Data Characteristics of This Category
The data sources for baijiu intelligent due diligence include enterprise public financial reports, production area circulation filing archives, third-party quality inspection reports, vintage liquor traceability certificates, and dealer qualification documents. Data update cadence follows disclosure timelines: enterprise financial reports are updated quarterly or annually, production area circulation data is updated monthly, and traceability files for single liquor batches are generated synchronously upon production completion. Document types include structured filing tables and unstructured PDF quality inspection reports. Fields include batch number, alcohol content, total acid and total ester content, production workshop, circulation filing number. Common units are volume percentage, grams per liter, cases, and batch identification numbers.
Constraints for Deployment and Upgrade
Baijiu due diligence data includes both structured tables and unstructured quality inspection reports. During deployment, the parsing logic for mixed documents must be adapted. During upgrade, compatibility with existing OCR and table parsing configurations must be maintained. Data update nodes are scattered, so scheduled incremental sync tasks must be configured. During upgrade, running sync scripts must not be interrupted. Fields include measured items with clear units such as alcohol content and total acid content. During deployment, preset field mapping rules are required. During upgrade, unit conversion logic for legacy fields must be compatible to prevent unit mismatch issues during retrieval. Single-batch traceability documents may contain multiple pages of quality inspection content. Parsing and recall-related parameters must be adjusted to avoid content truncation or incomplete recall.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single-batch baijiu traceability documents may contain multiple pages of quality inspection reports, requiring support for large PDF or scanned files |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long document parsing requires extended processing time to avoid mid-process timeout interruptions |
Chunk size | 800–1200 characters | Baijiu quality inspection reports contain dense measurement data. Segments that are too long lose contextual association, while segments that are too short increase retrieval redundancy |
Recall count | Top 8–12 results | Due diligence reports require multi-dimensional data coverage. Too few recalls cannot support complete analysis, while too many recalls introduce irrelevant content |
Similarity threshold | 0.75–0.85 | Balances precision and recall rate, adapting to the semantic similarity characteristics of baijiu industry data |
Incremental sync interval | 2:00 AM daily | Matches the monthly update cycle of production area circulation data and quarterly update cycle of enterprise financial reports, avoiding resource occupation from high-frequency synchronization |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material form, data volume and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Errors
- A "field format mismatch" error occurs when importing a CSV file of a baijiu due diligence knowledge base exported using v4.9.2, modified according to the v4.12.1 template. The cause is that different versions of CSV templates add required fields, and format adaptation was not completed.
- The locally deployed knowledge base search module returns a fixed number of references, and the upper limit cannot be adjusted as needed. The cause is that the recall count configuration parameter was not modified, and the default low value setting was retained.
- The currently deployed FastGPT version number cannot be viewed. The cause is that the SaaS version does not offer a public version query entry, and the local deployment did not enable version information display in the configuration file.
How to Confirm Proper Configuration
- Upload a baijiu quality inspection report PDF, and check that the parsed text completely retains measured fields with units such as alcohol content and total acid content, with no truncation or garbled characters.
- Trigger an incremental sync task, and check that the sync log only updates newly added filing data, with no repeated import of historical files.
- Initiate a baijiu due diligence query, and check that the number of references in the returned results matches the configured recall count, and field units conform to preset rules.
- View the deployed version information, and confirm that it matches the currently used FastGPT version, with no version inconsistency issues.
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.