HTTP API and External Systems for siRNA Nucleic Acid Drug Regulations

Data Characteristics

siRNA nucleic acid drug regulations and Standard Operating Procedures (SOPs) typically exist as PDFs, Word documents, or structured text. These documents originate from internal pharmaceutical company regulatory departments, R&D teams, or external regulatory bodies. Update frequencies vary; new drug development phases might see monthly revisions, while post-market documents might update annually or as regulatory requirements dictate. Content covers manufacturing processes, quality control, clinical trial protocols, pharmacokinetics, toxicology reports, and approval procedures. Fields and units are highly specialized. For example, "half-life" uses hours (h) or minutes (min), "purity" uses percentages (%), and "dosage" may involve micrograms (µg) or nanomoles (nM). Complex charts, chemical structures, and statistical data often accompany these values. These documents are characterized by large text volumes, dense specialized vocabulary, and frequent cross-references.

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

The specialized and complex nature of siRNA nucleic acid drug regulation documents imposes specific requirements on HTTP APIs and external system integration. First, non-textual information like chemical structures and charts requires the API to handle rich text or embedded objects, or convert them into searchable textual descriptions during preprocessing. Second, uncertain update frequencies demand external systems support flexible incremental update mechanisms to avoid resource waste from full synchronization. Internal cross-references necessitate establishing effective inter-document linking during knowledge base construction, allowing traceability to original sources during Q&A. Furthermore, the extensive specialized terminology and measurement units require text parsers to possess high domain vocabulary recognition capabilities. Parameter configurations must reserve sufficient context windows to ensure accurate understanding of specialized expressions. API response time and data throughput must also meet requirements to handle large file transfers and parsing.

Configuration Settings

Common Pitfalls

• Symptom: An external system calls the FastGPT API to upload a document and receives a 504 Gateway Timeout error. Reason: siRNA regulation documents are large, and file parsing time exceeds the default timeout settings of the gateway or FastGPT service.
• Symptom: When querying the "half-life" of a specific siRNA drug via the HTTP API, the result is empty or inaccurate. Reason: The knowledge base did not adequately consider the close association between units (e.g., h, min) and numerical values during text segmentation, leading to information loss or insufficient context.
• Symptom: After increasing the custom retrieval count to 6 via the API, further increases are not possible, and no error is reported. Reason: In a self-hosted environment, the MAX_RETRIEVAL_COUNT parameter in system environment variables or configuration files has reached its upper limit and requires manual adjustment.

Verification Steps

• Upload a siRNA nucleic acid drug regulation document containing complex charts and specialized terminology via FastGPT's API. Check if it successfully parses and stores the document.
• Use FastGPT's testing tools or a custom interface to query the knowledge base. Questions should cover key specialized vocabulary and measurement units from the document. Observe the accuracy and completeness of the returned results.
• Check FastGPT's backend logs for any abnormal information during document upload and parsing. Verify that parameters like PARSE_FILE_TIMEOUT_SECONDS are effective.

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.