Develop chat flow#

Experimental feature

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

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.

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