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112 lines
4.1 KiB
Markdown
112 lines
4.1 KiB
Markdown
# Input output format
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:::{admonition} Experimental feature
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This is an experimental feature, and may change at any time. Learn [more](../faq.md#stable-vs-experimental).
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:::
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## Supported types
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Promptflow officially support below types in flow.
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- Inputs: primitive types(`int`, `float`, `bool`, `str`), `dict`, `TypedDict`, `list`
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- Outputs: primitive types(`int`, `float`, `bool`, `str`), `dict`, `TypedDict`, `dataclass`, `list`
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- Init: primitive types(`int`, `float`, `bool`, `str`), `Connection`(including custom connections), `ModelConfiguration`, `TypedDict`, `list`
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If user has non-supported types in code/YAML, validation error will be raised.
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### YAML support
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Here's a mapping from python types to YAML types:
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Python Type | YAML type | Description
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--------------------------------|----------------------------------------------------------------------------------|----------------------------------------------------
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`int` | int | Integer type
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`float` | double | Double type
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`bool` | bool | Boolean type
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`str` | string | String type
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`list` | list | List type
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`dict` | object | Dictionary type
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`TypedDict` | object | Typed dictionary type
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`dataclass` | object | Data class type
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`CustomConnection` | [Connection](../../concepts/concept-connections.md) | Connection type, will be handled specially
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`OpenAIModelConfiguration` | [OpenAIModelConfiguration](./model-config.md#openaimodelconfiguration) | Model configuration type, will be handled specially
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`AzureOpenAIModelConfiguration` | [AzureOpenAIModelConfiguration](./model-config.md#azureopenaimodelconfiguration) | Model configuration type, will be handled specially
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Here's an sample YAML for above supported types.
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```yaml
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inputs:
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int_input:
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type: int
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float_input:
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type: double
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bool_input:
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type: bool
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string_input:
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type: string
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dict_input:
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type: object
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list_input:
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type: list
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outputs:
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int_output:
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type: int
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float_output:
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type: double
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bool_output:
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type: bool
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string_output:
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type: string
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dict_output:
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type: object
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list_output:
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type: list
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init:
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int_init:
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type: int
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float_init:
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type: double
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bool_init:
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type: bool
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string_init:
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type: string
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open_ai_connection:
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type: OpenAIConnection
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azure_open_ai_connection:
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type: AzureOpenAIConnection
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custom_connection:
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type: CustomConnection
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open_ai_model_config:
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type: OpenAIModelConfiguration
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azure_open_ai_model_config:
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type: AzureOpenAIModelConfiguration
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```
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### Unsupported type sample
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```python
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# using unsupported types in flow will fail with validation error
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class MyOwnClass:
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pass
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class MyFlow:
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# not supported
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def __init__(self, my_own_obj: MyOwnClass):
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pass
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# not supported
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def my_flow(my_own_obj: MyOwnClass):
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pass
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```
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Sample validation error: "The input 'my_own_obj' is of a complex python type. Please use a dict instead."
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## Stream
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Stream is supported in flow, you just need to return a generator type in your function.
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Reference openai doc on how to do it using plain python code: [how_to_stream_completions](https://cookbook.openai.com/examples/how_to_stream_completions).
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Reference this flow [sample](../../tutorials/chat-stream-with-flex-flow.ipynb) for details.
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