What the data for this category looks like
The data for glass research reports comes from public reports released by building materials industry associations, securities firm industry research reports, and monthly operational data from glass manufacturing enterprises. There are three update frequency categories:
- Spot price data is updated weekly
- Production capacity and inventory data is updated monthly
- Special industry research reports are released irregularly
Document structure includes core category parameters, regional market trends, upstream and downstream supply-demand relationships, and policy compliance requirements. Fields include product thickness, unit price, production capacity scale, and inventory turnover period, with units of millimeters, yuan/weight box, tons, and days respectively.
Constraints imposed by data characteristics on vector models and indexing
The above data characteristics create multiple constraints for the vector model and indexing link.
- Differentiated index refresh strategies are required for data with different update frequencies. Weekly spot price data needs high-frequency synchronization, while monthly production capacity data can use low-frequency synchronization.
- Documents contain both structured metrics and unstructured analysis content, so the vector mapping logic for text semantics and structured fields must be balanced.
- Valuation units vary across different data sources, so unit normalization must be completed in advance to avoid deviations in the vector space.
- There are many regional segmented data, so index shards must be split by geographic dimension to improve recall accuracy.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Glass research reports include structured metrics and analytical text. This range can fully cover a single set of core metrics and associated analysis content, avoiding semantic fragmentation |
EMBEDDING_ENABLE_IMAGE | Enabled | Research reports contain visual content such as glass production capacity distribution maps and price trend charts. Vectorization must be enabled to support mixed text-image retrieval |
INDEX_REFRESH_CRON | 0 2 * * 1 | Spot price data is updated weekly. Indexes must be refreshed synchronously after weekly data updates on Monday mornings |
retrieval_top_k | Top 8 results | Glass research report scenarios focus on regions or specific categories. Excessive recall results will increase semantic interference |
SIMILARITY_THRESHOLD | 0.72–0.78 | Core metrics in glass research reports have strong correlation. This threshold can filter redundant results with low relevance |
PARSE_STRUCTURED_FIELD | Enabled | Research reports include standardized production capacity and price fields. Structured parsing can improve the accuracy of vector matching |
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. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- Symptom: Retrieval results do not return the glass production capacity distribution map attached to the research report, only text content. Cause: The
EMBEDDING_ENABLE_IMAGEconfiguration item is not enabled, and image content is not vectorized. - Symptom: The specified high-end vector model cannot be found in the model selection list. Cause: The API key and interface address of the corresponding model are not added in the system configuration, or the model version is not compatible with the current vector library version.
- Symptom: After importing the research report, the custom core indicator fields are not correctly indexed. Cause: The
PARSE_STRUCTURED_FIELDconfiguration is not enabled, or the glass industry-specific fields to be extracted are not specified in the parsing rules.
How to verify successful configuration
- Upload a glass research report that includes images and structured metrics, and check whether the vector task log contains successful records of image vectorization.
- Run a retrieval test by entering "float glass price", verify whether the number and relevance of recall results meet expectations, and adjust
SIMILARITY_THRESHOLDto an appropriate range. - View the index refresh log to confirm that data synchronization is completed according to the set
INDEX_REFRESH_CRONcycle. - Manually extract structured fields from the research report, and verify whether the vector data of the corresponding fields is included in the index library.
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.