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126 lines
4.1 KiB
Python
126 lines
4.1 KiB
Python
import os
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from collections.abc import Generator
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import pytest
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from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
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from core.model_runtime.entities.message_entities import (
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AssistantPromptMessage,
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ImagePromptMessageContent,
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PromptMessageTool,
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SystemPromptMessage,
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TextPromptMessageContent,
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UserPromptMessage,
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)
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from core.model_runtime.entities.model_entities import AIModelEntity, ModelType
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from core.model_runtime.errors.validate import CredentialsValidateFailedError
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from core.model_runtime.model_providers.stepfun.llm.llm import StepfunLargeLanguageModel
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def test_validate_credentials():
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model = StepfunLargeLanguageModel()
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with pytest.raises(CredentialsValidateFailedError):
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model.validate_credentials(model="step-1-8k", credentials={"api_key": "invalid_key"})
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model.validate_credentials(model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")})
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def test_invoke_model():
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model = StepfunLargeLanguageModel()
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response = model.invoke(
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model="step-1-8k",
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credentials={"api_key": os.environ.get("STEPFUN_API_KEY")},
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prompt_messages=[UserPromptMessage(content="Hello World!")],
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model_parameters={"temperature": 0.9, "top_p": 0.7},
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stop=["Hi"],
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stream=False,
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user="abc-123",
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)
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assert isinstance(response, LLMResult)
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assert len(response.message.content) > 0
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def test_invoke_stream_model():
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model = StepfunLargeLanguageModel()
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response = model.invoke(
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model="step-1-8k",
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credentials={"api_key": os.environ.get("STEPFUN_API_KEY")},
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prompt_messages=[
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SystemPromptMessage(
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content="You are a helpful AI assistant.",
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),
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UserPromptMessage(content="Hello World!"),
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],
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model_parameters={"temperature": 0.9, "top_p": 0.7},
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stream=True,
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user="abc-123",
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)
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assert isinstance(response, Generator)
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for chunk in response:
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assert isinstance(chunk, LLMResultChunk)
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assert isinstance(chunk.delta, LLMResultChunkDelta)
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assert isinstance(chunk.delta.message, AssistantPromptMessage)
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assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
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def test_get_customizable_model_schema():
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model = StepfunLargeLanguageModel()
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schema = model.get_customizable_model_schema(
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model="step-1-8k", credentials={"api_key": os.environ.get("STEPFUN_API_KEY")}
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)
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assert isinstance(schema, AIModelEntity)
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def test_invoke_chat_model_with_tools():
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model = StepfunLargeLanguageModel()
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result = model.invoke(
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model="step-1-8k",
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credentials={"api_key": os.environ.get("STEPFUN_API_KEY")},
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prompt_messages=[
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SystemPromptMessage(
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content="You are a helpful AI assistant.",
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),
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UserPromptMessage(
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content="what's the weather today in Shanghai?",
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),
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],
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model_parameters={"temperature": 0.9, "max_tokens": 100},
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tools=[
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PromptMessageTool(
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name="get_weather",
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description="Determine weather in my location",
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parameters={
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"type": "object",
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"properties": {
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"location": {"type": "string", "description": "The city and state e.g. San Francisco, CA"},
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"unit": {"type": "string", "enum": ["c", "f"]},
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},
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"required": ["location"],
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},
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),
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PromptMessageTool(
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name="get_stock_price",
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description="Get the current stock price",
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parameters={
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"type": "object",
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"properties": {"symbol": {"type": "string", "description": "The stock symbol"}},
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"required": ["symbol"],
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},
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),
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],
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stream=False,
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user="abc-123",
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)
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assert isinstance(result, LLMResult)
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assert isinstance(result.message, AssistantPromptMessage)
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assert len(result.message.tool_calls) > 0
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