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chore: fix the code review issues

This commit is contained in:
Novice 2025-04-17 19:34:20 +08:00
parent 56ef622447
commit e6a7a1884c
8 changed files with 37 additions and 43 deletions
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1
api/.env.example
View File

@ -326,7 +326,6 @@ UPLOAD_AUDIO_FILE_SIZE_LIMIT=50
MULTIMODAL_SEND_FORMAT=base64
PROMPT_GENERATION_MAX_TOKENS=512
CODE_GENERATION_MAX_TOKENS=1024
STRUCTURED_OUTPUT_MAX_TOKENS=1024
PLUGIN_BASED_TOKEN_COUNTING_ENABLED=false
# Mail configuration, support: resend, smtp

2
api/controllers/console/app/generator.py
View File

@ -96,13 +96,11 @@ class RuleStructuredOutputGenerateApi(Resource):
args = parser.parse_args()
account = current_user
structured_output_max_tokens = int(os.getenv("STRUCTURED_OUTPUT_MAX_TOKENS", "1024"))
try:
structured_output = LLMGenerator.generate_structured_output(
tenant_id=account.current_tenant_id,
instruction=args["instruction"],
model_config=args["model_config"],
max_tokens=structured_output_max_tokens,
)
except ProviderTokenNotInitError as ex:
raise ProviderNotInitializeError(ex.description)

18
api/core/llm_generator/llm_generator.py
View File

@ -10,7 +10,7 @@ from core.llm_generator.prompts import (
GENERATOR_QA_PROMPT,
JAVASCRIPT_CODE_GENERATOR_PROMPT_TEMPLATE,
PYTHON_CODE_GENERATOR_PROMPT_TEMPLATE,
STRUCTURED_OUTPUT_GENERATE_TEMPLATE,
SYSTEM_STRUCTURED_OUTPUT_GENERATE,
WORKFLOW_RULE_CONFIG_PROMPT_GENERATE_TEMPLATE,
)
from core.model_manager import ModelManager
@ -343,16 +343,7 @@ class LLMGenerator:
return answer.strip()
@classmethod
def generate_structured_output(cls, tenant_id: str, instruction: str, model_config: dict, max_tokens: int):
prompt_template = PromptTemplateParser(STRUCTURED_OUTPUT_GENERATE_TEMPLATE)
prompt = prompt_template.format(
inputs={
"INSTRUCTION": instruction,
},
remove_template_variables=False,
)
def generate_structured_output(cls, tenant_id: str, instruction: str, model_config: dict):
model_manager = ModelManager()
model_instance = model_manager.get_model_instance(
tenant_id=tenant_id,
@ -361,7 +352,10 @@ class LLMGenerator:
model=model_config.get("name", ""),
)
prompt_messages = [UserPromptMessage(content=prompt)]
prompt_messages = [
SystemPromptMessage(content=SYSTEM_STRUCTURED_OUTPUT_GENERATE),
UserPromptMessage(content=instruction),
]
model_parameters = model_config.get("model_parameters", {})
try:

4
api/core/llm_generator/prompts.py
View File

@ -325,7 +325,5 @@ Your task is to convert simple user descriptions into properly formatted JSON Sc
]
}
Now, generate a JSON Schema based on my description:
**User Input:** {{INSTRUCTION}}
**JSON Schema Output:**
Now, generate a JSON Schema based on my description
""" # noqa: E501

13
api/core/model_runtime/entities/model_entities.py
View File

@ -202,12 +202,13 @@ class AIModelEntity(ProviderModel):
def validate_model(self):
supported_schema_keys = ["json_schema"]
schema_key = next((rule.name for rule in self.parameter_rules if rule.name in supported_schema_keys), None)
if schema_key:
if self.features is None:
self.features = [ModelFeature.STRUCTURED_OUTPUT]
else:
if ModelFeature.STRUCTURED_OUTPUT not in self.features:
self.features = [*self.features, ModelFeature.STRUCTURED_OUTPUT]
if not schema_key:
return self
if self.features is None:
self.features = [ModelFeature.STRUCTURED_OUTPUT]
else:
if ModelFeature.STRUCTURED_OUTPUT not in self.features:
self.features.append(ModelFeature.STRUCTURED_OUTPUT)
return self

