Knowledge Base Retrieval and Recall for Medical Aesthetic

Data Characteristics of This Category

Data sources for medical aesthetic marketing content include internal institution project manuals, doctor practice qualification documents, compliance-registered advertising copy, new equipment promotion materials, and more. Update cycles adjust based on compliance requirements and new project launches. There is no fixed schedule, but update frequency is high. Document structures typically include fields such as project name, target audience, operation procedures, compliance document numbers, reference prices, and others. The price field uses yuan per session as the unit. Operation procedures fields are mostly long text paragraphs. Some documents include image annotations.

Constraints on Knowledge Base Retrieval and Recall

Mixed data from multiple sources requires retrieval logic to distinguish between compliance fields and marketing fields. This prevents the recall of non-compliant content. Frequently updated documents require the retrieval system to support incremental updates. Full indexing causes information delays, so full indexing must be avoided. Long text operation procedure documents require segmentation logic that preserves semantic integrity. This avoids breaking the coherence of project descriptions. Fields with units require matching unit information during retrieval. For example, only recall price content marked with yuan per session, and exclude price content using other pricing methods.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`Recall Count`	3-5	Medical aesthetic marketing content has lengthy length. Too many results exceed context window limits. Too few fail to cover core user query requirements.
`Similarity Threshold`	0.75-0.85	Medical aesthetic project descriptions have high professionality. Low-match irrelevant content must be filtered to avoid recalling unrelated items from other categories.
`Segment Length`	800-1200 characters	Medical aesthetic documents often include continuous operation steps and compliance notes. Overly long segments lose contextual semantics. Overly short segments break complete project descriptions.
`Incremental Update Trigger Interval`	12 hours	Medical aesthetic marketing content updates frequently based on compliance requirements and new project launches. Latest information must be synchronized in a timely manner.
`PARSE_FILE_TIMEOUT_SECONDS`	300 seconds	Large compliance registered document parsing takes significant time. Sufficient parsing time must be reserved.
`Rerank Return Count`	Top 3	Marketing scenarios prioritize displaying the most matching core medical aesthetic project content. Too many redundant results interfere with user judgment.

The parameter values provided here are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Each situation requires specific analysis. Testing on local samples is recommended before finalizing values.

Three Common Mistakes

Symptom: A blank page or 502 status code appears when loading the knowledge base page under a specific version. Conversation pages may crash. Cause: Document parsing plugin adaptation issues exist. For example, compatibility problems are present in parsing dependencies for version 4.8.20 and earlier versions. Or incremental update tasks do not properly release system resources.
Symptom: Retrieval results forcibly include redundant text labeled "knowledge base", or source annotations are not hidden as required. Cause: Default source annotation configuration items are not disabled. Or custom prompt words do not cover the field filtering logic.
Symptom: Retrieval results do not combine current conversation context. Only individual query keywords are matched. Cause: Contextual retrieval configuration is not enabled. Or the maxContext parameter is set too small to capture medical aesthetic project keywords from historical conversations.

How to Confirm Proper Configuration

Upload a latest medical aesthetic compliance registered document. Check if parsed segments conform to the preset segment length.
Initiate a query that includes historical conversation content. Verify if retrieval results link to medical aesthetic project keywords mentioned in history.
Adjust the similarity threshold value. Verify that retrieval result matching quality adjusts reasonably with threshold changes.
Trigger an incremental update task. Check if update logs show that latest project information has been successfully indexed.

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.