FastGPT v4.17.0 Compatible Version
What This Category of Data Looks Like
This category of data is collected from administrative law enforcement case handling systems, law enforcement recorder footage, the national enterprise credit information publicity system, and departmental supervision databases. The update frequency is daily. Common documents involved include on-site inspection records, interrogation transcripts, evidence lists, prior administrative penalty notification letters, hearing notification letters, penalty decisions, and delivery receipts. Data fields include law enforcement subject, description of illegal circumstances, penalty basis clauses, document number, creation time, and others. The data includes both structured fields and semi-structured text content.
What Constraints These Characteristics Impose on Workflow Orchestration
Daily updated data requires scheduled synchronization nodes to ensure the timeliness of policy basis and law enforcement data. Mixed input of multiple types of law enforcement documents requires the workflow to perform pre-classification by document type, to avoid irrelevant content interfering with policy matching. The high time-consuming nature of fixed evidence and transcript links requires adding pre-check nodes in the workflow to ensure complete input data. Penalty case files need to form a traceable evidence chain, so the workflow must associate the corresponding relationship between evidence and penalty basis, to avoid mismatches between evidence and clauses.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Similarity Threshold | 0.75-0.85 | Accurately match law enforcement-related policy clauses, filter irrelevant content, and meet the strict requirements of administrative penalty case files |
| Single Search Limit | Top 10 entries | Law enforcement policy document volume is relatively controllable; the top 10 entries cover common penalty basis and avoid redundant information |
| Maximum Context Length | 8000-12000 characters | Cover the total length of multiple law enforcement documents and policy clauses, ensuring complete answer logic |
| Node Timeout Duration | 600 seconds | Adapt to the time required for large models to process complex law enforcement policy Q&A, avoiding mid-run interruptions |
| Variable Mapping | Associate law enforcement subject and case ID in variables | Enable dynamic calling of case-specific information within the workflow, adapting to different law enforcement scenarios |
| Question Optimization Switch | Enabled | Convert colloquial questions from law enforcement personnel into standard policy query statements, improving matching accuracy |
Three Common Configuration Mistakes
- When the AI chat node has the temperature switch enabled and set to 0, the answer still has random differences. The reason is that the temperature parameter only controls generation randomness; fixed output logic is only achieved by disabling the temperature switch.
- The specified reply node cannot implement continuous multi-line line breaks. After inputting multi-line content, the output remains a single line. The reason is that standard line break markers were not added at line breaks, or the rich text editing mode was not enabled.
- The question classification node processes too slowly, with no response for more than 10 seconds after triggering. The reason is that the classification rule set corresponding to
nodeIdwas not configured, or the associated knowledge base data was not properly chunked.
How to Confirm Successful Configuration
- Run test cases to verify that the AI output does not include unconfigured system prompt content, such as unexpected platform statement phrases.
- Submit multiple sets of questions from different law enforcement scenarios, confirm that the matching results of the question classification node meet expectations, such as market supervision-related questions matching corresponding supervision policies.
- Check workflow logs to confirm that law enforcement subject and case ID in
variablesare correctly mapped to corresponding configuration items. - Review node timeout logs to confirm that no node timeout errors occur.
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.