What the data for this category looks like
Data sources for refinery yield daily reports include internal manufacturing execution systems (MES) of refinery enterprises, bulk commodity trading market APIs, and financial accounting ERP systems. Data is updated daily with full historical data for the previous calendar day. External release typically occurs after internal accounting is completed by 24:00 on the same day. Data documents primarily use structured tables, with a small amount of supplementary textual explanations. Core fields include operating parameters of each production unit, raw material procurement costs, ex-factory prices of each terminal product, and unit gross margin values. Units are mostly physical measurement and financial valuation units such as yuan/ton and ton/hour. No percentage-based statistical fields are included.
Constraints Imposed on Deployment and Upgrade
The multi-source data nature of refinery yield daily reports requires configuring parsing rules adapted to different data sources during deployment, to avoid cross-system field mapping errors. The daily update rhythm requires deploying scheduled trigger synchronization tasks, and matching the industry's data daily accounting window to ensure complete previous-day data is pulled. The large number of structured fields requires configuring field validation rules to filter abnormal null values and data with format errors. During the upgrade process, existing data source configurations and scheduled task rules must be retained, to avoid data synchronization interruptions or format incompatibility caused by version changes. New versions must also be pre-verified for compatibility with existing data formats.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DATA_SYNC_CRON | 0 1 0 * * * | Refinery industry daily production and financial data is typically finalized by 24:00 on the same day. Triggering synchronization 1 minute in advance ensures complete previous-day data is retrieved |
PARSE_STRUCTURED_DATA | Enabled | Refinery daily report data mostly uses standardized table formats. Enabling structured parsing automatically matches the correspondence between fields and broadcast content |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Refinery daily reports may include monthly historical data attachments for multiple units. Single file size usually exceeds the default limit for general scenarios |
SYNC_DATA_TIMEOUT | 1200 seconds | Multi-source data pulling, cleaning, and aggregation processes take a long time. This setting prevents synchronization tasks from timing out and interrupting mid-process |
SYNC_DATA_RETRY_TIMES | 3 times | Multi-source data sources may experience temporary fluctuations. Multiple retries ensure successful data synchronization |
AUTO_VERSION_UPDATE | Disabled | Broadcast logic in refinery scenarios is tightly bound to data formats. Automatic upgrades may introduce incompatible configuration changes |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom:
model not founderror is returned when calling the broadcast function. Cause: The API key and interface address for the target model are not configured in the deployment environment, or the installed FastGPT version does not support the target model. - Symptom: Scheduled synchronization tasks fail to trigger normally after upgrading the version, and the interface returns
500 Internal Server Error. Cause: The originalDATA_SYNC_CRONconfiguration item was not retained during the upgrade, or the configuration file format of the new version was changed without adaptation. - Symptom: No changes are visible after modifying local code and deploying, and the page displays old content. Cause: Modified local code was not synchronized to the corresponding directory on the deployment server, or the FastGPT service was not restarted to load the new code.
How to Confirm Proper Configuration
- Run a manual data synchronization task, check the synchronization logs, and confirm there are no abnormal records such as timeouts or missing fields.
- Enter the FastGPT model configuration interface, confirm that the API key and interface address for the target model have been correctly filled in.
- View the scheduled task execution records, confirm that the most recent synchronization task completed at the preset time.
- Modify local test code, synchronize it to the deployment directory, restart the service, and verify whether the page content is updated.
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.