What the data for this category looks like
Data for medical beauty financing daily reports comes from publicly disclosed documents from medical beauty industry associations, official financing announcements from medical beauty institutions, and compliant third-party industry information platforms. Updates are issued daily, covering medical beauty sector financing events from the current day and the past 72 hours. Each document follows a fixed structure, with fields including full institution name, financing round, financing amount (unit: ten thousand RMB), investor entity, financing completion time, core business track (such as light medical beauty, surgical plastic surgery), and landing city. There are no nested complex hierarchies.
Constraints on vector models and indexing from these data characteristics
The daily incremental update requirement means indexes must support incremental synchronization, to avoid resource consumption and delays caused by full index reconstruction. Numeric financing amount fields must align with the numeric encoding logic of vector models, to prevent deviation from semantic vectors of text fields. Limited enumerated core business track categories can act as pre-filter conditions, narrowing the candidate range for vector recall and reducing computational pressure. Each document has a short overall length, and batch data scale is moderate, so no overly long text segmentation configuration is needed. Abbreviated and full names exist for medical beauty institutions, so vector recall must support both semantic matching and exact matching.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1000 characters | Each medical beauty financing daily report document is short. This segmentation range preserves complete business field semantics and avoids excessive splitting |
embedding_batch_size | 32–64 | Adapts to batch data processing rhythms, balancing computational resource usage and embedding efficiency |
recall_top_k | Top 8–12 entries | For the vertical medical beauty financing scenario, the candidate range does not need to be overly broad. This range covers valid relevant information |
similarity_threshold | 0.72–0.78 | Based on semantic similarity distributions of industry terminology, filters low-relevance recall results |
incremental_index_enable | Enabled | Matches the daily update rhythm of daily report data, avoiding resource costs from full index reconstruction |
embedding_api_base | https://api.doubao.com/ (or local embedding service address) | Adapts to the access path of the configured vector model, matching platform interface specifications |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing the configuration.
Three Common Mistakes
- Phenomenon: After switching the
embedding_model, index construction shows no progress, and rollback to the original model is not possible. Cause: The incremental index switch is not disabled, or a forced index reconstruction operation is not performed, causing the platform to lock the current model configuration. - Phenomenon: A 404 error is returned when testing after configuring
embedding_api_baseandembedding_api_key. Cause: The API address does not include the correct version path (such as omitting/v1/embeddings), or the key does not have permission for the corresponding service. - Phenomenon: Newly added medical beauty institution names are not correctly recalled after an index update. Cause: Pre-filter fields are not configured, or segmentation length is too short and truncates the full institution name, leading to semantic matching deviation.
How to Verify the Configuration Is Set Up Correctly
- Navigate to the index management page of the knowledge base, and confirm that the currently bound vector model and configuration parameters match the preset plan.
- Upload a single test medical beauty financing daily report document, trigger manual index construction, and check whether the progress status updates normally.
- Initiate a vector recall test, enter a query statement containing medical beauty institution names or financing track keywords, and verify that the relevance of recall results meets scenario requirements.
- Manually trigger an incremental synchronization task, and check whether newly added test data is automatically included in the index scope.
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.