What this category’s data looks like
Data sources for water treatment intelligent due diligence reports include water utility online monitoring systems, third-party paper water quality test reports, pipe network operation logs, environmental impact assessment approval archives, and similar sources. Real-time monitoring data updates at minute-level intervals, stored in structured format with fields such as point number, monitoring time, and water quality indicators. Unstructured reports include treatment process parameters, operation cycle records, compliance status explanations, and other content. Core fields cover influent flow rate, COD concentration, ammonia nitrogen concentration, total phosphorus removal rate, and similar metrics. A complete due diligence report ranges from tens to hundreds of pages in length.
What constraints these characteristics impose on deployment and upgrade
Minute-level real-time monitoring data updates require configuring streaming data synchronization channels during deployment to avoid data backlogs. Multi-source heterogeneous data formats require adapting to both structured parsing and unstructured OCR parsing modes. Upgrades must ensure both parsing capabilities remain available. Differences in update rhythms across data sources require configuring incremental synchronization trigger rules to avoid excessive resource usage from full synchronization. Water treatment due diligence fields use clear industry units and standard naming conventions. Deployment requires presetting field mapping rules to prevent unit confusion or missing fields after parsing. Upgrade processes must support rolling updates to avoid interrupting access to online monitoring data.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Water treatment due diligence reports often include multiple cross-month monitoring logs, and the volume of a single packaged file is usually larger than that of general document scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Parsing long-cycle pipe network operation logs requires longer processing time to avoid interrupting the parsing process due to timeout |
maxContext | 12000 characters | Correlation analysis of water treatment indicators requires covering data from multiple points and multiple cycles. A sufficient context window improves correlation accuracy |
Recall count | Top 8 entries | Water treatment due diligence requires covering core monitoring points and key process parameters. The recall volume adapts to multi-index correlation query requirements |
Similarity threshold | 0.72–0.80 | Balances precision and recall rate, avoids incorrectly recalling monitoring data from non-corresponding points or missing valid indicators |
Segment length | 800–1000 characters | Adapts to the length of technical description paragraphs in water treatment reports, improves parsing accuracy for unstructured documents |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing values.
Three common misconfigurations
- Code execution components in workflows throw errors, even for simple code. The root cause is failure to correctly configure the local deployment environment variable
FASTGPT_WORKER_RUNTIME, resulting in missing runtime dependencies. - Parsed document fields are empty or use incorrect units. The root cause is failure to configure the
PARSE_FIELD_MAPPINGparameter, and failure to map non-standard fields from original monitoring data to standard fields for water treatment due diligence. - Local deployments cannot enable team edition features. The root cause is failure to set the
TEAM_ENABLEDparameter totrue, and failure to run the database initialization script for the team edition.
How to confirm correct configuration
- Upload a typical water treatment monitoring log document, confirm parsed fields include preset standard indicators and their corresponding units.
- Run a test workflow, execute the preset code component, confirm the run returns results without errors.
- View system operation logs, confirm no timeout errors related to
PARSE_FILE_TIMEOUTappear. - Access the team management interface, confirm team spaces can be created and member permissions can be assigned.
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.