What the Data for This Category Looks Like
Financial report data for the cosmetics category comes from publicly disclosed periodic reports from brands, industry retail monitoring datasets, and offline store operation ledgers. Update cadence primarily follows quarterly periodic updates and annual comprehensive updates, with temporary promotion data synced alongside corresponding campaign cycles. Each document typically includes core operating data summaries, sales details by channel, cost breakdowns, and member operation modules. Fields covered include brand name, report period, total revenue, channel sales proportion, SKU sales quantity, and cost breakdown amounts. Units: total revenue and cost breakdown amounts use Chinese Yuan, while SKU sales quantity uses pieces.
Constraints on Deployment and Upgrade From These Data Characteristics
Multi-source heterogeneous data, wide variation in document length, and layered update cycles for cosmetics category financial reports impose multiple constraints on deployment and upgrade workflows. Multi-source data requires compatibility with formats including PDF periodic reports, Excel sales details, and CSV operation ledgers, so parsing modules must support batch format adaptation. Both full quarterly and annual data and temporary incremental data coexist, so incremental synchronization mechanisms must be configured to avoid repeated loading of redundant content. Single annual report documents have significant length, so parsing and splitting thresholds must be adjusted to avoid memory overflow. Differences in numerical types across multiple fields require preset field mapping rules to ensure accurate data extraction.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long length of single cosmetics financial report documents requires sufficient parsing time to avoid mid-run interruptions |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Meets total upload volume requirements for single annual report PDF and supporting sales detail Excel files |
maxContext | 8000–12000 characters | Retains sufficient context for split document segments, linking cross-module data such as revenue and costs |
RECALL_CHUNK_NUM | Top 8 entries | Covers multi-field recall requirements for financial reports, avoiding omission of core metrics |
SYNC_INCREMENTAL | Enabled | Adapts to scenarios of quarterly incremental data synchronization, reducing resource consumption from full parsing |
SIMILARITY_THRESHOLD | 0.72 | Filters low-relevance document segments, ensuring extracted financial report fields accurately match query requirements |
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. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- System lag occurs when loading financial report documents after deployment, with sustained high memory usage. This happens when the
UPLOAD_FILE_MAX_SIZEandmaxContextparameters are not adjusted, leading to loading of large files and long context segments that exceed hardware adaptation ranges. - Database backup fails during container environment migration, and existing knowledge base configuration cannot be restored. This occurs when complete backup files of the FastGPT built-in database are not properly exported, and vector index configurations associated with the knowledge base are omitted.
- Conversation request response delay exceeds 30 seconds, with some requests returning 504 timeout errors. This happens when
PARSE_FILE_TIMEOUT_SECONDSis set too short, or GPU-accelerated parsing is not configured, leading to excessively long parsing times for long documents.
How to Verify Successful Configuration
- Upload a single annual financial report document, verify that the parsing progress bar completes normally with no error prompts.
- Run an incremental synchronization test, confirm that only newly added temporary data is loaded, and existing data is not duplicated in the database.
- Submit a test request with multi-field queries, check that the returned result field coverage matches the preset configuration.
- View the system monitoring panel, confirm that memory and CPU usage remain in stable ranges with no sustained abnormal peaks.
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.