What Data for This Category Looks Like
Data for this category originates from the engineering construction project approval management system, construction drawing review system, enterprise qualification database, and public credit platform. The update frequency is daily. Daily documents include construction permit application materials, construction drawing review qualification certificates, quality and safety supervision procedures, and completion acceptance record forms. Data fields cover approval node status, participating construction unit qualifications, project leader information, material record numbers, and other relevant items. All fields come from standard output of official business systems, with no custom special units.
Constraints on Citation Sources and Traceability
Data for this category mostly comes from official business systems and is updated daily. Citation and traceability processes must use the latest version of approval materials to avoid citing expired information. Daily documents cover the full engineering approval workflow. Material fields across different process links have clear corresponding relationships. During traceability, links must be established to specific approval nodes and material numbers to ensure citation accuracy. Fields such as participating construction unit qualifications and personnel information are sourced from a unified qualification database. During retrieval, field dimensions must be strictly matched to prevent cross-category confusion. Incorrect citations may delay approval processes, so the traceability link must be bound to the unique identifier of the original data.
Configuration Settings
Configuration references for FastGPT v4.17.0 are listed below:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
quoteMaxToken | 8000–12000 token | Adapts to the average length of engineering approval documents, avoiding truncation of key approval process and qualification information |
responseData | Enable material number and approval node fields | Binds unique identifiers and business scenarios of documents in this category, ensuring traceability can accurately locate specific approval materials |
detail | Enabled | Displays complete source document paths and field information, meeting the requirements for rigor of evidence in party building learning Q&A |
| Single search limit | Top 3 results | Core documents for this category are concentrated in key links of the approval process, avoiding excessive results that distract from learning focus |
| Maximum context | 14000–16000 characters | Accommodates content from multiple associated approval materials, ensuring the integrity of Q&A logic |
Three Common Configuration Mistakes
- Phenomenon: The Q&A result only displays 1 knowledge base citation, and cannot show multiple approval material sources. Cause: The
quoteMaxTokenor single search limit configuration was not adjusted, limiting the number of recalled documents. - Phenomenon: An insufficient citation quota prompt is displayed when calling the knowledge base. Cause: The knowledge base synchronization task was not configured according to the daily update frequency, causing redundant old data to occupy too much quota.
- Phenomenon: The cited approval material fields are empty or cannot be traced back to the original system. Cause: The field binding configuration of
responseDatawas not enabled, and the unique identifier field of the engineering approval system was not associated.
How to Verify Successful Configuration
- Launch a party building learning-related question, such as a query about the approval basis for engineering construction permits. Check if the citation list below the answer includes multiple approval-related documents.
- Review citation details to confirm that each citation is marked with category-specific fields including material numbers and approval nodes.
- Verify that returned data includes the original data identifier from the engineering approval system, ensuring the traceability link is complete.
- Adjust the value of
quoteMaxToken, then observe if the number of recalled documents matches the configured result.
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 2026-09-28.