HTTP Interface and External Systems for Attenuated

Data Characteristics

Data sources for attenuated inactivated vaccine regulations and SOP documents primarily come from official releases by the National Medical Products Administration (NMPA) and the World Health Organization (WHO), internal management systems of vaccine manufacturers, and clinical research institution reports. These documents update infrequently, mainly when regulatory policies change, vaccine batches update, or production processes improve. Document formats are primarily PDF, Word, or XML. Content includes detailed vaccine production specifications, quality control standards, storage and transportation requirements, clinical trial data, and adverse reaction monitoring guidelines. Core fields include vaccine name, batch number, production date, expiration date, storage conditions, target population, contraindications, and adverse reaction incidence. Units include temperature (Celsius), time (year/month/day), dosage (IU/µg), and percentage (%).

Constraints from "HTTP Interface and External Systems"

The low update frequency of attenuated inactivated vaccine regulation documents means external systems do not need frequent polling for data synchronization. Long-interval scheduled tasks are sufficient. The variety of document formats (PDF, Word, XML) requires HTTP interfaces to have robust file parsing capabilities. The system must support multiple MIME types and accurately extract key information from unstructured text, for example, using OCR for scanned PDFs. The complexity of fields and specificity of units demand higher standards for data cleaning and standardization after extraction. For instance, ensure all temperature units are standardized to Celsius and dosage units are consistent to prevent answer deviations due to unit inconsistencies. Additionally, sensitive information in documents (e.g., manufacturer internal data) requires strict security protocols during data transmission and storage, such as using HTTPS for encrypted transmission and anonymizing critical fields.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`HTTP_REQUEST_TIMEOUT_SECONDS`	`120 seconds`	Large PDF or Word documents require more time for parsing; this prevents timeouts.
`MAX_FILE_SIZE_MB`	`50 MB`	Attenuated inactivated vaccine SOP documents are often large; this ensures full file uploads.
`SUPPORTED_MIME_TYPES`	`application/pdf, application/msword, application/vnd.openxmlformats-officedocument.wordprocessingml.document, application/xml`	Covers common regulation document formats, ensuring compatibility.
`DATA_SYNC_INTERVAL_HOURS`	`24–72 hours`	Vaccine regulations update infrequently; this reduces unnecessary resource consumption.
`API_KEY_AUTHENTICATION`	`Bearer Token`	Provides secure API access control, ensuring legitimate data sources.
`FIELD_MAPPING_RULES`	`Calibrate based on actual measurements`	Standardizes field name differences across various document sources.

Three Common Mistakes

Symptom: After an external system calls the FastGPT interface to upload a document, a 400 error returns with "Unsupported Media Type." Reason: The Content-Type request header is incorrect, or the uploaded file type is not in FastGPT's configured SUPPORTED_MIME_TYPES list.
Symptom: When retrieving the conversation history list via API, the results do not start from the expected position despite setting the offset parameter. Reason: The calculation logic or default value of the offset parameter does not align with actual business requirements, or the external system does not handle pagination correctly.
Symptom: In the regulation Q&A results obtained via API, critical numerical values (e.g., storage temperature) show unit confusion or numerical errors. Reason: After document parsing, the FIELD_MAPPING_RULES configuration is insufficient to standardize field units from different data sources, leading to unstandardized information before storage.

How to Confirm Correct Configuration

Upload attenuated inactivated vaccine regulation documents in various formats (PDF, Word, XML) via API. Check if FastGPT successfully identifies and stores them, returning a 200 status code.
Call the "Get Conversation History List" interface using different offset and limit parameter combinations. Verify that the starting position and quantity of the returned results match expectations.
Ask questions involving critical numerical values and units from the uploaded document content (e.g., "What is the storage temperature of vaccine X?"). Verify that FastGPT's answers match the original text and have correct units.

Note: The values provided are common starting points. Measure them against your 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.