What This Category of Data Looks Like
Reference only; verify against the target FastGPT release and deployment documentation.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Business data is categorized by specific service items. Multi-turn dialogue must first identify the user’s current business needs, then match the standardized process for the corresponding item. A unique dialogue identifier must be bound to trace progress. Data fields have clear format and unit requirements. Prompts must strictly limit the scope of AI output to avoid creating non-standardized information. Data updates occur frequently, so knowledge bases must be synchronized regularly. Multi-turn dialogue context must filter expired process information to prevent guiding users to use updated processing rules. Users may also upload JPG format material images, so image content recognition and verification must be supported.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 800–1200 characters | Multi-turn dialogue for a single urban gas service application typically has 2-3 rounds. The context must retain the current business type and information already provided by the user, avoiding redundancy |
chatId Binding Rule | Bind to the unique work order number of the user’s application | Ensure dialogue logs for each service can be traced, matching the user’s actual application progress |
messages Context Retention Rule | Only retain dialogue rounds related to the current service item, discard expired irrelevant dialogue | Avoid context pollution, ensuring the AI’s process guidance matches the current business |
variables Parameter Configuration | Pre-set three variables: business item, required materials, processing time limit | Quickly call standardized data for the corresponding business, reducing prompt redundancy |
| Input Content Upper Limit Interception | 1000 tokens, calibrated through actual testing | Avoid exceeding the input limits of the AI model, intercepting overly long input errors in advance |
| Image Input Support | Enable the image recognition function of the AI dialogue node | Support users uploading JPG format application materials, matching the verification rules for corresponding materials |
Three Common Mistakes
- Phenomenon: Dialogue logs cannot be associated with specific users or service work orders. Cause:
chatIdis not bound to the service work order number, resulting in logs without unique identifiers. - Phenomenon: Errors or no response occur after entering overly long text. Cause: No input content upper limit interception rule is configured, and the length of user input is not verified in advance.
- Phenomenon: The AI cannot recognize JPG materials uploaded by users. Cause: The image recognition function of the AI dialogue node is not enabled, and the prompt does not indicate that JPG format application materials are acceptable.
How to Verify Successful Configuration
- Launch a multi-turn dialogue for a simulated gas account opening service, check if the dialogue log is bound to a unique
chatIdand service work order number. - Enter test text exceeding 1000 tokens, confirm that the system intercepts and prompts that the input is too long in advance.
- Attempt to delete the current dialogue record, confirm that the operation can be executed normally.
- Upload a JPG format business license image, check if the AI can recognize it and associate it with the material verification rules required for account opening.
The values provided here are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.