36
api/core/workflow/nodes/llm/node.py
View File

@ -102,6 +102,12 @@ class LLMNode(BaseNode[LLMNodeData]):
_node_type = NodeType.LLM
def _run(self) -> Generator[NodeEvent | InNodeEvent, None, None]:
def process_structured_output(text: str) -> Optional[dict[str, Any] | list[Any]]:
"""Process structured output if enabled"""
if not self.node_data.structured_output_enabled or not self.node_data.structured_output:
return None
return self._parse_structured_output(text)
node_inputs: Optional[dict[str, Any]] = None
process_data = None
result_text = ""
@ -201,19 +207,8 @@ class LLMNode(BaseNode[LLMNodeData]):
self.deduct_llm_quota(tenant_id=self.tenant_id, model_instance=model_instance, usage=usage)
break
outputs = {"text": result_text, "usage": jsonable_encoder(usage), "finish_reason": finish_reason}
if self.node_data.structured_output_enabled and self.node_data.structured_output:
structured_output: dict[str, Any] | list[Any] = {}
try:
parsed = json.loads(result_text)
if not isinstance(parsed, (dict | list)):
raise LLMNodeError(f"Failed to parse structured output: {result_text}")
structured_output = parsed
except json.JSONDecodeError as e:
# if the result_text is not a valid json, try to repair it
parsed = json_repair.loads(result_text)
if not isinstance(parsed, (dict | list)):
raise LLMNodeError(f"Failed to parse structured output: {result_text}")
structured_output = parsed
structured_output = process_structured_output(result_text)
if structured_output:
outputs["structured_output"] = structured_output
yield RunCompletedEvent(
run_result=NodeRunResult(
@ -759,6 +754,21 @@ class LLMNode(BaseNode[LLMNodeData]):
stop = model_config.stop
return filtered_prompt_messages, stop
def _parse_structured_output(self, result_text: str) -> dict[str, Any] | list[Any]:
structured_output: dict[str, Any] | list[Any] = {}
try:
parsed = json.loads(result_text)
if not isinstance(parsed, (dict | list)):
raise LLMNodeError(f"Failed to parse structured output: {result_text}")
structured_output = parsed
except json.JSONDecodeError as e:
# if the result_text is not a valid json, try to repair it
parsed = json_repair.loads(result_text)
if not isinstance(parsed, (dict | list)):
raise LLMNodeError(f"Failed to parse structured output: {result_text}")
structured_output = parsed
return structured_output
@classmethod
def deduct_llm_quota(cls, tenant_id: str, model_instance: ModelInstance, usage: LLMUsage) -> None:
provider_model_bundle = model_instance.provider_model_bundle

5
docker/.env.example
View File

@ -622,11 +622,6 @@ PROMPT_GENERATION_MAX_TOKENS=512
# Default: 1024 tokens.
CODE_GENERATION_MAX_TOKENS=1024
# The maximum number of tokens allowed for structured output.
# This setting controls the upper limit of tokens that can be used by the LLM
# when generating structured output in the structured output tool.
# Default: 1024 tokens.
STRUCTURED_OUTPUT_MAX_TOKENS=1024
# Enable or disable plugin based token counting. If disabled, token counting will return 0.
# This can improve performance by skipping token counting operations.
# Default: false (disabled).

1
docker/docker-compose.yaml
View File

@ -279,7 +279,6 @@ x-shared-env: &shared-api-worker-env
SCARF_NO_ANALYTICS: ${SCARF_NO_ANALYTICS:-true}
PROMPT_GENERATION_MAX_TOKENS: ${PROMPT_GENERATION_MAX_TOKENS:-512}
CODE_GENERATION_MAX_TOKENS: ${CODE_GENERATION_MAX_TOKENS:-1024}
STRUCTURED_OUTPUT_MAX_TOKENS: ${STRUCTURED_OUTPUT_MAX_TOKENS:-1024}
PLUGIN_BASED_TOKEN_COUNTING_ENABLED: ${PLUGIN_BASED_TOKEN_COUNTING_ENABLED:-false}
MULTIMODAL_SEND_FORMAT: ${MULTIMODAL_SEND_FORMAT:-base64}
UPLOAD_IMAGE_FILE_SIZE_LIMIT: ${UPLOAD_IMAGE_FILE_SIZE_LIMIT:-10}