What the data for this category looks like
Engineering consulting supervision declaration materials and file review data mainly come from documents such as project approval replies, supervision weekly reports, on-site acceptance records, and rectification receipts for submission. Update rhythm is adjusted in phases with project progress, and common update cycles are weekly or monthly. Documents exist in the form of structured fields plus attachments. Core fields include project ID, supervision unit, submission date, rectification list, and acceptance conclusion. Units involve square meters, construction days, project cost in ten thousand yuan, and other units. Attachments are mostly formal reports in PDF or Word format.
What constraints these characteristics impose on the citation sources and traceability link
The project-based nature of engineering consulting supervision data requires traceability to be accurately bound to project IDs and submission nodes, rather than broadly referencing general documents. The fact that original documents are stored on third-party websites requires adding external links for reviewers to directly verify. The phased update rhythm requires the knowledge base to synchronize data incrementally by project, to avoid citing outdated old file materials. The length and field complexity of individual documents require focusing on core information when citing, to avoid redundant content interfering with review judgments.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
quoteMaxToken | 800–1200 token | The valid content of a single engineering consulting supervision declaration document is usually around 1000 characters. Matching the corresponding token count can fully display the citation basis |
responseData | Return top 3 related documents | File review should focus on materials for the current submission batch. Excessive results will distract reviewers |
detail | Display project ID and submission date fields | The core identifiers of engineering consulting supervision documents are project ID and submission node, which facilitate quick location of corresponding files |
| Citation link configuration | Bind the original document address from external storage | Original supervision declaration materials are stored on third-party websites. Links need to be added for reviewers to trace and verify |
| Context loading timeout | 600 seconds | File retrieval for large supervision projects requires loading multiple related documents. A reasonable timeout threshold can avoid mid-process interruptions |
Three Common Misconfigurations
- Phenomenon: AI responses do not include external links to original documents, preventing reviewers from directly jumping to verify. Reason: Relevant settings for binding third-party storage addresses are not configured. Documents are only uploaded to the FastGPT knowledge base, and the source address is not linked.
- Phenomenon: The number of related documents returned by retrieval is too large, exceeding the scope required for review. Reason: The return limit for
responseDatais not set correctly, and the default excessive value is used. - Phenomenon: Cited supervision document content is truncated, and core fields are missing. Reason: The value of
quoteMaxTokenis too small, and it does not cover the valid citation content of a single supervision document.
How to Confirm Proper Configuration
- Submit a query about the submission materials of a specific supervision project, and check if external links to the corresponding documents are attached at the end of the response.
- Review the source information cited in the response, and confirm that core fields such as project ID and submission date are included.
- Count the number of related documents returned in the response, and confirm that it meets the preset quantity requirements.
- Test citation of large-format supervision documents, and check if the content is complete and not truncated.
Note: The configuration values listed are common starting points. They should be evaluated against the user’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.