mirror of https://github.com/langgenius/dify.git
fix(telemetry): remove app_id parameter from standalone prompt generation endpoints
Remove app_id=None from three prompt generation endpoints that lack proper app context. These standalone utilities only have tenant_id available, so we don't pass app_id at all rather than passing incomplete information. Affected endpoints: - /rule-generate (RuleGenerateApi) - /code-generate (RuleCodeGenerateApi) - /structured-output-generate (RuleStructuredOutputGenerateApi)
This commit is contained in:
GareArc
parent
22c8d8d772
commit
a4bebbb5b5
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@ -1,4 +1,5 @@
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from collections.abc import Sequence
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from typing import Any
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from flask_restx import Resource
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from pydantic import BaseModel, Field
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@ -11,12 +12,10 @@ from controllers.console.app.error import (
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ProviderQuotaExceededError,
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)
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from controllers.console.wraps import account_initialization_required, setup_required
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from core.app.app_config.entities import ModelConfig
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from core.errors.error import ModelCurrentlyNotSupportError, ProviderTokenNotInitError, QuotaExceededError
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from core.helper.code_executor.code_node_provider import CodeNodeProvider
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from core.helper.code_executor.javascript.javascript_code_provider import JavascriptCodeProvider
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from core.helper.code_executor.python3.python3_code_provider import Python3CodeProvider
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from core.llm_generator.entities import RuleCodeGeneratePayload, RuleGeneratePayload, RuleStructuredOutputPayload
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from core.llm_generator.llm_generator import LLMGenerator
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from core.model_runtime.errors.invoke import InvokeError
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from extensions.ext_database import db
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@ -27,13 +26,28 @@ from services.workflow_service import WorkflowService
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DEFAULT_REF_TEMPLATE_SWAGGER_2_0 = "#/definitions/{model}"
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class RuleGeneratePayload(BaseModel):
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instruction: str = Field(..., description="Rule generation instruction")
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model_config_data: dict[str, Any] = Field(..., alias="model_config", description="Model configuration")
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no_variable: bool = Field(default=False, description="Whether to exclude variables")
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class RuleCodeGeneratePayload(RuleGeneratePayload):
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code_language: str = Field(default="javascript", description="Programming language for code generation")
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class RuleStructuredOutputPayload(BaseModel):
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instruction: str = Field(..., description="Structured output generation instruction")
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model_config_data: dict[str, Any] = Field(..., alias="model_config", description="Model configuration")
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class InstructionGeneratePayload(BaseModel):
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flow_id: str = Field(..., description="Workflow/Flow ID")
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node_id: str = Field(default="", description="Node ID for workflow context")
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current: str = Field(default="", description="Current instruction text")
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language: str = Field(default="javascript", description="Programming language (javascript/python)")
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instruction: str = Field(..., description="Instruction for generation")
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model_config_data: ModelConfig = Field(..., alias="model_config", description="Model configuration")
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model_config_data: dict[str, Any] = Field(..., alias="model_config", description="Model configuration")
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ideal_output: str = Field(default="", description="Expected ideal output")
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@ -50,7 +64,6 @@ reg(RuleCodeGeneratePayload)
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reg(RuleStructuredOutputPayload)
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reg(InstructionGeneratePayload)
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reg(InstructionTemplatePayload)
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reg(ModelConfig)
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@console_ns.route("/rule-generate")
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@ -65,28 +78,27 @@ class RuleGenerateApi(Resource):
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@login_required
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@account_initialization_required
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def post(self):
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args = RuleGeneratePayload.model_validate(console_ns.payload)
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account, current_tenant_id = current_account_with_tenant()
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args = RuleGeneratePayload.model_validate(console_ns.payload)
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account, current_tenant_id = current_account_with_tenant()
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try:
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rules = LLMGenerator.generate_rule_config(
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tenant_id=current_tenant_id,
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instruction=args.instruction,
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model_config=args.model_config_data,
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no_variable=args.no_variable,
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user_id=account.id,
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app_id=None,
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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except QuotaExceededError:
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raise ProviderQuotaExceededError()
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except ModelCurrentlyNotSupportError:
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raise ProviderModelCurrentlyNotSupportError()
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except InvokeError as e:
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raise CompletionRequestError(e.description)
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try:
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rules = LLMGenerator.generate_rule_config(
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tenant_id=current_tenant_id,
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instruction=args.instruction,
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model_config=args.model_config_data,
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no_variable=args.no_variable,
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user_id=account.id,
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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except QuotaExceededError:
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raise ProviderQuotaExceededError()
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except ModelCurrentlyNotSupportError:
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raise ProviderModelCurrentlyNotSupportError()
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except InvokeError as e:
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raise CompletionRequestError(e.description)
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return rules
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return rules
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@console_ns.route("/rule-code-generate")
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@ -111,7 +123,6 @@ class RuleCodeGenerateApi(Resource):
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model_config=args.model_config_data,
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code_language=args.code_language,
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user_id=account.id,
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app_id=None,
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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@ -143,14 +154,9 @@ class RuleStructuredOutputGenerateApi(Resource):
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try:
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structured_output = LLMGenerator.generate_structured_output(
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tenant_id=current_tenant_id,
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<<<<<<< HEAD
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args=args,
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=======
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instruction=args.instruction,
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model_config=args.model_config_data,
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user_id=account.id,
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app_id=None,
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>>>>>>> c56e5a5b71 (feat(telemetry): add prompt generation telemetry to Enterprise OTEL)
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)
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except ProviderTokenNotInitError as ex:
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raise ProviderNotInitializeError(ex.description)
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@ -200,53 +206,29 @@ class InstructionGenerateApi(Resource):
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case "llm":
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return LLMGenerator.generate_rule_config(
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current_tenant_id,
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<<<<<<< HEAD
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args=RuleGeneratePayload(
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instruction=args.instruction,
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model_config=args.model_config_data,
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no_variable=True,
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),
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=======
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instruction=args.instruction,
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model_config=args.model_config_data,
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no_variable=True,
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user_id=account.id,
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app_id=args.flow_id,
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>>>>>>> c56e5a5b71 (feat(telemetry): add prompt generation telemetry to Enterprise OTEL)
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)
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case "agent":
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return LLMGenerator.generate_rule_config(
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current_tenant_id,
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<<<<<<< HEAD
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args=RuleGeneratePayload(
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instruction=args.instruction,
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model_config=args.model_config_data,
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no_variable=True,
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),
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=======
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instruction=args.instruction,
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model_config=args.model_config_data,
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no_variable=True,
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user_id=account.id,
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app_id=args.flow_id,
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>>>>>>> c56e5a5b71 (feat(telemetry): add prompt generation telemetry to Enterprise OTEL)
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)
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case "code":
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return LLMGenerator.generate_code(
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tenant_id=current_tenant_id,
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<<<<<<< HEAD
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args=RuleCodeGeneratePayload(
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instruction=args.instruction,
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model_config=args.model_config_data,
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code_language=args.language,
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),
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=======
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instruction=args.instruction,
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model_config=args.model_config_data,
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code_language=args.language,
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user_id=account.id,
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app_id=args.flow_id,
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>>>>>>> c56e5a5b71 (feat(telemetry): add prompt generation telemetry to Enterprise OTEL)
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)
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case _:
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return {"error": f"invalid node type: {node_type}"}
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