What the Data for This Category Looks Like
Auto parts research report data primarily comes from industry association public reports, securities firm sector-specific research reports, original equipment manufacturer (OEM) supporting technical documents, and third-party supply chain consulting reports. There are three update frequency categories:
- OEM supporting announcements are updated monthly
- Securities firm event-driven research reports are updated immediately alongside vehicle launches and supply chain changes
- Annual industry consulting reports are updated every six months
Document structures include vehicle adaptation lists, BOM level fields, material performance parameters such as tensile strength in MPa, and cost breakdown items. Fields include component model, compatible vehicle manufacturers, and units such as kg, yuan per piece, ten thousand pieces per year. Some documents contain multi-page tables and technical parameter appendices.
Constraints on Knowledge Base Retrieval and Recall
The dispersed, multi-source nature of auto parts research report data requires retrieval systems to support cross-data source field association recall. This prevents missing information from single data sources. Content with varying update frequencies needs incremental synchronization rules. These rules distinguish update cycles for high-frequency event-based data and low-frequency annual reports. Nested multi-page tables and precise parameter fields in documents require retrieval to prioritize matching structured fields like component model and compatible vehicle manufacturers. Do not rely solely on full-text semantic matching. Supply chain-related content structures require recall logic to associate related research report fragments from upstream and downstream. This improves information completeness.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
PARSE_TABLE_MAX_ROWS | 500 rows | Auto parts research report BOM lists and adaptation tables usually do not exceed 500 rows. This avoids parsing timeouts and redundant content |
chunk_size | 800–1200 characters | Core semantic units such as component models and adaptation parameters fall within this range. Splitting text here preserves field association integrity |
recall_top_k | Top 8–12 results | Relevant content for auto parts research reports is concentrated in the first 10 results. Too many recalled results introduce irrelevant general automotive content |
rerank_threshold | 0.72–0.78 | Precise matching of component models and parameters requires a high similarity threshold. This filters low-relevance general automotive research report content |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single research reports may include multi-page technical attachments. This size covers most uncompressed research report packages |
SYNC_INCREMENTAL_INTERVAL | Every 6 hours | This differentiates update cycles for high-frequency OEM supporting announcements and low-frequency industry reports. It balances timeliness and resource usage |
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
- Phenomenon: Empty results or irrelevant general automotive content are returned when searching for a specific component model. Cause: Structured field recall rules are not configured. Only full-text semantic matching is used. This cannot precisely match component model fields.
- Phenomenon: The knowledge base training task shows the
PARSE_FAILEDstatus code. Logs prompt "table parsing row limit exceeded". Cause: ThePARSE_TABLE_MAX_ROWSparameter is not adjusted. Long tables in research reports exceed the default parsing limit. - Phenomenon: Unformatted nested array text appears in retrieval results. Core parameters cannot be read directly. Cause: The document structured parsing switch is not enabled. Table content is not converted into retrievable structured fields. This leaves original nested formatting intact.
How to Verify Correct Configuration
- Upload a single auto parts research report that includes a long table. Check the parsing task status. Confirm there are no
PARSE_FAILEDerrors. Verify that parsed text retains table fields. - Enter a known component model. Confirm that retrieval results prioritize research report fragments containing this model. Check that the number of recalled results matches the preset range.
- Review incremental sync logs. Confirm that sync intervals for high-frequency supporting announcements meet configuration requirements. Confirm that low-frequency report syncs have no abnormalities.
- Test similarity threshold adjustments. Confirm that when precise parameters are entered, recall result relevance meets expectations. No low-relevance content is included.
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.