Data characteristics of this category
Financial report data for the black home appliance category comes primarily from publicly disclosed periodic reports of listed companies and market monitoring documents released by industry associations. Update cycles center on quarterly and annual periods, with temporary performance announcements as supplementary content. Documents are mostly in PDF or web formats, and include core fields such as segmented business revenue, product shipment volume, average selling price, channel proportion, R&D investment, and supply chain costs. Units include CNY, ten thousand units, CNY per unit, and similar metrics. Some reports from overseas manufacturers also include revenue data denominated in foreign currencies.
Constraints for deployment and upgrade
The long documents and multiple fields of black home appliance financial reports require deployment phase adaptation for large-volume file parsing and multi-entity extraction rules. Fixed quarterly and annual update cycles require configuring scheduled crawling and knowledge base synchronization mechanisms to avoid data lag. Large format differences across manufacturer reports, plus embedded charts and complex tables in some reports, require updating parsing plugins during the upgrade phase to adapt to new announcement formats. Sufficient computing resources must also be reserved to handle batch parsing tasks. Additionally, the presence of multiple unit fields requires configuring unified unit conversion rules during deployment to ensure consistency of analysis results.
Configuration settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600-900 seconds | Black home appliance financial report PDFs typically include multiple pages of business data and charts, with longer parsing times than general-purpose documents |
UPLOAD_FILE_MAX_SIZE | 200-500 MB | Annual financial reports may include multiple attachments and detailed data tables, with larger average sizes than general-purpose documents |
chunk_size | 1200-1500 characters | Financial report fields are highly specialized and content-heavy. Excessively long segments lose contextual connections, while excessively short segments break terminology integrity |
Recall count | Top 8-12 entries | Key financial report information is scattered across multiple sections, requiring sufficient retrieved coverage to ensure core data is not missed |
Similarity threshold | 0.75-0.85 | Financial reports include a large number of specialized terms, requiring a high matching threshold to filter out irrelevant general industry content |
SCHEDULE_CRAWL_INTERVAL | 7-30 days | Financial reports are updated quarterly, so high-frequency crawling is unnecessary to avoid unnecessary computing 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. Each scenario requires individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- In a local deployment environment, after uploading a financial report PDF, the file parsing node shows a waiting status with no response for more than 10 minutes. Background logs return
504 Gateway Timeout. The cause is failure to adjust thePARSE_FILE_TIMEOUT_SECONDSparameter; the default value is insufficient for long document parsing. - When building a custom deployment image, a
Connection reset by peererror occurs during dependency package installation. The cause is failure to configure a domestic mirror source to speed up dependency installation, leading to timeout when connecting to overseas sources. - The generated financial report analysis result has empty revenue data fields for the black home appliance business. The cause is failure to configure category-specific entity extraction rules, so segmented business revenue fields in the financial report are not identified.
How to confirm correct configuration
- Upload a test public financial report PDF from a black home appliance manufacturer. Wait for parsing to complete, then check if preset fields such as "black home appliance business revenue" and "shipment volume" are extracted in the knowledge base to confirm the parsing process is working normally.
- View the execution logs of scheduled crawling tasks to confirm tasks trigger at the set interval with no consecutive failure records.
- Trigger a single financial report analysis request, then check if the generated report includes accurate extracted results of core financial data.
- Check the deployment environment’s resource monitoring to confirm CPU and memory usage do not exceed pre-set thresholds, with no abnormal restart records.
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.