Reference only; verify against the target FastGPT release and deployment documentation.
What This Type of Data Looks Like
Data sources for power generation group service consultation and reply include internal service ticket systems, hotline call records, official website consultation messages, and offline window ledgers. The update rhythm is real-time new ticket creation, daily updates of reply progress, and monthly archiving of historical data. The document structure includes fields such as ticket number, consultation subject, consultation category (such as unit operation and maintenance, grid connection procedures, electricity price policies), submission time, problem details, associated business node, reply time limit requirements, and processing status. The structure varies slightly based on the type of consultation matter.
Constraints These Characteristics Impose on Workflow Orchestration
Dispersed data sources require workflow configuration with multiple data source pull nodes to integrate consultation data from different channels. Fields include associated business numbers, requiring binding each field via variables in the workflow to enable cross-node data transfer. Real-time update requirements mean the workflow trigger mode must be set to event trigger, with no scheduled polling needed. Archiving cycle requirements need configuring a scheduled node to complete historical ticket archiving per calendar month to avoid data redundancy. Some consultations involve compliance requirements, so a compliance check node must be added to the workflow to ensure reply content complies with power generation group policy specifications.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Variable Binding | Map ticket fields to variables | Matches the multi-field data structure of power generation group service consultations |
| Node ID Configuration | Assign a unique nodeId to each workflow node | Connects the complete process of ticket entry, AI reply, manual review, and archiving |
| Trigger Mode | Event trigger | Adapts to the real-time submission update rhythm of service tickets |
| Single-Processing Limit | Top 10 pending tickets | Avoids data overload in single-batch processing |
| Timeout Threshold | 600 seconds | Matches the standard response time limit for power generation group business handling |
| Reordering Rule | Sort by consultation matter priority | Prioritizes urgent consultations related to unit operation and maintenance and grid connection |
Three Common Misconfigurations
- Phenomenon: The running result of a code node in the workflow cannot be passed to the AI model node, triggering the error
chat:ai_input_is_e. Cause: The result field is not correctly mapped to thevariablesparameter, resulting in missing AI input parameters. - Phenomenon: When using the database connection plugin to connect to PostgreSQL, workflow verification fails with a prompt about missing, null, or abnormal connections. Cause: Database connection parameters are not bound to
variables, or the connections between nodes do not match the configured variable order. - Phenomenon: No response occurs after configuring knowledge base variable reference, and the
[{datasetId: xxx}]format does not take effect. Cause: The datasetId is not configured in the workflow'svariablesparameter according to FastGPT's variable binding rules.
How to Confirm Proper Configuration
- Manually submit a test service consultation ticket, check if the workflow triggers automatically and moves to the next node.
- Verify that the
variablesparameter includes all necessary service ticket fields, with no missing or formatting errors. - Run the workflow test node to confirm that the code running result is successfully passed to the AI model, with no errors.
- Check the database connection plugin's running logs to confirm successful connection to PostgreSQL, with no verification failure prompts.
The values provided are common starting points and should be measured 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.