What the data for this category looks like
Business data for metal material processing mainly comes from production workshop ledger systems, physical and chemical test reports, and process parameter libraries. Teams update data per production batch. Single-batch data covers fields including material grade, tensile strength, yield strength, elongation, batch number, production team, inspection time, and more. Supported units include megapascals (MPa), percentage (%), tons (t), and others. A complete single business document runs 800–1500 characters, with a high share of structured fields. Some non-standard custom orders include additional process description documents.
What constraints do these characteristics impose on HTTP interfaces and external systems
The high share of structured fields paired with non-standard custom fields requires HTTP interfaces to support dynamic variables parameters for matching custom business fields. This avoids field missing caused by fixed mapping rules. Data updates per production batch, so interfaces must support pulling latest data by batch number. Request timeout must adapt to the regular response rhythm of workshop production. Single-batch data volume fluctuates, so batch calls must limit the maximum number of batches per request. This prevents the request body from exceeding transmission limits. Diverse units for physical and chemical parameters require interfaces to have built-in unit standardization logic. This avoids unit mismatches during cross-system calls.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Fixed as Bearer {interface key assigned by the platform} format | Complies with FastGPT interface authentication standards to ensure call legitimacy |
variables | Map fields including metal material processing batch number, material grade, test results, etc. | Adapts to dynamic business parameter requirements of the category, supports custom data input |
responseData | Extract structured business field set, filter redundant descriptive text | Matches the structured characteristics of category data, reduces interface transmission load |
| Request timeout | 60–120 seconds | Adapts to the pull response rhythm of workshop production data, avoids timeouts caused by data volume fluctuations |
| Maximum batches per request | First 10 batches | Controls the data scale of a single request to prevent exceeding HTTP transmission capacity limits |
Reference only; verify against the target FastGPT release and deployment documentation.
Three common configuration mistakes
- Batch execution nodes complete workflows during online debugging. They cannot finish all loops during API calls. This happens when the API call lacks batch execution timeout parameters, or the timeout period is too short to cover multi-batch data processing time.
- After calling the interface workflow, running data in the conversation log appears empty. This happens when the
responseDataparameter is not configured correctly, and valid business fields are not extracted. This causes the returned data to not be captured by the workflow. - After an agent with file upload enabled is published as an API, documents cannot be passed in. This happens when the temporary storage path for file uploads is not bound via the
variablesparameter, and document information is not passed to the workflow node.
How to confirm the configuration is correct
- Call the test interface, check if the returned
responseDataincludes the configured business fields. This confirms the field extraction logic is effective. - Pass single-batch test data, verify if the interface response duration falls within the preset timeout range. This confirms the timeout configuration is reasonable.
- Call the batch interface, check if the number of returned batch data matches the preset maximum batches per request. This confirms request scale control is effective.
- Check if the authentication parameter
Authorizationis configured correctly. Call the interface and receive a 200 status code to confirm identity verification is passed.
The values provided here are common starting points and should be measured against the reader's 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 2026-09-28.