What the data for this category looks like
Specialized equipment investment and research data primarily comes from equipment factory technical manuals, on-site operation logs, regular maintenance reports, industry compliance standard documents, and technical white papers updated by suppliers. Static data such as rated power, rated speed and other long-term unchanged parameters. Operation logs are updated hourly or when operating conditions trigger changes. Maintenance reports are released according to maintenance cycles. Industry standard documents have longer update cycles. Documents include structured parameter tables with units such as kW, rpm, MPa, unstructured fault analysis records, and long-text technical specifications. Some data requires association with equipment unique identifiers and operation time period fields.
What constraints these characteristics impose on deployment and upgrade
Structured parameter tables with clear units require dedicated field mapping rules to be configured during deployment, to avoid retrieval errors caused by unit confusion. Frequently updated operation logs require incremental synchronization tasks to be configured, to avoid excessive storage and computing resource usage from full synchronization. Long-text technical documents and fault records require reasonable preset segmentation and recall parameters during deployment, to adapt to token length limits. During the upgrade phase, dataset backups associated with historical equipment identifiers must be retained, while compatibility with older parsing formats must be maintained, to prevent historical data from being unavailable for retrieval after upgrade. Additionally, concurrent thresholds must be configured for batch-imported multi-equipment data, to prevent service overload during the initial deployment phase.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the typical size of single equipment technical manuals or batch log packages |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers parsing time for long-text technical documents and batch logs |
maxContext | 800–1200 characters | Matches the typical segment length of specialized equipment investment and research documents |
Recall Count | Top 6–8 entries | Balances retrieval coverage and context window usage |
Similarity Threshold | 0.72–0.85 | Calibrated through actual testing, to avoid missing equipment parameters or incorrectly matching unrelated logs |
Incremental Sync Interval | 15 minutes | Adapts to the high-frequency update rhythm of operation logs |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, 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
- Issue: After upgrading to version 4.9.9, datasets associated with historical equipment cannot be retrieved normally. Cause: No backup of equipment data snapshots under the
FASTGPT_DB_BACKUP_PATHpath was performed in advance, and the upgrade script does not maintain compatibility with older device ID field naming conventions. - Issue: When configuring an overseas OpenAI model, a
403 Forbiddenerror is returned, or the model option fails to load properly. Cause: TheOPENAI_API_BASEandOPENAI_API_KEYenvironment variables are not configured correctly, or access permissions for the model in the corresponding region have not been enabled. - Issue: When batch importing equipment operation logs, only a single task runs, and no parallel progress feedback is displayed. Cause: Parallel import functionality is not enabled in the deployment configuration, or the corresponding concurrency parameter values have not been adjusted.
How to Confirm Configurations Are Set Correctly
- Upload a single equipment technical manual, and check whether structured parameters with units are correctly extracted in the parsing results, and that field names match the preset mapping rules.
- Trigger an incremental synchronization task, and verify that only newly added operation logs are imported, and that historical data is not overwritten or deleted.
- Initiate a batch import test, confirm that the number of concurrently executing tasks matches expectations, and that service operating status remains stable.
- Configure the target model, initiate a retrieval test, and verify that the number of returned results matches the preset configuration, with no abnormal errors.
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.