What the data for this category looks like
Wind power intelligent due diligence report data mainly comes from project feasibility study documents, fan operation logs, grid connection approvals, environmental assessment archives and operation and maintenance ledgers. There are two types of data update rhythms: pre due diligence data is updated once per project initiation and approval milestone, while operational data is synced daily or weekly. Document structure includes fields such as project basic information, fan single-unit parameters, annual power generation, operation and maintenance records, and potential risk items. Fan parameter fields include single-unit capacity (unit MW), hub height (unit meters), and blade length (unit meters). Power generation fields are counted in kilowatt-hours.
What constraints do these characteristics impose on deployment and upgrade
Wind power due diligence data comes from diverse sources, including long-form feasibility reports, structured logs and tabular ledgers. Individual documents have many pages, data fields carry specific units, and update rhythms fall into two categories: bulk initial import and incremental sync. During deployment, it is necessary to adapt to multi-format file parsing and long-document splitting logic, to avoid parsing timeouts or incorrect field unit matching. During upgrade, it is necessary to be compatible with incremental sync modules, adapt to data access with different update frequencies, and retain historical field mapping rules to avoid unit confusion or missing fields after upgrade. Additionally, wind power data has a large storage volume, so sufficient database storage space must be reserved during deployment.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Individual wind power feasibility study reports are often large in size, to accommodate long-document upload requirements |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Long document parsing requires extended time, to prevent parsing process interruption due to timeout |
maxContext | 8000–12000 characters | Wind power due diligence reports have many fields and high information density, requiring sufficient context to support retrieval and generation |
Recall count | Top 8–10 results | Wind power data covers multiple categories including fan parameters and operation and maintenance records, expanding the recall range to ensure completeness |
Similarity threshold | 0.75–0.85 | Balance retrieval accuracy and recall coverage, to avoid missing critical operation and maintenance or parameter information |
Reranked return count | Top 3–5 results | Focus on core information, ensuring generated content is based on the most relevant wind power due diligence data |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three common errors
- Symptom:
exit code 137error occurs during local deployment packaging. Cause: Insufficient memory quota during packaging, unable to support parsing and preprocessing of large wind power due diligence documents. - Symptom: After packaging is complete and the local version is run, custom wind power field parsing rules are not loaded. Cause: The custom configuration file was not placed in the
configdirectory of the deployment package, or the service was not restarted to load updated configurations. - Symptom: Exclusive upgrade support cannot be obtained after private deployment. Cause: The enterprise-level deployment authorization verification process was not completed, and the official authorization consultation channel was not connected.
How to confirm the configuration is correct
- Upload a typical wind power feasibility study report, check if the parsed fields include preset categories such as fan parameters and operation and maintenance records, to confirm that the parsing rules match the data characteristics.
- Submit a due diligence report retrieval request, verify whether the number of returned results aligns with the set similarity threshold logic.
- After restarting the deployment service, check if custom configuration items are normally displayed in the backend interface, to confirm that the configuration has taken effect.
- Simulate an incremental data sync process, confirm that updated operation and maintenance logs can be normally accessed by the knowledge base, with no field mapping exceptions.
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.