What the data for this category looks like
The data for this category primarily comes from Figma or Axure prototype files, internal team design systems, user feedback, and usability test records. Daily deliverable documents include interactive prototypes, page flowcharts, component descriptions, and review records. Data update frequency is typically once per week or aligned with product version iterations. The document structure centers on page hierarchy, operation nodes, and state transitions as core fields. There are no uniform mandatory units, and some fields are updated synchronously with component library version changes.
Constraints on Multi-turn Dialogue and Prompt Engineering
Data sources for prototyping and interaction design are scattered and have significant format differences. Multi-turn dialogue must adapt to different export structures of Figma and Axure. Prompts must clearly distinguish field rules for the two file types. Data update frequency follows product version iterations. Overly long dialogue contexts may contain outdated prototype content, so the context window range must be reasonably limited. Review records are closely linked to prototype files. The dialogue process must automatically associate the corresponding prototype fragment of the current review node to avoid cross-node confusion. Additionally, document fields have no unified units, so prompts must be compatible with custom naming rules used by different designers.
Configuration Settings
This guide is written for FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique identifier of the current prototype review task | Ensure independent context for each review session, prevent cross-task data confusion |
messages | Retain the last 8 user-AI interaction records, attach associated prototype fragments | Balance context volume and response latency, align with the update rhythm of prototype data |
variables | Pass the current page ID, prototype version number, and review node ID | Enable the model to accurately match the currently discussed design content, reduce ambiguity |
| Maximum context window | 6000–10000 token, calibrated based on actual testing | Adapt to the total character count of prototype documents and review records, prevent context overflow |
| Context retention duration | 7 days | Align with the weekly update frequency of prototype data, automatically clean expired sessions |
Three Common Configuration Errors
- Issue: The AI’s response does not match the currently bound prototype page, and no improvement is seen after multiple prompt adjustments. Cause:
chatIdis not bound to the current prototype review task, causing context to mix historical data from other sessions. - Issue: The conversation record ID of the previous AI reply cannot be obtained when calling the interface. Cause: The context indexing rule for the
messagesparameter is not configured correctly, or a validchatIdis not generated during session initialization. - Issue: Review records from other users appear in the shared application chat dialog box. Cause: User identification is not bound to
chatId, resulting in unisolated session permissions.
How to Confirm Correct Configuration
- Launch a review dialogue, enter "Please sort out the operation path of the current page", and verify that the reply includes the page node name of the currently bound prototype.
- View the session management interface, confirm that each review task corresponds to a unique
chatId, with no duplicate or cross-user session records. - After 7 days have passed, verify that expired sessions have been automatically cleaned. If not, adjust the context retention duration configuration.
- Call the "Get Conversation Record List" interface, enter the offset parameter, and verify that session records in the specified range can be correctly filtered.
The values provided are common starting points and should be measured against the samples used in the target deployment.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.