What the data for this category looks like
Marketing-related data for automated equipment primarily comes from industrial IoT gateways, on-device PLC logs, and on-site condition collection systems. Real-time condition data updates every 1 to 5 seconds, and includes fields such as device SN code, operating temperature (℃), working pressure (MPa), spindle speed (r/min), and online status. Equipment marketing materials such as parameter manuals and case videos update quarterly, while alert logs update when device abnormal events occur. A single data structure includes a unique device identifier, parameter group, associated material ID, and update timestamp, and supports mixed storage of multimodal data.
What constraints these characteristics impose on the deployment and upgrade phase
High-frequency updates of real-time condition data require adapting low-latency vector ingestion workflows during deployment to avoid data backlogs. Varied sizes of multimodal marketing materials require upload configurations that support adjusting large file thresholds. Using the device SN code as the unique identifier requires configuring vector database primary key mapping rules during deployment to ensure accurate association between data and marketing materials. The upgrade process must be compatible with legacy device data formats to prevent historical data from being unretrievable due to field changes. Additionally, the sensitivity of equipment data in the financial sector requires configuring data encryption and access permission rules during deployment, and updating encryption strategies during upgrades.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Large high-definition condition videos and comprehensive parameter manuals for automated equipment require support for large file uploads |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Multimodal marketing materials take longer to parse, preventing parsing failures due to timeout |
VECTOR_STORE_BATCH_SIZE | 50–100 | Adapts to batch ingestion of high-frequency updated equipment condition data, balancing ingestion efficiency and system load |
recall_top_k | 10–15 | Equipment marketing content must align with precise condition parameters; too many values cause content redundancy, too few fail to cover business needs |
similarity_threshold | 0.75–0.85 | High precision is required for equipment parameter matching; too low introduces irrelevant marketing materials, too high leads to insufficient recall |
DB_CONNECTION_TIMEOUT | 60 seconds | IoT databases may experience network fluctuations, requiring a reasonable connection timeout setting |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material formats, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: A
2003 Can't connect to MySQL server on '127.0.0.1:3306'error appears after deployment, making it impossible to load equipment condition data. Cause: TheMYSQL_HOSTandMYSQL_PORTparameters are not correctly configured indocker-compose.yml, or the local firewall blocks the database communication port. - Phenomenon: An incorrect port number is entered when configuring
OPENAI_BASE_URL, but equipment marketing content can still be generated normally. Cause: Port legitimacy verification for the proxy is not enabled, or the upstream reverse proxy does not enforce verification of the target service port. - Phenomenon: In version v4.8.7, condition data for a single device cannot be associated with multiple sets of marketing material vectors, and only one vector model can be bound. Cause: The "Multi-vector Association" switch is not enabled in the knowledge base settings, or the vector database grouping mapping rules are not configured.
How to confirm the configuration is correct
- Upload a parameter manual for automated equipment, verify that the parsed text includes the device SN code, operating parameter fields and units, to confirm the upload configuration is effective.
- Simulate batch upload of equipment condition data, review batch processing records in the vector ingestion logs, to confirm the ingestion batch size matches the expected configuration.
- Initiate a recall request for equipment marketing content, review the similarity scores of returned results, and adjust the threshold to a range that meets business requirements.
- Run the
docker pscommand, confirm that the currently running image version matches the version configured indocker-compose.yml, to confirm that the upgrade deployment has taken effect.
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.