HTTP Interface and External Systems for CSO Quality

Data Characteristics for this Category

CSO (Contract Sales Organization) quality document data in the biopharmaceutical sector has unique characteristics. Data sources typically include quality agreements signed between CSOs and pharmaceutical companies, sales compliance reports, training records, audit reports, and adverse event handling procedures. These documents are stored in formats like PDF, Word, and Excel. Their content is highly structured, containing information such as drug batch details, sales regions, salesperson qualifications, training dates, compliance check results, and deviation handling records.

Update frequency varies: quality agreements are usually updated annually or when terms change, sales compliance reports may be generated monthly or quarterly, and training records are updated immediately after each training session. Fields and units are specific; for example, "training duration" is measured in "hours," "number of adverse events" in "count," and "batch number" is a string following specific encoding rules.

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

The data characteristics of CSO quality documents impose specific constraints on HTTP interfaces and external system integration. The highly structured nature of document content requires interfaces to accurately parse different document formats and extract key fields. For example, automatically identifying and extracting drug batch numbers and compliance statuses from PDF reports.

Inconsistent update frequencies necessitate flexible trigger mechanisms in interface design. These mechanisms must support both scheduled tasks (e.g., quarterly report retrieval) and event-driven actions (e.g., uploading new training records). The diversity of document formats demands robust file parsing capabilities from interfaces, enabling them to handle various file types such as PDF, DOCX, and XLSX. The specificity of fields and units, such as batch number encoding rules, requires strict validation and standardization during data transmission and storage to ensure data accuracy and consistency.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	A single quality document (e.g., an annual audit report) may contain numerous images and attachments, leading to large file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Complex PDFs or scanned documents requiring OCR can take considerable time to parse; sufficient processing time is allocated.
`maxContext`	`32000 token`	Ensures complete loading and understanding of long texts such as quality agreements and compliance reports.
`Chunk size`	`800–1200 characters`	Balances semantic completeness with retrieval efficiency, avoiding excessive segmentation or overly long paragraphs.
`Recall count`	`Top 5 entries`	Ensures retrieval results cover core compliance points and key clauses, providing sufficient context.
`Similarity threshold`	Determined by actual measurement	Requires adjustment based on actual data, targeting specific quality document terminology and phrasing.

Three Common Pitfalls

When calling the API, the file upload function returns "unsupported file format" or parsing failure. This occurs because the interface lacks correct MIME type identification rules or compatibility for specific PDF/DOCX versions.
When querying the knowledge base, results are unexpected or lack critical information. This may be due to an undersized Chunk size truncating important information, or insufficient maxContext to accommodate the full context for inference.
When viewing historical records via the HTTP interface, the source field is empty or incomplete. This indicates that document source identifiers were not correctly passed or recorded during external system integration, making traceability difficult.

How to Verify Correct Configuration

Upload CSO quality documents in various formats (PDF, DOCX, XLSX) and sizes to confirm successful upload and system recognition for all files.
Perform searches on documents containing specific batch numbers and compliance clauses. Check that the returned results accurately include this key information and that the number of recalled items meets expectations.
After successful API calls, verify that the source field correctly records the document origin (e.g., "Quality Agreement System" or "Training Management Platform") to ensure complete traceability.
Simulate concurrent uploads of multiple large quality documents. Observe system processing times to confirm that the PARSE_FILE_TIMEOUT_SECONDS setting covers most processing scenarios.

Note: The values provided are common starting points. They 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.