Input output format

Experimental feature

This is an experimental feature, and may change at any time. Learn more.

Supported types

Promptflow officially support below types in flow.

• Inputs: primitive types(int, float, bool, str), dict, TypedDict, list

• Outputs: primitive types(int, float, bool, str), dict, TypedDict, dataclass, list

• Init: primitive types(int, float, bool, str), Connection(including custom connections), ModelConfiguration, TypedDict, list

If user has non-supported types in code/YAML, validation error will be raised.

YAML support

Here’s a mapping from python types to YAML types:

Python Type	YAML type	Description
int	int	Integer type
float	double	Double type
bool	bool	Boolean type
str	string	String type
list	list	List type
dict	object	Dictionary type
TypedDict	object	Typed dictionary type
dataclass	object	Data class type
CustomConnection	Connection	Connection type, will be handled specially
OpenAIModelConfiguration	OpenAIModelConfiguration	Model configuration type, will be handled specially
AzureOpenAIModelConfiguration	AzureOpenAIModelConfiguration	Model configuration type, will be handled specially

Here’s an sample YAML for above supported types.

inputs:
  int_input:
    type: int
  float_input:
    type: double
  bool_input:
    type: bool
  string_input:
    type: string
  dict_input:
    type: object
  list_input:
    type: list
outputs:
  int_output:
    type: int
  float_output:
    type: double
  bool_output:
    type: bool
  string_output:
    type: string
  dict_output:
    type: object
  list_output:
    type: list
init:
  int_init:
    type: int
  float_init:
    type: double
  bool_init:
    type: bool
  string_init:
    type: string
  open_ai_connection:
    type: OpenAIConnection
  azure_open_ai_connection:
    type: AzureOpenAIConnection
  custom_connection:
    type: CustomConnection
  open_ai_model_config:
    type: OpenAIModelConfiguration
  azure_open_ai_model_config:
    type: AzureOpenAIModelConfiguration

Unsupported type sample

# using unsupported types in flow will fail with validation error
class MyOwnClass:
  pass

class MyFlow:
    # not supported
    def __init__(self, my_own_obj: MyOwnClass):
        pass

# not supported
def my_flow(my_own_obj: MyOwnClass):
    pass

Sample validation error: “The input ‘my_own_obj’ is of a complex python type. Please use a dict instead.”

Stream

Stream is supported in flow, you just need to return a generator type in your function. Reference openai doc on how to do it using plain python code: how_to_stream_completions.

Reference this flow sample for details.