HTTP Interface and External Systems for Molecular

Data Characteristics in this Category

Data sources for molecular diagnostics regulatory submissions primarily include In Vitro Diagnostic (IVD) clinical trial reports, performance verification reports, manufacturing process documents, quality management system documents, and relevant regulations and standards. This data typically exists in a mixed format of structured (e.g., clinical trial data tables) and unstructured (e.g., detailed experimental records, expert opinion reports, literature reviews) content. Update frequency aligns with regulatory revisions, clinical research progress, and new product launch cycles, usually quarterly or annually. However, some regulatory updates may trigger urgent data organization and supplementation. Document structure often follows the National Medical Products Administration (NMPA) regulatory submission requirements, typically including product specifications, registration testing reports, clinical evaluation reports, and risk management reports, each as a separate document. Fields and units are highly specialized, such as nucleic acid concentration unit ng/µL, gene copy number copies/mL, sensitivity LOD, and specificity Specificity. These often accompany descriptions of specific detection methodologies.

Constraints Imposed by these Characteristics on "HTTP Interface and External Systems"

The multi-source and mixed structure of molecular diagnostics data requires HTTP interfaces to support various Content-Type formats, such as application/json, application/xml, and multipart/form-data for file uploads. The irregular nature of data updates necessitates idempotent processing mechanisms in the interface to prevent duplicate submissions or data inconsistencies. Large volumes of unstructured text content, such as experimental records and expert opinions, require interfaces to accept large text data volumes and may need additional text vectorization services for preprocessing. Specialized fields and units demand strict adherence to data type definitions during data transmission, including floating-point precision and string length limits. Due to the high sensitivity of the data, mandatory requirements exist for interface security, authentication mechanisms (e.g., OAuth2 or API Key), and transmission encryption (HTTPS). Potentially large data volumes require specific considerations for interface timeout durations, concurrency handling capabilities, and error retry mechanisms.

Configuration Guidelines

Configuration Item	Suggested Value	Rationale
`HTTP_TIMEOUT_SECONDS`	`300 seconds`	Addresses potential response delays from large file uploads and complex queries.
`MAX_FILE_SIZE_MB`	`200 MB`	Accommodates the potential size of individual clinical reports or attached documents.
`RETRY_ATTEMPTS`	`3 times`	Handles occasional network fluctuations or temporary unavailability of external services.
`AUTH_HEADER_NAME`	`Authorization`	Follows industry standard `Bearer Token` authentication patterns.
`CONTENT_TYPE_SUPPORT`	`["application/json", "multipart/form-data", "application/xml"]`	Ensures handling of structured data and file uploads.
`ERROR_RETRY_CODES`	`[500, 502, 503, 504]`	Enables automatic retries for common server-side errors.

Three Common Mistakes

Symptom: API calls return Connection refused or Connection timed out errors. Reason: The network environment where FastGPT is located cannot access the external system's IP address or port, typically due to misconfigured firewall rules or proxy settings.
Symptom: HTTP request succeeds, but the external system does not perform the expected operation, and logs show parameter parsing failure. Reason: The submitted JSON or XML data structure does not match the external system's interface definition. For example, the field name sampleID was written as sampleid, or a required field reportDate was missing.
Symptom: After uploading a file, the external system reports the file is corrupted or unreadable. Reason: Content-Type was not correctly set to multipart/form-data, or the byte stream was truncated during file transfer.

How to Verify Correct Configuration

Use FastGPT's tool debugging interface to send an HTTP POST request containing all required parameters. Confirm the external system successfully receives and processes it.
Upload a typical molecular diagnostics regulatory submission file (e.g., a PDF clinical trial report). Check if the external system can correctly parse the file content and extract key information.
Configure an Agent in FastGPT that includes an HTTP tool. Attempt to ask a question and observe if the Agent can use the HTTP call to the external system to retrieve the correct data response. Also, check if the Agent can generate an expected reply based on the response content, and verify that external system logs show normal call records.

The values provided are common starting points and should be measured against specific 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.