Data Characteristics for This Category
IVD diagnostic reagent regulations and SOP documents typically exist as PDFs, Word files, or internal system pages. These documents are highly structured. They cover regulatory requirements, production processes, quality control, and risk management. Update frequency is relatively low, primarily occurring with regulatory changes, product upgrades, or internal process optimizations, usually quarterly or annually. Documents extensively use professional terminology, abbreviations, and standard codes, such as classification codes from the "Administrative Measures for the Registration of In Vitro Diagnostic Reagents" and ISO 13485 standard clause numbers. Common fields include batch number, expiration date, storage conditions, detection principle, intended use, and applicable instruments. Units involve temperature (°C), time (hours, days), and concentration (mg/dL, IU/mL), requiring high precision.
Constraints Imposed by These Characteristics on "HTTP Interface and External Systems"
The low update frequency of IVD diagnostic reagent regulation documents means external system synchronization does not require frequent polling. Timed triggers or event-driven methods can be used, reducing system load. The specialized and structured nature of the documents requires the HTTP interface to accurately identify and extract key information during parsing, for example, by using regular expressions or specific tags to identify standard clause numbers and product batch information. The precision requirements for fields and units necessitate strict data type validation and unit conversion mechanisms when exchanging data with external systems, preventing parsing failures or data errors due to format mismatches. For instance, for storage temperature fields, the interface must ensure received data is within the preset numerical range and correctly handle units. Documents may contain numerous tables and diagrams, demanding higher data extraction capabilities from the interface, requiring support for parsing complex structured data.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
FETCH_INTERVAL_HOURS | 24 hours | IVD regulation documents have a low update frequency; reducing fetch frequency minimizes unnecessary system overhead. |
PARSE_FILE_TYPE_WHITELIST | pdf,doc,docx | Common formats for IVD regulation documents; ensures only supported document types are processed. |
MAX_DOCUMENT_SIZE_MB | 20 MB | IVD regulation documents may contain many charts and text; this size covers most cases. |
CHUNK_SIZE_TOKENS | 512–768 token | Ensures chunks contain sufficient context while preventing individual chunks from being too large, which could affect model processing efficiency. |
METADATA_EXTRACT_REGEX | batch number:([A-Z0-9]{6,}) | Targets common batch number formats in IVD documents, used for extracting key metadata from text. |
ERROR_RETRY_COUNT | 3 times | Provides a retry mechanism for transient network fluctuations or temporary external system failures. |
Common Pitfalls
- HTTP status codes return 404 or 500 errors. This happens when the external system interface address is incorrectly configured or authentication information has expired.
- Document content fetched from the external system is empty. The parser cannot process the content or reports an error. This occurs when the system does not correctly handle empty response bodies or abnormal data formats returned by the external interface.
- IVD product batch numbers or expiration date fields are missing from parsed Q&A results. This is due to inaccurate extraction rules for specific fields in the document, failing to correctly match and extract them.
How to Verify Configuration
- Check the HTTP request and external system interaction return status code via FastGPT's log interface to confirm it is 200.
- Manually upload an IVD regulation document containing batch number and expiration date information. Verify if the parser correctly identifies and extracts these key fields.
- Query IVD regulation-related questions in the FastGPT knowledge base. Check if the Q&A results include the latest regulation content synchronized from the external system and verify content accuracy.
The values provided are common starting points and should be measured 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.