Supplier Audit Regulations: HTTP Interface and External

Data Characteristics for this Category

Supplier audit regulation data primarily originates from internal quality management system documents, external regulatory requirements, supplier qualification files, and historical audit reports. This data typically exists in various unstructured and semi-structured formats, such as PDFs, Word documents, and Excel spreadsheets.

Update frequency varies: regulatory requirements and internal policies might be revised annually or biennially. Supplier qualification files are usually submitted during initial collaboration and updated upon expiration or significant changes. Historical audit reports are generated after each audit.

Document structure: Policy documents include chapters, clauses, and appendices. Audit reports contain fixed fields like audit findings, non-conformities, and corrective action plans.

Fields and units: Data may include supplier codes, audit dates, non-conformity IDs, and rectification completion dates. Some fields might contain references to regulatory clauses or specific technical parameters.

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

Diverse document formats require the HTTP interface to have robust file parsing capabilities. It must handle text extraction from PDFs, structured conversion of Word documents, and data extraction from Excel spreadsheets.

Inconsistent update frequencies mean the interface design needs to support both incremental updates and full synchronization, avoiding redundant processing of unchanged data.

The complex structure of policy documents and audit reports demands a sophisticated text segmentation strategy to ensure semantic completeness. For example, a regulatory clause might span multiple pages or include several sub-clauses; segmentation must avoid splitting these apart.

The specificity of fields and units, such as regulatory clause number 21 CFR Part 11 or rectification completion date YYYY-MM-DD, requires standardization during data preprocessing for subsequent semantic understanding and retrieval.

Interface response speed must meet user demands for real-time queries, especially when quickly verifying regulatory provisions during an audit.

Configuration Settings

Configuration Item	Recommended Value	Rationale for Recommendation
`maxContext`	`800–1200 characters`	Ensures the completeness of regulatory clauses or audit finding contexts, preventing semantic fragmentation.
`Chunk size` (Segment Length)	`500 characters`	Balances semantic completeness with recall efficiency, suitable for paragraph lengths in policy documents and reports.
`Recall count` (Number of Retrieved Items)	`Top 5`	Prioritizes the return of the most relevant policy provisions or audit records, improving answer accuracy.
`Similarity threshold` (Similarity Threshold)	`0.75`	Filters out low-relevance results, reduces noise, and ensures returned content highly matches the query.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Accommodates parsing time for large PDFs or complex Word documents, preventing parsing failures due to timeouts.
`HTTP_REQUEST_TIMEOUT_SECONDS`	`300 seconds`	External systems (e.g., document management systems) may respond slowly; this provides sufficient time to retrieve file content.

Common Pitfalls

External system interface returns an HTTP 504 Gateway Timeout error, preventing file import. This usually happens when files are too large or the external system processes slowly, and HTTP_REQUEST_TIMEOUT_SECONDS is set too low.
After uploading policy documents, the AI fails to accurately answer questions involving specific clauses, providing only general responses. This is due to an improper document segmentation strategy where key clauses are split, indicating unreasonable maxContext or Chunk size (Segment Length) settings.
After an update, an external speech-to-text service (e.g., POST /v1/audio/transcriptions) that previously worked correctly now fails. This might be due to changes in interface signatures, authentication methods, or request parameters after the version upgrade, requiring adjustments according to the new API documentation.

How to Verify Configuration

Upload a large PDF audit report containing complex tables and images. Check if its parsing status is successful. Randomly query key information from the report to verify answer accuracy.
Query a specific compliance requirement, such as GMP Clause 4.12, via the HTTP interface. Verify that the returned result accurately points to the original clause and includes its complete context.
Simulate a delayed response from an external document management system, for example, by artificially setting a 200-second delay. Then, attempt to import a file and observe if PARSE_FILE_TIMEOUT_SECONDS and HTTP_REQUEST_TIMEOUT_SECONDS configurations effectively prevent timeout errors.
Compare the original policy text stored in FastGPT's internal knowledge base with the source files from the external system. Randomly select 5-10 key paragraphs and confirm that their content and format are consistent, especially regulatory numbers and date formats.

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.