What the Data for This Category Looks Like
Data sources include 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. Daily documents include on-site inspection records, interrogation records, evidence lists, prior administrative penalty notification letters, hearing notification letters, penalty decisions, and service receipts. Core fields for each case file include law enforcement subject, case number, illegal facts, discretion basis, penalty decision, document status, and archiving progress.
Constraints Imposed on Multi-turn Dialogue and Prompts
The data for this category is scattered across multiple systems. Multi-turn dialogue must integrate case file documents and data from different sources, and ensure that every piece of evidence association is retained in the dialogue context. Daily updated case file data requires that prompts can retrieve the latest case status in real time, to avoid using expired data. Because the consequences of errors are severe, prompts must strictly verify the matching between documents and evidence to ensure compliance with law enforcement procedures. At the same time, a traceable evidence chain must be formed. Multi-turn dialogue must gradually confirm the completeness of documents such as on-site records and evidence lists, to avoid missing key steps.
Configuration Settings
These configurations apply to FastGPT v4.17.0:
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | Retain the first 20 dialogue records | The core process steps for administrative penalty case file processing do not exceed 20 turns, and this covers key evidence associations and law enforcement links |
variables | Bind preset variables such as law enforcement subject and case number | Quickly locate target case files and avoid ineffective cross-system data retrieval |
chatId | Bind the unique ID of the current session | Isolate dialogue records for different users, ensuring each user only views their own case file dialogue |
| Maximum context length | 8000–12000 characters | Total character count of core documents for a single set of administrative penalty case files, calibrated via actual testing |
| Offset parameter | Set to 0 on first call, adjust based on the number of records already obtained | Corresponds to scenarios where dialogue record lists are retrieved, to precisely control the returned record range |
Three Common Configuration Errors
- Phenomenon: Prompts do not execute in the expected order, and preset variables are not replaced. Cause: The context loading order of
messagesis not clearly defined, leading to the prompt's preconditions not being loaded correctly. - Phenomenon: The dialogue record ID of the previous AI reply cannot be accurately obtained. Cause: The
chatIdparameter is not correctly bound, leading to the session context not being properly associated. - Phenomenon: The offset parameter is used incorrectly when retrieving dialogue record lists, leading to the number of returned results not matching expectations. Cause: The role of the offset parameter as specifying the starting position of returned records is not clearly understood, leading to duplicate or missing case file data.
How to Verify Successful Configuration
- A test dialogue is run, an instruction to query a specified case file is input, and whether the dialogue context retained in
messagesincludes key law enforcement process steps is verified. - Dialogues are initiated using different
chatIdvalues, and it is confirmed that each session can only view its own dialogue records, with no cross-session access. - The interface for retrieving dialogue record lists is called, the offset parameter is adjusted, and whether the number of returned records matches the expected starting range is verified.
- Variables in the prompt are checked for correct replacement, and it is confirmed that preset fields in
variableshave been correctly loaded into the dialogue.
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.