What the data for this category looks like
Financial report data for beauty and personal care brand agencies is sourced primarily from partner brand e-commerce backends, advertising management backends, and monthly settlement ledgers for agency services. Update cycles follow two schedules: regular monthly updates, and weekly updates during major promotional events. Each document is a structured table, aggregated by partner store and advertising channel. Fields include store name, channel type, revenue amount, service hours, advertising spend, and others. Monetary units are Renminbi yuan. Behavioral metrics such as impressions and clicks use units of times.
What constraints these characteristics impose on deployment and upgrade
Financial reports for beauty and personal care brands include data from multiple vertical advertising channels. Multi-source, multi-channel financial report data requires support for configuring multiple data source connections during deployment, and adaptation to export formats from different platforms. Alternating monthly and weekly update cycles require flexible adjustment of scheduled task trigger frequencies during upgrades. This meets high-frequency data synchronization needs during major beauty promotional events. Structured documents with multiple fields require custom parsing rules to match format differences across individual beauty and personal care brands. Data scale grows with the number of partner stores. This requires adjustment of vector database storage and retrieval parameters during upgrades to maintain query efficiency.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Covers the file size requirements for aggregated monthly financial reports across multiple brands and stores |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to parsing time for combined multi-channel reports |
RECALL_SCORE_THRESHOLD | 0.75 | Filters low-relevance fragments in financial report data to ensure analysis accuracy |
PARSE_CHUNK_SIZE | 1500 characters | Balances completeness of financial report fields and retrieval efficiency |
WORKFLOW_TIMEOUT | 1200 seconds | Covers multi-round data aggregation and calculation time required for financial report generation |
VOLUME_MOUNT_PATH | /app/fastgpt/data/brand_reports | Enables mapping between local financial report directories and container internal paths, supporting automatic synchronized uploads |
The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three common errors
- A 500 Internal Server Error is returned after executing JS code in a workflow code run node. The cause is that required dependency packages are not declared in the node configuration, resulting in missing dependencies in the runtime environment.
- A 404 Not Found error is returned during model calls. The cause is incorrect configuration of the
MODEL_CHANNELparameter, failure to bind the model channel from the corresponding vendor, or a configuration path that does not match the actual deployment. - Financial report files in the local mounted directory are not automatically synchronized to the knowledge base. The cause is incorrect configuration of the
VOLUME_MOUNT_PATHparameter, failure to map the local directory to the specified path inside the container, preventing the container from accessing local files.
How to confirm the configuration is complete
- Upload a monthly financial report test file for a single store, confirm the parsed generated text includes all preset fields, with no missing or misaligned content.
- Configure a scheduled synchronization task, confirm newly added financial report files in the mounted directory are automatically imported into the knowledge base.
- Initiate a model call test, check that the returned analysis results are consistently associated with the fields in the financial report data.
- Run the code node in the workflow, confirm the execution log has no errors and the output meets expected standards.
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.