What Data for This Category Looks Like
Data for this category comes from four sources: health supervision information systems, medical institution electronic registration systems, complaint reporting platforms, and law enforcement inspection records. Data updates occur once per month.
Daily processed documents include supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Each document type corresponds to workflow links including on-site inspection, qualification verification, rectification tracking, and law enforcement disposal. Covered fields include institution name, practice scope, inspection date, rectification requirements, penalty basis, and more. There is no unified fixed format, and exclusive fields must be extracted based on individual document types.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Data sources for this category are scattered, and require association with information across multiple systems. Multi-turn dialogue must gradually guide users to provide key information such as institution name and inspection items. Requesting too many fields at once will interrupt user interaction.
Monthly updated data requires clear prompts about data timeliness during dialogue flows, to prevent compliance risks caused by citing expired information.
There are many different daily document types. Prompt engineering must adapt to the field extraction logic of each document type. For example, extract qualification scope from medical institution practice licenses, and extract rectification requirements from rectification notices.
Law enforcement-related documents involve compliance determination. Information accuracy must be gradually verified during multi-turn dialogue, to avoid directly generating unsupervised opinions that have not been verified.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | First 8000–12000 characters | Adapt to the total length of cross-system associated data, avoid truncating key qualification and rectification information |
| Question optimization switch | Enabled | Help organize scattered user inquiry content, focus on core demands such as institution qualification and inspection items |
messages context round limit | First 10 dialogue turns | Reduce redundant information interference, focus on supervision matters and institution information for the current inquiry |
variables preset variable configuration | Bind institution name, inspection type | Quickly call historical data from corresponding systems, improve dialogue efficiency |
| Maximum tokens per reply | 1500–2000 tokens | Adapt to summary output for long documents such as supervision opinions and rectification notices |
| Timeout setting | 600 seconds | Match the time required for cross-system data retrieval, avoid dialogue interruption |
Three Common Misconfigurations
- LaTeX formats render correctly in debug preview, but only display raw LaTeX code in the published dialog box. This occurs because the LaTeX rendering switch is not enabled in the published configuration, or the deployment environment lacks LaTeX rendering dependency packages.
- Continuous lag and no response after deployment. This occurs because reasonable timeout settings are not configured for cross-system data retrieval, or system resources are insufficient to support real-time associated calculations for multi-institution data.
- AI dialogue results inserted in the workflow are included in the final output. This occurs because output hiding rules are not configured for workflow nodes, and all node results are aggregated into the final output by default.
How to Verify Proper Configuration
- Initiate a test dialogue involving institution qualification query, and verify that the bound institution information from
variablespreset variables is correctly included in the reply. - Simulate a multi-turn inquiry scenario, verify that the dialogue context only retains valid information for the specified number of rounds, with no redundant content causing interference.
- Trigger a dialogue flow that retrieves cross-system data, confirm that the dialogue does not experience timeout interruption, and that the reply content complies with the field extraction rules for corresponding documents.
- Test compliance description content in LaTeX format, confirm that the display effect is consistent between the published interface and the preview interface.
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.