Data Characteristics in This Category
Rehabilitation equipment regulations and Standard Operating Procedure (SOP) documents primarily source data from internal quality management system files of medical device manufacturers, regulatory guidelines published by national drug administration agencies, and technical specifications from industry associations. These documents have a relatively low update frequency. Updates typically occur with regulatory revisions or product iterations, which can take months or even years. Document structures are often hierarchical, with distinct sections. They contain extensive specialized terminology, technical parameters, operating procedures, and risk assessments. Fields related to equipment performance indicators often include units, such as mm (millimeters), kg (kilograms), kPa (kilopascals), or rpm (revolutions per minute). They may also include specific model numbers, serial numbers, or batch information.
Constraints Imposed by These Characteristics on "Multi-Turn Conversations and Prompts"
The low update frequency of rehabilitation equipment regulatory documents means full data synchronization is not required frequently when building the knowledge base. However, initial import accuracy and completeness are critical. The presence of specialized terminology and parameters in documents requires the multi-turn conversation system to accurately identify and link to corresponding definitions or operating instructions when understanding user queries. This prevents misunderstandings due to ambiguous terms. The hierarchical document structure prompts the system to maintain logical coherence in its responses and to pinpoint specific sections. Fields with units require the model to correctly match and convert units when processing numerical queries, ensuring answer precision.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
maxContext | 8 | Rehabilitation equipment regulatory documents have long logical chains. A longer conversation history is needed to support complex problem tracing. |
Chunk size (Segment Length) | 800–1200 characters (characters) | Regulatory and SOP documents are information-dense. Longer segments help capture complete semantics and reduce information fragmentation. |
Recall count (Recall Count) | Top 5 entries (top 5) | Ensures more potentially relevant regulatory clauses or SOP steps are recalled for complex queries. |
Similarity threshold (Similarity Threshold) | 0.75–0.85 | Precise matching of domain-specific terms and the rigor of regulatory provisions require a higher similarity threshold to filter irrelevant content. |
Rerank result count (Rerank Return Count) | 3 | After reranking, the 3 most relevant pieces of information are selected, improving user efficiency in obtaining key information. |
Prompt Template (Prompt Template) | Includes "as a rehabilitation equipment regulation expert," "based on the provided regulatory documents," etc. | Reinforces the model's role as an expert in rehabilitation equipment, guiding responses to focus on the normative aspects of regulations and SOPs. |
Three Common Mistakes
- Model answer quality significantly degrades after multi-turn conversations, but the same question is answered accurately in a new conversation. This usually results from improper context management, where early irrelevant information pollutes the focus of subsequent dialogue.
- The system fails to recall or incorrectly matches when users query equipment models or serial numbers. This may be due to an overly coarse knowledge base segmentation strategy, which does not treat model numbers and other key identifiers as independently retrievable entities.
- The system responds inaccurately to queries with numerical values and units (e.g., "pressure range 500 kPa"). This occurs when the prompt does not explicitly instruct the model to focus on and verify unit consistency.
How to Confirm Proper Configuration
- Conduct multi-turn simulated conversations. Focus on testing complex questions spanning multiple chapters and paragraphs to verify the coherence and accuracy of the dialogue context.
- Query specific professional terms, models, and parameters related to rehabilitation equipment. Check if the recall results precisely match the original text and verify if numerical values and units in the answers are correct.
- Test whether the system can effectively filter interference and remain focused on core regulatory and SOP issues after introducing a small amount of irrelevant information into the conversation. Confirm if the
maxContextparameter functions as expected.
The values provided are common starting points. Measure them against your own samples.
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.