Tool Calling and Plugins for IVD Diagnostic Reagent Quality

Data Characteristics

IVD diagnostic reagent quality documents include registration certificates, instructions for use, batch production records, inspection reports, risk management reports, and user manuals. These documents typically exist as PDFs, Word files, or scanned images, with varying degrees of structural organization. Data sources are primarily internal quality management systems, R&D departments, and production department archives. Document update frequency is relatively fixed, for example, changes to registration certificates, revisions to instructions for use, and batch production records generated per batch. Documents contain extensive specialized terminology, technical parameters, performance indicators, and operational procedures. Fields include Batch Number, Expiration Date, Storage Conditions, Intended Use, Detection Principle, Sensitivity, and Specificity. Units include ℃, %, IU/mL, and ng/mL.

Constraints on Tool Calling and Plugins from These Characteristics

The complex structure and specialized nature of IVD diagnostic reagent quality documents demand precise information extraction capabilities from tool calling and plugins. The presence of numerous scanned documents and unstructured files requires high accuracy in Optical Character Recognition (OCR) and document parsing. Periodic document updates mean tools must support version management and incremental updates to ensure the timeliness of recalled information. Diverse technical parameters and units require plugins to identify and standardize this information during cross-document comparison or data validation, preventing misjudgment due to format differences. For example, a query for Storage Conditions might involve converting multiple temperature units, or parsing Inspection Results in Batch Production Records might require the plugin to understand threshold ranges for different test items.

Configuration Recommendations

Configuration Item	Recommended Value	Rationale
`maxContext`	`3000` characters	Many IVD document paragraphs are long; ensures context completeness; avoids single request overload.
`PARSE_FILE_TIMEOUT_SECONDS`	`120` seconds	Accounts for the time required to parse large PDFs or complex Word documents; reduces parsing interruptions.
`Chunk size` (Chunk Length)	`800` characters	Balances semantic integrity with recall granularity; suitable for IVD documents with multiple parameter descriptions.
`Recall count` (Recall Count)	`Top 8 entries` (top 8 entries)	Ensures sufficient information from multiple relevant documents; covers potential associated knowledge points.
`Similarity threshold` (Similarity Threshold)	`0.75`	Filters out irrelevant or weakly related document segments; improves recall accuracy.
`Rerank result count` (Rerank Return Count)	`Top 5 entries` (top 5 entries)	Focuses on the most critical content through reranking, building on high recall volume; improves final presentation efficiency.

Common Pitfalls

After calling a plugin, the return result shows 400 Bad Request or Parameter Missing. This typically occurs when the plugin's expected input parameters do not match the actual document field names or data types passed, for example, expecting Batch Number but receiving Product Batch Number.
Query results for specific technical parameters (e.g., Linear Range) in a document are empty, even if the document clearly contains the information. This happens when document parsing or OCR struggles with complex tables and special characters, failing to correctly extract or normalize the field.
After using a search plugin to query Expiration Date or Storage Conditions, the returned links are inaccessible or incomplete. This might be because the search plugin failed to correctly parse the document's internal link structure or convert the original document content into an accessible URL.

How to Verify Configuration

Upload a typical IVD diagnostic reagent quality document (e.g., an instruction manual with tables and figures). Verify that after document parsing, key fields like Product Name, Batch Number, and Production Date are correctly identified and extracted.
Configure a tool to query key information such as Intended Use or Detection Principle from documents. Cross-reference the returned results with the original text to ensure semantic understanding accuracy.
Use a plugin for data comparison, for example, comparing Sensitivity or Specificity indicators in inspection reports from different batches. Verify that the plugin correctly retrieves numerical values and performs logical judgments, confirming its performance in handling units and numerical types.
Simulate a user query for Storage Conditions. Check if the tool call returns the correct temperature range and units, and verify its compatibility with multilingual or different format expressions.

The values given 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.