Data Characteristics
Data for seed compound screening protocols primarily originates from internal R&D management systems, Quality Management System (QMS) documents, and laboratory Standard Operating Procedures (SOPs). These documents are typically in PDF, Word, or internal knowledge base page formats. Content includes experimental screening procedures, equipment operation specifications, data recording standards, result determination criteria, and anomaly handling processes. Protocol documents have a relatively low update frequency, usually revised only when regulations change, technology evolves, or internal processes are optimized, with cycles ranging from six months to several years. Document structures commonly include chapter titles, body text, figures, and appendices. Fields and units involve compound ID, screening batch, target, activity values (e.g., IC50, EC50, in nM or µM), screening conditions (temperature, pH), operation step numbers, and responsible personnel. Activity values and screening conditions require high precision.
Constraints on Multi-turn Conversations and Prompts
The low update frequency of seed compound screening protocol documents means less pressure for daily maintenance after knowledge base construction. However, the accuracy of initial data entry and parsing is critical. Documents contain extensive specialized terminology and experimental parameters. The model must accurately understand and differentiate screening conditions and results for various compounds and targets in multi-turn conversations, avoiding confusion. Complex document structures and figures demand high document parsing capabilities; plain text parsing may lose critical information. For high-precision fields like activity values, the model must precisely cite original document data to avoid numerical deviations. Additionally, process-oriented content in protocols requires the model to decompose steps and perform logical reasoning, guiding engineers through specific operations or problem diagnosis in multi-turn conversations.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size (Chunk Length) | 800–1200 characters | Protocol documents often have long paragraphs, containing multiple steps or detailed descriptions, ensuring contextual completeness. |
Recall count (Recall Count) | Top 5 | Queries for screening protocols typically need to cover multiple relevant regulations, ensuring no critical information is missed. |
Similarity threshold (Similarity Threshold) | 0.75 | Ensures recalled results are highly relevant to the query intent, reducing interference from irrelevant information. |
Rerank result count (Reranked Return Count) | 3 | Reranking further focuses on the most relevant information, improving answer precision. |
maxContext | 4096 tokens | Ensures multi-turn conversations can accommodate sufficient historical conversation information and recalled document snippets. |
temperature | 0.3 | Reduces the randomness of model-generated answers, ensuring responses are based on the original protocol text and minimizing hallucinations. |
Common Pitfalls
- The message "Insufficient permissions to operate this conversation record" appears during a conversation. This usually indicates incorrect user role or permission configuration, preventing access or modification of specific conversation history or knowledge base.
- The AI fails to accurately identify activity values or screening conditions in the document. This may be due to inaccurate extraction of numbers and units during document parsing or the model's misunderstanding of specialized terminology.
- After refreshing the conversation page, conversation history is lost, and a new conversation is displayed. This might be due to issues with the backend session management mechanism, where the session ID is not correctly saved or passed, causing each refresh to be treated as a new request.
Verification Steps
- Conduct simulated multi-turn conversation tests. Ask questions about screening procedures and results for different compounds. Verify that the model's answers align with the original protocol document, especially for numerical values and operational steps.
- Check document parsing logs to confirm that figures, specialized terminology, and key numerical values in the document are correctly extracted and indexed. For example, examine the content of the
chunk_textfield. - Test access to historical conversations and the knowledge base under different user permissions. Verify that permission controls function as expected, without unintended access restrictions or unauthorized access.
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Note: The values provided are common starting points. Measure them against your own samples for optimal configuration.
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.