In-Group Q&A for WeCom Group Automation: HTTP Interface and

Data Characteristics for This Category

WeCom in-group Q&A data in the biomedical field originates from daily member interactions, professional knowledge inquiries, and requests for help. Data updates frequently, especially during R&D progress announcements, clinical trial data releases, or regulatory policy changes, when information volume can surge. Document structures typically include fields like asker ID, ask time, question text, answerer ID, answer time, and answer text. Question text may contain specialized terms, abbreviations, drug names, and disease codes. Answer text may include professional terminology explanations, operational procedures, and reference links. Time units are usually precise to the second, and text length is measured in characters. There are no complex numerical unit conversions.

Constraints Imposed by "HTTP Interface and External Systems"

High-frequency updates require the HTTP interface to have efficient data retrieval mechanisms, such as incremental synchronization or Webhook pushes, to avoid re-transmitting large amounts of historical data. The presence of specialized terms and abbreviations demands robust natural language processing capabilities from external systems to ensure accurate semantic understanding. The multi-field nature of the data structure means HTTP request or response bodies need to support complex JSON or XML formats to transmit full Q&A context information. Data transmission security (e.g., HTTPS, authentication mechanisms) is a critical constraint due to potential involvement of sensitive R&D or patient information. For large data volumes, external system data storage and retrieval efficiency become challenging, requiring consideration of optimization measures like pagination and indexing.

Configuration Guidelines

Configuration Item	Suggested Value	Rationale
`externalApi.url`	`https://api.example.com/wechat/qa`	Points to the actual address of the WeCom group message or Q&A service interface.
`externalApi.method`	`POST`	Suitable for transmitting request bodies containing complex structured data.
`externalApi.headers`	`Authorization: Bearer YOUR_TOKEN`	Ensures external system authentication and secures data transmission.
`externalApi.bodyTemplate`	`{"question": "{{question}}", "senderId": "{{senderId}}"}`	Constructs the request body with question and sender ID according to external system API requirements.
`externalApi.timeoutSeconds`	`60`	Allows sufficient time for external systems to process complex queries and responses, preventing timeouts.
`response.extractField`	`$.answerText`	Extracts the answer text field from the JSON returned by the external system, e.g., `answerText`.

Three Common Mistakes

HTTP request timeout. Logs show Connection timed out or Read timed out. This usually happens when the external system takes too long to process complex queries, or network latency is high, and the timeoutSeconds parameter is set too low.
External system returns 401 Unauthorized or 403 Forbidden errors. This typically indicates incorrect, expired, or insufficient permissions for the Bearer Token in the Authorization header.
Q&A results lack critical information, such as an empty or incomplete answer text. This may be due to an inaccurate JSON path configured in response.extractField, failing to correctly parse the corresponding field in the external system's response body.

How to Verify Configuration

Use FastGPT's debugging interface to send a simulated in-group question containing biomedical specialized terms. Check if the HTTP request is successfully sent and an external system response is received.
Check external system logs to confirm receipt of the HTTP request from FastGPT. Verify that the question and senderId fields in the request body match expectations.
Validate the parsed answer text in FastGPT. Confirm its content exactly matches the answerText field returned by the external system, without truncation or parsing errors.
Adjust the timeoutSeconds parameter to simulate external system response delays. Verify FastGPT's behavior under different timeout settings.

Note: 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.