What the data for this category looks like
Wind power investment research data comes from multiple sources: industry public research reports, turbine manufacturer technical documents, grid operation monitoring data, meteorological department wind power prediction reports, and industry association policy documents. Public research reports and policy documents are updated quarterly and semi-annually. Manufacturer technical documents are updated irregularly alongside product iterations. Grid monitoring and meteorological prediction data is updated hourly. Document structures include parameter tables (such as turbine model, rated output, hub height), project feasibility study reports, fragments of operation and maintenance logs, and policy clauses. Fields include turbine model, rated output, annual utilization hours, grid connection voltage level, and more. Corresponding units are kW, m, h, kV respectively.
Constraints imposed by these characteristics on deployment and upgrade
Multi-source heterogeneous data formats require adapting parsing rules for PDF, CSV, JSON and other formats during deployment. This prevents data from some formats from failing to import into the knowledge base. Hourly updated monitoring data requires supporting incremental indexing during the upgrade phase. This reduces resource consumption and time overhead of full index rebuilding. Professional data with fixed fields and units requires configuring precise field extraction rules during deployment. This avoids unit confusion or missing fields. Document structures with both long and short texts require segmented configuration that balances semantic completeness and retrieval accuracy. This prevents semantic breakage from overly short segments, or redundant recall from overly long segments.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Wind power investment research data includes PDF research reports with dozens of pages per file. Single-file volume usually falls within this range, to avoid interruptions during large-file uploads |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Wind power research report PDFs contain complex parameter tables and technical formulas, requiring sufficient parsing time to prevent mid-process timeout failures |
CHUNK_SIZE | 800–1200 characters | Wind power data includes both long feasibility study reports and short operation and maintenance log texts. This range balances the rationality of long-document segmentation and the integrity of short texts |
INCREMENTAL_SYNC_INTERVAL | 1 hour | Wind power grid monitoring data is updated hourly. Incremental synchronization matches the data update rhythm, reducing resource usage from full index rebuilding |
SIMILARITY_THRESHOLD | 0.75–0.85 | Wind power investment research data has high professionality. A higher threshold filters low-relevance recall results, ensuring retrieval accuracy |
ARM64_SUPPORT_ENABLED | Enabled | Adapts to Arm64 architecture server deployment, covering requirements for low-power computing scenarios |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material form, data volume, and business rules. Specific issues require on-site analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Slow download speed when pulling the
fastgpt-minioimage, with the image pull progress stuck for extended periods. Cause: No domestic mirror acceleration source is configured. The default official mirror source loads slowly in overseas network environments. - Phenomenon: After upgrading the platform version, identical CSV-format wind power operation and maintenance log files cannot be segmented normally, triggering the
PARSE_FAILEDerror code. Cause: The new version’s parsing rules optimize extraction logic for multi-field CSVs. The old configuration’sCHUNK_SIZEdoes not adapt to the new field structure. - Phenomenon: No image dataset upload entry appears in the private deployment interface. Wind power project site photos cannot be uploaded as knowledge base materials. Cause: The
ENABLE_IMAGE_DATASETenvironment variable is not enabled. The image dataset upload function is disabled by default.
How to confirm configuration is complete
- Run the
docker pull fastgpt-minio:latestcommand. Verify the image can be pulled normally to confirm mirror acceleration configuration takes effect. - Upload a single wind power research report PDF and an operation and maintenance log CSV. Check that the parsing task status shows "Completed", with no timeout or
PARSE_FAILEDerror prompts. - Enter the knowledge base settings page. Confirm that values for configuration items such as
CHUNK_SIZEandSIMILARITY_THRESHOLDmatch the preset plan. - Initiate a professional retrieval test. Verify that the relevance of recall results meets the preset professional scenario threshold requirements.
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.