What the data for this category looks like
Medical device investment research data sources include public medical device registration and filing information, official manufacturer technical white papers, multi-center clinical study reports, and medical insurance payment-related policy documents. Data updates proceed irregularly alongside regulatory policy adjustments, new device approvals, and existing product changes. Clinical study data is supplemented and improved along follow-up cycles.
Documents include two categories: long-text clinical reports and structured registration and filing forms. Fields cover device model, registration certificate validity period, clinical follow-up duration, imaging parameters, and more. Units include millimeters, kilovolts, number of cases, follow-up months, and more.
What constraints do these characteristics impose on deployment and upgrade
Medical device investment research data includes two categories: long-text clinical reports and structured registration and filing forms, and has multi-dimensional unit fields. Therefore, the deployment link must support large file parsing and multi-field vector index configuration.
Data updates are triggered irregularly alongside regulatory policies and new device approvals. The upgrade link must support incremental synchronization to reduce resource consumption from full reprocessing.
Medical data involves compliance requirements. Data encrypted storage configuration must be enabled during deployment, and a log audit interface must be reserved for regulatory traceability. Additionally, structured fields have diverse units, so field standardization conversion rules must be configured during deployment to avoid unit mismatches during retrieval.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600-900 seconds | Medical device clinical reports are mostly long texts, requiring sufficient time for text splitting and structured extraction |
UPLOAD_FILE_MAX_SIZE | 2000-5000 MB | Large multi-center clinical study report files have large sizes, so upload limits must be relaxed |
RECALL_TOP_N | Top 8-12 entries | Medical device investment research requires balancing multi-dimensional parameters and clinical data, increasing the number of recalled entries to cover more relevant information |
FIELD_EXTRACT_RULE | Configure by classification: registration certificates, clinical reports, policy documents | Data field structures for medical devices from different sources vary significantly, requiring targeted extraction template configuration |
SYNC_INCREMENTAL_ENABLE | Enabled | Medical device data updates have no fixed cycle, and incremental synchronization reduces resource usage from repeated processing |
VECTOR_INDEX_DIM | 1536-2048 | Medical device data includes multi-unit fields and long texts, requiring higher-dimensional vectors to adapt to complex semantic matching |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: After uploading a large clinical report file via API, the agent backend process becomes unresponsive and freezes. Cause: The default value of
PARSE_FILE_TIMEOUT_SECONDSin version 4.9.7 is too low, causing timeout blocking before long-text parsing completes. - Phenomenon: After deploying with docker-compose, the knowledge base and application workflow configuration items become blank after several hours, but the API interface works normally. Cause: No persistent storage volume is mounted, and configuration files are lost after container restart, causing interface configuration data to be cleared.
- Phenomenon: Running the docker start command on a server without a GPU returns an
OCI runtime create failederror. Cause: GPU-related container runtime parameters are not disabled, and the default enabled CUDA image cannot initialize properly in a GPU-free environment.
How to confirm the configuration is correct
- Upload a single medical device clinical report over 1000 MB in size, check that the upload progress bar completes and the file parsing status shows success, confirming that upload and parsing configurations meet current data requirements.
- Trigger an incremental synchronization task, check that only newly added registration and filing information is synchronized to the knowledge base, with no full duplicate data appearing, confirming that the incremental synchronization configuration is effective.
- Call the knowledge base retrieval interface, enter a query term containing device model and clinical parameters, check that the returned results include matching content across multiple dimensional fields, confirming that field extraction and vector index configurations are effective.
- Restart the docker container, check that the original knowledge base configuration and application workflow are not lost, confirming that the persistent storage volume is mounted correctly.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.