What data for this category includes
Daily documents for this category include winding and core assembly records, vacuum drying records, insulating oil reports, partial discharge and withstand voltage test reports, nameplate parameter tables, and more. Data sources include design BOM, silicon steel sheet and insulating material data, vacuum and drying equipment operation records, oil test reports, and test station detection data. Data is updated on a per-unit product or per-batch purchased material cycle. Each document includes clear product model, batch number, core parameter values and test results, with fields covering exclusive industrial parameters such as insulation distance, water content, withstand voltage level, and partial discharge value.
What constraints these characteristics impose on deployment and upgrade
Documents for this category are mostly structured records for full life cycle traceability of individual units, with high data update frequency. During deployment, support for high-frequency, small-batch data synchronization and associated retrieval is required. Core documents include high-precision industrial data such as high-voltage test and insulation parameter data, so strict permission isolation and storage encryption rules must be configured during deployment. The document association relationship for a single product is complex, so deployment must adapt to multi-source data association matching logic to avoid cross-batch data confusion. At the same time, errors in this category’s data can cause serious production and power grid faults, so a basic data verification mechanism must be built into deployment to prevent incorrect parameters from entering the Q&A process.
How to set configurations
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
DB_MAX_LINK | 20–30 | Adapts to concurrent retrieval requirements for multi-dimensional documents of a single product, avoiding database connection overflow |
MONGODB_URI | Intranet access address bound to a dedicated storage volume | Isolates sensitive industrial data such as high-voltage test and insulation parameter data to ensure data security |
REDIS_URL | Dedicated instance with 1000 MB memory | Caches frequently retrieved nameplate parameters and test report data to reduce database pressure |
STORAGE_S3_ENDPOINT | Intranet object storage service address | Adapts to storage requirements for batch uploading large-volume documents such as insulating oil reports and test records |
FILE_TOKEN_KEY | Set based on actual measurement | Ensures permission verification for document download and preview, preventing unauthorized access to sensitive test data |
Three common mistakes
- Inconsistent models between chat and workspace: Deployment fails to unify configuration rules for global models and application-bound models, resulting in mismatched model versions called by different application nodes.
- Intranet Docker Compose deployment is accessible, but OneApi calls fail: Fails to open cross-service access permissions for intranet storage or databases, causing OneApi to fail to pull necessary configurations and data.
- Response timeout during post-retrieval reranking: Fails to set reasonable processing logic for multi-document associated retrieval of a single product, and does not optimize the caching strategy for frequently retrieved data, resulting in processing time exceeding expected limits.
How to confirm successful configuration
- Check the memory usage of the instance corresponding to
REDIS_URL, confirm that the cache hit logic meets the retrieval frequency requirements for single-product documents. - Initiate a cross-application model call test, confirm that all bound process Q&A applications call the same baseline model version.
- Upload an insulating oil report document, verify that the storage path and document metadata associated with
STORAGE_S3_ENDPOINTare correct. - Trigger a complete process Q&A flow, confirm that the number of database connections does not exceed the configuration range of
DB_MAX_LINK.
The values provided are common starting points and should be measured against the reader's own samples.