What this type of data looks like
Data sources for water utility due diligence reports include monthly operation reports from water supply and drainage enterprises, pipe network GIS system files, real-time data from water quality monitoring stations, and water facility ledgers from local housing and urban-rural development departments.
Data update cadences vary. Real-time water quality and flow data updates every 15 minutes. Monthly operation reports update on a monthly basis. Facility ledgers update quarterly.
Supported document formats include structured CSV flow tables, PDF operation logs, and large GIS vector files. Included fields cover average daily water supply, COD concentration, pipe network pressure, and operation staff allocation. Corresponding units are cubic meters, mg/L, kilopascals, and number of people.
Constraints imposed by these characteristics on workflow orchestration
Multi-source heterogeneous data formats require the workflow to integrate multiple types of parsing nodes, to adapt to different parsing logic for CSV, PDF, and GIS files.
Varying update cadences require the workflow to support mixed scheduled trigger rules, to distinguish between real-time pull tasks and periodic batch processing tasks.
Inconsistent field units require the workflow to include built-in unit conversion nodes, to unify measurement standards across data sources.
Large GIS files and long-text logs require adjustments to parsing timeout and segmented processing configuration parameters, to avoid task interruptions.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Water utility data includes large GIS files and long-text operation logs, requiring longer parsing durations |
maxContext | 8000–12000 characters | Water utility due diligence reports require integration of multi-source associated fields, requiring sufficient context to cover all due diligence dimensions |
RECALL_TOP_K | Top 6–10 entries | Water utility data has many fields and close business associations, requiring sufficient recalled entries to cover all dimensions needed for due diligence |
SIMILARITY_THRESHOLD | 0.75–0.85 | Low-match, non-water utility data must be filtered to avoid deviations in due diligence results |
WORKFLOW_TRIGGER_INTERVAL | Differentiated by task type: real-time data every 15 minutes, monthly reports every 1 month | Adapt to varying update cadences of water utility data, avoid repeated pulls or delayed processing |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Accommodate large pipe network GIS system files and batch operation log packages |
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 targeted analysis. It is recommended to test on your own samples before finalizing values.
Three Common Mistakes
- Phenomenon: A
400 Bad Requesterror occurs during workflow execution, with a prompt indicating payload format error. Cause: TheappIdparameter is not passed according to specifications, or thestreamparameter is not used as a boolean value and is mistakenly passed as a string format. - Phenomenon: External links configured in the workflow are displayed as a "Click to Ask Immediately" button in responses, rather than directly jumpable links. Cause: The native link rendering switch is not enabled in the response component, and links are converted to session interaction buttons by default.
- Phenomenon: Water utility data fields are not extracted as preset instructions after workflow execution, and returned results do not match due diligence requirements. Cause: The workflow input instruction does not clearly specify the water utility-specific fields to be extracted, or the instruction format does not comply with the syntax rules of FastGPT workflows.
How to Confirm Proper Configuration
- Upload a single large water utility GIS file, check if the workflow parsing node completes the task within the set timeout period, with no timeout errors.
- Trigger a scheduled task to pull real-time water utility data, verify that the workflow trigger interval matches the data update frequency, with no duplicate or missed pull records.
- Launch multiple rounds of due diligence conversations, check if global variables retain data such as pipe network diameter and water quality indicators entered in the previous conversation.
- After configuring external links, test response content to confirm that links are displayed in native format and not converted to interaction buttons.
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.