What the data for this category looks like
Data sources include the Ministry of Industry and Information Technology Road Motor Vehicle Manufacturers and Product Announcements, monthly statistical data from the Commercial Vehicle Branch of the China Association of Automobile Manufacturers, public technical white papers from vehicle manufacturers, terminal license plate traceability data, and logistics company operation ledgers. Update cycles fall into three categories: announcement data is updated quarterly, industry statistical data is updated monthly, and operation ledgers and real-time order data are updated daily. Document structures include structured parameter manuals, long-text industry analysis reports, and supply chain contract documents with nested tables. Fields cover engine displacement (unit: liters), rated load mass (unit: kilograms), wheelbase (unit: millimeters), and operating mileage (unit: kilometers). Some export compliance documents also include multilingual parameter fields.
What constraints do these characteristics impose on the "context and token" link?
The varied update frequencies of commercial vehicle data cause fluctuations in token consumption during knowledge base synchronization. High-frequency synchronization of real-time operation data adds extra token usage. Structured parameter manuals have dense fields with attached units, and unnormalized fields lead to token redundancy during recall. Long-text industry reports and supply chain documents with nested tables can reach tens of thousands of tokens per single document. Without proper segmentation, these documents will exceed the model's context limit. Cross-document associated investment research requirements further expand the token usage scale of the context.
How to set the configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The token count of a single core parameter document for commercial vehicles is approximately 2000-3000. This range can accommodate 3-4 associated documents, matching the multi-data source association needs of investment research |
recallTopK | Top 6–8 entries | Commercial vehicle data has high field granularity. A sufficient number of documents must be recalled to cover core parameters, while controlling the token consumption scale |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Commercial vehicle supply chain documents mostly have complex nested tables, which take longer to parse. 120 seconds covers the parsing process for most long documents |
UPLOAD_FILE_MAX_SIZE | 500 MB | Single annual commercial vehicle industry reports can reach hundreds of MB. Raising the upload upper limit supports complete knowledge base file imports |
chunkSize | 1000–1500 characters | Commercial vehicle structured documents have strong field correlation. This segmentation length preserves the logical integrity of fields and avoids breaking parameter associations during splitting |
similarityThreshold | 0.75–0.85 | Commercial vehicle parameters have high precision requirements. A threshold that is too low will introduce irrelevant field data, while a threshold that is too high may miss parameter documents with fine-grained matches |
The parameter values provided on this page are all common recommendations used as starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common configuration mistakes
- Phenomenon: An "IPROXYAPIENDPOINT or AIPROXYAPITOKEN is not set" error is returned when starting knowledge base parsing or a workflow. Cause: Commercial vehicle investment research requires synchronization of external industry data interfaces. Failure to configure the proxy endpoint and token causes the model to fail to call external data sources, resulting in additional uncounted token consumption.
- Phenomenon: Workflow node results include irrelevant document content from the global knowledge base. Cause: The global context call switch for the workflow node is not turned off, leading to cross-node token redundancy and exceeding the preset context limit.
- Phenomenon: A 404 error occurs when clicking "View Original Content" to download commercial vehicle documents uploaded to the knowledge base. Cause: The file storage path configuration for large industry reports does not match the front-end call path, causing the download link to fail and preventing normal access to original file content.
How to verify correct configuration
- Upload a commercial vehicle parameter manual, check the parsed segmentation results, and adjust the
chunkSizeconfiguration until the field correlation is complete. - Initiate a query involving multiple commercial vehicle documents, and verify whether the number of returned context recall entries falls within the range configured for
recallTopK. - Check the context settings of workflow nodes, confirm that only the knowledge base documents associated with the current node are called, and no global context content is introduced.
- View system logs, confirm that file parsing does not trigger timeout errors corresponding to
PARSE_FILE_TIMEOUT_SECONDS, and the parsing process completes normally.
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.