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126 lines
4.6 KiB
Plaintext
126 lines
4.6 KiB
Plaintext
---
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dimensions:
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type:
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primary: implementation
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detail: advanced
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level: advanced
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standard_title: Reverse Invocation Node
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language: en
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title: Node
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description: This document describes how plugins can reverse invoke the functionality
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of Chatflow/Workflow application nodes within the Dify platform. It primarily covers
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the invocation methods for two specific nodes, ParameterExtractor and QuestionClassifier.
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The document details the entry points, interface parameters, and example code for
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invoking these two nodes.
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---
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Reverse invoking a Node means that a plugin can access the capabilities of certain nodes within a Dify Chatflow/Workflow application.
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The `ParameterExtractor` and `QuestionClassifier` nodes in `Workflow` encapsulate complex Prompt and code logic, enabling tasks that are difficult to solve with hardcoding through LLMs. Plugins can call these two nodes.
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### Calling the Parameter Extractor Node
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#### **Entry Point**
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```python
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self.session.workflow_node.parameter_extractor
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```
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#### **Interface**
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```python
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def invoke(
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self,
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parameters: list[ParameterConfig],
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model: ModelConfig,
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query: str,
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instruction: str = "",
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) -> NodeResponse
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pass
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```
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Here, `parameters` is a list of parameters to be extracted, `model` conforms to the `LLMModelConfig` specification, `query` is the source text for parameter extraction, and `instruction` provides any additional instructions that might be needed for the LLM. For the structure of `NodeResponse`, please refer to this [document](/plugin_dev_en/0411-general-specifications.en.mdx#noderesponse).
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#### **Use Case**
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To extract a person's name from a conversation, you can refer to the following code:
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```python
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from collections.abc import Generator
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from dify_plugin.entities.tool import ToolInvokeMessage
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from dify_plugin import Tool
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from dify_plugin.entities.workflow_node import ModelConfig, ParameterConfig, NodeResponse # Assuming NodeResponse is importable
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class ParameterExtractorTool(Tool):
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def _invoke(
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self, tool_parameters: dict
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) -> Generator[ToolInvokeMessage, None, None]:
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response: NodeResponse = self.session.workflow_node.parameter_extractor.invoke(
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parameters=[
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ParameterConfig(
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name="name",
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description="name of the person",
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required=True,
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type="string",
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)
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],
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model=ModelConfig(
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provider="langgenius/openai/openai",
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name="gpt-4o-mini",
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completion_params={},
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),
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query="My name is John Doe",
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instruction="Extract the name of the person",
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)
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# Assuming NodeResponse has an 'outputs' attribute which is a dictionary
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extracted_name = response.outputs.get("name", "Name not found")
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yield self.create_text_message(extracted_name)
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```
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### Calling the Question Classifier Node
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#### **Entry Point**
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```python
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self.session.workflow_node.question_classifier
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```
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#### **Interface**
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```python
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def invoke(
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self,
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classes: list[ClassConfig], # Assuming ClassConfig is defined/imported
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model: ModelConfig,
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query: str,
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instruction: str = "",
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) -> NodeResponse:
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pass
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```
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The interface parameters are consistent with `ParameterExtractor`. The final result is stored in `NodeResponse.outputs['class_name']`.
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{/*
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Contributing Section
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DO NOT edit this section!
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It will be automatically generated by the script.
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*/}
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<CardGroup cols="2">
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<Card
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title="Edit this page"
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icon="pen-to-square"
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href="https://github.com/langgenius/dify-docs-mintlify/edit/main/plugin_dev_en/9243-reverse-invocation-node.en.mdx"
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>
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Help improve our documentation by contributing directly
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</Card>
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<Card
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title="Report an issue"
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icon="github"
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href="https://github.com/langgenius/dify-docs-mintlify/issues/new?title=Documentation%20Issue%3A%20reverse-invocation-node&body=%23%23%20Issue%20Description%0A%3C%21--%20Please%20briefly%20describe%20the%20issue%20you%20found%20--%3E%0A%0A%23%23%20Page%20Link%0Ahttps%3A%2F%2Fgithub.com%2Flanggenius%2Fdify-docs-mintlify%2Fblob%2Fmain%2Fplugin_dev_en%2F9243-reverse-invocation-node.en.mdx%0A%0A%23%23%20Suggested%20Changes%0A%3C%21--%20If%20you%20have%20specific%20suggestions%20for%20changes%2C%20please%20describe%20them%20here%20--%3E%0A%0A%3C%21--%20Thank%20you%20for%20helping%20improve%20our%20documentation%21%20--%3E"
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>
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Found an error or have suggestions? Let us know
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