Data Characteristics for This Category
Biopharmaceutical complaint ticket data typically originates from patient feedback platforms, internal medical institution systems, drug regulatory reports, and telephone consultation records. Data update frequency varies, ranging from weekly or monthly reports to real-time entry. Ticket document structures are usually semi-structured text. Fields include patient basic information, complaint subject (medication, device, or service), complaint details, incident time, involved medical personnel or institutions, processing status, and initial handling opinions. Field content often involves medical terminology, drug batch numbers, production dates, and expiration dates. Units may include dosage units (mg, ml), time units (days, hours), and batch units.
Constraints Imposed by These Features on "Forms and Interaction"
The semi-structured text nature of complaint tickets requires flexible form design. This design must accommodate diverse complaint content entry and support automatic recognition and standardization of key medical terms. The uncertainty of data updates means the smart customer service needs an efficient incremental knowledge update mechanism. This ensures patients receive the latest information when querying or processing tickets. Fields involving drug batches and production dates demand higher validation logic for forms, requiring precise matching or range validation. The specialized nature of medical terminology dictates that interaction design must provide professional vocabulary explanations or synonym association functions. This improves the accuracy of patient expression and reduces communication barriers.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale for This Approach |
|---|---|---|
chunkOverlapRatio | 0.15 | Ensures contextual continuity when segmenting long texts like complaint details. |
maxContext | 4000 | Covers the complete description and associated information of a typical complaint ticket. |
recallTopK | 8 | Increases the coverage of recalling relevant historical tickets or solutions from the knowledge base. |
similarityThreshold | 0.75 | Balances the relevance and accuracy of recall results, reducing false positives. |
reRankTopK | 3 | Selects the most relevant few tickets or solutions for reference. |
variable_mapping_strategy | auto_extract | Automatically extracts key entities like drug names and batch numbers from complaint text. |
Three Common Mistakes
- After form submission, the system returns "parameter error." This occurs because the
knowledge_base_selectionparameter for custom input fields does not correctly reference the configured knowledge base variable. - The patient's uploaded complaint video file cannot be parsed by the model, displaying "unsupported file format." This happens because the VLM model currently does not support the video encoding format, or the file size exceeds the
UPLOAD_FILE_MAX_SIZElimit. - When calling the API,
streamis set totrue, but the final result only returns partial content. This is because the client fails to correctly process chunked transfer data streams, leading to data truncation.
How to Confirm Correct Configuration
- Submit a simulated complaint ticket containing typical medical terminology. Check if the system correctly identifies and populates relevant fields. Verify if the knowledge base is updated with the latest drug information.
- Submit a reproduction ticket for a known historical complaint via the API interface. Verify if the smart customer service accurately matches and recalls relevant historical processing records. Check the actual effect of
similarityThreshold. - Test complaint texts of varying lengths and complexities. Ensure the form's
maxContextconfiguration completely captures information. Observe the impact ofchunkOverlapRatioon retrieval results. - Upload attachments of different formats and sizes. Check the system's compatibility and processing capabilities for file uploads, and the effectiveness of
UPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDS.
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.