What the data for this category looks like
Daily documents for this category typically include filing materials, operation subsidy applications, service quality inspection checklists, safety hazard rectification ledgers, and elderly admission files. Core fields include institution name, unified social credit identifier, number of beds, inspection date, rectification status, and more. Data sources are generally elderly care service information platforms, civil affairs statistics systems, fire inspection records, and institution operation ledgers, with a monthly update frequency. The data structure is scattered, and field formats vary widely across different documents. Multi-system data association is required to complete verification and review for business handling processes.
What constraints these characteristics impose on the "multi-turn dialogue and prompt words" link
Monthly updated data sources require that the knowledge base synchronization cycle should not be too short, to avoid occupying resources from repeated full data pulls. Scattered multi-system data and differentiated document fields require that multi-turn dialogue gradually guide users to clarify query dimensions—for example, first confirm the regulatory institution type and business handling type, then supplement specific time or identification numbers. Long-text regulatory documents and multi-turn dialogue history require prompt words to clearly distinguish internal configuration content from user-visible content, while limiting context length to avoid exceeding model processing limits, ensuring the dialogue process complies with the business logic of elderly care service supervision.
How to set up configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Question Optimization | Enabled, enable multi-turn follow-up questions | Adapt to the multi-dimensional query requirements of elderly care supervision business, and gradually clarify key information such as the institution, time, or rectification status mentioned by the user |
| Maximum Context | 8000–12000 characters | Accommodate multi-turn dialogue history and content from multiple regulatory documents, avoiding model processing exceptions caused by overly long contexts |
| Single Search Limit | Top 6 results | Cover different types of regulatory documents including filing, subsidies, inspections, rectifications, while avoiding result overload that affects response speed |
| Timeout Duration | 600 seconds | Support time-consuming business processes such as batch verification of institution filing data and review of subsidy applications |
| Variable Binding | Bind the institution ID field in variables | Quickly locate regulatory data for the corresponding institution, improving the accuracy of retrieval and dialogue |
| Session Persistence | Enable chatId binding | Ensure that dialogue records are not lost after window refresh, retaining context association for multi-turn dialogue |
Three common misconfigurations
- Calling the AI dialogue module returns a 422 status code, while knowledge base retrieval results are normal. The cause is that the
messagesparameter format for multi-turn dialogue does not meet requirements, and historical dialogue context and current query content are not correctly concatenated. - Refreshing the conversation window loses dialogue records, but the records remain accessible in the background. The cause is that session persistence configuration is not enabled, and
chatIdis not bound to the user session context, resulting in the session ID being reset upon window refresh. - Accidentally outputting internal system configuration guidance to end users. The cause is that prompt words do not clearly distinguish the scope of internally visible and user-visible content, resulting in non-business handling configuration details being returned together.
How to confirm configurations are correct
- Initiate a multi-turn query including institution name and business type, confirm that the system gradually follows up on missing key information such as specific inspection time or subsidy application identification number.
- View dialogue logs, confirm that the institution ID field in
variablescan be correctly bound to retrieved regulatory document content, with no field matching errors. - Simulate an upgrade deployment and refresh the conversation window, confirm that conversation records are not lost, and the
chatIdpersistence configuration takes effect. - Test calling the AI dialogue module, confirm that returned content only includes business handling process guidance, with no internal configuration or system prompt information leaked.
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.