Deployment and Upgrade for Water Utility Yield Reporting

Data for water utility yield daily reports comes primarily from operation statistics of local public utility regulatory platforms, daily operation

What this category’s data looks like

Data for water utility yield daily reports comes primarily from operation statistics of local public utility regulatory platforms, daily operation ledgers of water supply and sewage treatment enterprises, and financial accounting records of water projects. Reports are generated daily for the full previous calendar day. Documents use a two-level classification structure by administrative region and water plant/project site. Each document includes fields such as project identifier, water treatment volume, total revenue, unit operation cost, yield, year-over-year change value, and more. Units include tons, ten thousand yuan, yuan per cubic meter, and others.

Constraints on deployment and upgrade

The multi-source, region-classified, daily update characteristics of water utility yield daily report data impose clear constraints on deployment and upgrade workflows. Multi-source data integration requires configuration of multiple interface permission adaptations and format conversion logic to prevent data pull failures. The daily update cadence requires setting T+1 triggered scheduled tasks during deployment. During upgrade, synchronously verify that task trigger rules match data source update cycles. The region-based document structure requires dividing vector database shards by administrative region during deployment. During upgrade, synchronously adjust sharding strategies to avoid retrieval scope deviations. Multiple business indicator fields require configuration of unified field mapping rules. During upgrade, synchronously update mapping logic to adapt to new business fields.

How to set configurations

Configuration ItemRecommended SettingRationale
SCHEDULER_CRON0 0 2 * * ?Water utility daily reports typically generate previous day’s data in the early morning. This cron expression triggers tasks during business low peaks
DATA_SOURCE_TIMEOUT600 secondsMulti-source data pull may involve cross-system interface calls. This duration covers most normal pull scenarios
VECTOR_DB_SHARD_MODEShard by administrative regionDocuments are stored classified by region. Sharding reduces retrieval scope and improves retrieval efficiency
PARSE_FIELD_MAPPINGMap original field names to broadcast template fieldsUnifies field formats and prevents field mismatch issues during broadcast generation
UPLOAD_FILE_MAX_SIZE1000 MBA single water utility daily report document includes multi-region data. This size accommodates document volumes for most scenarios
WORKFLOW_NODE_TIMEOUT300 secondsData processing and field mapping links may take extended time. This duration prevents accidental termination of node execution

The parameter values provided on this page are common starting points for determining configurations. 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.

Three common errors

  • Workflow node execution returns empty results, with no output in the interface. Logs show FunctionExecutionError: No output generated, even when using a minimal function node. This occurs because a reasonable value for the WORKFLOW_NODE_TIMEOUT parameter was not configured during deployment, or there is a compatibility issue with an excessively short default workflow node timeout in version v4.8.17, causing code execution to terminate before completion.
  • Container startup fails with a database connection failure prompt. Logs show Invalid credentials for database, and the service cannot initialize normally. This occurs because DB_PASSWORD and SERVICE_SECRET parameters were not configured via environment variables during Docker deployment, or the container was not restarted after modifying configurations to apply new settings.
  • After configuring an Nginx proxy, knowledge base original document links return a 404 status code, and downloads or redirects fail. This occurs because incorrect reverse proxy rules were configured in Nginx to forward file service requests, or the correct proxy domain name was not configured in the FILE_SERVER_BASE_URL parameter.

How to confirm configurations are correct

  • Execute a manually triggered workflow, view node execution logs, and confirm no errors occur in data pull, field mapping, and broadcast generation links.
  • View scheduled task execution records, and confirm tasks triggered at the specified daily time have completed data synchronization and knowledge base updates.
  • Access the configured file service domain, and verify that Nginx proxy rules correctly forward requests to the FastGPT file service port.
  • Modify one configuration parameter and restart the service, confirm the updated parameter value is displayed in the system settings interface, and that workflow operation logic matches expectations.

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.