HTTP Interface and External Systems for Medical Information

Data Characteristics for This Category

Medical Information (MI) response tracing data primarily originates from clinical research, pharmacovigilance, medical conferences, and journal literature. This data typically exists as unstructured text, semi-structured reports (e.g., PDFs, Word documents), or structured tables (e.g., adverse event reports). Update frequencies vary; literature might update monthly or quarterly, while clinical trial data can generate in real-time as projects progress. Document structures are complex, involving medical terminology, abbreviations, dosage units (mg, ml, IU, etc.), and time units (hours, days, years). Key fields include patient identifiers, drug names, indications, adverse event descriptions, response content, response timestamps, responder personnel, information sources, and confidence levels.

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

The diverse sources and inconsistent update frequencies of response tracing data demand highly flexible HTTP interfaces. These interfaces must handle various data formats and real-time requirements. For example, bulk importing historical literature data requires interfaces that support large file uploads and asynchronous processing. Conversely, handling real-time adverse event reports necessitates low-latency synchronous interfaces. Complex document structures and specialized medical terminology mean external systems may require preprocessing before uploading, such as entity recognition and standardization, to ensure data quality. The specificity of fields, like dosage and time units, requires accurate mapping during transmission to prevent unit confusion or loss. High data sensitivity mandates robust security, authentication mechanisms (e.g., API_KEY, OAuth), and encrypted data transmission (HTTPS) for compliance.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`500 MB`	Medical reports and literature can contain numerous images and charts, leading to large file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Parsing large files and extracting text can be time-consuming, requiring sufficient processing time.
`maxContext`	`3000 Tokens`	Response tracing content may include detailed medical descriptions, necessitating a longer context window.
`Similarity threshold`	`0.75`	Ensures recalled tracing content is highly relevant to the query, reducing inaccurate medical information.
`Rerank result count`	`Top 5 entries`	For MI responses, precision takes precedence over quantity, focusing on the most relevant items.
`HTTP_REQUEST_TIMEOUT`	`120 seconds`	External systems may involve complex calculations or database queries, requiring ample response time.

Common Pitfalls

Observation: After uploading an image, it displays correctly in the chat interface but becomes unavailable after approximately one minute. Reason: The temporary signed URL from the external storage service (e.g., OSS) expires, causing the image link to become invalid. Ensure image links have persistent access permissions or are refreshed periodically.
Observation: When configuring a custom channel to call an external Rerank service, the HTTP status code returns 401 Unauthorized or 403 Forbidden. Reason: The API_KEY or Bearer Token is configured incorrectly, or the external service's IP whitelist does not include the FastGPT instance's egress IP.
Observation: Some critical fields (e.g., drug dosage) in response tracing data uploaded via the interface appear empty or are parsed incorrectly in the system. Reason: The JSON structure of the uploaded data does not match FastGPT's expected field mapping, or not all medical measurement units were standardized during data preprocessing.

Validation Steps

Upload response tracing files in various formats (PDF, Word, image). Verify that file content is correctly parsed and that all key fields (e.g., drug name, adverse event description) are accurately extracted.
Simulate high-concurrency scenarios by continuously submitting multiple MI response queries via the HTTP interface. Observe system response time stability and check if the HTTP_REQUEST_TIMEOUT configuration prevents timeout errors.
Test the external system interface's authentication mechanism. Attempt calls using an invalid API_KEY or Bearer Token to confirm the system correctly returns 401 or 403 error codes.
Compare the response tracing data stored in FastGPT's internal database with the original data source. Check data completeness, especially the accuracy of medical terminology and units, to ensure no data loss or misinterpretation.

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.