What the data for this category looks like
Vehicle marketing content data primarily comes from official automaker material libraries, dealer training systems, regional marketing policy documents, and brand promotional assets. Update cycles align with new vehicle launches, quarterly promotional campaigns, and regional policy adjustments. There is no fixed schedule, but high-frequency update periods cluster at quarter-end and during new vehicle launch windows. Documents fall into three structural categories: structured parameter tables, unstructured promotional copy, and campaign plans. Fields include vehicle model ID, configuration level, launch date, regional suggested retail price (unit: CNY), driving range (unit: km), torque (unit: N·m), and marketing tags tailored for different scenarios.
What constraints these characteristics impose on knowledge base retrieval and recall
The mixed document structure of structured parameters and unstructured copy requires the retrieval workflow to support both precise field matching and semantic recall. This avoids broken associations caused by splitting parameter data. Dynamically updated marketing materials require the knowledge base sync process to support incremental pulls. This prevents delays and server load pressure from full updates. The presence of regional policy fields requires retrieval to support filtering recall results by geographic region. This prevents cross-regional users from accessing inapplicable promotional information, and aligns with regional marketing compliance requirements. The characteristics of long documents and multi-field combinations require segment processing to preserve the integrity of parameter blocks. This avoids splitting individual configurations into multiple unrelated fragments.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall count | top 8-12 results | Vehicle marketing content includes structured parameters and unstructured copy. Too many results will exceed the model context window, while too few will overlook differences in detailed configurations |
similarity threshold | 0.72-0.85 | High precision is required for vehicle parameter fields. This range filters low-relevance generic promotional copy while retaining weakly matched regional policy results |
segment length | 800-1200 characters | Documents combine vehicle parameter tables and promotional copy. Excessively long segments split parameter associations, while excessively short segments break the integrity of individual promotional copy |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Vehicle promotional materials often include high-resolution image metadata and long documents, requiring sufficient time for parsing and metadata extraction |
incremental sync trigger interval | every 6 hours | Vehicle marketing content updates dynamically with promotions and regional policies. This interval balances sync delay and server load |
reranked return count | top 3-5 results | Core configurations and latest campaigns that best match user queries need to be prioritized, avoiding redundant information interfering with user decision-making |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Symptom: Unintended results are returned when calling the API in a production environment, but specified knowledge base content can be correctly recalled during local debugging and preview. Cause: The
knowledgeBaseIdfield is not passed in the production environment API parameters, or the global knowledge base is enabled by default instead of the bound vehicle marketing knowledge base. - Symptom: The document file name referenced in retrieval results does not match the actually matched content, and cross-vehicle model parameter confusion occurs. Cause: The metadata extraction function during document parsing is not enabled, so the system cannot associate recalled fragments with the originally uploaded files.
- Symptom: Some fragments are missing from batch-imported vehicle model parameter documents, and complete configuration information cannot be recalled. Cause: The segment length is set too short, splitting a single complete parameter configuration into multiple unrelated fragments, making it impossible to match complete queries during retrieval.
How to confirm configurations are set correctly
- Upload a latest vehicle promotional policy document, trigger knowledge base sync, and confirm that the sync log displays successful document parsing with no format errors.
- Submit a query for the regional suggested retail price of a specific vehicle model, verify that the recall results include the corresponding document fragment, and that the referenced file name matches the uploaded file.
- Pass the specified knowledge base identifier parameter when calling the API, check that the returned results only include document fragments from this knowledge base, with no content from other categories mixed in.
- Adjust the similarity threshold and submit multiple queries, observe changes in the relevance of recall results, and confirm that the values meet business requirements.
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.