Data Profile for This Category
Data originates from the road transport administration system, the national public service platform for dynamic information of road transport vehicles, and the vehicle and practitioner database. The update frequency is daily. Commonly processed documents include business license applications, vehicle technical files, driver qualification materials, safety production management systems, and road transport business licenses. These cover the full process of application, qualification verification, and daily management.
Document structures include structured fields such as vehicle license plate number and qualification certificate number, alongside unstructured text such as safety management system details. Some documents are scanned copies or mixed-format files exported across multiple systems.
Constraints for Document Parsing and Chunking
Daily updated batch data requires parsing processes to be efficient and stable, to avoid delaying inquiry response times. The mixed set of document types requires chunking strategies to support both structured field extraction and semantic retention for unstructured text. Format differences from cross-system exports require parsing links to have compatible support for document typesetting from different sources.
Some documents are scanned copies, so parsing tools must support image-to-text conversion and structured extraction to ensure full information availability during inquiries. Errors may lead to consequences such as license rejection and enterprise operational disruption, so parsing accuracy must meet business compliance requirements and prevent missing key fields.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Documents include long-text safety management systems and structured vehicle files. This range balances context integrity and chunk granularity, avoiding overly large or small single chunks |
chunkSplitter | Split by paragraph + title | Documents have clear chapter titles and paragraph divisions. Splitting according to this rule preserves semantic integrity and facilitates accurate matching of subsequent inquiry questions |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Parsing large vehicle technical files takes a long time. This range adapts to the processing rhythm of daily batch updated data and avoids timeout failures of batch tasks |
UPLOAD_FILE_MAX_SIZE | 1000 MB | The collection of enterprise qualification materials uploaded in a single batch may reach a large volume. This value meets daily batch upload requirements |
customPdfParse | Enabled | Some licenses and vehicle files are scanned copies. Enabling custom parsing optimizes the accuracy of image-to-text and embedded image extraction |
chunkSettingMode | Manual configuration | Different document types (application materials, vehicle files, management systems) require differentiated chunking parameters. Manual configuration offers stronger adaptability |
Three Common Configuration Errors
- Symptom: The parsed result of uploaded vehicle technical file PDF lacks embedded vehicle photo fields, and the interface shows empty image placeholders. Cause: The
customPdfParseconfiguration is not enabled, and the default parsing logic does not adapt to the image extraction process for scanned PDFs. - Symptom: When batch uploading daily business license application materials, some tasks show timeout errors with a 504 status code. Cause: The
PARSE_FILE_TIMEOUT_SECONDSsetting is lower than the actual parsing time, and does not adapt to the processing rhythm of large application materials. - Symptom: When retrieving inquiries related to driver qualification, the returned chunked content includes irrelevant safety production management system paragraphs, leading to redundant recall results. Cause: The
chunkSizesetting is too large, and a single chunk contains irrelevant semantic content across chapters, making it impossible to accurately match inquiry keywords.
How to Verify Correct Configuration
- Upload a single driver qualification material PDF, verify that the parsed result includes structured fields such as qualification certificate number and issuance date, and confirm that both text and embedded images are correctly extracted.
- Upload a batch of daily updated enterprise qualification material collections, verify that all tasks do not experience timeouts or upload failures under the
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSconfigurations. - For inquiries about road transport business license changes, retrieve the knowledge base to confirm that the returned chunked content only includes license change-related clauses and processes, with no redundant irrelevant content.
- Adjust the
chunkSizeparameter to different ranges, compare the recall accuracy of the two retrieval results, and confirm that the chunk granularity adapts to the document structure characteristics of this category.
The values provided are common starting points and should be measured against samples from the actual deployment environment.
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.