What Data Looks Like for This Category
Data for water utility marketing scenarios primarily comes from payment ledgers in water utility operation systems, pipeline SCADA monitoring data, offline work orders, and user registration form data collected from marketing campaigns. Update rhythms vary significantly: payment ledgers are updated daily in batches, pipeline monitoring data is pushed minute-by-minute, and work orders and marketing registration forms are generated in real time. Most data is structured, primarily in CSV or JSON formats. Unstructured data includes work order text and water quality test PDF reports. Fields include water meter ID, user address, payment amount, monitoring point ID, chlorine residual concentration, registration phone number, and more. Units include yuan, cubic meters, mg/L, MPa, pH, and others.
Constraints on Forms and Interactions
Water utility marketing scenario forms must support customer acquisition and conversion, while adapting to the unique characteristics of water utility data. Marketing registration forms must collect dedicated fields such as water meter ID and residential address, and support custom field configuration. Batch-uploaded operation data and marketing form data must be mapped uniformly. Separate interactive entry points must be provided for single registration submissions and bulk user data imports. Water utility data includes multiple unit fields, so unit validation rules must be configured in forms to prevent errors where input values do not match their associated units. Additionally, registration data from marketing campaigns may surge during activity peaks, so form submission rate limiting and progress display must be supported.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Bulk imported registration user data from water utility marketing campaigns typically does not exceed 500 MB, to avoid excessive server load |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Bulk CSV or PDF parsing for water utility data requires processing many fields; 300 seconds covers standard parsing durations |
form_field_auto_match | Match by field name prefix | Fields exported from water utility systems often include fixed prefixes such as water_meter_ and payment_. Prefix matching reduces manual mapping workload |
max_context_length | 80000 characters | Water quality test reports have long text content; long context processing support is required to cover complete data |
UPLOAD_ALLOWED_EXTENSIONS | ["csv", "json", "pdf", "xlsx"] | Common export formats for water utility data are CSV, JSON, test report PDF, and payment ledger XLSX, to meet marketing data import needs |
form_submit_batch_limit | 10000 entries per batch | Bulk submitted registration data for water utility campaigns should not have too many entries, to avoid interface timeouts that impact campaign conversion |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Issue: When configuring an HTTP data source, the form prompts for incorrect request parameters, and logs show abnormal body parameter format. Cause: The body parameter name and value were not configured according to the interface parameter rules of the water utility system, and custom parameters for marketing campaigns were incorrectly written into the request body.
- Issue: After uploading a bulk registration CSV file for a marketing campaign, some users' water meter ID fields are empty. Cause: The
form_field_auto_matchrule was not configured, and the default matching logic cannot recognize prefixed fields exported from water utility systems, leading to mapping failures. - Issue: Uploaded JSON-format water quality test data is not included in the marketing content statistical analysis by the large model, and returned results are only based on conversation text. Cause: The
max_context_lengthconfiguration was not adjusted, and the default character limit cannot cover the full content of the JSON file, leading to data truncation before loading.
How to Verify Correct Configuration
- Upload a test CSV file for water utility marketing registrations, and verify that field mapping results match the preset marketing form fields.
- Submit a registration data file that exceeds normal campaign peak levels, and check whether upload rate limiting is triggered, or if submissions complete normally.
- Upload a water quality test report with long text, and confirm that the large model output includes analysis content from the report for marketing material generation.
- After configuring the data source, run a data pull test to confirm that fields match the operation ledger fields of the water utility system.
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.