What this category of data looks like
Water utility financing daily report data mainly comes from bid winning announcements of water utility projects on local public resource trading platforms, credit loan records of water utility enterprises in banking business systems, and bond issuance announcements of the water utility industry in public markets. The data updates daily, and complete data for the previous working day is generated on the current day. The structure of each individual data document is fixed, containing 7 core fields: project name, full name of the financing entity, financing amount, financing method, arrival date, water utility sub-category the project belongs to, and project location. The unit of financing amount is ten thousand yuan, and date fields use the YYYY-MM-DD format.
What constraints do these characteristics impose on workflow orchestration
The multi-source data feature of water utility financing daily reports requires configuring field standardization nodes in the workflow to align the formats of financing entities and amount fields from different sources. The daily update rhythm requires binding daily scheduled trigger rules to the workflow, and setting incremental pull logic to avoid reprocessing historical data. The fixed 7 core fields require that the output of workflow nodes must fully include the specified fields; missing fields will cause errors in subsequent links. The unified unit and date format requirements require adding unit conversion and format verification nodes to convert non-ten-thousand-yuan amount data to ten thousand yuan, and unify non-standard date formats to YYYY-MM-DD.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Scheduled Trigger Frequency | Daily 00:30 | Adapts to the generation rhythm of the previous working day's water utility financing daily report data, ensuring that the previous day's data is pulled and processed on the current day |
Incremental Pull Time Range | 1 day | Matches the daily update rhythm of data sources, avoiding pulling redundant data beyond the time range |
Code Execution Dependency Libraries | pandas、python-dateutil | Used for processing amount unit conversion and date format unification, must be installed in the Python runtime environment of the FastGPT container |
Tool Call Timeout | 600 seconds | Covers the average time required for multi-source data pulling and batch processing, avoiding task interruptions caused by fluctuations in data volume |
Knowledge Base Recall Count | Top 3 | The associated knowledge base content for water utility financing daily reports is mostly industry specifications and policy documents, a small number of recalls can meet context supplement requirements |
Similarity Threshold | 0.75–0.85 | Filters low-correlation knowledge base content, ensuring that the matching degree between recalled content and the current financing daily report meets business requirements |
The parameter values provided on this page are common starting points for configuration. The actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing the configuration.
Three common mistakes
- Phenomenon: No matching knowledge base content appears after the tool call module is configured, and the interface displays
Recall result is empty. Cause: The current financing daily report's project name or financing entity is not passed as a variable to the knowledge base recall link, resulting in failure to accurately match associated content. - Phenomenon: The code execution module throws
ModuleNotFoundErrorduring operation, and the importedpandaslibrary cannot be recognized. Cause: The dependency libraries are not installed in the global Python runtime environment of the FastGPT container, and are only installed in the local test environment. - Phenomenon: The tool call module does not trigger the corresponding data source pulling action, and the log displays
Tool not called. Cause: The trigger condition of the tool call module is not bound to the output of the workflow's preceding node, or the tool's API key configuration is invalid.
How to confirm the configuration is complete
- Manually trigger the workflow once, check that the output node fully includes the 7 core fields such as project name, financing amount, arrival date, etc., and that the field formats and units meet the preset requirements.
- Check the running logs of the code execution module to confirm that the dependency libraries have been successfully loaded, and there are no
ModuleNotFoundErrortype errors. - Trigger the tool call link to check that the number and relevance of knowledge base recall results meet the preset recall rules.
- Verify the scheduled trigger function by setting the trigger time to 5 minutes after the current time, and confirm that the workflow automatically executes at the specified time.
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.