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chore(api/tests): apply ruff reformat #7590 (#7591)

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Co-authored-by: -LAN- <laipz8200@outlook.com>
This commit is contained in:
Bowen Liang
2024-08-23 23:52:25 +08:00
committed by GitHub
parent 2da63654e5
commit b035c02f78
155 changed files with 4279 additions and 5925 deletions
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187
api/tests/unit_tests/services/workflow/test_workflow_converter.py
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@@ -83,18 +83,12 @@ def test__convert_to_http_request_node_for_chatbot(default_variables):
external_data_variables = [
ExternalDataVariableEntity(
variable="external_variable",
type="api",
config={
"api_based_extension_id": api_based_extension_id
}
variable="external_variable", type="api", config={"api_based_extension_id": api_based_extension_id}
)
]
nodes, _ = workflow_converter._convert_to_http_request_node(
app_model=app_model,
variables=default_variables,
external_data_variables=external_data_variables
app_model=app_model, variables=default_variables, external_data_variables=external_data_variables
)
assert len(nodes) == 2
@@ -105,10 +99,7 @@ def test__convert_to_http_request_node_for_chatbot(default_variables):
assert http_request_node["data"]["method"] == "post"
assert http_request_node["data"]["url"] == mock_api_based_extension.api_endpoint
assert http_request_node["data"]["authorization"]["type"] == "api-key"
assert http_request_node["data"]["authorization"]["config"] == {
"type": "bearer",
"api_key": "api_key"
}
assert http_request_node["data"]["authorization"]["config"] == {"type": "bearer", "api_key": "api_key"}
assert http_request_node["data"]["body"]["type"] == "json"
body_data = http_request_node["data"]["body"]["data"]
@@ -153,18 +144,12 @@ def test__convert_to_http_request_node_for_workflow_app(default_variables):
external_data_variables = [
ExternalDataVariableEntity(
variable="external_variable",
type="api",
config={
"api_based_extension_id": api_based_extension_id
}
variable="external_variable", type="api", config={"api_based_extension_id": api_based_extension_id}
)
]
nodes, _ = workflow_converter._convert_to_http_request_node(
app_model=app_model,
variables=default_variables,
external_data_variables=external_data_variables
app_model=app_model, variables=default_variables, external_data_variables=external_data_variables
)
assert len(nodes) == 2
@@ -175,10 +160,7 @@ def test__convert_to_http_request_node_for_workflow_app(default_variables):
assert http_request_node["data"]["method"] == "post"
assert http_request_node["data"]["url"] == mock_api_based_extension.api_endpoint
assert http_request_node["data"]["authorization"]["type"] == "api-key"
assert http_request_node["data"]["authorization"]["config"] == {
"type": "bearer",
"api_key": "api_key"
}
assert http_request_node["data"]["authorization"]["config"] == {"type": "bearer", "api_key": "api_key"}
assert http_request_node["data"]["body"]["type"] == "json"
body_data = http_request_node["data"]["body"]["data"]
@@ -207,37 +189,25 @@ def test__convert_to_knowledge_retrieval_node_for_chatbot():
retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE,
top_k=5,
score_threshold=0.8,
reranking_model={
'reranking_provider_name': 'cohere',
'reranking_model_name': 'rerank-english-v2.0'
},
reranking_enabled=True
)
reranking_model={"reranking_provider_name": "cohere", "reranking_model_name": "rerank-english-v2.0"},
reranking_enabled=True,
),
)
model_config = ModelConfigEntity(
