What Data for This Category Looks Like
The data sources for optoelectronics industry research reports mainly cover track-specific reports from securities research institutes, monthly supply and demand statistics released by industry associations, and quarterly financial report summaries of publicly disclosed manufacturers. Update cycles vary: securities firm special reports are released irregularly, industry monthly reports are usually updated in the middle and late months of each month, and manufacturer financial reports are updated on a quarterly or semi-annual cycle. Document structures typically include core data such as track supply and demand scale, individual product gross profit margin, yield rate, shipment volume, etc. Most fields have clear units: for example, shipment volume is measured in millions or thousands of pieces, gross profit margin is marked as a percentage, and technical parameters include professional indicators such as panel resolution and response time.
What Constraints Do These Characteristics Impose on the "Workflow Orchestration" Link
The multi-source and heterogeneous nature of optoelectronics industry research reports requires adding data standardization nodes in the workflow to uniformly handle unit formats and field naming differences across different sources. The wide gap in update cycles requires configuring differentiated scheduled trigger rules to distinguish the synchronization rhythms of monthly industry data and quarterly financial report data. Individual research reports are lengthy and dense with professional terminology, so reasonable paragraph splitting and context stitching parameters must be set to avoid exceeding the model's context window. An industry-specific terminology library must also be mounted to ensure the accuracy of retrieval and Q&A. In addition, the multi-dimensional data requirements of segmented tracks require that the recall node of the workflow covers enough relevant fragments to avoid missing key information.
How to Set Configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Optoelectronics industry research reports contain lengthy professional content such as supply and demand, gross profit margin, and technical parameters, requiring coverage of complete data fragments to avoid truncation |
RECALL_TOP_K | Top 8–12 results | Segmented tracks cover multi-dimensional data, requiring sufficient relevant fragments to support complete Q&A |
SIMILARITY_THRESHOLD | 0.72–0.78 | Industry terminology has high similarity, balancing recall precision and coverage to avoid missing segmented track data |
PARSE_FILE_TIMEOUT_SECONDS | 300–600 seconds | Parsing lengthy single research report PDFs/Word documents takes longer, adapting to parsing requirements for complex layouts |
HTTP_REQUEST_TIMEOUT | 600 seconds | Some industry data source interfaces respond slowly, adapting to time requirements for batch pulling multiple rounds of research reports |
WORKFLOW_LOOP_MAX_TIMES | 5–8 times | Control loop times when cyclically pulling monthly industry data, avoiding invalid repeated execution |
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 targeted analysis, and testing on local samples is recommended before finalizing configuration.
Three Common Mistakes
- Phenomenon: An empty value is returned when an API is called to trigger a workflow nested with a knowledge base assistant. Cause: In versions v4.8.10 and above, the input variables of the knowledge base assistant node must strictly match the preset parameter format. An empty return occurs when valid query or context parameters are not provided.
- Phenomenon: A
quote type errorerror pops up when referencing knowledge base variables. Cause: The passed variable type does not match the receiving type preset by the node. For example, directly passing numeric shipment volume data into a string-type variable slot without pre-converting the type. - Phenomenon: After the tool call module executes, both an AI reply and a trigger for the next-level branch are output. Cause: The branch execution policy is not configured as serial mode. In the default parallel mode, multiple associated processes will be triggered simultaneously.
How to Confirm Configuration Is Complete
- Initiate a test API call, passing a query term for an optoelectronics industry segmented track, and check whether matching research report data fragments are included in the returned results.
- View the workflow running logs to confirm that the time consumption of data parsing, recall, and branch execution conforms to the preset timeout configuration.
- Manually trigger the loop node to check that the number of loops does not exceed the preset maximum limit, and no invalid repeated pulling behavior occurs.
- Check the reference configuration of knowledge base variables, and confirm that no
quote type erroris triggered after passing test variables.
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.