What this category’s data looks like
Data sources for professional chain investment research include internal operating systems, supply chain management platforms, regional consumption monitoring reports, and publicly available industry research materials. Store operating data is updated daily. Supply chain inventory data is updated every three days. Regional consumption data is updated weekly. Industry research reports are updated monthly. Document formats primarily include structured tables, semi-structured operating ledgers, and text-image combined business district analysis documents. Fields include unique store codes, sales per square meter per day (yuan/sqm/day), average daily passenger traffic, monthly revenue amount, replenishment cycle days, SKU sales ratio, and other relevant metrics.
Constraints for Multi-turn Dialogue and Prompt Engineering
The data sources for this category are scattered, and update schedules vary significantly. Multi-turn dialogue must clarify the priority of data calls, and prioritize retrieving daily updated store operating data. The mixed format of structured ledgers and text-image analysis documents requires prompt engineering to distinguish parsing logic for different documents, and clearly define structured field matching rules. Differences in statistical definitions for different indicators, such as the measurement dimensions of sales per square meter and regional revenue, require multi-turn dialogue to unify indicator dimensions to avoid cross-dimensional confusion. Additionally, distinguishing between internal operating data and external industry reports requires clear labeling of data source display rules in prompt engineering to ensure the credibility of dialogue results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Professional chain investment research queries mostly involve cross-store, multi-cycle associated queries. Context information such as store codes and statistical cycles in multi-turn dialogue must be retained to avoid context overflow |
recallTopK | Top 8–12 results | This category’s data includes multi-dimensional indicators. Too many recalled results will cause context overload, while too few will fail to cover associated store and supply chain data |
similarityThreshold | 0.75–0.85 | Structured data field matching requires high similarity to avoid matching irrelevant store operating data |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large supply chain ledgers or regional analysis documents takes significant time, so sufficient parsing duration must be reserved |
promptTemplate | Filter data by store code and statistical cycle, clarify indicator statistical definitions, label data sources | Investment research queries for this category mostly revolve around specific stores and cycles, so unified indicator statistical rules are required |
UPLOAD_FILE_MAX_SIZE | 500 MB | Supply chain data documents for professional chains are usually large in size, so batch uploads of large ledger files must be supported |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volumes, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: An error message reading “No available index model detected” appears after refreshing the dialogue page. Cause: The professional chain store operating data index is not bound to the dialogue agent, or the index update task did not trigger normally.
- Phenomenon: The dialogue interface returns a 404 status code with no response body. Cause: The API interface path of the dialogue agent is configured incorrectly, or the port of the index service is not open for access.
- Phenomenon: The dialogue result does not display the source document information for the corresponding data. Cause: The prompt template is not configured with source labeling rules, or the recalled document metadata is not correctly associated with the dialogue context.
How to Verify Successful Configuration
- Upload a single store operating ledger document, trigger the index construction task, and confirm that the index status shows as ready.
- Create a test dialogue, enter a query statement containing a specific store identifier and statistical cycle, and verify that the dialogue returns matching indicator data.
- Call the dialogue interface, check if the response body includes the
sourcefield, and confirm that source document information can be displayed normally. - Modify the context window parameter, initiate two associated queries, and verify that multi-turn context is correctly retained.
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.