HTTP Interface and External Systems for Solid Tumor

Data Characteristics for This Category

Solid tumor protocols and SOP (Standard Operating Procedure) data primarily originate from internal documents, industry guidelines, and national regulations published by medical institutions, pharmaceutical companies, and clinical research organizations. This data has a relatively low update frequency, typically revised quarterly or annually. However, temporary updates may occur with new drug approvals or significant breakthroughs in treatment plans. Document structures are mainly PDF, Word, and RTF formats. Content covers disease staging, diagnostic criteria, treatment pathways, medication specifications, and adverse reaction management processes. Common fields include Disease Type, Treatment Stage, Drug Name, Dosage Unit (e.g., mg/kg, mg), Administration Route, Adverse Reaction Grade (e.g., CTCAE v5.0 grading), and Follow-up Period. Some data may include charts or flowcharts, requiring structured extraction.

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

The dispersed sources and inconsistent update frequency of solid tumor protocol and SOP data require the HTTP interface to have flexible data source configuration capabilities. It must integrate with various document management systems or API interfaces. The diversity of document formats necessitates robust document parsing capabilities from external systems, especially for accurate text recognition within tables and charts in PDFs and Word documents. The low update frequency means that data synchronization strategies can employ periodic full synchronization supplemented by incremental updates, reducing unnecessary API call burdens. Standardizing fields like Dosage Unit and Adverse Reaction Grade requires external systems to perform normalized mapping after data extraction to ensure AI models correctly interpret them. Due to sensitive medical information, interface calls must strictly adhere to access control and data security protocols, such as using OAuth2 or API Keys for authentication and encrypting transmitted data.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale for Recommendation
`external_api_url`	`https://api.example.com/onco_protocols`	Points to the API endpoint of the authoritative internal institutional protocol library.
`request_method`	`POST`	Most document management system APIs use POST requests for data querying or retrieval.
`request_headers`	`Authorization: Bearer <token>`	Ensures authentication and access control for the external system accessing the interface.
`parse_timeout_seconds`	`300 seconds`	Allows sufficient time for parsing large SOP documents, preventing timeouts.
`data_update_frequency`	`Every 7 days`	Solid tumor protocols have longer update cycles, reducing unnecessary API call frequency.
`max_retries`	`3 times`	Handles network fluctuations or temporary external system failures, improving data acquisition stability.

Three Common Pitfalls

HTTP requests return 401 Unauthorized or 403 Forbidden status codes because the Authorization or API Key configuration is incorrect or expired, preventing the external system from authenticating.
The data structure returned by the external interface does not match expectations, leading to critical fields (e.g., Disease Type, Drug Name) not being extracted correctly. This typically occurs when the API response format changes, but the FastGPT HTTP node configuration is not updated accordingly.
After document parsing, AI responses show confusion in dosage units or errors in adverse reaction grade determination. This indicates the parser failed to correctly identify and standardize domain-specific units and grading systems like mg/kg or CTCAE v5.0.

How to Verify Correct Configuration

After calling the HTTP interface, check if the HTTP response status code is 200 OK and if the returned raw data contains the expected document list or content.
Validate the document parser's results for randomly selected solid tumor SOP documents, ensuring core fields like Disease Type, Drug Name, and Dosage Unit are accurately extracted.
Run test cases. Ask questions about specific protocol content and verify if the AI's answers correctly reference or summarize details from the external system, such as a specific drug's administration route or adverse reaction management process.
Check logs for frequent parse_timeout_seconds timeout warnings. Adjust the timeout duration based on actual document size and parsing efficiency.

Note: The values provided are common starting points. They 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.