Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
Daily documents for this category typically include elderly care institution filing materials, operation subsidy applications, service quality inspection forms, safety hazard rectification ledgers, and elderly admission files. Data is generally sourced from elderly care service information platforms, civil affairs statistics systems, fire inspection records, and institution operation ledgers, with a monthly update frequency. Document fields mostly cover institution main body information, number of beds, rectification status, subsidy application progress, and other related content. There is no unified fixed single-page length. Match the recall scope to actual business scenarios.
Constraints on Sharing and Embedding From These Data Characteristics
The monthly update frequency of the data requires the embedded Q&A knowledge base to synchronize the latest filing, rectification, and other documents regularly. This avoids using expired supervision information. The multi-source, multi-field document structure requires accurate limitation of the recalled document scope during sharing and embedding. This prevents mixing of non-party building learning related civil affairs business data. Supervision data involves sensitive information related to institution operations and elderly care. Configure identity authentication in the embedding scenario to control access permissions. Daily documents have high field complexity. Limit the number of recalled contents per request to avoid interface display overload or information interference.
How to Set the Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
shareId | Exclusive sharing ID bound to the elderly care service institution supervision party building knowledge base | Ensure that the Q&A only associates exclusive document data for this category, avoiding mixing other civil affairs business content |
| Embedding window height | 600–800 pixels | Adapt to the conventional interface layout of civil affairs office systems, ensuring complete display of document content |
| Context recall count | Top 3–5 entries | Match the number of fields in daily documents of this category, reducing irrelevant information interference |
| Timeout period | 30–60 seconds | Correspond to the time consumption requirements of multi-data source queries, avoiding interaction failures caused by data pull delays |
| Maximum context length | 1000–1500 characters | Match the conventional length of single documents in this category, controlling the total amount of context information |
| Identity authentication | Enabled (internal system scenario) | Comply with access control requirements for supervision data, preventing unauthorized access to sensitive business information |
Three Common Misconfigurations
- Phenomenon: Cross-domain errors display in the console after embedding in a Vue3 project. Q&A content fails to load normally. Cause: The FastGPT cross-domain whitelist is not configured. The front end cannot call the interface to retrieve returned data.
- Phenomenon: The Q&A content displayed after iframe embedding includes documents unrelated to elderly care supervision party building. Cause:
shareIdis not correctly bound. The sharing ID of a general knowledge base is used, leading to recall of irrelevant business data. - Phenomenon: The sharing link can be directly accessed by external personnel. Identity verification is not implemented. Cause: The identity authentication configuration for the embedding scenario is not enabled. The authentication rules do not adapt to the identity verification logic of internal office systems.
How to Confirm Successful Configuration
- Enter questions related to elderly care institution filing. Check whether returned content only includes party building learning and supervision related document information for this category.
- Call the FastGPT sharing interface. Pass in the
shareIdparameter. Verify that the returned knowledge base content matches the configured party building learning Q&A dataset. - Access the embedded page in an unauthorized browser environment. Confirm that Q&A content fails to load normally or is blocked.
- Adjust the size of the embedding window. Check that the Q&A interface adapts to the display, with no scrolling abnormalities or content truncation.
The values provided are common starting points. They should be evaluated against samples from the corresponding use cases.
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.