HTTP Interface and External Systems for Academic Promotion

Data Characteristics in This Category

Clinical trial pre-screening data for academic promotion primarily originates from global clinical trial registries (e.g., ClinicalTrials.gov, WHO ICTRP), public trial plans from pharmaceutical companies, academic conference abstracts, and relevant journal articles. This data updates frequently, with new trial registrations, status changes, and result publications occurring often. Document structures typically include basic trial information (title, investigator, sponsor), trial design (inclusion criteria, exclusion criteria, study phase), interventions, primary/secondary endpoints, recruitment status, and locations. Field content is complex; for example, inclusion criteria may contain disease diagnostic codes (e.g., ICD-10), biomarker results, and prior treatment history, involving medical terminology and numerical ranges with diverse units (e.g., mg/kg, mmol/L, years).

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

High-frequency data updates require HTTP interfaces to have efficient fetching and synchronization mechanisms to ensure information timeliness. Complex document structures and diverse field types mean interfaces must support flexible data parsing and mapping rules, such as unifying inclusion criteria from different sources into a comparable structure. The large volume of medical terminology and numerical range fields necessitates considering encoding consistency and data type validation during data transmission and storage to avoid errors due to inconsistent units or formats. When integrating external systems, the system needs to handle different registry API authentication methods and rate limits. It also needs to cope with timeouts or connection interruptions that may arise from large data volumes and frequent requests, ensuring data transmission stability and integrity.

Configuration Strategy

Configuration Item	Recommended Value	Rationale
`HTTP_REQUEST_TIMEOUT`	`60 seconds`	Handles transmission delays when external APIs respond slowly or data volumes are large.
`MAX_BODY_SIZE`	`100 MB`	Accommodates detailed descriptions and file attachments that clinical trial data may contain.
`RETRY_ATTEMPTS`	`3 times`	Addresses occasional external interface failures or network fluctuations causing data fetching errors.
`PARSE_FILE_TIMEOUT_SECONDS`	`300 seconds`	Processes complex document structures, preventing interruptions due to excessively long parsing times.
`CHUNK_SIZE`	`800–1200 characters`	Balances textual semantic integrity with vector retrieval efficiency, adapting to medical description lengths.
`CONCURRENT_REQUESTS_LIMIT`	Calibrate based on actual measurements	Adheres to external API rate limits, avoiding throttling or IP bans.

Common Pitfalls

HTTP interface calls return 400 InternalError.Algo.InvalidParameter because the uploaded document size exceeds the MAX_BODY_SIZE limit.
Some clinical trial data is missing after a knowledge base update because the external API returned data with an encoding format inconsistent with the system's expectations, leading to parsing failures.
Frequent API calls lead to connection interruptions, with logs showing a 500 error code. This occurs because CONCURRENT_REQUESTS_LIMIT is not configured correctly, triggering the external system's anti-scraping mechanism.

Verification Steps

Trigger a data synchronization manually via the "Data Source" module in the FastGPT backend. Check logs for 200 status codes and successful import records.
Randomly select several synchronized clinical trial records. Verify that key fields (e.g., trial title, primary endpoint, inclusion criteria) match the original data source.
Simulate high-concurrency requests in an integration testing environment. Observe if the system handles them stably and check if the success rate of external system API calls meets expected thresholds.

Note: The values provided are common starting points. Measure against your own samples for optimal performance.

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.