What Data for This Category Looks Like
Data for this category originates from online monitoring platforms, automatic pollution source monitoring data, ecological environment law enforcement systems, and third-party test reports. Update frequency is daily. Commonly processed documents include on-site inspection records, sampling records, monitoring reports, order for correction decisions, and administrative penalty decisions. Most document fields contain monitoring point codes, pollutant concentration values, law enforcement officer identification numbers, rectification time limits, and other information. Some documents require cross-verification by linking on-site operating condition data and automatic monitoring values.
Constraints Imposed on Workflow Orchestration
The daily data update requirement mandates that workflows support scheduled triggering or real-time data synchronization, to prevent use of expired monitoring and law enforcement data. The multi-source data cross-verification requirement mandates that workflows connect nodes from different sources to complete comparison between automatic monitoring data and on-site sampling data. Field differences across various documents mandate that workflows configure variable mapping rules to unify fields from different sources into the standard format required for law enforcement document generation. The timeliness requirement for on-site law enforcement and monitoring mandates that workflows set clear node execution timeout limits, to prevent process blocking that delays law enforcement progress.
Configuration Settings
The following configuration items apply to FastGPT v4.17.0:
| Configuration Item | Recommended Configuration | Rationale |
|---|---|---|
variables | Preset law enforcement data field mapping template | Match field differences across documents such as on-site inspection records and monitoring reports, unify standardized inputs |
nodeId | Bind corresponding nodeId using monitoring point codes | Distinguish source nodes of automatic monitoring data and on-site sampling data, ensure accurate data association |
| Node validation rules | Validate required fields including pollutant concentration values and law enforcement officer IDs | Avoid missing key law enforcement evidence fields, ensure compliance of generated documents |
| Timeout settings | 600 seconds | Adapt to the conventional execution duration of multi-source data comparison and document generation, prevent long-term process blocking |
| Single data pull limit | First 20 entries | Adapt to the daily updated multi-source data volume, avoid node overload |
| Special character handling | Automatically escape symbols such as double quotes | Handle special characters in monitoring reports and law enforcement documents, avoid workflow node parsing failures |
Three Common Misconfigurations
- Validation fails during debugging, with a prompt to check if nodes are correctly filled and connections are normal. The cause is incorrect configuration of the
variablesmapping rule, resulting in empty node input fields or unassociated connections to corresponding data source nodes. - Special character handling fails in the workflow, leading to parsing errors. The cause is failure to enable the special character automatic escape configuration, causing symbols such as double quotes to break the JSON parsing logic of workflow nodes.
- Content extraction nodes cannot call self-built model interfaces. The cause is incorrect configuration of tool call parameters, and failure to enable function call adaptation rules for the corresponding nodes, resulting in failure to trigger the self-built model interface.
How to Confirm Configurations Are Correct
- Manually trigger the workflow, verify that the input and output fields of each node match the preset
variablesmapping template. - Import test documents containing special characters such as double quotes, confirm that the workflow has no parsing errors and produces normal outputs.
- View node logs, confirm that the data source node bound by
nodeIdis correctly associated with the corresponding data source. - Simulate the multi-source data comparison process, confirm that the process completes execution within the set timeout threshold.
The values provided are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.