@ class TestOpenAIStandard(ChatModelIntegrationTests):
@property
def chat_model_params(self) -> dict:
return {"model": "gpt-4o"}
return {"model": "gpt-4o", "stream_usage": True}
@property
def supports_image_inputs(self) -> bool:

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@ -23,3 +23,7 @@ class TestTogetherStandard(ChatModelIntegrationTests):
@pytest.mark.xfail(reason=("May not call a tool."))
def test_tool_calling_with_no_arguments(self, model: BaseChatModel) -> None:
super().test_tool_calling_with_no_arguments(model)
@pytest.mark.xfail(reason="Not yet supported.")
def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
super().test_usage_metadata_streaming(model)

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@ -4,7 +4,7 @@ from typing import List, Optional
import httpx
import pytest
from langchain_core.language_models import BaseChatModel
from langchain_core.language_models import BaseChatModel, GenericFakeChatModel
from langchain_core.messages import (
AIMessage,
AIMessageChunk,
@ -14,6 +14,8 @@ from langchain_core.messages import (
SystemMessage,
ToolMessage,
)
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.pydantic_v1 import BaseModel, Field
from langchain_core.tools import tool
@ -129,6 +131,19 @@ class ChatModelIntegrationTests(ChatModelTests):
assert isinstance(result.usage_metadata["output_tokens"], int)
assert isinstance(result.usage_metadata["total_tokens"], int)
def test_usage_metadata_streaming(self, model: BaseChatModel) -> None:
if not self.returns_usage_metadata:
pytest.skip("Not implemented.")
full: Optional[BaseMessageChunk] = None
for chunk in model.stream("Hello"):
assert isinstance(chunk, AIMessageChunk)
full = chunk if full is None else full + chunk
assert isinstance(full, AIMessageChunk)
assert full.usage_metadata is not None
assert isinstance(full.usage_metadata["input_tokens"], int)
assert isinstance(full.usage_metadata["output_tokens"], int)
assert isinstance(full.usage_metadata["total_tokens"], int)
def test_stop_sequence(self, model: BaseChatModel) -> None:
result = model.invoke("hi", stop=["you"])
assert isinstance(result, AIMessage)
@ -171,6 +186,23 @@ class ChatModelIntegrationTests(ChatModelTests):
assert isinstance(full, AIMessage)
_validate_tool_call_message_no_args(full)
def test_bind_runnables_as_tools(self, model: BaseChatModel) -> None:
if not self.has_tool_calling:
pytest.skip("Test requires tool calling.")
prompt = ChatPromptTemplate.from_messages(
[("human", "Hello. Please respond in the style of {answer_style}.")]
)
llm = GenericFakeChatModel(messages=iter(["hello matey"]))
chain = prompt | llm | StrOutputParser()
model_with_tools = model.bind_tools([chain.as_tool()])
query = "Using the tool, ask a Pirate how it would say hello."
result = model_with_tools.invoke(query)
assert isinstance(result, AIMessage)
assert result.tool_calls
tool_call = result.tool_calls[0]
assert tool_call["args"].get("answer_style")
def test_structured_output(self, model: BaseChatModel) -> None:
if not self.has_tool_calling:
pytest.skip("Test requires tool calling.")