HTTP Interface and External Systems for Rehabilitation

Data Characteristics for This Category

Rehabilitation equipment quality documents, such as production batch records, inspection reports, calibration certificates, and risk management files, typically exist as PDFs, Word documents, or scanned images. Data sources are diverse, including internal systems of equipment manufacturers, third-party testing agencies, and feedback from clinical users. Update frequency varies by document type: production batch records generate in real-time with manufacturing processes, while annual quality review reports update periodically. Document structure often includes standardized test items, methods, acceptance criteria, and actual measured values in inspection reports. Fields and units are highly specialized; for example, "compressive strength" may use "MPa" as its unit, and "fatigue life" may use "cycles." Calibration certificates detail calibration dates, equipment, environmental conditions, and calibration results for "deviation" and "uncertainty."

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

The diversity of data sources for rehabilitation equipment quality documents requires FastGPT's HTTP interface to be highly flexible. It must integrate with various data transfer protocols, such as RESTful API or SOAP. Inconsistent document update frequencies necessitate external systems to employ polling, webhooks, or incremental synchronization strategies when calling the interface. This ensures the timeliness of knowledge base content. For real-time data like production batch records, the HTTP interface must support high-concurrency requests and fast responses. The large number of specialized fields and units in documents requires external systems to preprocess data structures during HTTP interface transmission. This ensures critical information is accurately parsed and mapped to specific knowledge base fields; for instance, values with "MPa" units must be recognized as strength parameters. Additionally, integrating scanned documents demands OCR capabilities from external systems, with results transmitted via the HTTP interface including text location information.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`HTTP_REQUEST_TIMEOUT_SECONDS`	`60 seconds`	Allows sufficient time for uploading or downloading potentially large rehabilitation equipment quality documents.
`maxContext`	`2000 characters`	Ensures capture of specialized terminology and detailed descriptions within documents.
`Chunk size` (Segment Length)	`500 characters`	Balances semantic completeness with efficient segment retrieval, avoiding overly long or short text blocks.
`Similarity threshold` (Similarity Threshold)	`0.75`	Guarantees high relevance of retrieval results to rehabilitation equipment-related queries, reducing irrelevant information.
`Rerank result count` (Reranked Return Count)	`Top 5`	Focuses on the most relevant few documents, improving user information retrieval efficiency.
`Knowledge Base Data Source Type`	`HTTP Interface`	Directly obtains data from external quality management systems or document repositories, enabling automated integration.

Three Common Mistakes

Symptom: After an external system uploads a file via the HTTP interface, no corresponding document content generates in the knowledge base. Reason: Incorrect Content-Type header setting prevents FastGPT from correctly parsing the file type.
Symptom: Data called via the HTTP interface appears empty or incomplete when referenced in the knowledge base. Reason: The JSON data structure returned by the external system does not match FastGPT's predefined field mappings for the knowledge base, preventing key information extraction.
Symptom: A CORS error occurs when calling an external API. Reason: The FastGPT server is not configured to allow cross-origin requests from third-party domains, or Access-Control-Allow-Origin does not include the correct origin.

How to Verify Configuration

Use the FastGPT management interface to confirm that rehabilitation equipment quality documents synchronized via the HTTP interface are correctly ingested and their content can be previewed.
Test the knowledge base's retrieval capabilities using queries containing specialized rehabilitation equipment terminology. Check the accuracy and relevance of returned results and verify reference sources.
Simulate an external system uploading a new rehabilitation equipment inspection report via the HTTP interface. Observe if the knowledge base content updates within the expected timeframe and check if key document fields are correctly parsed.

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.