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156 lines
3.8 KiB
Markdown
156 lines
3.8 KiB
Markdown
# Function based flow
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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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User can directly use a function as flow entry.
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## Function as a flow
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Assume we have a file `flow_entry.py`:
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```python
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from promptflow.tracing import trace
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class Reply(TypedDict):
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output: str
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@trace
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def my_flow(question: str) -> Reply:
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# flow logic goes here
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pass
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```
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**Note** function decorated with `@trace` will emit trace can be viewed in UI provided by PromptFlow. Check [here](../tracing/index.md) for more information.
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## Flow test
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### Test via function call
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Since flow's definition is normal python function/callable class. We recommend user directly run it like running other scripts:
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```python
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from flow_entry import my_flow
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if __name__ == "__main__":
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output = my_flow(question="What's the capital of France?")
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print(output)
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```
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### Convert to a flow and test
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It's also supported to convert your function entry to a flow and test with prompt flow's ability.
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You can test with the following CLI:
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```bash
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# flow entry syntax: path.to.module:function_name
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pf flow test --flow flow_entry:my_flow --inputs question="What's the capital of France?"
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```
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**Note**: currently this command will generate a flow.flex.yaml in your working directory. Which will become the flow's entry.
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Check out a full example here: [basic](https://github.com/microsoft/promptflow/tree/main/examples/flex-flows/basic)
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### Chat with a flow
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Start a UI to chat with a flow:
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```bash
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pf flow test --flow flow_entry:my_flow --inputs question="What's the capital of France?" --ui
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```
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Check [here](../chat-with-a-flow/index.md) for more information.
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## Batch run
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User can also batch run a flow.
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::::{tab-set}
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:::{tab-item} CLI
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:sync: CLI
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```bash
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pf run create --flow "path.to.module:function_name" --data "./data.jsonl"
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```
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:::
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:::{tab-item} SDK
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:sync: SDK
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```python
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from path.to.module import my_flow
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# Note directly run function in `pf.run` is only supported in local PFClient for now
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pf.run(flow=my_flow, data="./data.jsonl")
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# user can also directly use entry in `flow` param for batch run
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pf.run(flow="path.to.module:function_name", data="./data.jsonl")
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```
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:::
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::::
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Learn more on this topic on [Run and evaluate a flow](../run-and-evaluate-a-flow/index.md)
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## Define a flow yaml
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User can write a YAML file with name `flow.flex.yaml` manually or save a function/callable entry to YAML file.
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This is required for advanced scenario like deployment or run in cloud.
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A flow YAML may look like this:
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```yaml
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$schema: https://azuremlschemas.azureedge.net/promptflow/latest/Flow.schema.json
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entry: path.to.module:function_name
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sample:
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inputs:
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question: "what's the capital of France?"
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```
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## Batch run with YAML
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User can batch run a flow with YAML.
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::::{tab-set}
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:::{tab-item} CLI
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:sync: CLI
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```bash
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# against flow file
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pf run create --flow "path/to/flow/flow.flex.yaml" --data "./data.jsonl"
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# against a folder if it has a flow.flex.yaml file
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pf run create --flow "path/to/flow" --data "./data.jsonl"
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```
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:::
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:::{tab-item} SDK
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:sync: SDK
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```python
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pf = PFClient()
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pf.run(flow="./flow.flex.yaml", data="./data.jsonl")
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```
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:::
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::::
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## Deploy a flow
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User can serve a flow as a http endpoint locally or deploy it to multiple platforms.
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```bash
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# serve locally from a folder if it has a flow.flex.yaml file
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pf flow serve --source "path/to/flow/dir" --port 8088 --host localhost
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# serve locally from certain file
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pf flow serve --source "./flow.flex.yaml" --port 8088 --host localhost
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```
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Learn more: [Deploy a flow](../deploy-a-flow/index.md).
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## Next steps
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- [Class based flow](./class-based-flow.md)
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- [Input output format](./input-output-format.md)
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- [Function based flow sample](https://github.com/microsoft/promptflow/blob/main/examples/flex-flows/basic/README.md)
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