Data Characteristics for This Category
Deviation and Corrective and Preventive Action (CAPA) documents originate from internal enterprise quality management systems. Quality, production, or R&D departments generate these documents during daily operations. Document updates are frequent, especially after production batch changes, process optimizations, or audit findings. Document structures typically include fields such as deviation description, root cause analysis, corrective actions, preventive actions, responsible person, completion deadline, and effectiveness verification. The data format is primarily structured text and may include attachments like images, charts, or test reports. Field content involves specific production batch numbers, equipment IDs, material codes, inspection results, and quantitative indicators. Units vary, such as ppm, mg/L, ℃, and hours.
Constraints Imposed by These Characteristics on "Deployment and Upgrade"
The frequent updates and structured nature of Deviation and CAPA documents impose specific requirements on deployment and upgrade processes. First, frequent document updates necessitate an efficient incremental update mechanism to avoid full re-indexing each time, ensuring data timeliness. Second, documents contain numerous key fields and quantitative indicators. The system must support precise field extraction and numerical data identification for subsequent retrieval and analysis based on specific conditions. During deployment, pre-configuration of various document template parsing rules is necessary, along with consideration for field type and unit compatibility. During upgrades, older data structures might not be fully compatible with newer versions. A comprehensive data migration plan is required to ensure the integrity and availability of historical data. For example, a field that was free text in an older version might be an enumerated value in a newer version.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 200 MB | Accounts for high-resolution images or large attachments in Deviation and CAPA documents. |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Ensures parsing completion for complex structures or large documents. |
Chunk size (Chunk Size) | 800–1200 characters | Balances semantic completeness and retrieval efficiency for structured text. |
Overlap Length | 150 characters | Ensures contextual continuity and prevents critical information from being split. |
maxContext | 8192 | Ensures sufficient contextual information during retrieval to understand deviation details. |
Similarity threshold (Similarity Threshold) | Calibrate 0.75–0.85 based on actual measurements | Requires testing on actual data to balance recall and accuracy, avoiding interference from irrelevant information. |
Three Common Mistakes
internal server errorwhen importing a plugin: Typically due to incorrect plugin file format or insufficient server resources (memory, disk).- Model vendor icon fails to load after version update: The new version might have adjusted static resource paths or caching mechanisms, preventing the browser from correctly loading icon files.
- Knowledge base disk space usage far exceeds expectations: This can be due to an unreasonable document chunking strategy or not clearing historical version data, leading to the storage of a large number of redundant chunks and embedding vectors.
How to Confirm Correct Configuration
- Upload a deviation document containing images and tables. Verify that it parses correctly and extracts key fields, such as
Deviation IDandResponsible Person. - Use quantitative indicators from the document (e.g.,
批次合格率 < 98%(Batch pass rate < 98%)) for retrieval. Verify that relevant CAPA documents are accurately recalled. - Simulate a system upgrade. Verify that historical knowledge base data seamlessly migrates to the new version and supports normal question-answering.
The values given 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.