What the data for this use case looks like
Data sources for photovoltaic module encapsulation production ledgers include battery sheet grading records, glass adhesive film backplane batch archives, factory MES systems, string welding and lamination equipment logs, EL tester and IV power tester output, insulation voltage withstand test records, and more. Data is updated once per module, with batch information synchronized for each raw material batch. Daily archived documents include layout diagrams, material batch records, lamination process parameter logs, EL defect images, IV test reports, insulation voltage withstand records, packaging and shipping lists, and others. Data fields include component unique ID, battery sheet current grade, lamination temperature and time, EL crack location coordinates, IV test power value, insulation voltage withstand value, and other relevant fields. Units include degrees Celsius, seconds, watts, megapascals, and other professional industrial units.
What constraints these characteristics impose on deployment and upgrade
Photovoltaic module encapsulation production ledger data is dispersed across sources, has a high update frequency, and includes diverse document types. These factors create multiple constraints for FastGPT deployment and upgrade. Multiple data source connections require configuring multiple data connection parameters to avoid field mapping errors. High update frequencies require cache and database connection counts to be adjusted to meet concurrent write requirements, preventing connection exhaustion. Support for multiple document types such as images, tables, and logs requires compatible storage backends to be configured. Correlation analysis of professional industrial fields requires precise field matching rules to avoid data misalignment during ledger summary. Additionally, photovoltaic module encapsulation workflows require associating battery sheet grades with power grading results, so additional field association logic must be configured during deployment to ensure report generation accuracy.
Configuration settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
REDIS_URL | redis://:custom password@redis service address:6379/0 | Photovoltaic module ledger data updates frequently, requiring low-latency caching of sessions and temporary indexes. 6379 is the default Redis port, and database 0 is used to isolate business data |
MONGODB_URI | mongodb://username:custom password@mongodb service address:27017/fastgpt?authSource=admin | Stores unstructured documents such as EL images and IV test reports. MongoDB adapts to multi-format file storage requirements |
STORAGE_S3_ENDPOINT | http://minio service address:9000 | Stores batch production documents. 9000 is the default MinIO port, suitable for small-file batch upload scenarios |
DB_MAX_LINK | 50–80 connections | Handles simultaneous writes from multiple devices to avoid database connection exhaustion. The specific value should be calibrated based on actual test scenarios |
ROOT_KEY | 32-digit random hexadecimal string | Replaces the default key to prevent the Root account password from being automatically reset and improve administrator account security |
FILE_TOKEN_KEY | 16-digit random string | Generates file access tokens to prevent unauthorized access to production documents and test images |
Three common misconfigurations
- Phenomenon: Redis image pull fails or the container fails to start during deployment. Cause: The access password or port in
REDIS_URLis not configured correctly, or a Redis image version incompatible with FastGPT v4.17.0 is used. - Phenomenon: The system returns the error
{"code":500,"statusText":"","message":"URI malformedafter login. Cause: TheFE_DOMAINconfiguration lacks a protocol prefix such as http://, or the domain name format contains invalid characters, causing front-end callback URI parsing to fail. - Phenomenon: The Root account password is automatically reset to 123456 every other day. Cause: The default
ROOT_KEYconfiguration was not modified. Some older versions of FastGPT include a password reset mechanism when using the default key, and failing to set a custom key results in the configuration being overwritten.
How to verify successful configuration
- Run the
docker-compose pscommand to confirm that all dependent service containers such as Redis and MongoDB have a status of Up. - Access the access address configured in
FE_DOMAIN, and log in using the Root account to verify that no 500 error occurs. - Upload an EL test image or IV test report file to confirm that the file uploads successfully and appears in the document management list.
- Check the database connection log to confirm that the current connection count does not exceed the threshold set in
DB_MAX_LINK, with no connection exhaustion alerts.
The values provided are common starting points and should be measured against the reader's own samples.