Tool Calling and Plugins for Credit Application Risk Control

What the Data in This Category Looks Like

Credit application scenario data primarily comes from structured credentials and unstructured scanned documents submitted by applicants, plus connected third-party compliance APIs. Structured data includes fields such as identification numbers, monthly income, social security contribution base, with units of ID number (no unit), yuan, and month respectively. Unstructured data mostly consists of PDF-format bank statements and asset certification documents. Data update rhythm: A single application record is generated and updated only once at submission. For review scenarios, the latest data is only re-pulled when the review process is triggered. The document structure is organized per single application, integrating structured fields and corresponding attachment files, with no default batch aggregation data structure.

Constraints Imposed on the Tool Calling and Plugins Workflow

Structured fields have high format compliance requirements. Specialized tool plugins must be used to complete format verification and field extraction, to prevent invalid data from entering the review process. Parsing unstructured attachments takes a long time. Reasonable timeout parameters must be configured to ensure parsing completes. Tool calls for a single application must complete a multi-step workflow within a single session, such as credit inquiry, bank statement parsing, income calculation, and cannot rely on cross-session historical data. At the same time, data privacy compliance requirements mandate that sensitive information be desensitized during the tool calling stage to prevent applicant data leaks.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`maxToolCallsPerSession`	`3–5 times`	Credit applications require calls to core tools such as credit inquiry, bank statement OCR, and income calculation. 3-5 calls cover the complete review workflow and avoid timeouts
`PARSE_FILE_TIMEOUT_SECONDS`	`120–180 seconds`	Parsing PDF files such as bank statements and asset certification documents takes a long time. This range adapts to the parsing needs of most standard files
`UPLOAD_FILE_MAX_SIZE`	`100 MB`	Single certification documents submitted for credit applications typically do not exceed 100 MB. This value covers standard submission scenarios
`similarityThreshold`	`0.75–0.85`	Precise matching of knowledge base content related to credit rules is required. This range filters irrelevant recall while retaining valid associated content
`toolCallRetryTimes`	`2 times`	Third-party tool interfaces may experience temporary failures due to network fluctuations. Retrying 2 times improves success rates without increasing overall timeout risk
`pluginWhiteList`	`["Credit Inquiry Plugin","Bank Statement OCR Plugin","Income Calculation Plugin","Data Desensitization Plugin"]`	Only compliance-specific plugins are required for credit scenarios. Whitelist configuration avoids compliance risks caused by irrelevant plugin calls

The parameter values provided on this page are general recommendations for starting point configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis. Testing on available samples is recommended before finalizing settings.

Three Common Misconfigurations

Symptom: When deploying version 4.8.21 via Docker, after uploading a knowledge base file and starting parsing, logs continuously report slow operation xxxxms, and MongoDB responses are normal. Cause: PARSE_FILE_TIMEOUT_SECONDS was not configured to adapt to long document parsing, and the default timeout is too short, causing the parsing process to be classified as a slow operation.
Symptom: Tool calls and knowledge base search return no relevant results, making it impossible to obtain credit review rule references. Cause: The credit rule knowledge base was not associated with the context recall configuration for tool calls, or similarityThreshold was set too high, filtering out valid associated content.
Symptom: After configuring the deepseek-r1 model, tool calling performance is poor, and the complete credit review workflow cannot be completed. Cause: maxToolCallsPerSession was not set to adapt to multi-step tool calls, or toolCallRetryTimes was not enabled to handle temporary interface failures, preventing the model from completing the full workflow.

How to Verify Proper Configuration

Upload a credit application bank statement PDF, check the parsing logs, and confirm that the parsing time does not exceed the threshold set by PARSE_FILE_TIMEOUT_SECONDS.
Initiate a simulated credit application, check the tool call logs, and confirm that core plugins in the whitelist are called in sequence, and the total number of calls does not exceed the limit set by maxToolCallsPerSession.
Adjust similarityThreshold to 0.8, verify that all recalled knowledge base content is directly related to credit review rules, with no irrelevant entries returned.
Simulate a third-party tool interface timeout scenario, confirm that the system automatically retries the number of times set by toolCallRetryTimes before returning normal tool call results.

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.