Multi-turn Dialogue and Prompt Engineering for Medical

What the data for this category looks like

Medical device research report data adapted for financial, insurance, and wealth management scenarios is primarily sourced from the National Medical Products Administration Medical Device Registration and Filing Public Platform, third-party medical industry research report databases, official product specifications and listing announcements disclosed by medical device manufacturers, and clinical research literature databases. Data update frequency varies by source type: regulatory filing information is updated in real time with registration changes, industry research reports are updated quarterly, and clinical literature is synchronized in real time as academic papers are published. Each individual document includes fields such as product name, registration certificate number, manufacturing enterprise, model and specification, clinical application scope, technical principle, main performance indicators, filing status, and update date. Performance indicator fields have clear units, such as scanning resolution dpi and imaging speed seconds per frame, to meet analysis needs for medical device compliance and market value in financial, insurance, and wealth management scenarios.

Constraints on multi-turn dialogue and prompt engineering

The characteristics of medical device research report data adapted for financial, insurance, and wealth management scenarios require specific configurations for multi-turn dialogue prompts. Prompts must unify field extraction rules across documents from different sources to avoid confusion between filing information and manufacturer-disclosed content, supporting compliance review requirements. Differences in update frequency require configuring context retention policies to distinguish old historical retrieval data from the latest updated content in current requests, ensuring returned information matches the timeliness needs of investment research or underwriting. Performance indicator fields with clear units require prompts to restrict the large model to only use retrieved numerical values with units when answering, preventing fabricated parameters that could impact investment or underwriting decisions. Unique identifier fields such as registration certificate numbers require prompts to explicitly prohibit outputting unnecessary internal identifiers, while supporting targeted retrieval via identifiers for precise, compliant business scenarios. Enumerated attributes of clinical application scope can assist multi-turn dialogue in gradually narrowing retrieval dimensions and improving matching accuracy.

Configuration Settings

Configuration Item	Recommended Setting	Rationale
`maxContext`	`8000–12000 tokens`	Medical device research report documents have relatively long content. Multi-turn dialogue must retain multiple retrieval results and user historical questions to avoid information truncation caused by context overflow
`recall_top_k`	`Top 8–12 results`	Medical device professional terminology has high semantic similarity. Sufficient recall volume is needed to cover relevant content for different models and performance parameters, avoiding missed key information
`similarity_threshold`	`0.72–0.80`	A value that is too low will recall irrelevant medical device category content. A value that is too high will filter relevant retrieval results for detailed model variants, adapting to semantic matching needs in professional fields
`stream_response`	`Enabled`	Medical device research report content has significant length. Streaming output reduces user wait time perception and improves interaction fluency
`output_reference_id`	`Disabled`	Reference identifiers for medical device research reports are mostly registration certificate numbers or internal document IDs. Non-business-related identifiers do not need to be displayed in dialogue, to avoid interfering with user reading
`rerank_top_n`	`Top 4–6 results`	Reranking filters low-correlation retrieval results, retaining professional content that best fits user questions. This adapts to the professional retrieval scenario of medical device research reports

The parameter values provided on this page are conventional recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to conduct actual testing on your own samples before finalizing the settings.

Three Common Misconfigurations

Phenomenon: After adjusting the reference_limit parameter to above 2000, the large model's generated response does not associate with any retrieved reference content. Cause: The prompt does not explicitly require the large model to bind retrieved reference identifiers, or the reference association logic after reranking does not take effect correctly, causing the model to fail to match the corresponding source.
Phenomenon: The dialogue interface does not display medical device imaging sample images included in the retrieval results. Cause: The knowledge base image parsing configuration is not enabled, or the access permissions for image resources are not configured, causing images to fail to load into the dialogue interaction interface.
Phenomenon: The retrieved response includes internal paragraph ID fields from the knowledge base. Cause: The output_reference_id configuration item is not disabled, causing the system to automatically output non-business-related internal identifiers that interfere with user reading.

How to Verify Correct Configuration

Initiate a query that includes multiple medical device models and performance parameters. Check if the dialogue interface fully retains historical queries and multi-turn retrieval results without context truncation.
Adjust the similarity_threshold to different ranges, compare the correlation differences of retrieval results, and confirm that the current value adapts to the semantic matching needs of medical device professional terminology.
Enable the stream_response configuration, initiate a query with long content, and verify that the response is output incrementally in streaming segments, without overall lag or one-time return.
Initiate a targeted retrieval that includes a medical device registration certificate number, and confirm that the final response does not include internal paragraph ID identifiers from the knowledge base.

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.