What the data for this category looks like
Data for this category comes from design history files, component and material batch records, MES systems, clean environment monitoring equipment, sterilization equipment, and inspection and calibration systems. Daily documents include production process specifications, batch production records, clean area records, sterilization batch records, inspection reports, software version records, adverse event and traceability materials. Update data per product batch or per device, and synchronize updates in accordance with the clean environment monitoring plan. Data fields include unique device identifiers, sterilization batch numbers, clean environment parameters, software version strings, and others. Units follow corresponding measurement rules matching the field type, with no unified fixed format.
What constraints these characteristics impose during deployment and upgrade
This category’s data connects to multi-source production and compliance records. Configure permissions for multiple data source connections during deployment to avoid data silos. Follow update schedules based on batches or environmental monitoring. Configure deployment to support incremental synchronization, reducing resource use from full synchronization. Documents cover product traceability and compliance requirements. Ensure historical data is not lost and metadata is fully matched during deployment and upgrade. Fields like unique device identifiers have strong correlations. Bind corresponding business fields in knowledge base retrieval configurations to ensure Q&A results accurately link to production records.
How to configure settings
| Config Item | Recommended Value | Rationale |
|---|---|---|
MONGODB_URI | mongodb://[username]:[password]@[host]:[port]/fastgpt?authSource=admin | Connect to local or cloud-hosted MongoDB instances to store equipment inspection and maintenance Q&A logs and production-related data |
DB_MAX_LINK | 20–30 connections | This category’s data links to multiple devices and production records, preventing database connection overload from affecting production systems |
REDIS_URL | redis://[password]@[host]:[port]/0 | Cache session status and retrieval results to improve Q&A response speed in clean production environments |
FE_DOMAIN | Fill in according to the actual deployed internal front-end domain name | Adapt to internal access restrictions in clean production workshops to ensure access security |
ROOT_KEY | Random string generated according to enterprise internal key management rules | Ensure access permissions for background configurations, complying with compliance requirements for medical device production |
STORAGE_S3_ENDPOINT | Fill in according to the endpoint of the internal object storage service | Store sterilization batch records, inspection reports and other compliance documents to meet traceability requirements |
Three common errors
- After upgrading FastGPT to v4.17.0, existing browsers cannot access the front-end page. The new version updates front-end JS dependency libraries, and older browsers do not support ES2022 syntax.
- A locally deployed MongoDB instance fails to connect, and logs show authentication failure. The
MONGODB_URIconfiguration lacks the correct authentication source parameter, or special characters in the username or password are not escaped. - An extra number 0 appears in tool call debug results for equipment inspection Q&A. Knowledge base metadata is not correctly bound to the unique device identifier field, causing abnormal splicing of retrieval results.
How to verify successful configuration
- Access the configured
FE_DOMAINto confirm the front-end page loads normally with no console errors. - Run a MongoDB connection test to confirm the
MONGODB_URIconfiguration establishes a normal connection and supports read/write data. - Upload a sterilization batch record document to confirm the document can be indexed and returns matching results during retrieval.
- Send an equipment inspection Q&A request to confirm the session status can be stored and read normally.
The values provided are common starting points and should be measured against the reader's own samples.