What the data for this category looks like
Auto parts data sources include enterprise PDM systems, CRM dealer communication records, official product announcements, and after-sales repair parts documentation. Update cadences fall into three categories: batch update compatible vehicle lists and parameters when new products launch, update compatible vehicle ranges quarterly for regular model parts, and sync immediately when compliance certifications change. Document structures are mostly structured fields, including part number, compatible vehicle, material, specification parameters, and compliance certification marks. Supporting marketing documents include script templates, adaptation cases, and product real-shot images. Field units are mostly physical measurement units, and some fields are enumeration values for compatible vehicle series.
What constraints these characteristics impose on workflow orchestration
The characteristics of structured parameters and multi-field association require workflows to support field mapping and parameter validation, to avoid generated content mismatching part numbers and compatible vehicles. The multiple update cadence characteristic requires workflows to support scheduled synchronization of PDM data and real-time processing of dealer inquiry content. Parameters with physical units require built-in unit validation rules in workflows to prevent incorrect specification descriptions. Marketing content must combine part and vehicle information, requiring workflows to complete field association before invoking large language models to ensure output content accurately corresponds to target parts and compatible vehicles.
How to set configurations
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
Knowledge base recall count | Top 8-12 entries | Auto parts knowledge base entries are mostly structured parameters; a small number of entries can cover core parameters and adaptation information, avoiding redundant content interfering with model generation |
maxContext | 4000-6000 characters | Parts product manuals and BOM list content is lengthy; sufficient context is needed to associate part numbers, compatible vehicles, and marketing scripts |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Batch BOM list files for parts contain large amounts of row data; parsing takes longer than general documents |
Chunk size | 800-1000 characters | Paragraphs in parts product documents mostly contain parameters and adaptation information; segment length adapts to the information density of this type of document |
Similarity threshold | 0.75-0.85 | Precise matching of part numbers and vehicle keywords is required to avoid recalling irrelevant part content |
Routing Trigger Rules | Trigger multimodal models when input includes image/file tags; trigger tool calls for pure text input | Auto parts marketing content includes product real-shot images and parameter text; processing must be split by input type |
The parameter values provided on this page are common recommended 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 settings.
Three Common Mistakes
- The symptom is that the number of results returned by the workflow after calling the knowledge base is far lower than expected. The cause is that the
知识库召回上限parameter in the workflow was not modified, and the default 3000-character limit was retained, which is not synchronized with the configuration parameters on the application side. - The symptom is that multimodal inputs are not assigned to the corresponding model, and pure text inputs trigger the multimodal processing flow instead. The cause is that the
Routing Trigger Ruleswere not configured correctly, and model call paths were not distinguished based on input content type. - The symptom is that pure text questions entered by users trigger the document parsing process, leading to increased response latency. The cause is that the automatic parsing switch was not turned off at the workflow start node, and pure text input was mistakenly identified as a file to be parsed.
How to Confirm Configuration is Correct
- Trigger a test input, check the number of knowledge base recalled entries in the workflow log to confirm it matches the configured
Knowledge base recall countvalue. - Upload a product image and enter pure text parameters separately, check the branch direction of the workflow to confirm the corresponding model call path is triggered.
- View the workflow running log to confirm no timeout errors corresponding to
PARSE_FILE_TIMEOUT_SECONDSoccur. - Test input texts of different lengths to confirm that the
Chunk sizeconfiguration does not cause content truncation or loss of key information.
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.