What Data for This Category Looks Like
Daily data for this category includes documents such as supervision inspection forms, medical institution practice licenses, rectification notices, supervision opinions, and penalty case files. Data sources include the health supervision information system, medical institution electronic registration system, complaint and reporting platform, and law enforcement inspection records. Data updates occur once per month. Each document includes standardized fields such as institution unique identifier, inspection time, rectification requirements, and penalty basis. No additional custom statistical fields are included.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
The scattered data sources, fixed update rhythm, and diverse document types for this category impose three constraints on multi-turn dialogue and prompt engineering:
- Multi-turn dialogue must sequentially call dedicated data from different systems, and session contexts for different institutions must be isolated.
- Prompts must explicitly restrict use to datasets updated in the current month, to avoid referencing expired institution qualifications or inspection records.
- The system must adapt to field formats across multiple document types, to ensure accurate extraction of required information for dialogue interaction.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 characters | Covers complete content of multiple supervision case files, inspection forms, and rectification notices |
| Conversation history retention rounds | First 10 conversation turns | Matches the multi-turn communication logic of rectification tracking, retains the complete process of inspection, feedback, and rectification |
| Variable injection | Use the variables parameter | Injects dedicated data such as institution qualifications and inspection records classified by law enforcement scenarios |
| Session ID binding | Use the chatId parameter, bind to medical institution unique identifier | Isolates supervision files of different institutions, avoids context confusion in concurrent sessions |
| Prompt template update frequency | 1 update per month | Matches the monthly update rhythm of health supervision data, ensures prompts use the latest business rules |
| Workflow concurrency limit | Calibrated via actual testing, single node concurrency no more than 2 per second | Avoids concurrency thresholds that trigger empty system responses |
Three Common Misconfigurations
- Phenomenon: When calling workflows concurrently, the conversation content bound to the
messagesparameter displayed in the interface overlaps, and the final output includes supervision results from multiple sessions at the same time. Cause: No independentchatIdis assigned to each session, causing different requests to share context variables. - Phenomenon: The AI output only displays the final supervision opinion, and does not show the large model's thinking process. Cause: The prompt does not explicitly require outputting thinking steps, or the configuration for displaying thinking processes in multi-turn dialogue is not enabled.
- Phenomenon: When batch verifying institution qualifications, the returned result is empty. Cause: Expired data fields that have not been synchronized are called, and the monthly update frequency of health supervision data is not adapted.
How to Confirm Proper Configuration
- Initiate a simulated supervision inspection dialogue, verify that fields such as institution license number and inspection date injected via the
variablesparameter are correctly displayed in the dialogue. - Initiate 2-3 concurrent sessions for different medical institutions, check that the output of each session only includes supervision data for the corresponding institution, with no context overlap.
- Trigger a workflow call, confirm that the returned result includes field content from the corresponding law enforcement document, with no null values.
- Check the FastGPT v4.17.0 workflow logs, confirm that the number of runs does not reach the
WORKFLOW_MAX_RUN_TIMESlimit.
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.