Tool Calling and Plugins for Chemical Pharmaceutical Yield

What the Data for This Category Looks Like

Chemical pharmaceutical yield and market data comes from four main sources: periodic reports of publicly listed companies, pharmaceutical circulation trading APIs, stock exchange market data ports, and industry centralized procurement bid winning announcements. There are three update frequency categories:

Trading day market data updates within 1.5 hours after market close
Monthly product profit margin data updates on the first day of each month, covering statistics from the previous month
R&D pipeline data updates every Friday

Documentation uses structured CSV and JSON formats. Fields include company identifiers, product generic names, daily average trading price, unit cost-to-sales ratio, R&D investment-to-revenue ratio, sector correlation relative value, and more. All numeric fields are labeled using dimensionless ranges or relative value formats.

Constraints for Tool Calling and Plugins

The multi-source, heterogeneous nature of chemical pharmaceutical data creates multiple constraints for tool calling and plugins:

Cross-data-source pulling must support independent authentication configurations for listed company financial reports, market data ports, and centralized procurement announcements to avoid permission conflicts.
Update frequencies vary significantly across data sources. Set short-cycle call thresholds for high-frequency market data, and long-cycle cache rules for low-frequency R&D and centralized procurement data to reduce invalid requests.
Fields use dimensionless ratios and relative value formats. Plugins must include built-in format conversion logic to ensure returned data matches model input requirements.
Many multi-dimensional associated fields exist. Plugins must support linked queries for companies, products, and R&D pipelines to avoid data silos.

How to Configure Settings

Configuration Item	Recommended Value	Rationale
`tool_timeout`	`120 seconds`	Average time to pull multi-source data for chemical pharmaceuticals is 60-90 seconds. Reserve reasonable redundant time to prevent mid-call interruptions
`max_tool_calls_per_round`	`3 times`	A single yield rate query needs to pull three data sources: market data, product cost data, and R&D data. Avoid excessive calls that trigger rate limits
`plugin_cache_ttl`	High-frequency market data: `3600 seconds`, low-frequency R&D data: `604800 seconds`	Matches data source update schedules. Market data updates daily, R&D data updates weekly. Reduces invalid requests
`data_parse_mode`	`structured + semi-structured`	Data includes structured financial reports and semi-structured centralized procurement announcements. A mixed parsing mode adapts to different document formats
`multi_source_auth`	`Configure secrets independently per data source`	Different data sources (stock exchanges, pharmaceutical company public APIs) require separate authentication rules to avoid permission conflicts
`model_format_adapter`	`Configure based on target large model type`	Adapts to input format requirements of different large models to ensure tool-returned data can be parsed correctly

The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three Common Misconfigurations

Issue: Accurate recall of chemical pharmaceutical product data linked to the knowledge base fails. Cause: Duplicate removal rules for tool_result_duplicate_removal are not configured, or recall thresholds are set incorrectly, resulting in valid data being filtered out.
Issue: Tool calling duration exceeds 600 seconds, triggering model context timeout. Cause: No reasonable tool_timeout threshold is set, and more than 3 data sources are called simultaneously, with no limit on single-round call count.
Issue: Third-party MCP services cannot pull chemical pharmaceutical data normally. Cause: Authentication information is not configured independently per data source, or access permissions for corresponding data sources are not enabled.

How to Verify Proper Configuration

Run a single tool call test. Check if the field format of the returned results matches the preset chemical pharmaceutical data structure. Adjust data_parse_mode and model_format_adapter to match the requirements of the target large model.
Review tool call logs. Confirm that single-call execution time does not exceed the preset tool_timeout threshold. Adjust max_tool_calls_per_round or tool_timeout to a reasonable range.
Check cache refresh records. Confirm that high-frequency market data updates daily and low-frequency R&D data updates weekly. Adjust plugin_cache_ttl to match data source update schedules.
Verify authentication configurations for third-party MCP services. Attempt to pull different types of data sources. Confirm no permission errors or missing data. Adjust the multi_source_auth configuration item.

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.