Tool Calling and Plugins for Surgical Robot

Data Characteristics

Surgical robot pharmacovigilance data primarily originates from post-market surveillance reports submitted by device manufacturers, hospital adverse event reporting systems, and regulatory agency databases. Data update frequencies vary. Manufacturer reports may be quarterly or annual, while hospital reports can be real-time. Document structures typically include structured fields like device model, batch number, adverse event codes (e.g., MedDRA codes), de-identified patient information, surgical procedure records, and unstructured free-text descriptions. Field units involve time (date, duration), quantity (procedures, items), severity ratings (levels 1-5), and operational parameters (e.g., torque in N·m, angle in °).

Constraints Imposed by These Characteristics on Tool Calling and Plugins

Adverse event reports related to surgical robots contain significant amounts of unstructured text. This requires tool calls to effectively process long text for summarization and entity recognition, preventing loss of critical information. Discrepancies in field units, such as torque and angle, necessitate unit normalization or explicit unit specification during data preprocessing or plugin calls to avoid misinterpretation of values. Inconsistent update frequencies, particularly the periodic updates of regulatory databases, dictate the scheduling strategy for data synchronization plugins. High-frequency real-time synchronization is not suitable; plugins must adapt to batch update patterns. Additionally, adverse event reports often involve cross-referencing data from multiple systems. Tools must support cross-system queries and associations via IDs or codes to ensure data chain completeness.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`maxContext`	`3000 Tokens`	Accommodates common medium-to-long text descriptions in adverse event reports while maintaining processing efficiency.
`Chunk size`	`500 characters`	Ensures text segments retain contextual semantics and prevents excessively long segments from impacting recall efficiency.
`Recall count`	`Top 8 entries`	Covers multiple highly relevant potential knowledge points, improving information completeness.
`Rerank result count`	`Top 3 entries`	After re-ranking model filtering, focuses on the most relevant core information, reducing redundancy.
`PARSE_FILE_TIMEOUT_SECONDS`	`180 seconds`	Provides sufficient parsing time when processing PDF-formatted surgical records or device logs.
`MedDRA_Code_Extractor.enabled`	`True`	Automatically identifies and extracts standard MedDRA codes from adverse event reports for structured information extraction.

Common Pitfalls

A 400 error "Messages with role 'tool' must be a response to a preceding message" is returned after a tool call. This occurs when the tool execution result is not correctly passed back to the model, or the return format does not comply with the protocol, leading to context disruption.
Knowledge base retrieval results are not effectively ranked, causing critical information to be buried. This happens due to improper re-ranking model configuration, such as setting Rerank result count too high, or if the re-ranking model itself is not correctly activated, leading to reliance solely on vector similarity for recall.
Plugins fail to control external robotic arms or systems. This is caused by missing necessary control libraries in the Python environment or incorrect configuration of connection parameters like API keys and IP addresses in the plugin.

Verification Steps

Perform test calls and observe tool execution logs. Confirm that tool_code and tool_result fields are populated as expected, with no error messages.
Conduct multi-turn dialogue tests. Input queries containing long text descriptions of adverse events. Check if the responses accurately cite key details and MedDRA codes from the report.
Simulate adverse event query scenarios. Compare model responses with expected results. Confirm that Rerank result count effectively places the most relevant knowledge items at the top.
For robot control plugins, check if the plugin successfully connects to external systems using parameters like API_KEY and ENDPOINT_URL during execution, and receives correct response codes, such as 200 OK.

The values provided are common starting points and should be measured against the reader's own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.