What this category of data looks like
This category of data originates from project document libraries, configuration lists, meeting minutes, and test reports. Updates take place at the end of individual project phases or when full projects are delivered. Daily produced documents include completion documents, configuration manuals, training records, and acceptance certificates. Core fields include project unique identifier, document version number, handover and archiving date, recipient unit information, and electronic signature status. Most field formats follow standard project numbering, date text, and character content.
What constraints these characteristics impose on HTTP interfaces and external systems
The update rhythm of this category of data fluctuates with project phases. Single interface requests must support multiple batches of document submissions. Therefore, interfaces must support segmented batch uploads. Documents include verification fields such as project number, version number, and signature status. Interfaces must verify the completeness of required parameters to prevent invalid archiving. Data sources are scattered. Multiple types of document metadata must be synchronized through external systems. Therefore, interfaces must support structured text in different formats. Archived data must retain traceable identifiers. Interfaces must return unique archiving numbers for subsequent operation and maintenance queries.
How to configure settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Server environment variable AIPROXY_API_TOKEN | Must be configured with a non-empty administrator token matching the AI Proxy server | Meets AI Proxy dependency requirements for FastGPT v4.17.0+ |
| Number of documents per request | First 10 entries | Prevents overload from single requests, aligns with reasonable volume of project documents submitted in a single handover |
variables | Bind project number and document version number | Matches core verification fields of this category of documents, ensures accurate metadata |
| Timeout period | 600 seconds | Provides sufficient processing time for large project document handovers, prevents mid-process interruptions |
responseData | Extract archiving number and verification status | Obtains traceable archiving results for subsequent operation and maintenance verification |
| Single document size limit | 1000 MB | Aligns with reasonable thresholds for general file uploads, prevents transmission failures |
Three common configuration mistakes
- Symptom: Interface returns 401 unauthorized error, or prompts for missing authentication parameters. Cause: The server is not correctly configured with a non-empty
AIPROXY_API_TOKEN(AI Proxy administrator token, must match the AI Proxy server configuration), or application API authentication parameters are not correctly configured. - Symptom: HTTP request body parameters in the workflow cannot bind document metadata. Cause:
variablesare not correctly used to bind project-specific fields, resulting in parameters that cannot be automatically filled into the request body. - Symptom: Interface returns archiving verification failure. Cause: Required field completeness is not verified, and core fields of this category such as project number and document version number are not included.
How to confirm configuration is complete
- A request for a single test document is submitted, and the interface's
responseDatais verified to include the expected archiving number and verification status. - The App/Admin server is verified to have correctly configured a non-empty
AIPROXY_API_TOKENandAIPROXY_API_ENDPOINT(AI Proxy service root address, no additional path suffix required). - The workflow HTTP node is triggered, and project metadata bound via
variablesis confirmed to automatically populate the request body. - Multiple batches of test documents are uploaded, and the interface is confirmed to support segmented batch submissions without request interruptions.
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 2026-10-19.