What this type of data looks like
Refractory material investment research data mainly comes from public statistics of industry associations, public financial reports of upstream and downstream enterprises, raw material spot market price ledgers, national and industry standard documents, and test reports from research institutions. Update rhythms vary by data type:
- Spot prices are updated weekly or daily
- Industry analysis reports are released monthly or quarterly
- Corporate production capacity and technical documents are updated irregularly alongside project progress
Document structures include:
- Structured Excel tables with fields such as product name, specification, origin, and performance parameters
- Chaptered PDF analysis reports
- Structured ledger files
Most performance parameters have fixed units. For example, refractoriness is measured in degrees Celsius, and bulk density is measured in grams per cubic centimeter.
What constraints do these characteristics impose on the vector models and indexing link
The multi-type and multi-structure characteristics of refractory material investment research data create multiple constraints for the vector model and indexing process. Structured Excel tables contain multiple associated fields. Field associations must be retained during chunking to avoid losing parameter correspondence after splitting. High-frequency updates to spot quotations require incremental indexing to reduce resource consumption from full reindexing. Long-text technical documents and detailed parameter descriptions can easily exceed the context window of basic vector models, requiring targeted chunking adaptations. Structural differences across document types require matching chunking and indexing rules tailored to each type, to ensure the accuracy of recalled content.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Adapts to the context window limits of most open-source embedding models, while retaining the complete association of refractory material parameters and fields |
overlap_ratio | 10%–15% | Creates segment overlap for structured tables and associated parameter documents to avoid losing cross-chunk field correspondence after splitting |
RECALL_TOP_K | Top 8–12 results | Balances recall coverage and subsequent processing efficiency, as precise matching of professional parameters is required for investment research scenarios |
SIMILARITY_THRESHOLD | 0.75–0.85 | Filters low-similarity irrelevant content to ensure the accuracy of professional parameter recall |
UPLOAD_FILE_MAX_SIZE | 200 MB | Adapts to the common storage size of industry analysis reports and large ledger files, preventing upload timeouts |
PARSE_CHUNK_TIMEOUT | 60 seconds | Provides sufficient processing time for parsing and chunking large Excel tables, reducing the probability of parsing failures |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material forms, data volume and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Phenomenon: The correspondence between headers and data rows is lost in chunked content when parsing large Excel ledgers. Cause:
overlap_ratiois not configured or its value is too low, and context for field associations is not retained during splitting. - Phenomenon: Content truncation errors occur when generating vectors for long-text technical documents. Cause:
chunk_sizeis not adjusted to match the context window limit of the used embedding model, and vectors are generated directly for long texts. - Phenomenon: A large number of general building material parameter contents unrelated to refractory materials appear in retrieval results. Cause:
SIMILARITY_THRESHOLDis set too low, and low-similarity irrelevant recall results are not filtered.
How to confirm the configuration is correct
- Upload a single refractory material technical parameter document, check the chunk preview interface, and confirm that each chunk retains complete parameters and associated fields.
- Trigger an incremental update task, check the index operation log, and confirm that only recently updated data source entries are processed, with no full index reindexing triggered.
- Enter professional search terms, check the similarity scores of recall results, and confirm that the scores fall within the preset threshold range.
- Upload a large industry analysis report, and confirm that no timeout or failure prompts appear during the upload and parsing process.
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.