What This Category of Data Looks Like
Data sources for this category include medical insurance intelligent monitoring systems, fund supervision rule bases, medical insurance settlement data, drug and consumable traceability codes, and complaint clues. The update frequency is monthly. Daily office documents include audit notices, inspection work drafts, suspicious point lists, interview records, handling decision documents, and rectification reports. Fields cover violation types, involved entities, rectification status, handling opinions, and other related content. Data is only stored in a structured manner according to business processes, with no additional statistical or percentage data.
What Constraints Do These Characteristics Impose on the Multi-turn Dialogue and Prompts Link
Business data is updated monthly. Prompt templates must be synchronized with the latest supervision rules regularly to avoid rule lag. Multiple document types and multi-source data require multi-turn dialogue to retain complete audit process context. Each question from suspicious point screening to rectification confirmation must be associated with exclusive data for the corresponding task. Single audit tasks involve multiple steps. Prompts must clearly distinguish inputs for different links. This ensures the model focuses on the current business node being processed. Context length must be limited. This avoids exceeding the model's processing limits.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind to the 32-bit UUID string of a single audit task | Distinguish dialogue contexts of different audit tasks to avoid cross-task confusion |
messages | Concatenate historical dialogue and business document fragments in the order of the audit process | Retain complete process context from suspicious point investigation to rectification confirmation |
variables | Pass in the suspicious point list ID and involved medical institution name of the current audit task | Enable prompts to accurately call exclusive data for the corresponding task |
| Maximum context | First 20 dialogue turns + associated document fragments | Adapt to the multi-step process context of audit tasks, avoiding exceeding the model window limit of FastGPT v4.17.0 |
| Single search limit | First 8 suspicious point records | Focus on core data of the current audit link, reducing interference from irrelevant information |
Three Common Mistakes
- Fail to carry file parsing parameters when calling the dialogue interface, resulting in missing business document content such as audit notices and medical records and prescriptions. Cause: The parsed text fragments of front-end uploaded files are not correctly passed in the
messagesparameter. - Write all supervision rules into Human prompts, causing the model to confuse the context of the current task and historical dialogue. Cause: The System prompt is not clearly used to set the boundary of audit rules, and the Human prompt is not used to convey specific business issues.
- Incorrectly associate dialogue records across audit tasks, generating violation determination conclusions that do not match the current task. Cause: A unique
chatIdparameter is not assigned to each audit task, resulting in context interference.
How to Confirm Configuration is Complete
- Initiate a test dialogue, enter the keyword of the suspicious point list for the current audit task, and check whether the returned result includes exclusive data for the corresponding task.
- View the dialogue history records, confirm that each task's
chatIdis unique and not reused by other tasks. - Upload a test inspection work draft, check whether the interface correctly receives and parses the file content.
- Adjust the prompt template variables, confirm whether the model output correctly references the passed audit rule version number.
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.