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66 lines
3.3 KiB
Markdown
66 lines
3.3 KiB
Markdown
# Develop chat flow
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From this document, you can learn how to develop a chat flow by writing a flow yaml from scratch. You can
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find additional information about flow yaml schema in [Flow YAML Schema](../../reference/flow-yaml-schema-reference.md).
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## Flow input data
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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.
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- **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.
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- **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.
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An example of chat history:
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```python
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[
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{"inputs": {"question": "What types of container software there are?"}, "outputs": {"answer": "There are several types of container software available, including: Docker, Kubernetes"}},
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{"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..."}},
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]
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```
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You can set **is_chat_input**/**is_chat_history** to **true** to add chat_input/chat_history to the chat flow.
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```yaml
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inputs:
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chat_history:
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type: list
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is_chat_history: true
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default: []
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question:
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type: string
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is_chat_input: true
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default: What is ChatGPT?
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```
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For more information see [develop the flow using different tools](./develop-standard-flow.md#flow-input-data).
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## Develop the flow using different tools
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In one flow, you can consume different kinds of tools. We now support built-in tool like
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[LLM](../../reference/tools-reference/llm-tool.md), [Python](../../reference/tools-reference/python-tool.md) and
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[Prompt](../../reference/tools-reference/prompt-tool.md) and
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third-party tool like [Serp API](../../reference/tools-reference/serp-api-tool.md),
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[Vector Search](../../reference/tools-reference/vector_db_lookup_tool.md), etc.
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For more information see [develop the flow using different tools](./develop-standard-flow.md#develop-the-flow-using-different-tools).
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## Chain your flow - link nodes together
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Before linking nodes together, you need to define and expose an interface.
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For more information see [chain your flow](./develop-standard-flow.md#chain-your-flow---link-nodes-together).
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## Set flow output
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**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.
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You can set **is_chat_output** to **true** to add chat_output to the chat flow.
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```yaml
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outputs:
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answer:
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type: string
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reference: ${chat.output}
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is_chat_output: true
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```
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