What the data for this category looks like
The data for declaration materials and file review in the medical circulation sector comes primarily from enterprise business qualification filing systems, pharmaceutical inventory ledgers, and approval files required by drug regulatory authorities. Data is generated immediately when a single declaration business is triggered. Archived files are synced to the knowledge base in weekly batches. Documents exist as structured fields paired with attachments. Structured fields include the enterprise unified social credit code, drug approval number, declaration batch number, and file number. Their corresponding units are code, number, batch, and piece. Most attachments are PDF-format qualification scan files and physical file scan copies.
How these characteristics impose constraints on HTTP interfaces and external systems
Fixed format requirements for structured fields mean interfaces must complete field mapping in advance, to prevent data import failures due to format mismatches. The volume of data pushed per batch must match the per-batch limit of the pushData interface, to avoid triggering call restrictions due to excess volume. PDF-format attachments require interfaces to support file stream or file URL parameters, to ensure attachments can be parsed correctly. The real-time data update requirement means interface calls must be tied to business trigger nodes, to avoid data sync delays. The uniqueness of file numbers means interfaces must check for duplicate data when pushing, to prevent duplicate entries in the knowledge base.
How to configure settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Carry a Bearer-format authentication token with a validity period of 7200 seconds | Complies with FastGPT v4.17.0 API authentication requirements, and ensures call legitimacy |
variables | Map enterprise unified social credit code, drug approval number, and declaration batch number in the order of declaration material fields | Ensures structured data accurately matches knowledge base fields |
responseData | Only extract the code and message fields for exception judgment | Simplifies error handling workflows for subsequent business logic |
| Batch call threshold | 190 sets per batch | Below the 200-set limit of the pushData interface, to avoid triggering call rate limiting |
| Timeout setting | 300 seconds | Matches the average processing duration of medical circulation approval businesses, to prevent unnecessary interruptions |
Three common configuration mistakes
- When calling the
pushDatainterface, a 400 status code is returned, prompting parameter overlimit. Cause: The batch call is not set to the 190 sets per batch threshold, and pushing more than 200 sets of data directly triggers rate limiting. - When using an HTTP tool to call the interface, PDF-format declaration attachments cannot be uploaded, and the attachment field in the knowledge base is empty. Cause: Interface parameters that support file stream or file URL input are not configured, causing attachments to fail to be correctly identified and stored.
- When deploying the deepseek-r1 model of ollama locally, FastGPT returns connection error logs. Cause: The local address of ollama is not configured as an external service address accessible to FastGPT, or the access permission for the corresponding port is not opened.
How to verify a successful configuration
- Call the
pushDatainterface, then check the returnedcodeandmessagefields to confirm there are no abnormal prompts. - Go to the FastGPT knowledge base management backend, view the pushed declaration material data, and confirm that the field mapping matches the actual business data.
- Upload a test PDF attachment via the interface, and confirm that the attachment content can be viewed normally in the knowledge base.
- After configuring the access address of the ollama model, initiate a test call to confirm that no connection error logs are generated.
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.