What the data for this category looks like
Data for specialized chain industry research reports comes from professional research institutions in the commercial and retail sector, publicly available operational reports of chain brands, and monthly monitoring data from industry associations. Core operational fields are updated monthly. Full-link analysis content is updated quarterly. Industry landscape reports are updated annually.
Document structure includes two parts: structured fields and unstructured analysis. Structured fields include number of stores (unit: stores), per-store revenue per square meter per month (unit: yuan/square meter/month), supply chain turnover times (unit: times/quarter), member visit frequency (unit: times/year). Unstructured content includes regional store performance, supply chain optimization suggestions, and similar content.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompting
The monthly update feature of specialized chain industry research reports requires that multi-turn dialogue clearly guide users to specify the report time range, to avoid retrieving expired data. Structured fields have clear units. Prompts must mandate that models annotate corresponding units when citing data, to prevent confusion between operational indicators of different categories.
Documents are divided into structured and unstructured types. Multi-turn dialogue must first guide users to clarify the retrieval type, to avoid invalid cross-type queries. The track limitation requires prompts to clearly specify that the retrieval scope is limited to the commercial retail specialized chain track, to prevent retrieval of general retail data.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Single analysis content of specialized chain industry research reports is relatively long. Sufficient multi-turn dialogue context must be retained to avoid truncation of key retrieval conditions and historical responses |
Recall count | Top 6–8 entries | Structured data of specialized chain industry research reports is scattered across different documents. A sufficient number of entries must be retrieved to cover multi-dimensional data such as stores and supply chains |
Similarity threshold | 0.72–0.78 | Balance the relevance and coverage of research report content, to avoid retrieving general retail data from non-chain tracks |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Specialized chain industry research reports contain multi-dimensional structured tables. Parsing takes a long time, so the timeout period must be extended |
Enable Source Citation Mark | Enabled | Each retrieval result must be bound with source document information to support dialogue log annotation and compliant citation |
Auto-reply to Dialog Box | Disabled | AI-generated content must be passed to the text splicing component for processing before output, to meet workflow custom display requirements |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: No field units are annotated in AI dialogue responses, and the per-store revenue per square meter per month value does not match its corresponding unit. Cause: The prompt does not clearly require the model to annotate corresponding units when citing data, and the
Recall countconfiguration does not cover enough structured data entries. - Phenomenon: AI dialogue-generated content is directly displayed in the front-end dialog box in the workflow, without being processed by the text splicing component. Cause: The
Auto-reply to Dialog Boxswitch of the AI dialogue module is not turned off, and the AI output node is not bound to a custom output component. - Phenomenon: The annotation function of the dialogue log cannot be associated with the corresponding research report fragment, and the retrieval source is not displayed in the response. Cause: The
Enable Source Citation Markconfiguration is not enabled, and the prompt does not specify that retrieval source information must be retained.
How to Verify Proper Configuration
- Initiate two rounds of dialogue. First ask "Per-store revenue per square meter per month for national specialized chain supermarkets in the first quarter of 2024", then follow up with "Corresponding data for the East China region". Check that the context retains the time range and regional restrictions, and no unit confusion occurs.
- Enter the workflow test page, trigger the complete link. Check that there is no temporary output in the front-end dialog box, and only the final organized response is displayed after the text splicing component completes execution.
- View the dialogue log. Confirm that each retrieval result has a jumpable source document mark, and the annotation function can normally associate with the corresponding chapter and field of the research report.
- Pass custom research report retrieval source data. Check that the AI dialogue can correctly identify field names and corresponding units, and generate compliant citation annotations.
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.