What the Data for This Category Looks Like
Marketing-related data for medical devices serving financial, insurance, or wealth management scenarios primarily comes from internal enterprise product registration certificates, clinical validation reports, official product manuals, compliance filing materials, and reviewed clinical case documents. Update cycles are tied to product iterations and compliance changes, with no fixed schedule. Data updates trigger when new device models receive approval or registration certificates are modified. Document structures typically include structured parameter tables, long-form compliance explanations, and single-page product introductions. Fields cover product model, registration certificate number, technical parameters with specific units such as dpi, seconds per sheet, applicable departments, and contraindicated populations. All content must comply with standard terminology from the national medical device classification catalog.
Constraints on Multi-turn Dialogue and Prompt Engineering
Medical device marketing data has many structured parameters, strict compliance requirements, and no fixed update cycle. These factors impose multiple constraints on multi-turn dialogue and prompt engineering configurations. First, multi-turn dialogue must accurately match technical parameters with specific units such as product models and registration certificate numbers, to avoid unit confusion or parameter misalignment. Second, long-form compliance explanations must be split during retrieval to prevent context window overflow and truncation of critical content. Third, compliance verification logic must be added to prompt templates, to ensure generated content stays within filing scope. Knowledge bases must also be updated regularly to match the latest compliance information. Finally, for applicable scenarios across different departments, parameter calling logic must be differentiated in multi-turn dialogue, to avoid cross-scenario misuse.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Medical device marketing documents often contain long compliance texts and multiple sets of technical parameters. This range can fully accommodate multi-turn dialogue context and retrieved knowledge base content |
recallTopK | Top 6–8 entries | Medical device data has many parameter fields. Sufficient structured data must be retrieved to support multi-turn dialogue, while avoiding interference from redundant information |
similarityThreshold | 0.75–0.85 | Precise matching of key fields such as product models and registration certificate numbers is required, to avoid retrieval of irrelevant documents with low similarity |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Medical device clinical reports and registration certificate files are often long documents. Sufficient time is needed to complete structured parsing |
promptTemplate | Fixed compliance verification statements added; parameters called grouped by product model | Medical device marketing content must strictly comply with regulations. Multi-turn dialogue must split parameters by different models to avoid confusion |
CORS_ALLOW_ORIGINS | Fill in the corresponding frontend domain name for private deployment scenarios | Frontend calls to the dialogue interface must comply with browser cross-domain security specifications to avoid cross-domain errors |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: An HTTP request node for web search and AI dialogue is configured in the workflow, but the node is not triggered during dialogue execution. Built-in AI capabilities are called directly. Cause: The HTTP request node is not connected to the pre-trigger logic of the dialogue chain, or the node's trigger conditions and parameter transfer rules are not configured.
- Symptom: Frontend calls to the dialogue interface return
403 Forbiddenor CORS-related errors. Cause: TheCORS_ALLOW_ORIGINSparameter is not configured, or the filled domain name does not match the actual frontend access domain name, violating browser cross-domain security policies. - Symptom: Token consumption per dialogue cannot be accurately counted after private deployment. Cause: Token statistics log collection rules are not configured, or the token counting function during dialogue is not enabled.
How to Verify Successful Configuration
- Trigger a query that includes product models and technical parameters, and check whether the returned results contain accurate parameters and compliance statements from the knowledge base.
- View workflow execution logs to confirm whether the HTTP request node executes normally after dialogue is triggered and returns corresponding data.
- Use frontend development tools to initiate a dialogue interface request, and confirm that no CORS-related errors occur.
- Simulate a multi-turn dialogue parameter follow-up scenario, and confirm that the system can accurately associate product models and corresponding parameters across different turns.
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.