Tool Calling and Plugins for Dedicated Equipment Yield Rates

What the data for this category looks like

Data sources for the dedicated equipment yield rate and market daily report broadcast scenario mainly come from compliant on-exchange trading interfaces and locally collected transaction logs from equipment. There are two data update frequencies: Full daily report data is generated after each trading day closes, and full synchronization completes the next early morning. Real-time snapshot data updates every 15 minutes. Data uses structured JSON format, including fields such as device unique identifier, target trading code, daily opening price, daily closing price, daily total trading volume, daily profit change value, data generation time, etc. Their corresponding units are string identifier, trading code, currency unit, currency unit, trading unit, numerical unit, and timestamp.

What constraints these characteristics impose on the tool calling and plugins workflow

First, the time-separated data update rhythm requires tool calling to adapt to two trigger logics: use the real-time snapshot interface during non-update periods, switch to the full daily report interface after market close, to avoid invalid pulls or delayed access to core data. Second, structured fields require plugins to pre-set fixed parsing templates, preventing the model from generating valid broadcast content due to missing fields or format exceptions. Third, financial data compliance requirements require tool calling to carry device authentication parameters to prevent unauthorized access. Fourth, in multi-device deployment scenarios, use the device unique identifier to distinguish different data sources to avoid data confusion.

How to Set Configurations

Configuration Item	Recommended Value	Rationale
`data_fetch_interval`	`86400 seconds` between 23:00 previous day and 01:00 current day, `900 seconds` for all other periods	Matches the full daily report update and real-time snapshot frequency of dedicated equipment
`plugin_auth_type`	`API signature verification`	Adapts to the compliance authentication requirements of financial data interfaces
`response_parse_schema`	`Pre-set JSON validation rules for fields including device identifier, target code, daily profit change value`	Matches the structured document structure returned by dedicated equipment
`max_retries`	`3 times`	Addresses occasional timeouts or disconnections from financial data interfaces
`timeout_threshold`	`30 seconds`	Fits the typical response delay range of financial data interfaces
`device_id_bind`	`Required, bind the unique identifier of the corresponding dedicated equipment`	Distinguishes different data sources in multi-device deployments

The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

Symptom: Cross-origin error returned when calling the api/v1/chat/completions interface, with Access-Control-Allow-Origin missing in the frontend console. Cause: No allowed domain whitelist configured in the plugin backend, or cross-origin response headers not added correctly.
Symptom: chat:llm-model-response-empty returned after tool calling. Cause: The dedicated equipment data interface returns empty fields, or the plugin fails to correctly parse structured data, preventing the model from obtaining valid context.
Symptom: The number of retrieved market data entries does not match expectations, with non-current day data returned excessively. Cause: No device unique identifier bound in the request parameters, or no filter condition specified for data generation time.

How to Confirm the Configuration Is Correct

Initiate a full data pull request, check if the returned JSON fields include the preset required items such as device identifier and target code.
After configuring the cross-origin whitelist, use the frontend fetch tool to send a test request, confirm no cross-origin errors are returned.
Simulate the update period of the next early morning, trigger the plugin to pull data, check if the returned update_time field is the closing time of the previous trading day.
Initiate three consecutive pull requests, confirm the retry mechanism is active, with no consecutive timeout errors.

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.