What the data for this use case looks like
Data sources include credit approval systems of local corporate financial institutions, interbank borrowing reporting platforms, and financing monitoring reports from local financial regulatory authorities. The data update cadence generates full statistics for the previous day on a T+1 basis, with updates completed each early morning. Documents use structured format, categorized by institution, and include fields such as institution name, daily new financing transactions, daily new financing amount, weighted average financing cost, matured payout amount, and guarantee method. Amount unit is ten thousand yuan, transaction count unit is transactions, and financing cost unit is basis points.
Constraints for Tool Calling and Plugins
The T+1 update cadence requires scheduled pull tasks for plugins to match the daily update cycle, to avoid frequent requests for unupdated data. Clear units for structured fields require built-in validation and formatting logic in plugins, to prevent unit confusion during parameter passing. Data structures categorized by institution require that input parameters for tool calls support precise validation of institution name and statistical date, to filter invalid requests. Data sources aggregated across multiple systems require plugins to configure field mapping rules across data sources, to unify field names and formats across different systems. The limited number of local institutions requires the loop processing logic of plugins to adapt to traversal needs for small-scale data volumes.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
cache_ttl | 86400 seconds | Matches the T+1 update cycle of the financing daily report, to avoid repeated pulling of unupdated data |
request_timeout | 120 seconds | Adapts to interface response delays for cross-system aggregated data, to prevent single request timeout interruptions |
plugin_input_schema | Configured as three required fields: "Institution Name", "Statistical Date", "Data Range", with field types being string, date, and enumeration (local/entire jurisdiction) respectively | Matches the filtering requirements of the financing daily report, to ensure accurate and valid input parameters |
max_retries | 2 times | Handles occasional fluctuations in cross-system interfaces, to avoid task termination from a single failed request |
workflow_loop_max_iterations | 10 times | Adapts to the typical scale of local financial institutions, to avoid loop counts exceeding reasonable limits |
plugin_output_format | Configured as structured JSON containing preset institution and financing data fields | Unifies output format, to facilitate subsequent process handling and front-end display |
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 settings.
Three Common Misconfigurations
- Symptom: After adding a custom plugin to a workflow task, input and output parameters do not display, and no error logs are generated. Cause: JSON format of
plugin_input_schemaandplugin_output_schemais not correctly configured, or there are syntax errors in parameter configuration. For open-source deployments of version v4.8.20-fix2 and above, this issue is often caused by indentation errors in schema configuration. - Symptom: External calls to the chat interface result in response timeout, returning a
504 Gateway Timeoutstatus code. Cause: No reasonablerequest_timeoutparameter is set, or data caching is not enabled. Each request directly pulls full cross-system data, leading to excessive processing time. - Symptom: When looping through AI session processing array elements, the institution list output by the plugin is not correctly passed, resulting in no valid data at the loop input. Cause: The structured array output by the plugin is not bound to the input parameter of the loop node, or the loop configuration data source does not match the field format of the plugin output.
How to Verify Correct Configuration
- Trigger plugin calls, check if the fields of the returned results match the preset financing daily report fields, and verify that units comply with business requirements.
- Simulate external interface calls, check if the interface response duration meets expectations, and adjust
request_timeoutandcache_ttlparameters to reasonable ranges. - Add a loop node in the workflow, bind the array field output by the plugin, and test if the process for processing single-institution data via looping executes normally.
- View plugin runtime logs, confirm there are no records of
plugin_input_schemaparsing errors or data source connection failures.
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.