microsoft--promptflow/docs/how-to-guides/develop-a-dag-flow/develop-chat-flow.md

Develop chat flow

From this document, you can learn how to develop a chat flow by writing a flow yaml from scratch. You can find additional information about flow yaml schema in Flow YAML Schema.

Flow input data

The most important elements that differentiate a chat flow from a standard flow are chat input and chat history. A chat flow can have multiple inputs, but chat history and chat input are required inputs in chat flow.

• Chat Input: Chat input refers to the messages or queries submitted by users to the chatbot. Effectively handling chat input is crucial for a successful conversation, as it involves understanding user intentions, extracting relevant information, and triggering appropriate responses.

• Chat History: Chat history is the record of all interactions between the user and the chatbot, including both user inputs and AI-generated outputs. Maintaining chat history is essential for keeping track of the conversation context and ensuring the AI can generate contextually relevant responses. Chat history is a special type of chat flow input, that stores chat messages in a structured format.

  An example of chat history:

  [
    {"inputs": {"question": "What types of container software there are?"}, "outputs": {"answer": "There are several types of container software available, including: Docker, Kubernetes"}},
    {"inputs": {"question": "What's the different between them?"}, "outputs": {"answer": "The main difference between the various container software systems is their functionality and purpose. Here are some key differences between them..."}},
  ] 
  

You can set is_chat_input/is_chat_history to true to add chat_input/chat_history to the chat flow.

inputs:
  chat_history:
    type: list
    is_chat_history: true
    default: []
  question:
    type: string
    is_chat_input: true
    default: What is ChatGPT?

For more information see develop the flow using different tools.

Develop the flow using different tools

In one flow, you can consume different kinds of tools. We now support built-in tool like LLM, Python and Prompt and third-party tool like Serp API, Vector Search, etc.

For more information see develop the flow using different tools.

Chain your flow - link nodes together

Before linking nodes together, you need to define and expose an interface.

For more information see chain your flow.

Set flow output

Chat output is required output in the chat flow. It refers to the AI-generated messages that are sent to the user in response to their inputs. Generating contextually appropriate and engaging chat outputs is vital for a positive user experience.

You can set is_chat_output to true to add chat_output to the chat flow.

outputs:
  answer:
    type: string
    reference: ${chat.output}
    is_chat_output: true