Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
The core data for this specific category comes from the random inspection and public disclosure supervision platform, enterprise credit information public disclosure system, law enforcement officer directory, and industry supervision system. Daily documents cover inspection plans, inspection target lists, inspection item lists, on-site inspection records, rectification notices, and inspection result disclosures. These include structured fields such as unified social credit codes, law enforcement officer IDs, inspection item entries, rectification time limits, and free-form text content. The data update frequency is typically monthly. Core business databases must regularly synchronize the latest supervision targets and law enforcement officer information.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Data sources are scattered and require regular updates. Multi-turn dialogue must support dynamic injection of monthly updated business data, to avoid using expired inspection targets or law enforcement officer information. Documents contain structured fields and free-form text. Prompts must clearly distinguish task boundaries between required field verification and scenario-based description generation. Law enforcement documents have strict compliance requirements. Multi-turn dialogue must verify key fields round by round, to avoid issues such as missed disclosures or non-compliant selections.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Conversation Link Identifier | chatId | Used to associate multi-turn dialogue historical context, ensuring dialogue coherence for law enforcement scenarios |
| Context Window Limit | 8000–12000 token | Documents in this category are mostly structured lists and mixed text, requiring capacity for multi-turn law enforcement scenario dialogues and historical records |
variables | Preset exclusive variables such as "law enforcement officer directory", "inspection item list", "inspection result template" | Fixed business data must be injected into dialogue context to avoid repeated external interface calls |
messages | Arranged in the order of "system prompt → initial user request → intermediate verification → final output" | Regulatory documents must strictly follow law enforcement procedures, clarifying roles and tasks for each dialogue turn |
| Maximum Single Dialogue Turns | 6–8 rounds | Drafting a single inspection document usually covers three core links: plan generation, target matching, and result entry. Excessive rounds will increase context redundancy |
| Knowledge Base Update Trigger Rule | Full synchronization triggered monthly | The core data update frequency for this category is monthly, matching the business update rhythm |
Three Common Mistakes
- Issue: In a dialogue chain orchestrated via HTTP requests, the document content generated by the interface is not displayed in the front-end dialogue window. Cause: No context injection rule for output fields configured via
variables, resulting in returned content not being included in dialogue context. - Issue: When using a locally deployed vector model, index recall for inspection target lists shows no progress. Cause: No dedicated chunking strategy set for structured lists, resulting in loss of key identification fields such as unified social credit codes during long text splitting.
- Issue: On-site inspection photos uploaded during the dialogue link are not parsed as valid input. Cause: Full-modal dialogue configuration is not enabled, and only a plain text interaction interface is called.
How to Confirm Proper Configuration
- Initiate a dialogue that includes "generate monthly inspection plan", check if the
messagessequence includes system prompts, user requests, and preset business variables. - Trigger a knowledge base synchronization task, confirm that the synchronization cycle matches the monthly update rhythm.
- Initiate multi-turn dialogue, verify that output content includes required fields such as inspection target lists and law enforcement officer information.
- Test the HTTP request orchestration process, confirm that returned structured document content can be displayed normally in the dialogue window.
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.