mirror of https://github.com/langgenius/dify.git
feat: code
This commit is contained in:
parent
736e386f15
commit
cb02b1e12e
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@ -132,3 +132,7 @@ SSRF_PROXY_HTTP_URL=
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SSRF_PROXY_HTTPS_URL=
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BATCH_UPLOAD_LIMIT=10
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# CODE EXECUTION CONFIGURATION
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CODE_EXECUTION_ENDPOINT=
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CODE_EXECUTINO_API_KEY=
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@ -59,7 +59,9 @@ DEFAULTS = {
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'CAN_REPLACE_LOGO': 'False',
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'ETL_TYPE': 'dify',
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'KEYWORD_STORE': 'jieba',
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'BATCH_UPLOAD_LIMIT': 20
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'BATCH_UPLOAD_LIMIT': 20,
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'CODE_EXECUTION_ENDPOINT': '',
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'CODE_EXECUTION_API_KEY': ''
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}
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@ -293,6 +295,9 @@ class Config:
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self.BATCH_UPLOAD_LIMIT = get_env('BATCH_UPLOAD_LIMIT')
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self.CODE_EXECUTION_ENDPOINT = get_env('CODE_EXECUTION_ENDPOINT')
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self.CODE_EXECUTION_API_KEY = get_env('CODE_EXECUTION_API_KEY')
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self.API_COMPRESSION_ENABLED = get_bool_env('API_COMPRESSION_ENABLED')
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@ -0,0 +1,70 @@
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from os import environ
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from httpx import post
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from yarl import URL
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from pydantic import BaseModel
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from core.workflow.nodes.code.python_template import PythonTemplateTransformer
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# Code Executor
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CODE_EXECUTION_ENDPOINT = environ.get('CODE_EXECUTION_ENDPOINT', '')
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CODE_EXECUTION_API_KEY = environ.get('CODE_EXECUTION_API_KEY', '')
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class CodeExecutionException(Exception):
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pass
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class CodeExecutionResponse(BaseModel):
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class Data(BaseModel):
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stdout: str
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stderr: str
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code: int
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message: str
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data: Data
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class CodeExecutor:
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@classmethod
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def execute_code(cls, language: str, code: str, inputs: dict) -> dict:
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"""
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Execute code
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:param language: code language
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:param code: code
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:param inputs: inputs
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:return:
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"""
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runner = PythonTemplateTransformer.transform_caller(code, inputs)
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url = URL(CODE_EXECUTION_ENDPOINT) / 'v1' / 'sandbox' / 'run'
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headers = {
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'X-Api-Key': CODE_EXECUTION_API_KEY
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}
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data = {
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'language': language,
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'code': runner,
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}
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try:
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response = post(str(url), json=data, headers=headers)
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if response.status_code == 503:
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raise CodeExecutionException('Code execution service is unavailable')
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elif response.status_code != 200:
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raise Exception('Failed to execute code')
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except CodeExecutionException as e:
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raise e
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except Exception:
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raise CodeExecutionException('Failed to execute code')
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try:
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response = response.json()
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except:
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raise CodeExecutionException('Failed to parse response')
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response = CodeExecutionResponse(**response)
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if response.code != 0:
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raise CodeExecutionException(response.message)
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if response.data.stderr:
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raise CodeExecutionException(response.data.stderr)
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return PythonTemplateTransformer.transform_response(response.data.stdout)
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@ -1,9 +1,23 @@
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from typing import Optional
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from typing import Optional, cast, Union
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from core.workflow.entities.node_entities import NodeRunResult, NodeType
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from core.workflow.entities.variable_pool import VariablePool
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from core.workflow.nodes.base_node import BaseNode
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from core.workflow.nodes.code.entities import CodeNodeData
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from core.workflow.nodes.code.code_executor import CodeExecutor, CodeExecutionException
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from models.workflow import WorkflowNodeExecutionStatus
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MAX_NUMBER = 2 ** 63 - 1
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MIN_NUMBER = -2 ** 63
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MAX_PRECISION = 20
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MAX_DEPTH = 5
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MAX_STRING_LENGTH = 1000
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MAX_STRING_ARRAY_LENGTH = 30
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class CodeNode(BaseNode):
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_node_data_cls = CodeNodeData
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node_type = NodeType.CODE
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@classmethod
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def get_default_config(cls, filters: Optional[dict] = None) -> dict:
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"""
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@ -62,3 +76,167 @@ class CodeNode(BaseNode):
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]
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}
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}
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def _run(self, variable_pool: Optional[VariablePool] = None,
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run_args: Optional[dict] = None) -> NodeRunResult:
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"""
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Run code
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:param variable_pool: variable pool
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:param run_args: run args
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:return:
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"""
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node_data = self.node_data
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node_data: CodeNodeData = cast(self._node_data_cls, node_data)
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# SINGLE DEBUG NOT IMPLEMENTED YET
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if variable_pool is None and run_args:
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raise ValueError("Not support single step debug.")
