What This Type of Data Looks Like
Survey and design work consulting data comes from project survey reports, construction drawing design documents, project approval ledgers, and on-site construction feedback records. Data updates trigger at project progress milestones. Updates synchronize when plans adjust or approvals change. Each document includes a unique project ID, survey point coordinates, design parameters, and approval status fields. Survey hole depth uses meters as its unit. Design load uses kilonewtons as its unit. Some documents include associated construction node IDs and on-site test data.
Constraints for HTTP Interfaces and External Systems
Multiple fields in survey and design data require specific units. HTTP interfaces must retain original unit information during transmission. Losing unit information during parameter parsing causes errors in consulting replies. Each document has large content. Interface request and response body maximum sizes must support long text transmission. Data updates trigger at project milestones, with no fixed cycle. Interface calls must pull latest data on demand, or synchronize via external system project status change events. Some data links to multiple approval stages. Interfaces must include the unique project ID as a matching identifier. This ensures returned consulting data binds to the correct project. This page supports FastGPT v4.17.0.
How to Set Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Authorization | Bearer {configured API key} | Follow FastGPT interface authentication specifications to verify request legitimacy |
variables | {"project_id": "survey and design project ID", "unit": "meters/kilonewtons"} | Match field identifiers and unit requirements for survey and design data, accurately bind consulting data for the corresponding project |
responseData | Return only structured fields and associated approval status | Filter redundant long text, reduce interface transmission load, and meet the precise reply needs of consulting work |
| Maximum request duration | 600 seconds | Survey and design document parsing takes a long time; avoid request timeouts from short durations |
| Number of data items per request | First 8 items | Consulting work focuses on single project stages; excessive data increases reply delay |
| Number of timeout retries | 2 times | Balance request success rate and interface call costs, adapt to the non-fixed update rhythm of survey and design data |
Three Common Mistakes
- When sending consecutive consulting requests at short intervals, subsequent requests cannot interrupt the previous generation process, resulting in duplicate or outdated replies. No unique session identifier is included in the request, causing the interface to reuse previous context and not trigger a new generation task.
- The interface returns a 401 status code, indicating authentication failure. This occurs when the
Authorizationparameter does not include theBearerprefix, or the provided API key is invalid. - The interface reply does not include unit information for survey and design data, such as not labeling "meters" for survey hole depth or "kilonewtons" for design load. This happens when unit-related parameters are not passed in
variables, causing field units to be lost during data parsing.
How to Confirm Configuration is Correct
- Call the interface and check the returned
responseDatafield to confirm that structured fields and associated approval status information for the survey and design project are included. - Review the interface response results to confirm that no timeout error is triggered, and that the reply content matches the passed project identifier.
- Send multiple consulting requests at short intervals, and confirm that each returned reply is independent, with no context reuse or old data returned.
- Verify authentication validity, confirm that the
Authorizationparameter format meets requirements, and that no authentication failure prompt appears.
The values provided are common starting points and should be validated against actual deployment samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.