Tool Calling and Plugins for siRNA Nucleic Acid Drug Quality

Data Characteristics for this Category

siRNA nucleic acid drug quality documents typically include manufacturing process records, analytical method validation reports, stability study data, and batch release test reports. These documents exist in various formats such as PDF, Word, and Excel. Excel files are often used for recording batch analysis data, containing complex table structures and specific units (e.g., ug/mL, nM, %). Data sources primarily include export files from internal Laboratory Information Management Systems (LIMS) and Manufacturing Execution Systems (MES), as well as Certificates of Analysis (CoA) from suppliers. Document update frequency is high, especially during research, development, and clinical trial phases, where process changes and batch production generate a large volume of new documents. Document content is highly specialized, involving key quality attributes such as chemical structure, biological activity, purity, impurity profiles, and degradation products.

Constraints Imposed by these Characteristics on "Tool Calling and Plugins"

The complexity of siRNA nucleic acid drug quality documents places specific demands on tool calling and plugin functionalities. First, a large amount of structured and semi-structured data (e.g., test results in Excel tables) requires specialized parsing tools to ensure accurate data extraction; traditional text parsing methods may not effectively handle this. Second, the high frequency of document updates means tool calling needs to support incremental updates and version management, avoiding redundant processing of historical data. Furthermore, the specialized nature of document content requires tools to understand biochemical terminology and specific analytical methods, which may necessitate customized semantic understanding models or integration of industry-specific knowledge graph plugins. Finally, standardization of units and fields in batch data is crucial. Tools must identify and convert different units and map them to standard fields during data extraction to ensure accuracy in subsequent analysis.

Configuration Settings

Configuration Item	Recommended Value	Rationale for this Value
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	siRNA nucleic acid drug documents are often large, especially PDFs containing numerous charts and tables, requiring longer parsing times.
`maxContext`	`800–1200 characters`	Ensures sufficient context is included when processing descriptions of individual quality attributes, while avoiding overly long text blocks that could hinder retrieval efficiency.
`Chunk size` (Segment Length)	`500 characters`	Accommodates longer descriptive paragraphs in quality documents, ensuring semantic completeness and reducing semantic loss due to segmentation.
`Recall count` (Recall Count)	`Top 8`	Given the specialized nature of document content, increasing the recall count improves the probability of retrieving relevant information, especially when comparing multi-dimensional quality attributes.
`Similarity threshold` (Similarity Threshold)	`0.75`	Ensures retrieved results are highly relevant to the query intent, avoiding the introduction of a large amount of irrelevant or generalized information, suitable for precise quality parameter queries.
`Rerank result count` (Reranked Return Count)	`Top 3`	Further improves the ranking of the most relevant information based on initial recall, focusing on key quality control points.

Three Common Mistakes

After calling the file upload interface, xlsx files fail to correctly recognize table content, leading to empty fields in AI conversations. This occurs because a default generic parser is used or no specific parser is configured, which cannot handle complex merged cells or specific data types in Excel.
Tool calling workflows experience timeout errors when repeatedly calling HTTP interfaces. This happens because the HTTP interface response time is too long or the number of concurrent requests exceeds system limits.
The knowledge base selection option is missing when configuring tool calling functionality. This indicates incomplete integration configuration between the tool calling and knowledge base modules, or that related features like mcp are not enabled in the backend.

How to Confirm Proper Configuration

Upload a typical siRNA nucleic acid drug Excel batch data file. Ask the AI via chat for a specific test result from a certain batch (e.g., purity or residual solvent). Observe whether it can accurately extract and return the value with units.
Build a tool calling workflow that includes an HTTP request. Simulate querying the LIMS system for a CoA report link for a specific batch. Confirm that the link is returned correctly and that the workflow executes without abnormal interruptions.
Check system logs to see if there are any PARSE_FILE_TIMEOUT_SECONDS related timeout errors when processing PDF or Word format quality documents, and confirm that the file parsing task ultimately succeeds.

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.