What the data for this category looks like
Data for auto service intelligent due diligence reports comes from four main sources: vehicle administration registration systems, partner repair shop work order systems, partner insurance claims systems, and second-hand vehicle transaction data sources. Update frequencies vary across sources. Basic vehicle registration information syncs in real time. Repair records update when work orders are completed. Insurance claims data syncs within 24 hours after case closure. Second-hand vehicle transaction data updates in daily batches.
Each due diligence report has a fixed document structure, including fields such as VIN, registration date, total mileage, repair item details, claim amount, and number of vehicle transfers. Mileage uses km as the unit, amount uses yuan as the unit, and number of transfers is an integer count.
What constraints these characteristics impose on HTTP interfaces and external systems
Connecting multiple heterogeneous data sources requires compatibility with different authentication protocols. Some vehicle administration data sources only support OAuth2.0 authentication. Repair shop interfaces use static API key verification. Separate adaptations must be made in HTTP interface configurations.
Different update frequencies require differentiated interface call cycle configurations. Real-time registration data must be pulled via webhook triggers. Batch-updated second-hand vehicle data requires daily scheduled pull tasks.
Special requirements apply to field formats. VIN codes must follow the 17-character validation rule. Total mileage may contain null values. Field validation and null value handling logic must be configured in interface requests.
A single due diligence report may include multiple repair details, resulting in large interface return data volumes. Pagination parameters must be adjusted to avoid request timeouts. When importing large numbers of due diligence reports in batches, single upload document count limits must be respected to avoid MAX_CONTENT_LENGTH errors.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_BATCH_SIZE | 50–100 documents per batch | Auto service due diligence reports include multiple repair details per document. Uploading too many documents at once triggers MAX_CONTENT_LENGTH errors. This range adapts to reasonable load for batch import scenarios |
HTTP_SYNC_INTERVAL | Real-time/daily, configured as needed | Update frequencies differ across data sources. Set the pull interval to 0 seconds for real-time registration data, and 86400 seconds for batch second-hand vehicle data |
API_AUTH_TYPE | OAuth2.0/API_KEY, selected as needed | Different data sources require matching authentication methods. Vehicle administration systems use OAuth2.0, and repair shop interfaces use API_KEY |
VIN_VALIDATION_ENABLE | Enabled | The VIN code, a core field for auto service data, follows a fixed 17-character format. Enabling validation filters invalid data |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Single due diligence reports include multiple repair details, resulting in longer parsing times. Extend the timeout to avoid request interruptions |
MAX_RESPONSE_BODY_SIZE | 10 MB | Batch-imported due diligence report collections have large data volumes. Adjust the response body size limit to accommodate batch requests |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- A batch import request returns a
413 Request Entity Too Largeerror. This occurs because theUPLOAD_BATCH_SIZEconfiguration is not adjusted, the number of documents uploaded in a single batch exceeds the system default limit, andMAX_RESPONSE_BODY_SIZEis not set to accommodate batch data. - Calling a workflow HTTP interface after embedding in a business system returns a
401 Unauthorizederror. This occurs because theWORKFLOW_HTTP_AUTHparameter is not configured, and the business system user identity token is not included in the request header, so the FastGPT platform cannot verify request legitimacy. - Querying vehicle data via an integrated SQL database returns an
Empty Result Seterror. This occurs because the correct database table field mapping is not configured, or core query conditions such as VIN code are not included in the request, so target data cannot be matched.
How to confirm configuration is complete
- Send a single-document HTTP import request, check that the return status code is
200 OKand that the document content is correctly synced to the knowledge base. - Call the workflow HTTP interface, include the business system user identity token, check that the return status code is
200 OKand that the corresponding workflow is triggered. - Execute a SQL database query request, check that the returned results include vehicle data matching the VIN code, and that field formats meet expectations.
- Send a batch import test, check that
413orMAX_CONTENT_LENGTHrelated errors are not triggered, and that all documents are successfully imported.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.