Data Characteristics for This Category
Rehabilitation equipment data comes from various sources. These include product manuals, technical specification sheets, user guides, clinical reports, and regulatory certificates compliant with medical device regulations. Data updates are infrequent, typically occurring with product model iterations or regulatory changes. Annual or quarterly updates are common. Document structures tend to be standardized. For example, medical device registration certificates usually contain fixed fields like product name, model, intended use, structural components, and accessories. Technical specification sheets detail dimensions, weight, power, operating modes, and safety levels. Units strictly follow international standards (e.g., millimeters, kilograms, watts, volts). Some data appears in charts, such as performance curves or operation flow diagrams.
Constraints Imposed by These Characteristics on Workflow Orchestration
Infrequent data updates for rehabilitation equipment mean that data extraction and knowledge base updates do not require frequent full synchronization. The focus can be on incremental updates or periodic manual review. Standardized document structures facilitate automated parsing within workflows. For instance, pre-set rules can extract specific fields from registration certificates, reducing manual intervention. However, some performance data exists in chart form. This requires workflows to have image recognition and data extraction capabilities, or manual annotation during data preprocessing. Strict unit specifications necessitate unit validation and conversion for extracted values within the workflow to prevent misinterpretations due to inconsistent units. Furthermore, medical device compliance requirements mean that workflows must include dedicated review nodes when handling queries involving regulations and safety, ensuring the accuracy and authority of the output information.
Configuration Guidelines
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
maxTokens | 2048 | Handles medium to long documents like rehabilitation equipment product manuals, ensuring context completeness. |
Recall count (Recall Count) | Top 5 entries (Top 5) | Ensures the retrieval of the most relevant key information to user queries, reducing irrelevant interference. |
Similarity threshold (Similarity Threshold) | 0.75 | The medical device field demands high information accuracy. Increasing the threshold filters for more precise matches. |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds (300 seconds) | Rehabilitation equipment manuals may contain many images and complex layouts, requiring sufficient parsing time. |
Chunk size (Chunk Length) | 500 characters (500 characters) | Balances chunk granularity and semantic completeness, facilitating RAG model understanding. |
Rerank result count (Rerank Return Count) | 3 entries (3 items) | Further optimizes ranking based on high-similarity recall, improving user experience. |
Three Common Mistakes
- During workflow execution, an external API returns a
401 Unauthorizederror. A common reason is that thetokenpassed to the external API was not correctly obtained or has expired, leading to authentication failure. - A user repeatedly asks questions already answered by the first node in a conversation, and subsequent nodes fail to activate. This typically occurs because the conditional branching logic of the workflow is not rigorous enough, preventing the conversation flow from correctly transitioning to subsequent processing nodes.
- When reading data from an uploaded Excel file, some field content is empty. This can be because the file parser failed to correctly recognize merged cells or specific data formats in Excel, resulting in incomplete data extraction.
How to Confirm Correct Configuration
- Simulate user queries to observe if the workflow accurately identifies key information such as product models and technical parameters. Compare the extracted information with the original documents to confirm accuracy.
- Check workflow logs to confirm that the status code for each node is
200 OKorSuccess. Verify that key variable values (e.g.,token,product_id) are correctly passed. - For workflows involving external API calls, verify that the returned data structure and content meet expectations, especially ensuring units and numerical values align with rehabilitation equipment technical standards.
- Test multiple queries of varying complexity to validate the workflow's performance in handling multi-turn conversations and conditional branching, ensuring the conversation flow proceeds as expected.
Note: The values provided are common starting points. Measure performance 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.