What the Data for This Category Looks Like
Data sources for this category include the national primary and secondary school student status management system, local enrollment platforms, household registration and property data, and school academic affairs systems. Update frequency is daily. Daily documents include enrollment application forms, student status information forms, transfer applications, enrollment plans, admission rosters, and student status change approval forms. Core fields focus on student identity, admission eligibility, and student status transfer status. Data is linked to multiple departmental business systems, with no unified single-document format. Cross-system consistency verification is required.
Constraints Imposed on Conversation Logs and Audit
Because data updates daily and is linked to multiple departmental systems, conversation logs must bind specific business identifiers for precise traceability. Documents involve sensitive information such as student status and admission eligibility. The audit process must fully record the entire interaction flow, and avoid missing key verification steps. Errors in operations such as student status changes and admission results directly affect student enrollment and progression. Audits must allow traceability of policy explanations and qualification verification steps in conversations, to ensure every operation is traceable. Additionally, linkage of data from multiple systems requires logs to support field formats from different sources, to facilitate cross-system audit verification.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Conversation log association identifier | Bind chatId, responseChatItemId, student ID number, and enrollment batch fields | Link business data and conversation records, enable quick retrieval of audit logs by student ID or enrollment batch, and comply with FastGPT v4.17.0 interaction specifications |
| Log detail storage switch | Enable the detail parameter | Store complete conversation context and response content, to meet audit requirements for checking interaction details |
| Log retention period | 180–365 days | Comply with audit traceability period requirements in the education public service sector |
| Sensitive information desensitization rules | Set based on actual testing | Cover exclusive sensitive fields such as student ID numbers, property addresses, and student ID numbers, to avoid data leaks |
| Log query timeout threshold | 600 seconds | Adapt to audit query response speeds of education systems, and avoid query timeouts that interrupt operations |
| Audit trigger timing | Trigger after each round of conversation ends | Cover the complete interaction flow, and avoid missing key conversation steps |
Three Common Misconfigurations
- Conversation history records are not loaded, leading to failed context association.
chatIdandresponseChatItemIdare not correctly bound to business identifiers corresponding to student status or enrollment batches, causing historical conversations to fail to match. - Audit logs do not fully record interaction details, making key verification steps untraceable. The
detailparameter is not enabled to store complete conversation content, and only simplified response summaries are saved. - FastGPT containers fail to start after Docker deployment, with no valid error logs. Docker Compose configuration has mounting directory permissions that do not adapt to local business data storage paths, or resource allocation is insufficient.
How to Verify Successful Configuration
- Initiate a conversation that includes student status information queries, and check whether logs contain records associating
chatIdwith the corresponding student ID number. - Open the audit log detail page, verify that complete conversation context and response content are stored, and confirm the
detailparameter is active. - Attempt to log in to the system with a regular administrator role, confirm that full audit logs cannot be viewed, and verify that permission configurations are active.
- Check the Docker container running status, confirm that the FastGPT container has no abnormal exits, and verify that deployment configurations are error-free.
The values provided here are common starting points, and should be evaluated 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.