What the data for this category looks like
Medical device intelligent due diligence data mainly comes from the National Medical Products Administration Medical Device Registration and Filing Database, public registration declaration materials from manufacturing enterprises, clinical verification reports, financial compliance documents required for financial due diligence, and publicly available industry compliance documents. Data updates synchronize in real time with newly approved products. Existing products are updated quarterly alongside regulatory announcements. A single due diligence document includes fields such as registration certificate number, full manufacturing enterprise name, model and specification, scope of application, performance parameters, approval date, validity period, and financial compliance indicators. Performance parameters often use exclusive units such as mm, Pa, or kV. The length of a single core document typically falls within the several-thousand-character range.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Professional fields and exclusive units in medical device due diligence data require repeated calibration of parameter units during multi-turn dialogue. This prevents mismatches between performance indicators and units that could compromise financial due diligence compliance. Real-time updated regulatory data requires prompts to link to the latest filing fields. During multi-round questioning, the system must explicitly call the currently valid data source to ensure due diligence results align with latest regulatory requirements. The long document structure requires dialogue context to filter non-core fields, avoiding redundant information that could interfere with core financial due diligence judgments. The rigor of professional terminology requires prompts to preset exclusive terminology mappings, preventing compliance risks from simplified terminology.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Medical device due diligence documents have relatively large single-document lengths. Multi-turn dialogue must retain context for multiple rounds of questioning while staying within model context limits |
recall_top_k | Top 6–8 results | Medical device data has many specialized fields. Too many recalled results introduce redundant information, while too few omit key compliance fields required for financial due diligence |
similarity_threshold | 0.75–0.85 | Professional terminology matching requires high precision, to avoid recalling irrelevant medical device models or non-compliance-related data |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Parsing batch medical device registration certificate documents or long clinical reports takes significant time. Sufficient parsing time must be reserved |
prompt_template | Preset exclusive medical device terminology mappings, explicitly require returned fields to match units | Medical device professional terminology is highly rigorous. Predefining term mappings ensures compliance and accuracy during multi-turn dialogue |
history_save_mode | Store bound to user ID | Aligns with the multi-user scenario of financial due diligence, ensuring different users can only view their own dialogue history |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: After calling the dialogue API to upload medical device due diligence documents, returned results lack core compliance fields. Cause: A reasonable value for the
recall_top_kparameter is not configured, so recalled document fragments fail to cover key information required for financial due diligence. - Phenomenon: After multiple rounds of questioning in multi-turn dialogue, logical confusion occurs due to redundant context. Cause: A reasonable upper limit for the
maxContextparameter is not set, so overly long historical context interferes with current dialogue judgments. - Phenomenon: When configuring a multi-round question-and-answer link in a workflow, only a single question can be asked, and follow-up questioning is not possible. Cause: Persistent storage of dialogue context is not enabled, so the dialogue state resets with each question, making it impossible to carry over information from the previous round of questioning.
How to Verify Correct Configuration
- Upload a single medical device registration certificate document, initiate multi-round questioning, and verify that returned results include preset core fields with accurate unit matching.
- Adjust the similarity threshold parameter, test the number of recall results across different values, and confirm that recall results cover key information without redundancy.
- Create multiple test accounts, initiate a dialogue and save the history, and verify that different users can only view their own dialogue records.
- Upload batch medical device documents, check parsing status, and confirm that no timeout errors occur, and parsing duration meets preset requirements.
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.