Data Characteristics
Surgical robot clinical trial data originates from multi-center clinical study reports, investigator brochures, protocol amendment records, ethics committee approvals, subject informed consent forms, adverse event reports, and various device operation logs and patient follow-up records. This data typically exists as PDF documents, Word documents, CSV files, and database records. Update frequency varies based on the clinical trial stage and progress, ranging from several times per week (e.g., adverse event reports) to quarterly (e.g., phase reports). Document structure is highly standardized, adhering to GCP (Good Clinical Practice) and relevant medical device regulatory requirements. Documents include clear section headings, tables, and figures. Fields include patient demographic information, diagnostic results, surgical procedure parameters (e.g., operation time, incision precision, complication types), postoperative recovery indicators, device operating status codes, and maintenance records. Units strictly follow medical and engineering conventions, such as millimeters, seconds, joules, volts, pascals, and international units.
Constraints Imposed by Data Characteristics on Deployment and Upgrade
The highly structured and standardized nature of surgical robot clinical trial data requires the knowledge base to accurately parse document structures and identify key fields during construction. The uncertain update frequency necessitates a deployment solution that supports flexible incremental indexing and version management, avoiding the performance overhead of full re-indexing. The large volume of PDF and Word documents demands robust file parsing capabilities, including handling complex tables, charts, and embedded objects. High-frequency, fine-grained data in device operation logs means the knowledge base must efficiently process large numbers of short text fragments and correlate data points from different sources. Strict unit specifications require accurate identification and use of correct units during querying and answer generation, preventing misinterpretation or errors. Additionally, the sensitive nature of clinical trial data imposes stringent requirements on deployment environment security, data isolation, and access control.
Configuration Guidelines
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 500 MB | Clinical trial reports often contain numerous charts and images, resulting in large file sizes. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Parsing large PDF documents can be time-consuming; sufficient processing time is required. |
maxContext | 3000 characters | Clinical trial protocols and reports are dense; a longer context length is needed to maintain semantic integrity. |
Chunk size | 800–1200 characters | Balances semantic integrity and retrieval efficiency, avoiding excessive fragmentation or information redundancy. |
Recall count | Top 8 entries | Ensures coverage of multiple relevant data points and report sections, enhancing information comprehensiveness. |
Similarity threshold | Calibrate by actual measurement | For clinical terminology and specialized vocabulary, actual testing is needed to balance recall and accuracy. |
Common Pitfalls
- Issue: After an upgrade, some clinical trial report content is not retrievable, or retrieval results do not match expectations. Reason: Older parsers might have incomplete handling of specific PDF table formats or embedded objects. If re-indexing is not performed during an upgrade, old indexed data might be incompatible with new parsing logic.
- Issue: After configuring an AI proxy in
docker-compose.yml, system logs show connection timeouts or authentication failures. Reason: Environment variables such asAI_PROXY_URLorAI_PROXY_API_KEYare set incorrectly, or firewall rules on the proxy server do not allow access from the FastGPT container. - Issue: When integrating into an external webpage, speech recognition functionality shows
permission denied. Reason: Browser security policies (e.g., cross-origin restrictions or insecure contexts) block microphone access, or theiframesandbox attributes of the embedded page restrict media device permissions.
Verification Steps
- Upload a clinical trial report PDF containing complex tables and figures. Confirm that all text content, including table data, is correctly indexed and retrievable.
- Conduct multi-turn dialogue tests using query terms that include specialized terminology and abbreviations. Verify that the model accurately understands and extracts relevant information from different reports, providing answers with correct units.
- Check system logs for any warnings related to file parsing failures, index construction errors, or external service connection timeouts, specifically focusing on logs related to
PARSE_FILE_TIMEOUT_SECONDS.
Note: The values provided above are common starting points. Measure against your own samples for optimal performance.
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.