HTTP Interface and External Systems for Regulatory

Data Characteristics

Regulatory submission quality documents in the biopharmaceutical field primarily originate from pharmaceutical research, clinical trials, non-clinical studies, and quality management systems. These documents typically use formats such as PDF, Word, and Excel. They are highly structured and adhere to ICH guidelines and regulations from national drug administrations (e.g., NMPA, FDA, EMA). Update frequency is relatively low, occurring mainly at key development milestones and when submitting supplementary information. Document content includes extensive specialized terminology, abbreviations, experimental data, charts, and statistical results. Key fields include batch number, expiry date, active ingredient content, impurity profile, stability data, and clinical endpoints. Units are precise to multiple decimal places, demanding extremely high data accuracy and consistency.

Constraints from "HTTP Interface and External Systems"

The standardized and specialized nature of regulatory submission quality documents requires HTTP interfaces to ensure field completeness and type matching during data transmission, especially for sensitive data types like numerical values and dates. The low update frequency means external systems do not require real-time synchronization but need version management capabilities to handle document revisions and corrections. Complex charts and specialized terminology in documents challenge interface data formats, requiring support for rich text or binary file transfer and high parsing capabilities for unstructured information. The strictness of fields and units demands that interfaces perform precise unit conversions and range checks at the data validation layer to prevent submission failures due to data format errors.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Regulatory submission documents often contain many images and charts, leading to large single file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Parsing large PDF or Word documents can be time-consuming; sufficient time must be allocated.
`maxContext`	`8192 token`	Ensures the capacity to accommodate lengthy descriptions and complex contexts found in regulatory submission documents.
`chunkSize`	`800–1200 characters`	Balances long-text comprehension with retrieval efficiency, preventing semantic loss from over-segmentation.
`requestTimeout`	`30000 ms`	Accounts for network latency and document processing time when external systems call the interface.
`CORS_ORIGINS`	Calibrate based on actual measurements	Ensures front-end applications can securely call back-end interfaces, avoiding cross-origin issues.

Common Pitfalls

Receiving 400 Bad Request or 500 Internal Server Error when calling an interface often results from field names in the request body not matching interface definitions or incorrect data types.
System unresponsiveness or parsing failure after uploading large documents is frequently due to PARSE_FILE_TIMEOUT_SECONDS being set too short, causing the file to time out before processing completes.
Empty critical fields when external systems retrieve document content typically indicate that the interface's returned data structure does not match expectations, or the external system did not correctly parse nested fields in the JSON response.

Verification Steps

Use Postman or curl to simulate HTTP POST requests with actual regulatory submission document data. Check for a 200 OK status code and verify that critical data fields in the response body are complete and correct.
Upload a typical regulatory submission PDF document containing many charts and long text. Observe if the parsing process completes successfully and if the document content is correctly segmented and vectorized.
Perform end-to-end testing in the external system for the regulatory submission data returned by the interface. Ensure data is correctly stored, displayed, and referenced by other modules. Verify the precision and unit consistency of numerical fields.
Check FastGPT's system logs to confirm no Timeout, Parsing Error, or Schema Validation Failed exceptions occurred during the processing of regulatory submission documents.

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 2026-09-21.