provider='openai',
model='gpt-4',
mode='chat',
parameters={},
stop=[]
)
model_config = ModelConfigEntity(provider="openai", model="gpt-4", mode="chat", parameters={}, stop=[])
node = WorkflowConverter()._convert_to_knowledge_retrieval_node(
new_app_mode=new_app_mode,
dataset_config=dataset_config,
model_config=model_config
new_app_mode=new_app_mode, dataset_config=dataset_config, model_config=model_config
)
assert node["data"]["type"] == "knowledge-retrieval"
assert node["data"]["query_variable_selector"] == ["sys", "query"]
assert node["data"]["dataset_ids"] == dataset_config.dataset_ids
assert (node["data"]["retrieval_mode"]
== dataset_config.retrieve_config.retrieve_strategy.value)
assert node["data"]["retrieval_mode"] == dataset_config.retrieve_config.retrieve_strategy.value
assert node["data"]["multiple_retrieval_config"] == {
"top_k": dataset_config.retrieve_config.top_k,
"score_threshold": dataset_config.retrieve_config.score_threshold,
"reranking_model": dataset_config.retrieve_config.reranking_model
"reranking_model": dataset_config.retrieve_config.reranking_model,
}
@@ -251,37 +221,25 @@ def test__convert_to_knowledge_retrieval_node_for_workflow_app():
retrieve_strategy=DatasetRetrieveConfigEntity.RetrieveStrategy.MULTIPLE,
top_k=5,
score_threshold=0.8,
reranking_model={
'reranking_provider_name': 'cohere',
'reranking_model_name': 'rerank-english-v2.0'
},
reranking_enabled=True
)
reranking_model={"reranking_provider_name": "cohere", "reranking_model_name": "rerank-english-v2.0"},
reranking_enabled=True,
),
)
model_config = ModelConfigEntity(
provider='openai',
model='gpt-4',
mode='chat',
parameters={},
stop=[]
)
model_config = ModelConfigEntity(provider="openai", model="gpt-4", mode="chat", parameters={}, stop=[])
node = WorkflowConverter()._convert_to_knowledge_retrieval_node(
new_app_mode=new_app_mode,
dataset_config=dataset_config,
model_config=model_config
new_app_mode=new_app_mode, dataset_config=dataset_config, model_config=model_config
)
assert node["data"]["type"] == "knowledge-retrieval"
assert node["data"]["query_variable_selector"] == ["start", dataset_config.retrieve_config.query_variable]
assert node["data"]["dataset_ids"] == dataset_config.dataset_ids
assert (node["data"]["retrieval_mode"]
== dataset_config.retrieve_config.retrieve_strategy.value)
assert node["data"]["retrieval_mode"] == dataset_config.retrieve_config.retrieve_strategy.value
assert node["data"]["multiple_retrieval_config"] == {
"top_k": dataset_config.retrieve_config.top_k,
"score_threshold": dataset_config.retrieve_config.score_threshold,
"reranking_model": dataset_config.retrieve_config.reranking_model
"reranking_model": dataset_config.retrieve_config.reranking_model,
}
@@ -293,14 +251,12 @@ def test__convert_to_llm_node_for_chatbot_simple_chat_model(default_variables):
workflow_converter = WorkflowConverter()
start_node = workflow_converter._convert_to_start_node(default_variables)
graph = {
"nodes": [
start_node
],
"edges": [] # no need
"nodes": [start_node],
"edges": [], # no need
}
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.provider = 'openai'
model_config_mock.provider = "openai"
model_config_mock.model = model
model_config_mock.mode = model_mode.value
model_config_mock.parameters = {}
@@ -308,7 +264,7 @@ def test__convert_to_llm_node_for_chatbot_simple_chat_model(default_variables):
prompt_template = PromptTemplateEntity(
prompt_type=PromptTemplateEntity.PromptType.SIMPLE,
simple_prompt_template="You are a helpful assistant {{text_input}}, {{paragraph}}, {{select}}."
