HTTP Interface and External Systems for Preclinical Safety

Data Characteristics

Preclinical safety assessment data originates from toxicology study reports, pharmacokinetic data, pathological analysis results, and in vitro/in vivo experimental data. This data typically exists in a mixed format, including structured data (e.g., CSV, JSON) and unstructured data (e.g., PDF, Word documents). The data update frequency is relatively low, usually occurring in batches after completing an experimental phase or generating a periodic report. Report document structures are often complex, containing multi-level nested sections and tables. Field names frequently use specialized abbreviations or specific terminology (e.g., NOAEL, AUC, Cmax), and units are highly specialized (e.g., mg/kg/day, μg·h/mL). The data volume is typically large, with individual study reports reaching hundreds of pages.

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

The diversity of data sources requires interfaces to handle various data formats for upload and parsing. The infrequent update characteristic means real-time requirements are low, but data completeness and consistency are critical. Therefore, batch data synchronization or scheduled task-triggered modes are more suitable. The complexity of document structures challenges parsing capabilities, requiring robust text extraction and structuring tools to accurately identify key toxicity indicators like NOAEL. The specialized nature of fields and units necessitates custom parsing rules and unit conversion logic to prevent data errors caused by misinterpreting field meanings or unit mismatches. Large data volumes demand efficient data transmission and processing capabilities from the interface to avoid timeouts or resource exhaustion.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`requestTimeoutSeconds`	`300 seconds`	Handles parsing large reports and multi-file transfers, preventing timeouts due to extended processing times.
`maxPayloadSizeMB`	`100 MB`	Accommodates the file size of a single toxicology report or batch data, ensuring complete data upload.
`chunkSizeTokens`	`800–1200 characters`	Optimizes the segmentation of lengthy professional documents, ensuring each segment contains sufficient context while avoiding excessive length that could reduce processing efficiency.
`maxConnections`	`10`	Balances concurrent processing capability with system resource consumption, suitable for non-real-time data updates.
`errorRetryAttempts`	`3 times`	Addresses network fluctuations or temporary external system failures, enhancing data synchronization robustness.
`customHeaders`	`Content-Type: application/json`	Ensures correct communication with external APIs, especially when integrating with specific data lakes or data warehouses.

Common Pitfalls

HTTP requests return 4xx or 5xx error codes, but the FastGPT workflow shows success. This usually occurs due to incorrect configuration of HTTP response status code judgment logic, causing the workflow to consider the request successful even if the external system returns an error.
After parsing a report, critical fields (e.g., NOAEL values) are empty or inaccurate. This happens when text parsing rules do not adequately cover all variations or special formatting in the report, leading to critical information extraction failure.
Data synchronization tasks frequently time out, even with seemingly small data volumes. This could be due to unstable network conditions during file transfer or the external system's response time being too long, exceeding the requestTimeoutSeconds setting.

Verification Steps

Review FastGPT's debug logs to inspect the complete HTTP request sending and response receiving process, and verify that response status codes meet expectations.
Upload a preclinical safety assessment report with known NOAEL values, execute the parsing process, then check if the extracted field results in FastGPT match the original report, confirming the effectiveness of the parsing rules.
Conduct multiple data synchronization tests using report files of varying sizes and complexities. Observe if the task execution time remains within the requestTimeoutSeconds threshold and verify data transfer completeness.

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.