What Data Looks Like for This Category
Publicly traded baijiu industry financial report data comes from regular disclosures posted on the Shanghai and Shenzhen Stock Exchanges, plus production and sales monitoring data released by industry associations. Updates follow annual reports, semi-annual reports, and quarterly reports. Leading enterprises additionally release monthly operating data. Document structures include modules for core operating metrics, channel sales data, base liquor inventory details, and more. Fields cover revenue, gross margin, inventory volume, sales expense ratio, and similar metrics. Units are typically ten thousand RMB, kiloliters, or tons. Some enterprise reports include charts and explanatory notes. Text lengths vary widely, from brief quarterly reports to detailed annual reports spanning dozens of pages.
Constraints Imposed on Vector Models and Indexing
The unique traits of this data create constraints for the vector model and indexing workflow. Baijiu financial reports contain many industry-specific terms. This requires vector models to have semantic understanding capabilities tailored to the baijiu industry, otherwise term matching errors will occur. The wide range of document lengths, from brief quarterly reports to detailed annual reports, requires indexing to support flexible text chunking strategies. This avoids semantic fragmentation or redundant chunks. High-frequency quarterly and monthly updates require indexes to support incremental updates. This eliminates the need for full reindexing and reduces computing resource usage. Fine-grained base liquor inventory and channel data require higher precision for retrieved context matches. This ensures the accuracy of analysis conclusions.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
embedding_model | Industry-fine-tuned Embedding-3 or equivalent model | Baijiu financial reports include many industry-specific terms. Fine-tuned models improve the accuracy of term semantic recall |
chunk_size | 800–1200 characters | Baijiu financial report text lengths vary widely across pages. This range balances semantic completeness and indexing chunk density |
index_type | HNSW index | Supports high-frequency incremental updates and high recall rates, matching the periodic update schedule of financial report data |
recall_top_k | Top 10–15 results | Financial report analysis requires coverage of multi-dimensional metrics. More recall results ensure comprehensive information |
vector_db_batch_size | 50–100 items per batch | Adapts to incremental update scenarios for batch uploads of financial reports. Prevents overload from single requests |
similarity_threshold | 0.75–0.85 | Filters low-correlation matches for non-industry terms, improving retrieval precision |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Each use case requires individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: After calling the
create_train_orderAPI, the knowledge base does not generate the corresponding index, and the interface shows "Task Pending" timeout. Cause: The calling logic for full training and incremental updates is not differentiated. Incremental data for baijiu financial reports is only uploaded via collection data addition, without triggering the vectorization and index synchronization process. - Symptom: After uploading financial report notes with charts, retrieval cannot return the text parsing content of the corresponding charts. Cause: Multimodal vectorization configuration is not enabled. Only plain text content is vectorized, and OCR metadata associated with images is not linked.
- Symptom: The
embeddingAPI returns a400 Bad Requesterror with the prompt "Model not supported". Cause: The corresponding model's API key and interface address are not added in the platform configuration page, or the vector model address is not synchronized to the service configuration file during local deployment.
How to Verify Proper Configuration
- Upload a single baijiu financial report sample, call the
embeddingAPI, and confirm that the returned vector dimension matches the preset dimension of the selected model. - Submit an incremental update task, check the update progress in the index management interface, and confirm that incremental data has been vectorized and mounted to the vector database.
- Retrieve industry-specific terms such as "base liquor inventory" and "sales turnover rate", check the relevance ranking of returned results, and adjust
similarity_thresholdto a range that matches business requirements. - Upload a financial report screenshot with a chart, verify that retrieval can return the corresponding OCR-parsed text fragment, and confirm that the multimodal configuration is active.
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.