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https://github.com/hwchase17/langchain.git
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fbfed65fb1
```python
class UsageMetadata(TypedDict):
"""Usage metadata for a message, such as token counts.
Attributes:
input_tokens: (int) count of input (or prompt) tokens
output_tokens: (int) count of output (or completion) tokens
total_tokens: (int) total token count
"""
input_tokens: int
output_tokens: int
total_tokens: int
```
```python
class AIMessage(BaseMessage):
...
usage_metadata: Optional[UsageMetadata] = None
"""If provided, token usage information associated with the message."""
...
```
45 lines
1.3 KiB
Python
45 lines
1.3 KiB
Python
"""Standard LangChain interface tests"""
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from typing import Type
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import pytest
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from langchain_core.language_models import BaseChatModel
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from langchain_standard_tests.integration_tests import ChatModelIntegrationTests
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from langchain_fireworks import ChatFireworks
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class TestFireworksStandard(ChatModelIntegrationTests):
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@pytest.fixture
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def chat_model_class(self) -> Type[BaseChatModel]:
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return ChatFireworks
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@pytest.fixture
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def chat_model_params(self) -> dict:
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return {
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"model": "accounts/fireworks/models/firefunction-v1",
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"temperature": 0,
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}
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@pytest.mark.xfail(reason="Not implemented.")
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def test_usage_metadata(
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self,
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chat_model_class: Type[BaseChatModel],
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chat_model_params: dict,
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) -> None:
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super().test_usage_metadata(
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chat_model_class,
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chat_model_params,
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)
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@pytest.mark.xfail(reason="Not yet implemented.")
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def test_tool_message_histories_list_content(
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self,
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chat_model_class: Type[BaseChatModel],
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chat_model_params: dict,
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chat_model_has_tool_calling: bool,
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) -> None:
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super().test_tool_message_histories_list_content(
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chat_model_class, chat_model_params, chat_model_has_tool_calling
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)
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