What the Data for This Category Looks Like
Data related to yield rates in water treatment scenarios comes primarily from on-site water quality monitoring terminals, PLC control systems, and ERP production management modules. Data update frequency aligns with industrial collection cycles, typically once every 5 to 30 minutes. Multiple batches of structured records are generated each day.
Each individual record uses a fixed-field table format, containing device unique identifiers, collection timestamps, core water quality indicator values, supporting operating parameters, and calculated processing load and cost items. Field units must comply with industrial general standards: water quality indicators use mg/L, energy consumption uses kilowatt-hours, and chemical dosing amounts use kilograms.
What Constraints These Characteristics Impose on Deployment and Upgrade
The requirement for high-frequency real-time data writing requires adjusting API concurrency and batch thresholds during deployment, to avoid data packet loss or interface overload. The fixed structured field feature requires retaining original field mapping rules during upgrades, to prevent failure of yield rate calculation logic.
Some on-site facilities have scenarios where offline monitoring data is temporarily stored. During upgrades, a data breakpoint resume mechanism must be configured to prevent loss of offline data generated during the update window. Additionally, yield rate calculation in water treatment scenarios relies on multi-parameter linked calculations. After an upgrade, verify that the calculation logic for each parameter has not been altered, to avoid calculation errors.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_BATCH_SIZE | 20-50 records/batch | Matches the single-batch scale of high-frequency water treatment data, avoids overload during single upload |
PARSE_STRUCTURED_TIMEOUT | 600 seconds | Structured data requires matching multi-field linked logic, parsing time is longer than general unstructured documents |
RECALL_TOP_K | Top 8-12 records | Water treatment data has fixed fields, a small number of highly relevant records is sufficient to support yield rate calculation |
RERANKER_ENABLE | Enabled | Correlation sorting of multi-source operating parameters is required to improve calculation accuracy |
VERSION_CHECK_AUTO | Disabled | Most water treatment scenarios use private deployments, manual verification of upgrade package compatibility is required before triggering updates |
MAX_CONTEXT_LENGTH | 1000-1500 characters | The total field length of a single water treatment data record is fixed, no overly long context is needed |
The parameter values provided on this page are common recommended 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
- Issue: After upgrading to a specified version, the system does not display the corresponding version update log, making it impossible to confirm upgrade content. Cause: The version description file was not synchronized to the static resource directory during deployment, preventing the frontend from loading the update log.
- Issue: For Docker-deployed reranking components, the API call returns a 200 status code, but the result field is false with no valid sorting results. Cause: The input format of the reranking model does not match the structured field requirements of water treatment data, preventing the model from generating valid output.
- Issue: After upgrading to version 4.8.12, the plugin editing interface always displays the 'Unsaved' prompt at the top, regardless of whether changes are saved. Cause: The frontend cached state verification logic was not updated after the upgrade, causing a mismatch between the local state and the actual saved state.
How to Confirm Proper Configuration
- Submit a single water treatment data record, check that the parsed result fields fully match the original collected data, confirming that the structured parsing configuration takes effect as required for the scenario.
- Submit multiple batches of high-frequency data consecutively, check that the interface has no packet loss or timeouts, confirming that the concurrency and batch settings for data writing meet current scenario requirements.
- Enter the retrieval configuration interface, adjust the custom retrieval quantity parameter, verify that the number of retrieval results matches the expected setting, confirming that the global retrieval configuration overrides temporary API parameters.
- Manually trigger the version upgrade process, check that the system pops up the preset upgrade verification prompt, confirming that the automatic version check configuration is adjusted according to private deployment requirements.
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.