Data Characteristics in This Category
Solid tumor data primarily originates from clinical trial reports, pathological diagnosis systems, molecular testing platforms, and drug discovery databases. Data update frequencies vary. Clinical trial data is released incrementally as trials progress, while molecular test results are generated in real-time or near real-time. Document structures are complex, often including semi-structured medical text, structured experimental results, and image reports. Field names are highly specialized, such as tumor type, staging, gene mutation sites, and PD-L1 expression levels. Units involve biological and pharmaceutical measurements like micromolar (µM), nanomolar (nM), and copy number (CN). Data frequently contains numerous medical abbreviations and coding systems.
Constraints Imposed by These Characteristics on "HTTP Interface and External Systems"
The diversity and specialized nature of solid tumor data require HTTP interfaces with robust data parsing and validation capabilities. Parsing semi-structured text necessitates complex regular expression matching or natural language processing (NLP) pre-processing to extract key information. High-frequency updates from molecular testing data demand an interface design that supports high concurrency and low-latency responses to ensure real-time information. The presence of multiple units means interfaces must clearly label units when receiving and sending data to avoid confusion. Additionally, when integrating external systems involving sensitive patient information or clinical data, strict data security and privacy protection protocols must be followed, such as OAuth 2.0 authentication and encrypted data transmission, to ensure data flow compliance.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxRequestTimeout | 30000 ms | Allows sufficient time for complex data processing and external system response. |
requestBodyType | application/json | Most biomedical APIs use JSON for data exchange. |
authMethod | OAuth 2.0 | Industry standard for secure user authorization and data access. |
responseParsingRules | Custom Regex or JSONPath | Adapts to semi-structured data and complex JSON nesting, precisely extracting key fields. |
retryAttempts | 3 times | Handles network fluctuations or transient external service failures, improving success rate. |
rateLimitPerMinute | Calibrate by actual measurement | Adjust flexibly based on external API rate limiting policies and business needs. |
Three Common Pitfalls
- HTTP interfaces return 5xx status codes or empty responses. This may be due to external system overload or incorrect interface path configuration.
- Certain key fields in the response data are empty. This usually indicates inaccurate response parsing rules that failed to correctly match the data.
- Requests sent without a response for a long time, resulting in a timeout. This may be due to
maxRequestTimeoutbeing set too short or the external API taking too long to process.
How to Verify Correct Configuration
- Invoke core solid tumor data query interfaces multiple times with different parameters. Check if the response data is complete and matches the expected field structure.
- Simulate abnormal responses from external systems (e.g., returning error status codes). Verify that FastGPT correctly captures and handles these exceptions.
- Perform interface performance tests during peak hours or under concurrent scenarios. Ensure response times are within acceptable limits and check for rate limiting errors.
- Cross-reference external API documentation. Verify request headers, request body parameters, response body fields, and their units to ensure data transmission format and content are correct.
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.