simple_prompt_template="You are a helpful assistant {{text_input}}, {{paragraph}}, {{select}}.",
)
llm_node = workflow_converter._convert_to_llm_node(
@@ -316,17 +272,17 @@ def test__convert_to_llm_node_for_chatbot_simple_chat_model(default_variables):
new_app_mode=new_app_mode,
model_config=model_config_mock,
graph=graph,
prompt_template=prompt_template
prompt_template=prompt_template,
)
assert llm_node["data"]["type"] == "llm"
assert llm_node["data"]["model"]['name'] == model
assert llm_node["data"]['model']["mode"] == model_mode.value
assert llm_node["data"]["model"]["name"] == model
assert llm_node["data"]["model"]["mode"] == model_mode.value
template = prompt_template.simple_prompt_template
for v in default_variables:
template = template.replace('{{' + v.variable + '}}', '{{#start.' + v.variable + '#}}')
assert llm_node["data"]["prompt_template"][0]['text'] == template + '\n'
assert llm_node["data"]['context']['enabled'] is False
template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}")
assert llm_node["data"]["prompt_template"][0]["text"] == template + "\n"
assert llm_node["data"]["context"]["enabled"] is False
def test__convert_to_llm_node_for_chatbot_simple_completion_model(default_variables):
@@ -337,14 +293,12 @@ def test__convert_to_llm_node_for_chatbot_simple_completion_model(default_variab
workflow_converter = WorkflowConverter()
start_node = workflow_converter._convert_to_start_node(default_variables)
graph = {
"nodes": [
start_node
],
"edges": [] # no need
"nodes": [start_node],
"edges": [], # no need
}
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.provider = 'openai'
model_config_mock.provider = "openai"
model_config_mock.model = model
model_config_mock.mode = model_mode.value
model_config_mock.parameters = {}
@@ -352,7 +306,7 @@ def test__convert_to_llm_node_for_chatbot_simple_completion_model(default_variab
prompt_template = PromptTemplateEntity(
prompt_type=PromptTemplateEntity.PromptType.SIMPLE,
simple_prompt_template="You are a helpful assistant {{text_input}}, {{paragraph}}, {{select}}."
simple_prompt_template="You are a helpful assistant {{text_input}}, {{paragraph}}, {{select}}.",
)
llm_node = workflow_converter._convert_to_llm_node(
@@ -360,17 +314,17 @@ def test__convert_to_llm_node_for_chatbot_simple_completion_model(default_variab
new_app_mode=new_app_mode,
model_config=model_config_mock,
graph=graph,
prompt_template=prompt_template
prompt_template=prompt_template,
)
assert llm_node["data"]["type"] == "llm"
assert llm_node["data"]["model"]['name'] == model
assert llm_node["data"]['model']["mode"] == model_mode.value
assert llm_node["data"]["model"]["name"] == model
assert llm_node["data"]["model"]["mode"] == model_mode.value
template = prompt_template.simple_prompt_template
for v in default_variables:
template = template.replace('{{' + v.variable + '}}', '{{#start.' + v.variable + '#}}')
assert llm_node["data"]["prompt_template"]['text'] == template + '\n'
assert llm_node["data"]['context']['enabled'] is False
template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}")
assert llm_node["data"]["prompt_template"]["text"] == template + "\n"
assert llm_node["data"]["context"]["enabled"] is False
def test__convert_to_llm_node_for_chatbot_advanced_chat_model(default_variables):
@@ -381,14 +335,12 @@ def test__convert_to_llm_node_for_chatbot_advanced_chat_model(default_variables)
workflow_converter = WorkflowConverter()
start_node = workflow_converter._convert_to_start_node(default_variables)
graph = {
"nodes": [
start_node
],
"edges": [] # no need
"nodes": [start_node],
"edges": [], # no need
}
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.provider = 'openai'
model_config_mock.provider = "openai"
model_config_mock.model = model
model_config_mock.mode = model_mode.value
model_config_mock.parameters = {}
@@ -396,12 +348,16 @@ def test__convert_to_llm_node_for_chatbot_advanced_chat_model(default_variables)
prompt_template = PromptTemplateEntity(
prompt_type=PromptTemplateEntity.PromptType.ADVANCED,
advanced_chat_prompt_template=AdvancedChatPromptTemplateEntity(messages=[
