What Data Looks Like for This Category
Commercial vehicle marketing content data primarily comes from internal product parameter manuals of automakers partnered with financial institutions, dealer-side marketing script libraries, industry compliance evaluation reports, and official advertising approval documents. These materials support customer acquisition marketing for commercial vehicle owners and logistics enterprises. Update cycles vary based on new product launches, compliance policy adjustments, or promotional campaigns, with no fixed schedule.
Document structures fall into two categories: Structured parameter documents contain fields such as complete vehicle model, power parameters, load capacity specifications, with standard unit annotations. Scenario-based marketing materials include scripts for segmented customer groups such as logistics and construction, plus compliance copy templates. Fields and units must follow industry general standards strictly. Examples include curb weight measured in kilograms, cruising range in kilometers, and engine power in kilowatts.
Constraints These Characteristics Impose on Retrieval and Recall
The coexistence of structured parameters and scenario-based scripts in commercial vehicle marketing data requires retrieval and recall to match both semantic relevance and field associations. Fixed-length chunking alone disrupts the binding relationship between parameters and their corresponding descriptions, leading to recall results where parameters disconnect from their use scenarios. The approval status field in compliance copy requires retrieval logic to filter unapproved content, avoiding recall of non-compliant materials. Irregular update frequencies require retrieval systems to support incremental synchronization, reducing resource consumption from full parsing. Long product manuals create redundant fragments in vector recall, so field filtering and reranking mechanisms must combine to keep recalled content focused on core needs.
How to Set Configurations
| Configuration Item | Recommended Approach | Basis for This Approach |
|---|---|---|
Chunk size | 800–1200 characters | Commercial vehicle parameter documents include long parameter description paragraphs. This range preserves complete semantics for parameters and their associated scenario scripts, avoiding broken associations |
Recall count | Top 8-10 results | Commercial vehicle marketing content includes multi-dimensional parameters and scenario scripts. Too many results cause context redundancy, while too few miss key configuration information |
Similarity threshold | 0.75–0.85 | Commercial vehicle parameters have high semantic similarity. This threshold balances recall accuracy and coverage, avoiding missed matching content or irrelevant results |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Commercial vehicle product manuals are typically lengthy, with long parsing times. 300 seconds covers parsing needs for most long documents |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Commercial vehicle marketing materials often include high-definition images and detailed parameter tables. This value supports uploads of large-sized files |
Field Filter Rules | Filter by 审批状态 = "Approved" | Commercial vehicle advertising copy must meet industry compliance requirements. This rule filters non-compliant materials that failed approval |
Rerank result count | Top 3-5 results | Final output must focus on core parameters and scripts. Reranked results stay within a range users can browse quickly |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and testing against internal samples is recommended before finalizing settings.
Three Common Misconfigurations
- Symptom: Calling the
/api/v1/chat/completionsinterface withappIdspecified fails to recall uploaded content within the knowledge base. Cause: TheknowledgeBaseIdsparameter is missing from the request body, or the parameter value does not match the target knowledge base ID. - Symptom: Returned answers do not annotate the source document name for corresponding text blocks. Cause: The "retrieval document traceability" interface setting is not enabled, and document metadata is not carried in retrieval logic.
- Symptom: Retrieval results only return text fragments, and do not include supporting images from the source document. Cause: The "extract images within documents and associate them with retrieval results" option is not configured, and only text content is parsed.
How to Confirm Configurations Are Correctly Applied
- Upload a commercial vehicle product manual that includes parameter tables and embedded images, run a retrieval test, and verify returned results include image content.
- Initiate a retrieval request, review returned result metadata fields, and confirm traceability-related fields such as
sourceDocNameare present. - Call the specified interface, pass the correct knowledge base ID, and verify returned results include document content from that knowledge base.
- After configuring field filtering rules, upload a test document that failed approval, run a retrieval, and confirm the document is not recalled.
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.