What the data for this category looks like
Consumer electronics research reports primarily originate from consumer electronics teams at securities firm research institutes, vertical industry information platforms, and publicly disclosed reports from supply chain manufacturers. Update cadence adjusts based on new product release cycles and quarterly earnings report deadlines. Some supply chain dynamic reports receive weekly or real-time updates. Document structures typically include core summary viewpoints, supply chain upstream and downstream breakdowns, core product technical parameters, market shipment forecasts, and competitive benchmarking analyses. Fields include publishing institution, publish date, covered product category, shipment volume, core component model, and more. Shipment volume units are mostly millions of units, and technical parameter fields include specific values such as screen size and chip manufacturing process.
What constraints do these characteristics impose on the multi-turn dialogue and prompt engineering link
The multi-source heterogeneous sources, uneven update cadence, numerical fields with clear units, and multi-category coverage of consumer electronics research reports create multiple constraints for the multi-turn dialogue and prompt engineering link. Differences in formats across multi-source reports require prompt engineering to preset unified field alignment rules, ensuring standardized processing of content from different report sources. Differences in update cadence require multi-turn dialogue to retain context timestamps, associating report content across different periods and avoiding confusion between new and old data. Numerical fields such as shipment volume and technical parameters with units require prompt engineering to explicitly specify unit verification logic, preventing errors where numerical values do not match their units. Multi-category coverage requires dialogue context to recognize user-switched product categories, avoiding parameter confusion across categories.
How to configure settings
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | A single consumer electronics research report often spans thousands of characters. Multi-turn dialogue needs to retain 3-4 rounds of context. This range balances context completeness and computational efficiency |
recall_topk | Top 10–15 results | Consumer electronics research reports cover multiple subcategories. Too many recalled results introduce redundant information, while too few fail to cover professional content for specific scenarios |
similarity_threshold | 0.75–0.85 | The consumer electronics field has dense professional terminology. This threshold ensures recalled content highly matches query requirements while avoiding missing relevant reports for subcategories |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Parsing long-form research reports requires extended processing time. This value prevents mid-parsing timeouts for standard research reports |
max_history_length | 5–7 turns | Multi-turn queries for consumer electronics often involve category switches and time span adjustments. This length retains necessary context while avoiding interference with current query logic |
prompt_template | Combine past dialogue context, extract corresponding fields from recalled consumer electronics research reports, clearly label report sources and publish dates, and verify numerical units | Adapts to multi-turn dialogue association requirements and professional field verification needs for consumer electronics research reports |
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 it is recommended to test on your own samples before finalizing settings.
Three common misconfigurations
- Symptom: After passing custom parameters into the prompt code block of the text content extraction module, the complete response returns the code block content as
undefined. Cause: The binding logic for this custom parameter was not configured in the prompt template, causing the module to fail to parse the passed parameter values. - Symptom: After deleting a single conversation record, the associated logs generated by the system are also cleared. Cause: The binding deletion configuration for
delete_log_modeis enabled, and no independent log retention rule is set, causing logs to be cleared along with conversation deletion. - Symptom: Multi-turn dialogue fails to associate product category queries from the previous round, and the current response does not cover the previously mentioned consumer electronics subcategory parameters. Cause: The prompt template does not explicitly require association with historical context, and the
max_history_lengthconfiguration value is too low to retain sufficient dialogue context information.
How to verify successful configuration
- Initiate a multi-turn query involving category switches, verify whether the response associates the previous round's product parameters, confirming that the context retention logic is active.
- Pass custom parameters into the prompt, check whether the code block content in the complete response is parsed correctly, confirming that the parameter binding logic functions properly.
- Test a long-form research report parsing task, confirm that no parsing timeout errors occur, verifying that the timeout configuration value is reasonable.
- Perform a single conversation deletion operation, check whether associated logs are retained, confirming that the log retention configuration is correct.
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.