AdvancedChatMessageEntity(text="You are a helpful assistant named {{name}}.\n\nContext:\n{{#context#}}",
role=PromptMessageRole.SYSTEM),
AdvancedChatMessageEntity(text="Hi.", role=PromptMessageRole.USER),
AdvancedChatMessageEntity(text="Hello!", role=PromptMessageRole.ASSISTANT),
])
advanced_chat_prompt_template=AdvancedChatPromptTemplateEntity(
messages=[
AdvancedChatMessageEntity(
text="You are a helpful assistant named {{name}}.\n\nContext:\n{{#context#}}",
role=PromptMessageRole.SYSTEM,
),
AdvancedChatMessageEntity(text="Hi.", role=PromptMessageRole.USER),
AdvancedChatMessageEntity(text="Hello!", role=PromptMessageRole.ASSISTANT),
]
),
)
llm_node = workflow_converter._convert_to_llm_node(
@@ -409,18 +365,18 @@ def test__convert_to_llm_node_for_chatbot_advanced_chat_model(default_variables)
new_app_mode=new_app_mode,
model_config=model_config_mock,
graph=graph,
prompt_template=prompt_template
prompt_template=prompt_template,
)
assert llm_node["data"]["type"] == "llm"
assert llm_node["data"]["model"]['name'] == model
assert llm_node["data"]['model']["mode"] == model_mode.value
assert llm_node["data"]["model"]["name"] == model
assert llm_node["data"]["model"]["mode"] == model_mode.value
assert isinstance(llm_node["data"]["prompt_template"], list)
assert len(llm_node["data"]["prompt_template"]) == len(prompt_template.advanced_chat_prompt_template.messages)
template = prompt_template.advanced_chat_prompt_template.messages[0].text
for v in default_variables:
template = template.replace('{{' + v.variable + '}}', '{{#start.' + v.variable + '#}}')
assert llm_node["data"]["prompt_template"][0]['text'] == template
template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}")
assert llm_node["data"]["prompt_template"][0]["text"] == template
def test__convert_to_llm_node_for_workflow_advanced_completion_model(default_variables):
@@ -431,14 +387,12 @@ def test__convert_to_llm_node_for_workflow_advanced_completion_model(default_var
workflow_converter = WorkflowConverter()
start_node = workflow_converter._convert_to_start_node(default_variables)
graph = {
"nodes": [
start_node
],
"edges": [] # no need
"nodes": [start_node],
"edges": [], # no need
}
model_config_mock = MagicMock(spec=ModelConfigEntity)
model_config_mock.provider = 'openai'
model_config_mock.provider = "openai"
model_config_mock.model = model
model_config_mock.mode = model_mode.value
model_config_mock.parameters = {}
@@ -448,12 +402,9 @@ def test__convert_to_llm_node_for_workflow_advanced_completion_model(default_var
prompt_type=PromptTemplateEntity.PromptType.ADVANCED,
advanced_completion_prompt_template=AdvancedCompletionPromptTemplateEntity(
prompt="You are a helpful assistant named {{name}}.\n\nContext:\n{{#context#}}\n\n"
"Human: hi\nAssistant: ",
role_prefix=AdvancedCompletionPromptTemplateEntity.RolePrefixEntity(
user="Human",
assistant="Assistant"
)
)
"Human: hi\nAssistant: ",
role_prefix=AdvancedCompletionPromptTemplateEntity.RolePrefixEntity(user="Human", assistant="Assistant"),
),
)
llm_node = workflow_converter._convert_to_llm_node(
@@ -461,14 +412,14 @@ def test__convert_to_llm_node_for_workflow_advanced_completion_model(default_var
new_app_mode=new_app_mode,
model_config=model_config_mock,
graph=graph,
prompt_template=prompt_template
prompt_template=prompt_template,
)
assert llm_node["data"]["type"] == "llm"
assert llm_node["data"]["model"]['name'] == model
assert llm_node["data"]['model']["mode"] == model_mode.value
assert llm_node["data"]["model"]["name"] == model
assert llm_node["data"]["model"]["mode"] == model_mode.value
assert isinstance(llm_node["data"]["prompt_template"], dict)
template = prompt_template.advanced_completion_prompt_template.prompt
for v in default_variables:
template = template.replace('{{' + v.variable + '}}', '{{#start.' + v.variable + '#}}')
assert llm_node["data"]["prompt_template"]['text'] == template
template = template.replace("{{" + v.variable + "}}", "{{#start." + v.variable + "#}}")
assert llm_node["data"]["prompt_template"]["text"] == template