What the Data for This Category Looks Like
Data for this category comes from the national integrated government service platform item database, administrative licensing item list, departmental business approval systems, and electronic certificate database. The update frequency is daily. Daily processed documents include service guides, application forms, commitment letters, acceptance notices, correction notification letters, administrative licensing approval decisions, license certificates, and more. Documents for each licensing item include fields such as the item's unique identifier, legal setting basis, detailed handling conditions, application material list, and others. Q&A must be conducted in strict accordance with legal requirements.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Since data sources cover multiple government systems and are updated daily, multi-turn dialogue must clearly distinguish document contexts from different sources to avoid cross-system data confusion. Fields in legal document types strictly correspond to legal requirements. Prompts must mandate that answers cite specific document sources and clauses when responding. Q&A results for administrative licensing and approval are directly linked to approval workflows. Multi-turn dialogue must gradually guide users to confirm the match between submitted application materials and the legal list, to avoid missing legal handling conditions. Daily updated data also requires regular refreshes of the knowledge base vector database, to ensure Q&A content always aligns with latest administrative licensing item adjustments.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Context Window | First 10 turns of dialogue + most recent 8000 characters of knowledge base retrieved content | Matches multi-turn correction communication scenarios for administrative licensing items, prevents context overflow |
variables | Preset "administrative licensing item code" and "application material list" variables | Used to quickly bind specific item information submitted by users, reduces repeated input |
chatId | Bind unique identifier of user sessions | Ensures context isolation for multi-turn dialogue, approval consultations from different users do not interfere with each other |
| Multi-turn Dialogue Trigger Logic | Complete context step-by-step according to the messages sequence | Ensures each round of answers is generated based on historical interactions and current questions |
| Single Retrieval Limit | Top 5 matching documents | Controls information load per round of Q&A, meets precise matching requirements for legal documents |
| Timeout Threshold | 600 seconds | Adapts to waiting time for cross-departmental electronic certificate retrieval, prevents session interruption |
Three Common Misconfigurations
- Phenomenon: After configuring prompts, AI responses do not follow preset legal basis citation rules. Cause: Prompts are only configured in the global Q&A module, not bound to the specialized knowledge base scenario for administrative licensing and approval.
- Phenomenon: Session history cannot be exported, or exported content is missing interactions from the correction notification stage. Cause: Session log storage configuration for
chatIdis not enabled, resulting in loss of historical conversation data. - Phenomenon: After a user uploads an application material attachment, the AI cannot conduct follow-up Q&A based on the attachment content. Cause: Multimodal interaction functions are not enabled, or parsing rules for corresponding file formats are not configured.
How to Verify Successful Configuration
- Initiate a test question targeting a known administrative licensing item, check if the response cites specific document sources and clauses.
- Conduct multi-round interaction, submit different application material information in sequence, check if context correctly associates with historical conversation content.
- Upload a standard application form template, check if the AI can generate a corresponding material verification checklist based on the attachment content.
- Simulate a cross-departmental certificate retrieval waiting scenario, check if a response is completed within 600 seconds or a reasonable waiting prompt is provided.
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.