Multi-Turn Conversations and Prompts for Lead Compound

Data Characteristics

Lead compound screening data originates from high-throughput screening reports, compound activity test results, toxicology prediction reports, and relevant literature reviews. These documents typically exist as PDFs, Word files, or structured data tables (e.g., CSV, Excel). The update frequency depends on project progress, with new experimental data often generated weekly or bi-weekly. Document structure includes fixed sections in experimental reports such as objectives, methods, results, and discussion. The results section often contains fields like compound ID, activity values (e.g., IC50, Ki), selectivity indicators, and physicochemical properties (e.g., LogP, molecular weight). Activity values are commonly in nM or µM, while physicochemical properties use their respective international standard units.

Constraints Imposed by These Characteristics on Multi-Turn Conversations and Prompts

The highly structured experimental reports and numerical results in lead compound screening quality documents necessitate precise understanding of field meanings and numerical ranges in multi-turn conversations. For example, querying IC50 values requires the system to recognize units and perform numerical comparisons. High document update frequency means the knowledge base must support efficient incremental updates and version management to ensure conversations are based on the latest data. Additionally, common compound structure images in documents require the system to handle multimodal information to aid text comprehension. Users may frequently trace compound screening history and performance under different experimental conditions in multi-turn conversations. This demands robust context management and information traceability, requiring prompts to guide the model to focus on key information and avoid irrelevant distractions.

Configuration Guidelines

Configuration Item	Suggested Value	Rationale
`maxContext`	`8` rounds	Lead compound screening often involves multiple follow-up questions and condition refinements. Eight rounds of context cover common conversation scenarios.
`Chunk size`	`500` characters	Experimental report paragraphs are moderately sized. 500 characters maintain semantic integrity and prevent truncation of critical information.
`Recall count`	`7` items	This ensures highly relevant segments are recalled while controlling the number of tokens input to the model, balancing efficiency and accuracy.
`Similarity threshold`	`0.78`	Lead compound screening documents are highly specialized. Increasing the threshold filters out low-relevance noise.
`Rerank result count`	`3` items	After initial retrieval, selecting the 3 most relevant items further improves answer quality and precision.
`Prompt Template`	Includes `化合物ID`, `活性值范围`, `实验条件` placeholders	This guides the model to focus on core elements of lead compound screening, ensuring targeted and professional answers.

Common Pitfalls

Conversation results do not mention critical activity values or units: This often occurs because the prompt template does not explicitly require outputting specific fields and their units, or because document segmentation separates values from units.
When querying compound screening history, the system fails to provide a complete experimental sequence: The knowledge base index does not adequately consider timestamps or version information in documents, preventing information organization by time.
After uploading large experimental report files, the system remains unresponsive for an extended period or reports UPLOAD_FILE_MAX_SIZE errors: This indicates that the file upload configuration exceeds default limits, requiring adjustment of the UPLOAD_FILE_MAX_SIZE parameter.

Validation Steps

Submit a query containing a specific compound ID and activity value range. Check if the response accurately includes relevant compound information and corresponding IC50 values.
Simulate a user asking follow-up questions about a compound's performance under different experimental conditions. Confirm the system maintains context in multi-turn conversations and provides coherent, accurate traceability information.
Upload a typical lead compound screening report (PDF format). Check if the system processes it within a reasonable time and supports subsequent queries. Observe logs for any file processing-related exceptions.

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.