What the Data for This Category Looks Like
Glass-related financial report data originates primarily from annual and quarterly reports of publicly traded glass manufacturing companies, and monthly production capacity and price monitoring documents published by industry associations. Corporate financial reports are updated quarterly and annually, while industry monitoring data is updated monthly. Most documents use structured tables, which include production volume, sales volume, unit cost, and revenue data for product categories such as float glass and tempered glass. These tables are paired with text descriptions of industry supply and demand, and policy impacts. Fields include quantified items with clear units, such as thickness (millimeters), production volume (heavy boxes), and revenue (Chinese yuan). Unstructured paragraphs linked to upstream and downstream raw material prices are also included.
Constraints on Document Parsing and Chunking
Glass financial reports have a high share of structured tables, often with multi-dimensional data across multiple product categories. When chunking documents, do not split table cells, as this breaks row and column associations. Quantified data for different product categories uses exclusive units. Chunking must retain the link between numerical values and their corresponding units, to prevent unit confusion during vectorization. Long documents may include cross-page tables. Chunking must identify contextual connections across cross-page paragraphs, to avoid breaking logical chains. Financial reports also include unstructured paragraphs tied to upstream and downstream relationships. Chunking must keep semantic continuity between adjacent paragraphs, to prevent loss of business logic after splitting.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_CHUNK_SIZE | 800–1200 characters | Matches the average length of table rows and contextual paragraphs in glass financial reports, retains complete semantics within a single chunk while controlling vectorization load |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Covers the file size of most industry data attachments included in annual reports of publicly traded glass companies, prevents large file uploads from being blocked |
PARSE_TABLE_STRATEGY | Retain cell associations | Adapts to the characteristics of multi-dimensional structured tables in glass financial reports, prevents logical breaks in row and column data caused by split cells |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the parsing duration of large-volume glass financial report documents, prevents early termination of the parsing process |
CHUNK_OVERLAP_RATE | 10–15% | Fills contextual gaps from cross-page tables and linked paragraphs, ensures semantic continuity after chunking |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, 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 Mistakes
- Scenario: After uploading glass financial report documents larger than 10 MB, the number of generated chunks exceeds 1000, and some chunks throw vectorization errors with a 422 status code. Cause: The
PARSE_CHUNK_SIZEparameter was not adjusted. The default chunk length is too small, leading to excessive chunk count, which triggers the load limit of the vectorization interface. - Scenario: When importing glass industry data from an online spreadsheet tool, the backend knowledge base cannot recognize the unit information of table columns, and some fields are empty. Cause: The unit binding configuration for
PARSE_TABLE_STRATEGYwas not enabled, causing the association between numerical values and their corresponding units to be lost during parsing. - Scenario: When using the export feature, the generated
dataset.csvonly contains a question-and-answer format template, and cannot directly import uploaded glass financial report content. Cause: The incorrect knowledge base export type was selected. The question-and-answer dataset template was mistakenly chosen instead of the original chunk template generated after document parsing.
How to Verify Correct Configuration
- Upload a single test glass financial report document, check the number of chunks generated in the backend, and adjust
PARSE_CHUNK_SIZEuntil the chunk count meets business requirements. - Parse a test document containing multi-category tables, check whether the chunked content retains the row and column associations of cells, with no split breaks.
- Upload a quantified data document with units, verify that the vectorized result includes the binding information between numerical values and their corresponding units.
- Perform an export operation, confirm that the generated file format matches the parsed content of the uploaded document, and does not use the default question-and-answer template.
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.