What the data for this category looks like
Black home appliance research report data comes from public industry association statistics, quarterly financial reports of brand manufacturers, and public reports from third-party market research institutions. Updates follow a regular quarterly schedule. Temporary reports are added when new products launch, raw material prices shift, or new industry policies are issued. Documents include core data tables, channel analysis, competitor comparisons, and policy interpretation sections. Fields include shipment volume (unit: ten thousand units), terminal average price (unit: yuan per unit), product model, energy efficiency rating, issuing organization, and release date.
What constraints do these characteristics impose on knowledge base retrieval and recall
The multi-source and structured nature of black home appliance research reports creates multiple constraints for knowledge base retrieval and recall. Documents use varied formats: PDF financial reports, survey spreadsheets, and industry announcements. The system must support multi-format parsing and structured table content extraction to avoid breaking core data connections during splitting. Regular quarterly updates and ad-hoc temporary changes require an incremental sync setup. This ensures the latest raw material prices and new product data are added to the knowledge base promptly. Fields and units have specific requirements: shipment volume uses ten thousand units, energy efficiency rating uses graded labels. The embedding phase must standardize field semantics and units. This prevents semantic confusion or mismatched numerical values during retrieval.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_TABLE_ENABLE | Enabled | Black home appliance research reports contain a large number of core data tables. Enabling this option extracts structured table content and avoids damaging data relevance during text splitting |
CHUNK_SIZE | 800–1200 characters | The core data paragraphs and table description text of black home appliance research reports mostly fall within this range. Reasonable splitting ensures semantic integrity during retrieval |
RECALL_TOP_N | Top 8–12 results | Relevant results for black home appliance research reports usually fall within this range. Too many results increase subsequent processing burden, while too few may miss core content |
SIMILARITY_THRESHOLD | 0.75–0.85 | Black home appliance research reports have a high density of professional terminology. This threshold filters low-correlation results while retaining accurately matched professional content |
INCREMENTAL_SYNC_INTERVAL | 1 day | Black home appliance research reports are mainly updated regularly on a quarterly basis, with temporary updates requiring timely synchronization. Daily incremental synchronization balances timeliness and resource consumption |
EMBEDDING_MODEL | General text embedding models with 768 dimensions or higher | Black home appliance research reports contain professional financial terminology and multi-format text. High-dimensional embeddings better capture semantic associations and ensure recall accuracy |
The parameter values provided on this page are common starting points for configuration setup. Actual values will vary based on material format, data volume, and business rules. Analyze specific issues on a case-by-case basis, and test with your own samples before finalizing settings.
Three common configuration errors
- Phenomenon: After running batch re-embedding operations, the recall rate in multilingual scenarios remains below required standards. Cause: No multilingual-compatible embedding model was selected, and the full set of already stored documents was not re-embedded.
- Phenomenon: After creating a Feishu knowledge base, no available file list appears when adding files. Cause: The target folder access permissions for the Feishu application were not correctly configured, or application permissions were not synchronized.
- Phenomenon: When calling the interface to create a text collection, the returned chunk results do not follow the paragraph-first splitting logic. Cause: The chunking mode was not correctly specified in the request parameters, or the provided parameters do not match the interface requirements for version 4.9.10 and above.
How to verify proper configuration
- Upload one typical black home appliance research report. Check that core data tables are fully extracted in the parsing results, and that table content is not randomly split.
- Send a retrieval request that includes professional terminology. Verify the number of returned results and their similarity matching levels to confirm they align with preset recall rules.
- Run an incremental synchronization task. Confirm that newly added research report data is synced to the knowledge base promptly, with no omissions or duplicates.
- Compare retrieval results before and after adjusting chunking parameters. Confirm that the chunk length fits the research report's text structure, with no semantic breaks.
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.