Data Characteristics
Documentation and Standard Operating Procedures (SOPs) for imaging equipment (such as CT, MRI, X-ray machines) primarily originate from manufacturer operation manuals, maintenance guides, and internal hospital guidelines. These documents have a low update frequency, typically released with new equipment models or regulatory changes, which can range from months to years. Documents are often in PDF format, containing numerous diagrams, flowcharts, and specialized terminology. Fields frequently include equipment model, serial number, calibration parameters, error codes, operating steps, and safety protection levels. Units cover voltage (V), current (A), dose (mSv), time (s), and temperature (℃), with high precision requirements.
Constraints Imposed by These Characteristics on "Deployment and Upgrade"
The low update frequency of imaging equipment documentation means less pressure for daily synchronization after initial knowledge base import. However, version management requires careful attention. The abundance of diagrams and flowcharts in documents demands advanced parsing capabilities. Ensure image content is correctly recognized or described to prevent critical information loss. Specialized terminology and precise numerical units require the model to have a strong understanding of domain-specific vocabulary, preventing misinterpretations that could lead to incorrect guidance. During deployment, allocate sufficient storage space for large PDF files and configure appropriate parsing timeouts for complex documents. For upgrades, database compatibility and data migration strategies are crucial to ensure historical Q&A records and knowledge base content transition completely and without loss to the new version.
Configuration Guidelines
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Large PDF documents may contain high-resolution images, requiring large file uploads. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Complex document parsing takes longer; prevents parsing timeouts. |
maxContext | 8000 tokens | Policy documents often have closely related contexts, requiring a longer context window. |
Chunk size (Segment Length) | 800–1200 characters | Ensures semantic completeness of individual paragraphs, improving recall quality. |
Recall count (Recall Count) | Top 8 entries | Policy Q&A requires multi-faceted information support; increases recall coverage. |
Similarity threshold (Similarity Threshold) | 0.78 | Ensures precision of recalled content, filtering out irrelevant information. |
Three Common Mistakes
- After an upgrade, channel testing shows a
TypeError: Cannot read properties of undefined (r)error. This usually indicates frontend resources are not fully updated or the cache is not cleared. - Knowledge base data is lost or incomplete after a Docker deployment upgrade. This often occurs due to incorrect volume mounting, causing old data not to be retained when containers are rebuilt.
- When parsing PDF documents with many flowcharts, some image content is not extracted, leading to missing critical steps in Q&A results. This happens because the document parser's OCR capability for image content is insufficient or not enabled.
How to Confirm Correct Configuration
- Upload a complex imaging equipment operation manual containing diagrams and specialized terminology. Check if the segmented content in the knowledge base is complete and semantically correct, especially text descriptions near diagrams.
- For a document containing equipment error codes, ask about the processing steps for a specific error code. Verify the answer is accurate and the steps are clear.
- Simulate a version upgrade. Before and after the upgrade, query key information from the same policy document. Confirm data is not lost and query results are consistent after the upgrade.
- Test uploading and parsing PDF files of different sizes (e.g., 100MB and 400MB). Confirm that
PARSE_FILE_TIMEOUT_SECONDSandUPLOAD_FILE_MAX_SIZEconfigurations are effective and files are processed successfully.
The values provided are common starting points and should be measured against your 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.