What the Data for This Category Looks Like
The data for power grid equipment research reports primarily comes from publicly available industry reports, operation and maintenance technical documents from power grid enterprises, and special research results from third-party power consulting institutions. Update rhythm follows this schedule: core equipment operating condition parameters are updated monthly, complete category research reports are released quarterly, and industrial panorama analysis documents are updated annually. Document structure is fixed, including three modules: core parameter table, operating condition test data, and industrial chain correlation analysis. Core fields include technical parameters with clear physical units, such as rated voltage (unit: kV), rated capacity (unit: MVA), short-circuit impedance (unit: %), and installation altitude (unit: m).
Constraints Imposed on Workflow Orchestration
The fixed structure of power grid equipment research reports and the technical fields with units impose three constraints on workflow orchestration. First, core parameters include clear physical units. The text extraction node must be configured with unit matching rules to avoid extracting ambiguous values without units. Second, different update rhythms lead to different content focuses for documents. The workflow must filter data sources by release time, prioritizing recall of the latest monthly operating condition data and quarterly complete research reports. Third, the fixed document structure allows setting targeted segmentation rules. Skip irrelevant industrial chain analysis modules, only extract the core parameter table and operating condition test data, and reduce invalid recalled content.
Configuration Settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The core parameter table in power grid equipment research reports has relatively large content. Sufficient context must be retained to avoid truncation of core technical fields |
Recall count | Top 8–12 results | Need to cover mixed data sources of monthly operating condition data and quarterly complete research reports. Avoid excessive recall results that cause context overflow |
Similarity threshold | 0.75–0.85 | Technical parameters require high matching accuracy. Avoid recalling irrelevant general power documents |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Complete research reports have relatively many pages. Parsing takes a long time, so the timeout period must be extended |
Chunk size | 1000–1500 characters | Adapt to the length of single block content in the core parameter table. Avoid splitting parameter fields and causing extraction errors |
Rerank result count | Top 3–5 results | Focus on the most relevant core technical parameter documents. Reduce processing load on downstream nodes |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing the configuration.
Three Common Misconfigurations
- Symptom: Prompt variables passed during API calls do not take effect, and returned content is unrelated to the preset topic. Cause: The binding relationship of the corresponding parameters was not configured in the Variable Mapping node of the workflow, causing variables to not be correctly injected into the prompt template.
- Symptom: The
PARSE_FILE_TIMEOUTerror code is displayed during workflow debugging. Cause: The setPARSE_FILE_TIMEOUT_SECONDSvalue is less than the actual parsing time of a single research report, causing the parsing process to be forcibly terminated. - Symptom: The Text Content Extraction node returns empty fields, and the workflow does not enter the waiting for user input state after triggering Specified Reply. Cause: The Wait for User Input connection node was not configured after the Specified Reply node, causing the workflow to terminate directly.
How to Confirm Proper Configuration
- Trigger a test call, check whether the parameter values of the Variable Mapping node in the workflow log match the passed API parameters.
- Check the extraction results of the Text Content Extraction node, confirm that core technical fields such as rated voltage and rated capacity have been correctly extracted.
- View the return results of the Data Source Filtering node, confirm that the release time of the recalled documents complies with the preset update rhythm filtering rules.
- Verify the trigger conditions of the Specified Reply node, confirm whether the preset prompt content is correctly output when the extracted fields are empty.
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.