What the data for this category looks like
Jewelry intelligent due diligence report data primarily comes from official brand quality inspection documents, supply chain raw material test records, third-party compliance test institution reports, e-commerce platform product traceability data, and customs clearance documents. The data update rhythm adjusts with new product launch frequency. Regular in-stock items are updated monthly, and the first sync is completed within 72 hours after a new product launches. Each due diligence document includes raw material composition parameters, production batch number, actual test results of compliance inspection items, traceability number, and price fluctuation records. Core fields include gold_weight (unit: gram), stone_carat (unit: carat), inspection_batch (production batch), compliance_score (compliance score). All numeric fields are bound to clear units of measurement.
What constraints these characteristics impose on deployment and upgrade processes
The multi-source data and fields with clear units of measurement for jewelry due diligence data impose multiple constraints on deployment and upgrade processes. Configure field unit verification rules to ensure imported raw material parameters comply with standard formats, preventing non-standard data from entering the vector database. Set up flexible scheduled synchronization scheduling to support separate update cycles for new products and regular in-stock items, adapting to the update rhythms of different categories. Each document contains multiple high-definition quality inspection images, so adjust file upload size thresholds and vector database sharding configuration parameters to prevent large file import failures. During the upgrade phase, synchronously update data desensitization rules to cover sensitive fields such as raw material formulas and traceability numbers.
How to configure the settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 800–1200 MB | Jewelry due diligence reports include multiple high-definition quality inspection images, requiring a larger single-file upload limit |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Documents contain multiple sections of raw material test data and traceability information, requiring extended timeout thresholds due to longer parsing time |
maxContext | 8000–12000 characters | Full recall of jewelry raw material parameters, compliance inspection items, and traceability numbers requires sufficient context length |
Recall Count | Top 8 entries | Jewelry due diligence data has many fields, requiring sufficient recalled content to cover core due diligence dimensions |
Similarity Threshold | 0.75–0.85 | Precise matching of jewelry raw material compositions and compliance test results is required to avoid interference from irrelevant recalls |
Chunk Length | 1000–1500 characters | Jewelry due diligence documents have a clear structure, and chunking preserves field association to improve recall accuracy |
The parameter values provided on this page are general recommendations to serve as a starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- An error indicating file size limit exceeded is prompted when uploading a jewelry due diligence report, and import cannot be completed. Cause: The
UPLOAD_FILE_MAX_SIZEconfiguration item was not adjusted correctly, and the default small upload threshold was still used, failing to adapt to the feature of jewelry documents containing multiple high-definition images. - After enabling the
enable_thinkingswitch, the model's thinking process is always displayed and cannot be hidden as configured. Cause: The local deployment uses versionv0.9.2 fix2, which has compatibility issues with the model thinking logic, and the official adaptation patch was not synchronized for update. - During cross-machine deployment, the FastGPT application cannot call the remotely deployed large model, returning a
504 Gateway Timeouterror. Cause: The default port of the remote model service was not opened, and the correct remote host IP and port mapping address were not filled in the FastGPT model configuration.
How to confirm the configuration is complete
- Upload a jewelry due diligence report containing high-definition quality inspection images, and verify that the upload and parsing processes complete normally with no error prompts.
- Enter the knowledge base configuration interface, confirm that all preset configuration item parameters match the preset values, and trigger a reindex of the vector database after saving.
- Initiate a test query for jewelry raw material parameters, and verify that the returned result fields match the configured recall rules.
- Enable the model thinking switch and initiate a test, confirming that the display behavior of the thinking process meets the configuration requirements.
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.