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# Get code language
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code_language = node_data.code_language
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code = node_data.code
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# Get variables
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variables = {}
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for variable_selector in node_data.variables:
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variable = variable_selector.variable
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value = variable_pool.get_variable_value(
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variable_selector=variable_selector.value_selector
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)
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variables[variable] = value
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# Run code
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try:
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result = CodeExecutor.execute_code(
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language=code_language,
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code=code,
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inputs=variables
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)
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except CodeExecutionException as e:
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return NodeRunResult(
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status=WorkflowNodeExecutionStatus.FAILED,
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error=str(e)
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)
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# Transform result
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result = self._transform_result(result, node_data.outputs)
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return NodeRunResult(
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status=WorkflowNodeExecutionStatus.SUCCEEDED,
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inputs=variables,
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outputs=result
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)
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def _check_string(self, value: str, variable: str) -> str:
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"""
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Check string
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:param value: value
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:param variable: variable
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:param max_length: max length
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:return:
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"""
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if not isinstance(value, str):
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raise ValueError(f"{variable} in input form must be a string")
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if len(value) > MAX_STRING_LENGTH:
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raise ValueError(f'{variable} in input form must be less than {MAX_STRING_LENGTH} characters')
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return value.replace('\x00', '')
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def _check_number(self, value: Union[int, float], variable: str) -> Union[int, float]:
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"""
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Check number
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:param value: value
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:param variable: variable
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:return:
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"""
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if not isinstance(value, (int, float)):
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raise ValueError(f"{variable} in input form must be a number")
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if value > MAX_NUMBER or value < MIN_NUMBER:
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raise ValueError(f'{variable} in input form is out of range.')
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if isinstance(value, float):
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value = round(value, MAX_PRECISION)
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return value
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def _transform_result(self, result: dict, output_schema: dict[str, CodeNodeData.Output],
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prefix: str = '',
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depth: int = 1) -> dict:
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"""
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Transform result
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:param result: result
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:param output_schema: output schema
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:return:
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"""
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if depth > MAX_DEPTH:
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raise ValueError("Depth limit reached, object too deep.")
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transformed_result = {}
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for output_name, output_config in output_schema.items():
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if output_config.type == 'object':
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# check if output is object
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if not isinstance(result.get(output_name), dict):
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raise ValueError(
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f'Output {prefix}.{output_name} is not an object, got {type(result.get(output_name))} instead.'
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)
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transformed_result[output_name] = self._transform_result(
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result=result[output_name],
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output_schema=output_config.children,
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prefix=f'{prefix}.{output_name}' if prefix else output_name,
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depth=depth + 1
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)
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elif output_config.type == 'number':
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# check if number available
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transformed_result[output_name] = self._check_number(
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value=result[output_name],
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variable=f'{prefix}.{output_name}' if prefix else output_name
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)
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transformed_result[output_name] = result[output_name]
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elif output_config.type == 'string':
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# check if string available
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transformed_result[output_name] = self._check_string(
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value=result[output_name],
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variable=f'{prefix}.{output_name}' if prefix else output_name,
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)
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elif output_config.type == 'array[number]':
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# check if array of number available
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if not isinstance(result[output_name], list):
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raise ValueError(
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f'Output {prefix}.{output_name} is not an array, got {type(result.get(output_name))} instead.'
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)
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transformed_result[output_name] = [
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self._check_number(
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value=value,
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variable=f'{prefix}.{output_name}' if prefix else output_name
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)
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for value in result[output_name]
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]
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elif output_config.type == 'array[string]':
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# check if array of string available
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if not isinstance(result[output_name], list):
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raise ValueError(
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f'Output {prefix}.{output_name} is not an array, got {type(result.get(output_name))} instead.'
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)
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if len(result[output_name]) > MAX_STRING_ARRAY_LENGTH:
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raise ValueError(
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f'{prefix}.{output_name} in input form must be less than {MAX_STRING_ARRAY_LENGTH} characters'
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)
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transformed_result[output_name] = [
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self._check_string(
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value=value,
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variable=f'{prefix}.{output_name}' if prefix else output_name
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)
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for value in result[output_name]
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]
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else:
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raise ValueError(f'Output type {output_config.type} is not supported.')
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return transformed_result
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@ -0,0 +1,19 @@
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from core.workflow.entities.base_node_data_entities import BaseNodeData
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from core.workflow.entities.variable_entities import VariableSelector
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from pydantic import BaseModel
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from typing import Literal, Union
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class CodeNodeData(BaseNodeData):
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"""
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Code Node Data.
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"""
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class Output(BaseModel):
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type: Literal['string', 'number', 'object', 'array[string]', 'array[number]']
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children: Union[None, dict[str, 'Output']]
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variables: list[VariableSelector]
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answer: str
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code_language: str
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code: str
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outputs: dict[str, Output]
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@ -0,0 +1,55 @@
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import json
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import re
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PYTHON_RUNNER = """# declare main function here
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{{code}}
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# execute main function, and return the result
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# inputs is a dict, and it
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output = main(**{{inputs}})
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# convert output to json and print
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result = '''
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<<RESULT>>
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{output}
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<<RESULT>>
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'''
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print(result)
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"""
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class PythonTemplateTransformer:
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@classmethod
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def transform_caller(cls, code: str, inputs: dict) -> str:
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"""
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Transform code to python runner
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:param code: code
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:param inputs: inputs
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:return:
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"""
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# transform inputs to json string
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inputs_str = json.dumps(inputs, indent=4)
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# replace code and inputs
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runner = PYTHON_RUNNER.replace('{{code}}', code)
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runner = runner.replace('{{inputs}}', inputs_str)
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return runner
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@classmethod
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def transform_response(cls, response: str) -> dict:
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"""
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Transform response to dict
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:param response: response
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:return:
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"""
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# extract result
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result = re.search(r'<<RESULT>>(.*)<<RESULT>>', response, re.DOTALL)
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if not result:
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raise ValueError('Failed to parse result')
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result = result.group(1)
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return json.loads(result)
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