docs/guides/chat/feature_overview_and_creation.md
Chat is used to create dataset-based question-answering applications. After configuring the datasets, large language model, system prompt, and retrieval parameters for a Chat, users can ask questions based on dataset content in the chat interface.
Chat supports dataset retrieval, citation display, keyword analysis, multi-turn conversation optimization, cross-language search, web search, and other capabilities.
After creating a Chat, configure its datasets, model, system prompt, and retrieval parameters for the actual business scenario before using it to answer questions. You can modify these settings later.
You do not need to complete every setting when creating a Chat. You can return to the corresponding Chat from the Chat list and update its configuration later.
You can set the following basic information for a Chat:
Complete the main Chat settings according to the actual scenario:
Save the setting and test it in the chat window.
Start with the default parameters for a basic test. Then gradually adjust the retrieval parameters and system prompt based on the quality of the actual answers.
You can modify an existing Chat at any time. Find the Chat in the Chat list, open Chat setting, update its datasets, model, system prompt, or retrieval parameters, and save the changes.
After changing the configuration, rerun tests with representative questions to confirm that the new settings meet expectations.