dify/api/tests/integration_tests/model_runtime/wenxin/test_llm.py
Bowen Liang b035c02f78
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chore(api/tests): apply ruff reformat #7590 (#7591)
Co-authored-by: -LAN- <laipz8200@outlook.com>
2024-08-23 23:52:25 +08:00

215 lines
6.7 KiB
Python

import os
from collections.abc import Generator
from time import sleep
import pytest
from core.model_runtime.entities.llm_entities import LLMResult, LLMResultChunk, LLMResultChunkDelta
from core.model_runtime.entities.message_entities import AssistantPromptMessage, SystemPromptMessage, UserPromptMessage
from core.model_runtime.entities.model_entities import AIModelEntity
from core.model_runtime.errors.validate import CredentialsValidateFailedError
from core.model_runtime.model_providers.wenxin.llm.llm import ErnieBotLargeLanguageModel
def test_predefined_models():
model = ErnieBotLargeLanguageModel()
model_schemas = model.predefined_models()
assert len(model_schemas) >= 1
assert isinstance(model_schemas[0], AIModelEntity)
def test_validate_credentials_for_chat_model():
sleep(3)
model = ErnieBotLargeLanguageModel()
with pytest.raises(CredentialsValidateFailedError):
model.validate_credentials(
model="ernie-bot", credentials={"api_key": "invalid_key", "secret_key": "invalid_key"}
)
model.validate_credentials(
model="ernie-bot",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
)
def test_invoke_model_ernie_bot():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-bot",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="Hello World!")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
},
stop=["you"],
user="abc-123",
stream=False,
)
assert isinstance(response, LLMResult)
assert len(response.message.content) > 0
assert response.usage.total_tokens > 0
def test_invoke_model_ernie_bot_turbo():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-bot-turbo",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="Hello World!")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
},
stop=["you"],
user="abc-123",
stream=False,
)
assert isinstance(response, LLMResult)
assert len(response.message.content) > 0
assert response.usage.total_tokens > 0
def test_invoke_model_ernie_8k():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-bot-8k",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="Hello World!")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
},
stop=["you"],
user="abc-123",
stream=False,
)
assert isinstance(response, LLMResult)
assert len(response.message.content) > 0
assert response.usage.total_tokens > 0
def test_invoke_model_ernie_bot_4():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-bot-4",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="Hello World!")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
},
stop=["you"],
user="abc-123",
stream=False,
)
assert isinstance(response, LLMResult)
assert len(response.message.content) > 0
assert response.usage.total_tokens > 0
def test_invoke_stream_model():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-3.5-8k",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="Hello World!")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
},
stop=["you"],
stream=True,
user="abc-123",
)
assert isinstance(response, Generator)
for chunk in response:
assert isinstance(chunk, LLMResultChunk)
assert isinstance(chunk.delta, LLMResultChunkDelta)
assert isinstance(chunk.delta.message, AssistantPromptMessage)
assert len(chunk.delta.message.content) > 0 if chunk.delta.finish_reason is None else True
def test_invoke_model_with_system():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-bot",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[SystemPromptMessage(content="你是Kasumi"), UserPromptMessage(content="你是谁?")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
},
stop=["you"],
stream=False,
user="abc-123",
)
assert isinstance(response, LLMResult)
assert "kasumi" in response.message.content.lower()
def test_invoke_with_search():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.invoke(
model="ernie-bot",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="北京今天的天气怎么样")],
model_parameters={
"temperature": 0.7,
"top_p": 1.0,
"disable_search": True,
},
stop=[],
stream=True,
user="abc-123",
)
assert isinstance(response, Generator)
total_message = ""
for chunk in response:
assert isinstance(chunk, LLMResultChunk)
assert isinstance(chunk.delta, LLMResultChunkDelta)
assert isinstance(chunk.delta.message, AssistantPromptMessage)
total_message += chunk.delta.message.content
print(chunk.delta.message.content)
assert len(chunk.delta.message.content) > 0 if not chunk.delta.finish_reason else True
# there should be 对不起、我不能、不支持……
assert "" in total_message or "抱歉" in total_message or "无法" in total_message
def test_get_num_tokens():
sleep(3)
model = ErnieBotLargeLanguageModel()
response = model.get_num_tokens(
model="ernie-bot",
credentials={"api_key": os.environ.get("WENXIN_API_KEY"), "secret_key": os.environ.get("WENXIN_SECRET_KEY")},
prompt_messages=[UserPromptMessage(content="Hello World!")],
tools=[],
)
assert isinstance(response, int)
assert response == 10