What the data for this category looks like
Daily documents for prototyping and interaction design include interactive prototypes, page flowcharts, component descriptions, and review records. Common data sources are Figma or Axure files, internal design systems, user feedback, and usability test records. Documents are organized by chapter, with each group containing a chapter title, corresponding page link, and function overview. Updates are synced weekly or with each version iteration.
What constraints these characteristics impose on knowledge base retrieval and recall
Because documents are grouped with associated relationships, retrieval must prevent splitting of chapter titles, links, and descriptions from the same group. If split, operations staff cannot access complete operational path information. Prototype documents have a high update frequency, so incremental update recall logic is required to avoid matching duplicate or expired content. Additionally, on-call operations questions often use colloquial language to ask about operational paths. Queries must be optimized to match the structured fields of prototypes and improve recall accuracy.
Configuration settings
The following configurations are based on the interface and parameter logic of FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Similarity threshold | 0.75–0.85 | Prototype documents have high semantic relevance; filter low-match results to avoid recalling irrelevant review records |
| Maximum recall count per query | Top 8 | On-call operations questions typically correspond to 1-2 core prototype pages; excessive results interfere with context comprehension |
| Reranking switch | Enabled | Prototype document fragments have strong relevance; reranking optimizes result ordering to display more relevant content first |
| Query optimization switch | Enabled | Operations ticket questions use colloquial language; query optimization improves matching of prototype chapter titles and component descriptions |
| Collection ID filter | Specify the collection ID of the corresponding design knowledge base | Isolate prototype documents across projects to prevent accidental recall of non-current project content |
| Document structure matching | Enabled | Match the hierarchical structure of prototypes to ensure associated chapters, links, and descriptions are recalled together |
Three common configuration errors
- After uploading grouped prototype documents, recall results split chapter titles and their corresponding page links. This happens when the document structure matching configuration is not enabled. The system treats grouped content as independent fragments, failing to provide complete operational path information.
- Retrieval results include prototype documents from non-current projects. This occurs when the collection ID filter is not configured. The system recalls all documents in the knowledge base, introducing irrelevant interfering content.
- After submitting an operations ticket query, a large number of low-match review records are returned. This happens when the similarity threshold is set too low, failing to filter document fragments unrelated to the query.
How to verify correct configuration
- Upload a set of prototype documents containing chapter titles, page links, and function overviews. Submit a simulated operations query and confirm all associated information for the group is returned without splitting.
- View retrieval logs to confirm only documents matching the specified collection ID are recalled, with no prototype content from other projects.
- Adjust the similarity threshold below 0.75, verify that low-match irrelevant content is filtered, then revert to the original threshold to confirm results return to normal.
- Disable the query optimization switch, submit a colloquial query, and compare results with the switch enabled to confirm improved matching accuracy after optimization.
The values provided 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 2026-10-19.