Data Characteristics
siRNA nucleic acid drug regulations and Standard Operating Procedure (SOP) documents originate from regulatory agency publications, internal quality management system documents, and clinical trial protocols. These documents are typically in PDF, DOCX, or scanned image formats. Regulatory documents update annually or as policy changes. Internal SOPs may revise quarterly or semi-annually based on R&D progress, production process optimization, or quality audits. Regulatory documents often use a chapter structure. SOPs commonly feature step-by-step lists, flowcharts, and responsibility matrices. SOPs include specific fields and units like reagent batch numbers, concentration units (nM, μM), operation times (minutes, hours), and temperatures (℃). These details are critical operational information.
Constraints on Multiturn Conversation and Prompts
Data characteristics of siRNA nucleic acid drug regulatory documents impose specific requirements on multiturn conversation and prompt construction. First, various document formats (PDF, DOCX, scanned images) demand strong document parsing capabilities from FastGPT, especially accurate Optical Character Recognition (OCR) for scanned images. Second, frequent updates to regulations and SOPs mean the knowledge base requires regular incremental synchronization and index rebuilding to ensure timely answers. The chapter structure and step-by-step lists in documents require fine-grained text block splitting during RAG retrieval. This captures complete operational steps or regulatory clauses in context. Additionally, precise fields and units in SOPs, such as siRNA concentration and incubation time, require prompt design to accurately extract and match this key information. This avoids operational ambiguity due to vague units or values.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
Chunk Length | 300–500 characters | Adapts to the granularity of SOP steps and regulatory clauses. Ensures a single text block contains a complete operation or regulation for better understanding. |
Recall Count | 8–12 items | Considering the complexity of siRNA nucleic acid drug regulations, increasing recall helps cover multiple aspects and reduces the risk of missing critical clauses. |
Similarity Threshold | 0.75–0.82 | Balances recall and precision. Avoids interference from irrelevant information while capturing semantically relevant regulatory details. |
Rerank Return Count | Top 3 items | Prioritizes core regulations or SOP steps most relevant to the user's question, improving the efficiency of multiturn conversations. |
maxContext | 4096 tokens | Ensures sufficient dialogue context to support multiturn follow-up questions and clarifications on complex SOP processes or regulatory clauses. |
UPLOAD_FILE_SIZE | 500 MB | Accommodates potentially large file sizes for regulatory documents or SOPs with many diagrams. Ensures uploads are not restricted by file size. |
Three Common Mistakes
- Symptom: When users ask about specific
siRNA concentrationorincubation temperature, the AI provides inaccurate or missing information. Reason: Document chunks are too coarse. This causes critical numerical and unit information to be truncated or confused with irrelevant context. - Symptom: In a multiturn conversation, the AI cannot further refine or clarify an operational step based on previous follow-up questions. Reason: The
maxContextparameter is set too small. This causes the model to lose critical contextual information from the conversation history. - Symptom: After uploading a new regulatory document, the AI still references old content in its answers. Reason: The knowledge base failed to trigger timely incremental index updates or full rebuilding. This results in retrieved information being outdated.
How to Verify Configuration
- Upload an siRNA nucleic acid drug SOP document containing complex processes and precise parameters. Then, ask three or more follow-up questions about a key operational step. Verify the accuracy and coherence of the AI's answers.
- Randomly select 10 questions involving specific concentrations (e.g.,
50 nM), times (e.g.,30 minutes), or temperatures (e.g.,37 ℃). Check if these values and units are correct in the AI's answers. - Publish a new version of a regulatory document and ensure the knowledge base is updated. Then, ask questions about the differences between the new and old versions. Verify that the AI can correctly identify and cite the latest content.
The values provided are common starting points. Measure against your 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.