What the data for this category looks like
Core data for this category comes from the regulatory rule base, higher-level law database, departmental policy document library, and administrative regulatory document filing system. Update frequency is irregular. The system processes five types of documents daily: regulatory document drafts, drafting explanations, legality review opinions, solicited opinion summaries, and filing reports. Each document includes core fields such as issuing authority, article content, and drafting procedure explanation. Data processing focuses on the making authority, procedures, and article legality of abstract policy rules, which differs from administrative law enforcement case review scenarios. Core time-consuming steps include higher-level law comparison, rights and obligations clause review, and public opinion summary.
Constraints imposed by these characteristics on the multi-turn dialogue and prompt engineering link
Dispersed data sources and irregular updates require multi-turn dialogue to dynamically adapt to the latest regulatory library content. Prompts must include trigger logic for real-time data calls. Diverse document types with clear fields require multi-turn dialogue to guide users to upload different review materials in sequence, such as regulatory document drafts and drafting explanations, to avoid missing information. Error consequences directly affect policy release and implementation. Prompts must require review conclusions to include clear higher-level law basis entries. Reply formats must be strictly validated to ensure direct import into the filing system. Historical interaction content must be fully retained to allow retrospective review of opinion adjustments during the review process, ensuring traceable workflows.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Conversation context window | Retain the first 20 rounds of messages interaction content, or 10000–15000 tokens | Adapt to the interaction logic of multi-turn reviews, avoid processing delays caused by overly long context |
| Prompt variable configuration | Bind the regulatory library path and filing system ID in variables | Enable dynamic calls to the latest regulatory data and filing system interfaces |
| Reply format validation | Force output of JSON-standard content, including three fields: review conclusion, basis entries, modification suggestions. Each single field must not exceed 5000 characters | Ensure review results can be directly read by the filing system, meeting business process requirements |
| Session timeout | 300 seconds | Avoid long-term occupation of system resources, align with the average time required for the review process |
| Historical record storage | Enable chatId-associated session storage to fully save all interaction content | Support session review and workflow traceability, prevent loss of historical content |
| Multi-turn trigger conditions | Trigger according to review stages, divided into three nodes: drafting review, solicited opinion review, pre-filing review | Match the stage division of the business process, guide users to submit materials in sequence |
Three Common Misconfigurations
- Phenomenon: Custom JSON reply format does not take effect, returns plain text content. Cause: The prompt does not clearly specify the format validation rules for
messagescontext, and does not bind the format validation parameters invariables. - Phenomenon: Multi-turn dialogue workflow runs slowly. Cause: The context rounds of
messagesare not limited, too much historical interaction content is loaded, leading to excessive system resource occupation. - Phenomenon: Automatic reply is empty after reopening the session. Cause: The
chatId-associated historical storage function is not enabled, session data invariablesis not persistently saved, and data is lost after the session is closed.
How to Verify Proper Configuration
- Upload a regulatory document draft to trigger multi-turn dialogue, check if the reply meets the preset JSON format requirements.
- Initiate two or more review interactions, close the session and reopen it, check if all historical
messagesinteraction content is fully retained. - Adjust the conversation context window parameter, test the loading speed of dialogues with different rounds, confirm that the response meets the response requirements of the business scenario.
- Input a question involving higher-level law basis, check if the reply correctly associates with the regulatory library data configured in
variables.
The values listed are common starting points and 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.