Tool Calling and Plugins for siRNA Nucleic Acid Drug

Data Characteristics for this Category

siRNA nucleic acid drug regulations and standard documents typically exist in PDF, Word, or structured XML formats. Their content covers the entire lifecycle of drug development, production, quality control, clinical trials, and registration applications. Data sources primarily include official regulatory agency websites, pharmacopoeias, technical guidance principles from industry associations, internal company SOP documents, and academic journals. The update frequency is relatively low, usually revised with policy adjustments or technological advancements, which might be several times a year or once every few years. Documents have complex structures, containing numerous specialized terms, formulas, charts, cross-references, and attachments. Fields and units are highly specific, such as nucleic acid sequence length (nt), drug concentration (nM, μg/mL), dosage (mg/kg), purity indicators (%), batch numbers, limit of detection (LOD), and limit of quantitation (LOQ). High precision for numerical values and unit consistency is critical.

Constraints from these Characteristics on "Tool Calling and Plugins"

The complexity of siRNA nucleic acid drug regulatory documents imposes multiple constraints on tool calling and plugins. First, complex table and chart structures within documents, along with nested references, require tools with robust document parsing capabilities to accurately extract key information. Second, the low but impactful update frequency means that plugins must ensure they call the latest version of regulations or SOPs when executing queries, avoiding outdated information. Third, the large number of specialized terms and measurement units requires tools to accurately identify and differentiate them during semantic understanding, preventing misjudgments due to synonyms or unit confusion. For example, the order of magnitude difference between nM and μM could lead to serious errors. Furthermore, because the data involves highly specialized fields, plugins need to validate the professional relevance of results returned by external tools. This ensures that queried patent information, clinical data, or regulatory clauses are highly relevant to the characteristics of siRNA nucleic acid drugs. They must also correctly handle exceptions such as MongoServerError or company has no patent records returned by tools.

Configuration Guidelines

Configuration Item	Suggested Value	Rationale for this Value
`PARSE_FILE_TIMEOUT_SECONDS`	`300–600 seconds`	Processing large PDF or Word documents, especially those with complex charts, requires longer parsing times to avoid timeouts.
`Chunk size` (Segment Length)	`500–800 characters`	Ensures each segment contains enough context to understand siRNA pharmaceutical concepts and regulatory terms, while avoiding excessive length that could lead to semantic drift.
`Recall count` (Recall Count)	`10–15 items`	Given the strong interconnectedness of specialized documents, appropriately increasing the recall count helps cover a more comprehensive set of relevant regulatory clauses.
`Similarity threshold` (Similarity Threshold)	`0.75–0.85`	siRNA regulatory Q&A demands high accuracy, requiring a higher similarity threshold to ensure the precision of recalled content.
`Rerank result count` (Reranked Return Count)	`5 items`	Reranks the initially recalled results to prioritize the most relevant core regulatory clauses or operational steps.
`TOOL_EXECUTION_TIMEOUT_SECONDS`	`60 seconds`	External tools (e.g., patent search, database retrieval) may have longer response times, requiring sufficient execution time.

Three Common Pitfalls

Symptom: External tool call returns MongoServerError: The dollar ($) p error. Reason: Compatibility issues between the MongoDB version relied upon by the FastGPT plugin and the FastGPT core components, or the plugin's internal query statement uses an incompatible MongoDB operator.
Symptom: Querying patent information via a tool call component returns "company has no patent records" (company has no patent records), but a manual search yields results. Reason: The tool call component might have encoding issues, inaccurate field mapping, or called the wrong API endpoint when passing the company name or query parameters.
Symptom: Using the official Markdown to File plugin displays "File Upload Failed" (file upload failed). Reason: The uploaded file size exceeds the UPLOAD_FILE_MAX_SIZE limit, the file type is not supported by the plugin, or the backend storage service configuration is abnormal.

How to Verify Configuration

For core regulatory documents, conduct multiple rounds of complex questions involving specialized terms and units. Verify that the cited clauses in the answers are accurate and complete, comparing them with the original document content to confirm the effectiveness of Similarity threshold (Similarity Threshold) and Recall count (Recall Count).
Test multiple external tool calls, such as querying patent information for a specific siRNA drug, clinical trial data, or the latest regulatory revisions. Check the completeness and accuracy of the results returned by the tools to confirm if TOOL_EXECUTION_TIMEOUT_SECONDS is sufficient.
Upload and parse siRNA regulatory documents in different formats (PDF, Word, XML) and sizes. Observe the parsing time and segmentation results to ensure PARSE_FILE_TIMEOUT_SECONDS and Chunk size (Segment Length) are appropriately configured and document content is correctly extracted.
Construct specific questions for potentially ambiguous specialized terms or measurement units. Verify if the model can accurately differentiate and provide correct explanations, confirming the precision of semantic understanding.

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.