What Data for This Category Looks Like
Data sources for vehicle industry research include public announcements from vehicle manufacturers, MIIT vehicle declaration information, industry patent databases, professional automotive research reports, and public materials from supply chain enterprises. Update rhythms vary by source: MIIT announcements are updated in batches on a regular basis, patent information is released in real time, and research reports are published irregularly alongside industry developments. Document structures fall into three categories: long-form technical white papers, structured vehicle parameter tables, and unstructured analysis reports. Fields include vehicle model, production batch, cruising range, maximum power, wheelbase, and more, with corresponding units such as km, kW, mm, etc. Single document lengths vary widely; some technical white papers can span dozens of pages.
Constraints on Conversation Logging and Audit
The data characteristics of vehicle industry research impose multiple constraints on the conversation logging and audit process. First, data from multiple sources with inconsistent update frequencies requires logs to record the source and update time of each data entry associated with a conversation. This ensures data version traceability during audits. Second, the mixed structured and unstructured document structure requires logs to accurately link specific document fragments, rather than only storing overall document identifiers. This facilitates locating referenced original content. Third, parameter fields with clear units require logs to retain full original unit information. This prevents parameter unit confusion during audits. Fourth, the presence of long-form documents requires log storage to support segment-based association recording. This improves audit positioning efficiency.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
LOG_RETENTION_DAYS | 90 days | Compliance audit requirements for vehicle industry research scenarios mandate retaining complete conversation records for at least 90 days, to meet industry traceability needs |
maxContext | Previous 10 conversation turns | Vehicle industry research conversations often involve multi-turn parameter verification and reference resolution. Retaining 10 turns covers complete context association logic |
PARSE_SEGMENT_LENGTH | 800–1200 characters | Vehicle technical documents often contain long paragraphs of parameter descriptions. This segment length retains complete parameter association information, facilitating log association with specific document fragments |
Recall Count | Top 8 results | Knowledge base recall for vehicle industry research needs to cover multi-dimensional parameters. 8 recall results balance recall coverage and log storage overhead |
AUDIT_FIELD_INCLUDE_UNIT | Enabled | Vehicle industry research data contains a large number of parameterized fields with units. Enabling this configuration retains original unit information in logs, avoiding unit confusion during audits |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Vehicle technical white papers are typically lengthy. A 300-second timeout ensures long document parsing completes, avoiding incomplete log recording |
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 case-by-case analysis. It is recommended to test against your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: User original query content does not appear in conversation logs generated via API calls. Cause: The
API_LOG_RECORD_QUERYconfiguration is not enabled. API calls do not record user input query text by default. - Symptom: Reference errors occur after multiple conversation turns. For example, a subsequent user query "its range" fails to correctly associate with the previously mentioned vehicle model. Cause: The
maxContextconfiguration value is too low, failing to retain enough conversation turn context records, causing reference resolution logic to fail. - Symptom: Only partial parameter content displays in conversation logs after parsing lengthy vehicle technical white papers. Cause: The
PARSE_SEGMENT_LENGTHconfiguration value is too small, truncating complete parameter description paragraphs, preventing logs from fully associating with original data.
How to Verify Correct Configuration
- Access the system's log management settings page, check the
LOG_RETENTION_DAYSconfiguration value, confirm the storage period meets preset requirements. - Initiate a vehicle parameter query involving multiple turns of reference, check whether complete context records are retained in the conversation logs, verify that the
maxContextconfiguration is active. - Upload a vehicle technical white paper, initiate a query associated with specific parameters, check whether the logs display correct document segments and parameter unit information, verify that the
PARSE_SEGMENT_LENGTHandAUDIT_FIELD_INCLUDE_UNITconfigurations are active. - Call the official API interface to initiate a query, check whether the returned log fields include the user's original query, associated document title, and core parameters, verify that API logging configurations are correct.
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.