What data this category uses
Data comes from customer-provided BOM, Gerber files, mounting coordinates, MES systems, solder paste and component batch ledgers, mounter operation data, SPI/AOI inspection reports, and reflow oven temperature records. Daily maintenance documents include changeover sheets, stencil parameters, first-piece confirmation sheets, and maintenance traceability labels. Data update frequency triggers in real time during work order execution and changeover operations. Fields across different documents cover part numbers, reference designators, component specifications, soldering temperatures, inspection results, and other details. There is no unified fixed format. Adaptation to multi-source heterogeneous industrial document structures is required.
Constraints for deployment and upgrade
Multi-source heterogeneous industrial documents have large structural differences. Configure multi-format document parsing modules during deployment. Retain old parsing rules during upgrades to maintain compatibility with historical work order data. The real-time update feature requires deployed vector databases and knowledge base synchronization links to support low-latency writes. This avoids impacting the real-time performance of process Q&A. Updates triggered by work orders and changeovers require support for isolating knowledge base versions by production batch. This prevents mixing of process data across different work orders. Data sources include industrial device logs. Configure intranet access permissions during deployment to ensure data security.
Configuration settings
This page is compatible with FastGPT v4.17.0. The following are standard configuration items for this scenario.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
REDIS_URL | redis://:custom complex password@intranet server IP:6379/0 | Caches process Q&A context and temporary search results. Intranet deployment ensures cache data security |
MONGODB_URI | mongodb://username:custom complex password@intranet server IP:27017/fastgpt?authSource=admin | Stores multi-source heterogeneous process documents and knowledge base versions. Supports fast indexing by work order granularity |
DB_MAX_LINK | 150–200 | Limits database concurrent connection count. Adapts to concurrent Q&A requests across multiple work orders in industrial scenarios |
STORAGE_S3_ENDPOINT | http://intranet MinIO service address:9000 | Stores large-volume industrial documents such as stencil parameters and furnace temperature records. Intranet access prevents data leaks |
| Knowledge base synchronization interval | 10–30 seconds | Adapts to real-time updated work order and changeover data. Reduces latency of Q&A data |
ROOT_KEY | 32-bit or longer random string | Secures access permissions for FastGPT backend configuration. Prevents unauthorized modification of process Q&A knowledge bases and models |
Three common configuration errors
- Symptom: Slow model interface call response in FastGPT. Logs show interface call delay exceeding 30 seconds. Direct curl call to the interface returns normal response. Cause: FastGPT model call link not configured for intranet access. Public network requests experience network jitter. Timeout thresholds not adjusted to match real-time requirements of industrial scenarios.
- Symptom: After local FastGPT deployment, the login interface has no registration entry. Regular user accounts cannot be created. Cause: FastGPT local registration configuration not enabled. By default, only administrator account login is available. This does not adapt to multi-user permission requirements in industrial scenarios.
- Symptom: Knowledge base search results do not match current work order process requirements. Number of recalled results does not meet expectations. Cause: Knowledge base versions not isolated by work order granularity. Process data across different work orders is mixed. Document-type recall filtering rules not configured.
How to confirm correct configuration
- Perform model interface call tests in the intranet environment. Verify that response delay meets business requirements. Confirm that
REDIS_URLandMONGODB_URIconfigurations allow normal connections. - Log in to the FastGPT backend. Verify that
ROOT_KEYconfiguration restricts unauthorized access. Confirm that administrator accounts can normally create and manage process knowledge bases. - Upload a stencil record document. Trigger knowledge base synchronization. Verify that document parsing and indexing processes work normally. Confirm that
STORAGE_S3_ENDPOINTcan store industrial documents correctly. - Submit a process standard Q&A request for the current work order. Verify that returned results match current work order process data. Confirm that knowledge base synchronization interval configuration meets business real-time requirements.
The values provided are common starting points and should be measured against the reader's own samples.