Data Characteristics for This Category
Stability study data primarily originates from reports detailing physical, chemical, and biological property tests of drugs or preparations under specific storage conditions at various time points. These reports are typically generated automatically by laboratory analysis instruments or manually recorded. They exist in PDF, Excel, or Word document formats. Data update frequency depends on the study design, occurring weekly, monthly, or quarterly, and spanning several months to years. Document structures are relatively fixed, including fields such as batch number, sample number, storage conditions (temperature, humidity, light), test items (e.g., assay, dissolution, pH value, microbial limits), test results, and test dates. Result units are diverse, such as percentage content (%), dissolution (%), pH value, colony-forming units (CFU/g or CFU/mL). Multiple test items may share a single time point.
Constraints Imposed by These Characteristics on "Deployment and Upgrade"
The diversity of stability study data sources requires the deployment to support parsing multiple document formats. This particularly applies to handling mixed tabular data and unstructured text. The periodic update feature necessitates incremental update and version management capabilities to avoid re-importing historical data and to trace document changes. Fixed field structures and diverse units within documents demand high precision for data extraction and knowledge graph construction. Deployment must configure accurate entity recognition rules and unit conversion logic. Long-term study data can be voluminous, potentially containing thousands or tens of thousands of documents. This constrains system requirements for storage space and retrieval efficiency, requiring distributed storage and index optimization strategies during upgrades. Additionally, the ability to handle sensitive data, such as isolating stability study data from different batches or projects, is a critical security and compliance requirement during deployment.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Stability study reports often contain numerous charts and raw data, leading to large individual files. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing complex PDFs or large Excel files can be time-consuming; this prevents timeout interruptions. |
Chunk size | 800–1200 characters | Ensures each segment contains sufficient context while avoiding excessive length that could lead to redundancy or reduced retrieval efficiency. |
Recall count | Top 10 entries | Stability study queries often require synthesizing information from multiple reports; increasing recall aids comprehensiveness. |
Similarity threshold | 0.75–0.85 | Ensures the precision of recalled content, filtering out irrelevant study batches or test items. |
maxContext | 32000 tokens | Stability study analysis may require a longer context window for AI to understand complex trends and associations. |
Common Mistakes
- After a knowledge base update, query results for certain batches are empty or incomplete. This manifests as missing key numerical values in query results. The cause is insufficient document parsing configuration failing to identify all key fields and units in tables or text, leading to incomplete data extraction.
- After private deployment, login fails with "username or password error." This manifests as an inability to access the system from the login screen. The cause is typically incorrect setting of environment variables like
ONEAPI_DEFAULT_PASSWORD, or the default administrator account not being initialized in the database. - After a system upgrade, queries on stability reports imported in older versions show a significant decrease in relevance. This manifests as returned document snippets having low relevance to the question. The cause may be compatibility issues with models or vector libraries during the upgrade, leading to invalid old vector indexes or semantic understanding deviations.
How to Verify Correct Configuration
- Upload stability study reports in various formats (PDF, Excel, Word). Verify that the knowledge base correctly extracts key fields such as batch number, sample number, storage conditions, test items, test results, and dates.
- Query using stability report data from different time points and batches. Cross-check that the returned results accurately reflect the report content and correctly identify and display unit information for numerical values.
- Simulate multiple concurrent document import and update operations. Observe system resource utilization (CPU, memory, disk I/O) to ensure stable system operation under high load, without timeouts or errors.
Note: 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.