Data Characteristics for This Category
Quality documents from Contract Sales Organizations (CSOs) primarily originate from partner pharmaceutical companies. These documents include product quality standards, manufacturing process specifications, Standard Operating Procedures (SOPs) for inspections, and compliance records related to internal sales and marketing activities. Document update frequency typically aligns with the pharmaceutical product lifecycle management and regulatory changes. Revisions occur during events such as new drug launches, process changes, or regulatory updates. Annual audits are also common update points. Documents are usually formal PDF files, containing extensive tables, charts, and structured text. Fields include batch numbers, expiration dates, storage conditions, and ingredient content. Units such as mg/ml, °C, and %RH are common, requiring high precision.
Constraints Imposed by These Characteristics on Tool Calling and Plugins
The complex structure and high precision requirements of CSO quality documents impose specific constraints on tool calling and plugin configurations. Tables and charts in documents require OCR or specialized PDF parsing plugins for structured extraction. Traditional text segmentation can lead to information loss or context fragmentation. High update frequency necessitates efficient synchronization mechanisms for the knowledge base to avoid referencing outdated information. The strictness of fields and units means that after information extraction, external tools may be required for unit conversion or value validation to ensure answer accuracy. For example, when querying drug storage temperature ranges, the system must identify temperature units, standardize them with the user's query units, or call an external database for comparison.
Configuration Settings
| Configuration Item | Recommended Value | Rationale for This Value |
|---|---|---|
maxContext | 3000 tokens | Accommodates the context length of complex documents, ensuring completeness. |
Chunk size (Segment Length) | 500 characters (characters) | Balances semantic integrity with recall efficiency, preventing long paragraphs from diluting key information. |
Recall count (Number of Recall Items) | Top 8 entries (top 8 items) | Covers more relevant snippets, addressing multi-dimensional query needs. |
Similarity threshold (Similarity Threshold) | 0.75 | Improves recall precision and reduces interference from irrelevant information. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds (seconds) | Accommodates parsing time for large PDF documents, preventing timeout errors. |
plugin_timeout | 120 seconds (seconds) | Ensures external tool calls have sufficient time to complete, such as unit conversion services. |
Three Common Mistakes
- Errors starting with
software.amazon.awssdk.services.bedrockruntime.model.when calling a Claude model typically result from mismatched model interface parameters or permission configuration issues. - An
aiPointsNotEnoughAPI response indicates insufficient AI points in the account to support the current model call or plugin execution. - Multimodal system plugins fail to correctly recognize tabular data in documents, leading to missing key information. This occurs due to the lack of parser configurations optimized for table structures.
How to Verify Correct Configuration
- Upload an SOP document containing complex tables and charts. Verify that the parsed segments in the knowledge base fully retain the tabular structure information.
- Simulate a query involving unit conversion or numerical range. Observe whether the system correctly calls external tools and provides accurate answers.
- Perform API call tests. Check if external plugins complete complex requests as expected within the
plugin_timeoutsetting, without timeout errors. - Cross-reference the latest version of quality documents in the knowledge base. Confirm that the system promptly synchronizes updates and provides the most current information.
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.