What the data for this category looks like
Specialized chain industry research reports primarily come from national retail industry associations, quarterly or half-year financial reports publicly disclosed by chain brands, and store operation data from third-party retail monitoring agencies. Update cycles are fixed: quarterly financial reports follow natural quarters, industry monitoring data updates monthly, and store expansion announcements from top chain brands are released irregularly. Document structures include modules such as store geographic distribution, per-store efficiency per square meter, SKU proportion, supply chain costs, and regional revenue proportion. Some documents include detailed tables for multiple stores. Fields and units are clearly defined: efficiency per square meter uses yuan/square meter/month as the unit, number of stores uses units as the unit, revenue uses ten thousand yuan as the unit, and number of SKUs uses pieces as the unit.
Constraints on document parsing and chunking from these characteristics
Correlation data between store geographic distribution and regional revenue requires chunks to not be too short, to avoid breaking the geographic-revenue business logic. Multi-quarter financial report data must retain timestamp associations, so chunks must carry metadata for the corresponding quarter. Merged cells and multi-field linkage in detailed tables require parsing tools to retain table structure and avoid field misalignment. Large research report collections have large file sizes, which impose higher requirements on upload and parsing timeout settings. Some research reports include cross-store SKU comparison data, so chunks must retain cross-store contextual associations to avoid breaking the comparison logic after splitting.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Specialized chain research reports often include multi-store detailed tables and long financial reports, with parsing time exceeding general scenarios |
maxChunkSize | 800–1200 characters | Need to retain associated business fields such as store geography and efficiency per square meter, to avoid cutting core logic in chunks |
chunkOverlap | 150–200 characters | Cross-chunk store revenue and SKU linked data needs to retain contextual associations |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Some chain research reports include multi-quarter store data collections, with large file sizes |
recallTopK | Top 8 entries | Specialized research reports need to recall enough relevant chunks to cover multiple business dimensions such as stores and supply chains |
SIMILARITY_THRESHOLD | 0.72 | Filter low-relevance non-core data, retain key business fields such as efficiency per square meter and revenue |
The parameter values provided on this page are common 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.
Common Mistakes
- Phenomenon: After uploading a specialized chain industry research report, the model does not trigger file parsing and returns a general answer. Cause: The
AUTO_PARSE_ON_UPLOADconfiguration is not enabled, or the model's parsing trigger conditions do not match the research report's file suffix and content characteristics. - Phenomenon: When using
marker_pdfto parse large chain industry research reports, FastGPT returns a504 Gateway Timeouterror, and the parsing service log shows the task is completed. Cause: The value ofPARSE_FILE_TIMEOUT_SECONDSis lower than the actual parsing time. Large research reports include multi-store tables and long text, so parsing duration exceeds the preset threshold. - Phenomenon: After uploading an Excel research report containing store SKU detailed tables, the store field in the parsing result is empty. Cause: The
EXCEL_PARSE_WITH_HEADERconfiguration is not enabled, or merged cells in the table are not correctly identified, leading to failed field extraction.
How to Confirm Configuration is Correct
- Upload a single standard specialized chain industry research report, check the parsing task log to confirm that the
chunkfield includes core business fields such as store information and efficiency per square meter. - Test multiple research reports from different quarters, check if the chunk results carry the corresponding quarter's metadata, to ensure cross-quarter business associations are not broken.
- Upload a research report collection larger than 1000 MB, confirm that the upload task is not blocked by the
UPLOAD_FILE_MAX_SIZEconfiguration. - Initiate a question-and-answer session based on the research report, check that the returned content includes parsed store data, and no general answers unrelated to the document.
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.