What the data for this category looks like
Data sources for rural commercial bank intelligent due diligence reports include internal credit management systems, PBOC credit inquiry APIs, the National Enterprise Credit Information Publicity System, and business filing data from local government service platforms. Internal business data is synced daily. External public data is updated quarterly. Documents mostly combine structured tables with unstructured risk assessment notes. Fields include unified social credit code, enterprise name, credit limit, loan balance, operating transaction amount, and similar items. Common units are ten thousand yuan and transaction counts.
What constraints these characteristics impose on the tool calling and plugins workflow
The daily update requirement for internal data means tool calling must support high-frequency compliant API calls. Authentication and audit log retention rules must be configured. The quarterly update cycle for external public data allows using a caching mechanism to reduce repeated calls. This lowers API invocation costs. Most fields are standardized but have API-specific differences. This requires configuring unified field mapping rules in the tool calling link, to avoid data extraction failures caused by field name mismatches. Unstructured risk assessment notes require plugins to support text parsing and key information extraction capabilities. This adapts to multi-type data processing needs for due diligence reports.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
tool_call_max_retries | 2–3 attempts | Rural commercial bank due diligence data APIs are mostly internal compliant APIs; excessive retries will trigger risk control interception |
plugin_cache_ttl | 86400 seconds | External public data is updated quarterly, internal data is updated daily; setting cache duration to 1 day balances call efficiency and data freshness |
field_mapping_rule | Map per API documentation preset fields | Due diligence data fields for rural commercial banks are mostly standardized but have API differences; preset mapping avoids field mismatches |
tool_call_timeout | 30 seconds | Internal API responses are affected by compliance checks; setting a timeout that is too short will cause valid calls to fail |
plugin_audit_log_enabled | Enabled | Rural commercial bank due diligence businesses require retaining operation logs to meet compliance requirements |
max_tool_call_per_round | 5 attempts | Generating due diligence reports requires calling tools from no more than 5 different data sources, to avoid meaningless repeated calls |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Configuration Mistakes
- A
404 Not Founderror is returned when calling a locally created MCP service. The cause is that the local service's LAN access address and port mapping rules were not filled in the FastGPT plugin configuration. - After enabling tool calling, the model output only contains tool call parameters and no natural language thought process. The cause is that the
tool_call_think_stepconfiguration item was not enabled, or the model version does not support tool call formats with thought steps. - The number of due diligence data items returned by the external data source API does not match expectations. The cause is that the
max_tool_return_itemsparameter was not set correctly, or some required fields were missed during field mapping.
How to Verify the Configuration is Complete
- Initiate a test call, view the FastGPT plugin call logs, and confirm that the API request parameters match the preset field mapping rules.
- Compare the original data returned by the tool with the fields extracted in the due diligence report, and confirm that the units and field names match.
- Check that the audit log fully records the time, parameters and return results of each tool call.
- Simulate a high-frequency call scenario, and confirm that the tool call retry and caching logic conform to the preset configuration.
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.