What the data for this category looks like
Data is primarily sourced from public announcements of listed cosmetics companies, industry vertical media financing coverage, and financing disclosure information filed with regulatory authorities. Updates are event-triggered, and synchronized whenever a new cosmetics brand or company completes financing. Each document includes fields such as financing party brand name, affiliated sub-sector, financing round, financing amount, participating investors, publication time, and core brand business description. For field units, financing amount uses ten thousand yuan or hundred million yuan, time uses the YYYY-MM-DD format, and brand names and investor institutions are plain text fields.
What constraints do these characteristics impose on vector models and indexing
The event-triggered update rhythm requires the index to support incremental synchronization, avoiding repeated computing resource consumption caused by full index reconstruction. The mixed structured and unstructured field structure requires separate configuration of structured indexes and vector indexes, to prevent vector encoding of unstructured fields from interfering with matching of numerical fields. The large variation in unstructured content length across individual documents requires presetting reasonable segmentation thresholds to ensure semantic consistency during vector encoding. The timeliness of financing events requires the index to support rapid filtering by publication time, narrowing the recall scope to improve query efficiency.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
EMBEDDING_MODEL | m3e-base | Adapts to semantic encoding of Chinese financing text, supports local deployment and OneAPI calls |
CHUNK_SIZE | 800–1000 characters | Matches the average length of cosmetics financing business descriptions, avoids semantic truncation |
CHUNK_OVERLAP | 50 characters | Connects the semantics of adjacent segments, avoids key information being split |
INDEX_TYPE | HNSW | Adapts to fast recall of high-dimensional vectors, meets real-time query requirements for financing daily reports |
RECALL_TOP_K | Top 10 results | Matches the event scale of financing daily reports, avoids recalling too many irrelevant results |
RECALL_THRESHOLD | 0.75–0.85 | Filters low-similarity results, ensures relevance of recalled events |
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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Issue: When deploying a vector model locally, only a single 3090 GPU is recognized, and the second GPU resource cannot be accessed. Cause: The
CUDA_VISIBLE_DEVICESparameter is not used to specify multiple available GPUs, and the system loads only the first GPU by default. - Issue: After configuring the Baidu
embedding-v1model in OneAPI, a 404 error is returned. Cause: The interface path parameter of the model is not filled correctly, or OneAPI has not completed adaptive deployment for the corresponding model. - Issue: Adding a local index model in FastGPT 4.8.22 results in a startup failure error. Cause: The new version's index model loading rules are not matched, or the storage path configuration of the model file is incorrect.
How to confirm the configuration is complete
- Check the vector model's running logs to confirm that GPU resources are correctly recognized and video memory usage matches the expected configuration.
- Upload a single cosmetics financing daily report document to check whether the segmentation results conform to the settings of
CHUNK_SIZEandCHUNK_OVERLAP. - Initiate a test query, verify that the number of recalled results matches the configuration of
RECALL_TOP_K, and the similarity scores fall within the preset threshold range. - Verify that the OneAPI embedding interface returns normally, with no 404 or timeout errors, confirming that the model call link is unobstructed.
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.