Data Characteristics
Quality documents during the lead optimization phase include experiment records, analysis reports, batch production records, and stability study reports. These documents are typically in PDF, Word, or structured data formats (e.g., CSV, JSON). Data sources are diverse, covering Laboratory Information Management Systems (LIMS), Electronic Lab Notebooks (ELN), exported files from instrument analysis software, and manually entered tables. Document update frequency is high, especially for experiment records and analysis reports, with new versions potentially generated daily or even hourly. Document structure is complex, containing numerous specialized terms, chemical structures, reaction conditions, detection indicators, and units (e.g., ug/mL, nM, °C, min). Field names may not be uniform; for example, "Purity" might appear as Purity, Assay, or Purity (%).
Constraints Imposed by These Characteristics on Tool Calling and Plugins
The complex structure and high update frequency of lead optimization quality documents impose specific requirements on tool calling and plugins. First, chemical structures and specialized terms in documents require the model to recognize and parse this domain-specific knowledge. Without this capability, tool calls might fail due to incorrect interpretation of query intent. Second, diverse document formats require plugins to process different file types and extract key information. Examples include extracting tabular data from PDF reports or identifying specific paragraphs from Word documents. High update frequency means the knowledge base needs frequent synchronization with the latest data; otherwise, tool calls might retrieve outdated information. Inconsistent field names require semantic parsing or a preprocessing layer before tool calling to perform synonym mapping, ensuring queries accurately match actual fields in the documents. The specificity of units, such as nM or ug/mL, requires tools to correctly handle unit conversions during numerical comparisons or calculations.
Configuration Guidelines
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 4000–8000 tokens | Accommodates complex document structures and specialized terms, ensuring context completeness. |
Chunk size (Segment Length) | 800–1200 characters | Balances semantic completeness with retrieval efficiency, preventing information loss in long paragraphs. |
Recall count (Retrieval Count) | 10–15 items | Increases coverage of relevant document snippets, improving tool call success rates. |
Similarity threshold (Similarity Threshold) | 0.75–0.82 | Balances retrieval precision and generalization ability, preventing false positives or negatives. |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Handles parsing time for large analysis reports or multi-chart PDFs. |
tool_retries | 3 times | Addresses transient external system failures or network fluctuations, enhancing tool call resilience. |
Common Pitfalls
- Tool call returns an empty result or "no relevant information found." This might occur if the knowledge base fails to correctly parse specialized terms or chemical structures in the document, leading to search matching failures.
- Tool calling module does not execute as expected, or executes the wrong tool. This might occur if the model misinterprets user query intent, failing to accurately map it to predefined tool functions, especially when queries contain domain-specific ambiguous descriptions.
- Tool call returns outdated data. This might occur if the associated knowledge base is not updated in time, or if the file parser fails to recognize and process document version information, leading to retrieval of old experimental data.
Verification Steps
- Manually simulate user queries for typical scenarios to check if tool calls accurately identify intent and trigger the correct tool.
- Verify if key field values and units in tool call results align with the latest document content, especially in scenarios involving numerical calculations or comparisons.
- Upload new documents with the latest batch data to the knowledge base and immediately test tool calls to confirm that new information is retrieved and utilized promptly.
- Check system logs to confirm that the tool call return status code is
200and that theresponsecontains the expected data structure.
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.