What the Data for This Category Looks Like
Core data for this category is generated per vehicle VIN. Data sources include ERP/MES systems, VIN and configuration management systems, supplier batch libraries, tightening tool terminals, end-of-line (EOL) offline inspection lines, and quality traceability systems. Daily generated documents include production orders, VIN configuration lists, assembly work instructions, tightening torque data, offline inspection reports, rework records, and conformity release documents. Updates are triggered per vehicle. Key tightening and inspection data are synced in real time. Batch documents are updated per shift. Document structures use VIN as the unique identifier linked to multi-dimensional fields, including numeric torque parameters, qualification judgment markers, batch codes, and more. Units include newton meters, percentages, dates, and other specific types.
Constraints on Document Parsing and Chunking
The single-vehicle data binding tied to VIN requires the document parsing and chunking process to retain contextual association between VIN and its corresponding configuration, torque, and inspection results. This prevents field disconnection after chunking. Real-time updated tightening and offline inspection data require the parsing process to adapt to low-latency processing needs. Chunk length must match the compact size of single-vehicle data to prevent mixing of cross-vehicle data. Multi-source documents include multiple formats such as tabular inspection reports and textual work instructions. Parsing rules must adapt to different layouts. Chunking strategies must distinguish splitting logic for structured and unstructured content. Batch document collections updated per shift require the parsing process to support batch scheduling. Timeout thresholds must adapt to the total data size of a single batch of documents.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the compact size of single-vehicle core data, preventing loss of binding between VIN and associated fields after chunking |
chunkSplitter | Calibrated via actual testing | Ensures logical integrity for multi-format documents, distinguishing splitting rules for structured tables and unstructured text |
customPdfParse | Enabled | Adapts to structured PDF documents such as tightening data tables and VIN lists, improving parsing accuracy for tabular data |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the total parsing duration of batch documents per shift, preventing timeout interruptions for large batch documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Supports batch import of multiple document collections per shift, covering common batch bid-related document sizes |
chunkSettingMode | Manual configuration | For single-vehicle data tied to VIN, custom chunking rules offer more control than automatic mode |
Three Common Misconfigurations
- The symptom is a connection failure error when calling document parsing after deploying FastGPT v4.17.0 via local Docker. Attempting to use the local address 127.0.0.1 does not resolve the issue. The cause is network isolation between the parsing service and main service inside the Docker container, with incorrect port mapping or service linkage not configured.
- The symptom is that after uploading a document containing VIN and torque data, some fields in the parsing result are empty or the binding relationship with VIN is lost. The cause is that the
customPdfParseconfiguration is not enabled, leading to incorrect splitting of structured tabular data. - The symptom is that when uploading a batch of shift documents, the parsing task terminates early and returns a timeout error. The cause is that the
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted to match the duration for batch documents. The default threshold is insufficient to cover the total data volume of a single batch.
How to Verify Correct Configuration
- Upload a single test document containing VIN and tightening data, check whether the VIN field and corresponding torque parameters are fully bound in the parsing result.
- Adjust the
chunkSizeparameter, verify whether the length of the chunking result matches the preset range, and confirm that the chunking strategy takes effect. - Upload a batch of document collections, check whether the execution duration of the parsing task meets business requirements, and confirm that the timeout threshold configuration is reasonable.
- After verifying that
customPdfParseis enabled, check whether cell data from tabular documents is correctly extracted.
The values provided are common starting points and should be measured against the reader's own samples.