add new provider Solar (#6884)
This commit is contained in:
JuHyung Son
245
api/tests/integration_tests/model_runtime/upstage/test_llm.py
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245
api/tests/integration_tests/model_runtime/upstage/test_llm.py
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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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PromptMessageTool,
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SystemPromptMessage,
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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.__base.large_language_model import LargeLanguageModel
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from core.model_runtime.model_providers.upstage.llm.llm import UpstageLargeLanguageModel
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"""FOR MOCK FIXTURES, DO NOT REMOVE"""
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from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock
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def test_predefined_models():
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model = UpstageLargeLanguageModel()
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model_schemas = model.predefined_models()
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assert len(model_schemas) >= 1
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assert isinstance(model_schemas[0], AIModelEntity)
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@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
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def test_validate_credentials_for_chat_model(setup_openai_mock):
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model = UpstageLargeLanguageModel()
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with pytest.raises(CredentialsValidateFailedError):
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# model name to gpt-3.5-turbo because of mocking
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model.validate_credentials(
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model='gpt-3.5-turbo',
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credentials={
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'upstage_api_key': 'invalid_key'
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}
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)
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model.validate_credentials(
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model='solar-1-mini-chat',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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}
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)
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@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
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def test_invoke_chat_model(setup_openai_mock):
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model = UpstageLargeLanguageModel()
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result = model.invoke(
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model='solar-1-mini-chat',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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},
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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='Hello World!'
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)
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],
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model_parameters={
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'temperature': 0.0,
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'top_p': 1.0,
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'presence_penalty': 0.0,
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'frequency_penalty': 0.0,
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'max_tokens': 10
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},
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stop=['How'],
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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 len(result.message.content) > 0
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@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
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def test_invoke_chat_model_with_tools(setup_openai_mock):
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model = UpstageLargeLanguageModel()
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result = model.invoke(
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model='solar-1-mini-chat',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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},
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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 London?",
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)
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],
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model_parameters={
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'temperature': 0.0,
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'max_tokens': 100
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},
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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": {
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"type": "string",
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"description": "The city and state e.g. San Francisco, CA"
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},
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"unit": {
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"type": "string",
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"enum": [
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"c",
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"f"
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]
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}
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},
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"required": [
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"location"
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]
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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": {
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"symbol": {
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"type": "string",
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"description": "The stock symbol"
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}
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},
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"required": [
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"symbol"
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]
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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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@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
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def test_invoke_stream_chat_model(setup_openai_mock):
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model = UpstageLargeLanguageModel()
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result = model.invoke(
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model='solar-1-mini-chat',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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},
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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='Hello World!'
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)
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],
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model_parameters={
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'temperature': 0.0,
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'max_tokens': 100
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},
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stream=True,
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user="abc-123"
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)
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assert isinstance(result, Generator)
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for chunk in result:
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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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if chunk.delta.finish_reason is not None:
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assert chunk.delta.usage is not None
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assert chunk.delta.usage.completion_tokens > 0
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def test_get_num_tokens():
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model = UpstageLargeLanguageModel()
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num_tokens = model.get_num_tokens(
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model='solar-1-mini-chat',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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},
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prompt_messages=[
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UserPromptMessage(
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content='Hello World!'
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)
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]
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)
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assert num_tokens == 13
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num_tokens = model.get_num_tokens(
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model='solar-1-mini-chat',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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},
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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='Hello World!'
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)
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],
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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": {
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"type": "string",
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"description": "The city and state e.g. San Francisco, CA"
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},
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"unit": {
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"type": "string",
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"enum": [
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"c",
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"f"
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]
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}
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},
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"required": [
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"location"
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]
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}
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),
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]
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)
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assert num_tokens == 106
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@@ -0,0 +1,23 @@
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import os
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import pytest
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from core.model_runtime.errors.validate import CredentialsValidateFailedError
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from core.model_runtime.model_providers.upstage.upstage import UpstageProvider
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from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock
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@pytest.mark.parametrize('setup_openai_mock', [['chat']], indirect=True)
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def test_validate_provider_credentials(setup_openai_mock):
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provider = UpstageProvider()
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with pytest.raises(CredentialsValidateFailedError):
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provider.validate_provider_credentials(
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credentials={}
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)
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provider.validate_provider_credentials(
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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}
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)
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@@ -0,0 +1,67 @@
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import os
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import pytest
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from core.model_runtime.entities.text_embedding_entities import TextEmbeddingResult
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from core.model_runtime.errors.validate import CredentialsValidateFailedError
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from core.model_runtime.model_providers.upstage.text_embedding.text_embedding import UpstageTextEmbeddingModel
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from tests.integration_tests.model_runtime.__mock.openai import setup_openai_mock
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@pytest.mark.parametrize('setup_openai_mock', [['text_embedding']], indirect=True)
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def test_validate_credentials(setup_openai_mock):
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model = UpstageTextEmbeddingModel()
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with pytest.raises(CredentialsValidateFailedError):
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model.validate_credentials(
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model='solar-embedding-1-large-passage',
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credentials={
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'upstage_api_key': 'invalid_key'
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}
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)
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model.validate_credentials(
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model='solar-embedding-1-large-passage',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY')
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}
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)
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@pytest.mark.parametrize('setup_openai_mock', [['text_embedding']], indirect=True)
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def test_invoke_model(setup_openai_mock):
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model = UpstageTextEmbeddingModel()
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result = model.invoke(
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model='solar-embedding-1-large-passage',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY'),
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},
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texts=[
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"hello",
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"world",
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" ".join(["long_text"] * 100),
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" ".join(["another_long_text"] * 100)
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],
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user="abc-123"
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)
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assert isinstance(result, TextEmbeddingResult)
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assert len(result.embeddings) == 4
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assert result.usage.total_tokens == 2
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def test_get_num_tokens():
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model = UpstageTextEmbeddingModel()
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num_tokens = model.get_num_tokens(
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model='solar-embedding-1-large-passage',
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credentials={
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'upstage_api_key': os.environ.get('UPSTAGE_API_KEY'),
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},
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texts=[
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"hello",
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"world"
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]
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)
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assert num_tokens == 5
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