Data Characteristics for This Category
Registration documents for high-value consumables typically include product technical requirements, test reports, clinical evaluation reports, instructions for use, labels, and manufacturing information. This data often exists in structured documents (e.g., Word, PDF) and semi-structured tables (e.g., Excel). Data sources are diverse, including internal R&D departments, quality control departments, entrusted testing institutions, and clinical trial institutions. Data update frequency is relatively low, primarily occurring during product design changes, regulatory updates, or periodic reviews. Document structures are complex, containing extensive specialized terminology, technical parameters, and diagrams. Field units involve physical quantities (e.g., millimeters, grams, volts), chemical compositions (e.g., percentage, ppm), and biological indicators (e.g., IU, U/mL). Measurement units and expressions for the same parameters can vary across different countries or regions.
Constraints Imposed on "Tool Calling and Plugins" by These Characteristics
The complexity of data sources and the non-real-time update frequency for high-value consumables data require tool calling and plugins to have robust document parsing capabilities and version management mechanisms. Specialized terminology and diverse measurement units within documents challenge the semantic understanding capabilities of natural language processing models, necessitating more precise entity recognition and unit conversion functions. The mixture of structured and semi-structured data means plugins must flexibly handle different data formats and perform effective information extraction and integration. Furthermore, regulatory differences across countries and regions, along with specific field and unit requirements, dictate that plugins must customize output according to target market specifications when generating registration documents. This prevents submission failures due to format or unit discrepancies.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for Recommendation |
|---|---|---|
maxContext | 3000 Tokens | High-value consumable documents are lengthy, requiring a larger context window to maintain semantic coherence. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large PDF or Word documents can be time-consuming; this avoids timeout interruptions. |
Chunk size | 800 characters | Ensures each segment contains sufficient technical details for subsequent information extraction and retrieval. |
Similarity threshold | 0.75 | Improves relevance matching accuracy, reducing interference from irrelevant information, especially during specialized terminology retrieval. |
Rerank result count | Top 5 entries | Prioritizes displaying the most relevant few results, improving engineer review efficiency. |
ENABLE_FUNCTION_CALL | True | Allows the model to call external tools for tasks such as unit conversion and data validation. |
Three Common Mistakes
- LLMs in local deployment environments fail to call external functions, manifesting as unresponsive function call requests or 400 errors. This occurs because the Function Calling capability was not correctly configured during model deployment, or the API gateway did not forward Function Calling requests to a supported model.
- Timeout errors occur when parsing large declaration documents, with logs showing
PARSE_FILE_TIMEOUT_SECONDSexceptions. This happens because the default file parsing timeout is insufficient for documents containing numerous charts or complex layouts. - Measurement units in generated declaration documents are inconsistent or incorrect, for example, "Milliliter" (milliliter) is recognized as "ml" and not standardized. This is due to the plugin not integrating or calling a unit conversion tool, or the unit conversion rule base being incomplete.
How to Verify Correct Setup
- Upload a PDF document containing complex tables and specialized terminology. Check if the knowledge base index is complete and if segment content retains key information.
- Perform an information extraction task on a test report containing various measurement units. Verify that units in the output results are standardized.
- Invoke a query task that requires external tool assistance, such as asking for the maximum size limit of a certain consumable under specific regulations. Observe if the tool call is successful and returns the correct result.
The values provided are common starting points and should be measured against specific 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.