What the Data for This Use Case Looks Like
Data for this use case comes from the medical insurance intelligent monitoring system, fund supervision rule base, medical insurance settlement data, drug and consumable traceability codes, and complaint clues. The update frequency is monthly. Daily generated documents include audit notices, inspection working papers, list of suspected issues, interview records, handling decision letters, and rectification reports.
Medical insurance settlement data includes fields such as treatment time, expense details, and medical insurance code, with units including yuan and person-times. The rule base includes violation judgment standard entries, with fields for violation type and judgment basis.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Monthly updated data sources require prompts to adapt to the latest supervision rules, and avoid using expired judgment standards. Multi-source data requires gradual screening of suspected issues through multi-turn dialogue, to avoid overloading single inputs. Diverse document formats require prompts to clearly distinguish field requirements for different documents, ensuring generated content complies with supervision document specifications. The long text attribute of medical insurance settlement data requires the dialogue link to handle long segments, preventing truncation of key expense details and treatment records.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the conventional length of single records in medical insurance settlement data, avoid truncating key expense details |
| Maximum Context Window | 10000 token | Accommodate the complete content of the suspicion list and multiple inspection working papers required for monthly audits |
| Single Conversation History Limit | First 5 entries | Avoid context overload, focus on the dialogue logic of the current audit link |
| Prompt Variable | variables | Dynamically pass the current month’s supervision rule version number to ensure the latest judgment standards |
| Conversation Identifier | chatId | Bind the context of a single batch of audit tasks, avoid mixing dialogue content from different tasks |
| Single Request Timeout | 600 seconds | Adapt to the parsing and generation duration of long-text audit data |
Three Common Misconfigurations
- An error
The value of "offset" is out of rangeoccurs when executing long-text audit tasks. The cause is failure to truncate long text according to the configured chunk length, causing the model to process context segments beyond the supported range. - When uploading multiple audit-related documents, the
messagesparameter does not correctly nest the file content array, causing the model to fail to read all suspicion lists and settlement data. - Failure to adjust prompts for monthly updated supervision rules, resulting in expired violation judgment standards appearing in generated handling decision letters.
How to Verify Correct Configuration
- Input a single long medical insurance settlement data record, check that no
offset-related errors occur. - Upload multiple audit-related documents, verify that the
messagesparameter can correctly pass all file contents. - Generate an audit notice, check that the fields match the standard format of medical insurance supervision documents.
- Check the FastGPT v4.17.0 configuration log to confirm that parameters such as chunk length and maximum context window take effect.
The values provided here are common starting points, and should be evaluated against your own specific 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.