What the data for this category looks like
Photovoltaic marketing-related data falls into three categories. Business operation data comes from power station monitoring SCADA systems and third-party meteorological service interfaces. Product marketing data comes from the internal enterprise product library and third-party certification document libraries. Historical marketing materials are archived in the enterprise storage system. Real-time operating indicators update every 10 seconds. Product parameter documents are synchronized and updated every quarter. Historical marketing materials are archived monthly. The document structure includes structured parameter sets with fixed fields such as peak power Wp, open-circuit voltage Voc, and component size mm, as well as unstructured installation guide manuals and project case documents.
What constraints these characteristics impose on the "workflow orchestration" link
The second-level update requirement for real-time data means workflow trigger nodes must support event-driven or very short-interval scheduled scheduling, to avoid expired data being used for marketing content calls due to fixed long intervals. The fixed units and dedicated fields for structured parameters mean parameter parsing nodes need custom field mapping rules, and cannot rely on general parsing logic to match photovoltaic-specific parameters. The presence of long documents means document splitting nodes need to set reasonable segment thresholds, to retain the integrity of technical parameters while avoiding context overflow. The fixed format of historical archived materials means the workflow must support connecting to PDF and CSV format reading paths from archived storage, to ensure historical materials can be loaded normally.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
Trigger Mode | Event Trigger (every 10 seconds) | Matches the update rhythm of photovoltaic real-time operating data, ensuring marketing content calls the latest power station and meteorological data |
Document Segment Length | 800–1200 characters | Adapts to the long-text structure of photovoltaic installation manuals, retains the integrity of technical parameters while avoiding context overflow |
Field Mapping Rules | Custom mapping: Peak Power → Wp, Component Size → mm | Matches the dedicated fields and units of photovoltaic marketing materials, avoiding parameter confusion caused by general parsing |
AI Conversation Context Window | 4096 tokens | Covers the multiple sets of parameters and meteorological data context required for photovoltaic marketing content, ensuring the logical completeness of AI-generated content |
File Reading Path | Photovoltaic product library directory in archived storage | Uniformly reads the latest photovoltaic component certification and installation documents, ensuring the accuracy and timeliness of marketing materials |
The parameter values provided on this page are all conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- The symptom is a
Cannot convert undefined or null to objecterror when running the workflow. The cause is that the field mapping rules for photovoltaic parameters are not configured, resulting in empty parsed structured data, which triggers a type error when passed to downstream nodes. - The symptom is being unable to pass historical photovoltaic marketing materials as global variables into the workflow. The cause is that the reading trigger for the archived directory is not added in the workflow's variable configuration, resulting in historical data not being loaded as usable variables.
- The symptom is AI conversation output displayed directly without being processed by a text splicing component. The cause is that the
AI Conversation Direct Outputswitch is not turned off, and the trigger dependency for the output node is not configured, resulting in the splicing logic not being executed.
How to confirm the configuration is complete
- Manually trigger the workflow, check the output logs of the parameter parsing node, confirm that fields such as peak power and component size have been correctly extracted and matched with their corresponding units.
- Check the scheduling configuration of the trigger node, confirm that the trigger interval matches the update rhythm of photovoltaic data.
- After running the workflow, check the results of the output node, confirm that AI-generated content has been processed by the text splicing component before being output.
- View the global variable list, confirm that the reading path for historical photovoltaic marketing materials has been added as a usable variable.
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.