What the Data for This Category Looks Like
The typical entities in this category are suppliers of automotive brake, steering, chassis, and other system components. Daily generated documents include control plans, process flowcharts, work instructions, first article and patrol inspection records, SPC reports, PPAP materials, and 8D reports. Data sources include customer drawings and special characteristic lists, ERP/MES systems, measuring tool data, equipment process parameters, and supplier quality certificates. Update frequency follows per batch, per shift, or continuous collection. Documents contain structured fields such as part numbers, tolerance ranges, and inspection values, plus unstructured problem analysis content. Units include millimeters, newtons, hours, and other common industrial measurement standards.
What Constraints These Characteristics Impose on Document Parsing and Chunking
The multi-source data and high-frequency update characteristics of this category create multiple constraints for the document parsing and chunking workflow. First, the data includes two formats: structured tables and unstructured reports. The workflow must retain table structure while maintaining semantic context coherence. Second, key information such as special characteristics and tolerance ranges must be fully retained in a single chunk. This avoids splitting that prevents the audit link from associating critical parameters. Third, the high-frequency demand for batch uploads requires the parsing process to support large-volume files. It must also avoid overly high vectorization task loads caused by unreasonable chunking. Finally, per constraints from vehicle customer quality systems, parsing results must accurately match the process and batch association information in the document. Critical business context must not be lost.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Daily documents contain key fields such as special characteristics and tolerances. Chunk length must cover single-process job content to avoid splitting critical information. |
chunkSplitter | Paragraph + semantic chunking | Documents include structured reports and unstructured documents. Mixed chunking retains context association and adapts to parsing requirements for different formats. |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Batch-uploaded PPAP materials and SPC reports have large file sizes. Sufficient parsing time must be reserved to adapt to delays from third-party services or local deployments. |
customPdfParse | Enabled | Some documents contain embedded tables such as control plans. Enabling custom parsing retains table structure and avoids chaotic table content after parsing. |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Packaged files of multi-batch patrol inspection records for batch uploads must meet storage and parsing limits to adapt to batch business needs. |
chunkSettingMode | Manual configuration | Parameters must be adjusted for different document types such as structured reports and unstructured documents to adapt to business constraints. |
Three Common Mistakes
- Phenomenon: When uploading CSV or Excel files, the interface shows no table upload option, only a general document upload entry. Cause: The
customPdfParseconfiguration is not enabled, or the structured parsing mode for the corresponding file collection is not switched. - Phenomenon: When using a third-party deployed large language model, the file parsing interface returns a timeout or parsing failure error. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter is not adjusted to adapt to the parsing delay of the third-party model, or network configuration restricts access to the parsing service. - Phenomenon: After uploading batch PDF files, the vectorization task queue backs up severely, and processing takes much longer than expected. Cause: The
chunkSizeparameter is set too large. A single chunk contains too much irrelevant information, increasing the vectorization calculation load.
How to Confirm the Configuration Is Correct
- Upload a standard control plan PDF, and check if the parsed chunks retain complete context of key fields such as special characteristics and tolerance ranges.
- Upload a CSV-format patrol inspection record file, and confirm that structured fields such as process number, inspection result, and inspection time can be extracted after parsing.
- Adjust the
PARSE_FILE_TIMEOUT_SECONDSparameter, then upload a single PPAP material package with a volume not exceeding 1000 MB, and verify that the parsing task can be completed within the set time. - View the parsing logs of the file collection, confirm that there are no format errors or field loss records, and match the field structure of business documents.
- Confirm that the current FastGPT version is v4.17.0 to ensure the custom parsing function works properly.
Note: The configuration values listed above are common starting points. They should be evaluated against the reader's own samples and business requirements.