What the Data for This Category Looks Like
Footwear financing daily report data is sourced from brand dealer financing systems, footwear SKU inventory ledgers, and order payment collection records. Full data updates run every day at midnight. Documents are grouped by brand and footwear category. Each daily report includes fields including SKU code, footwear name, shoe size range, per-unit financing amount, total accumulated financing amount, payment arrival date, and number of overdue days. Shoe size ranges are labeled in the format "35-40 sizes". Financing amounts use Renminbi yuan as the unit, and overdue days use calendar days as the unit. The length of complete daily report documents varies widely. It is recommended to confirm based on internal sample statistics or actual testing.
Constraints for Multi-turn Dialogue and Prompt Engineering
The multi-SKU attribute of footwear financing daily reports requires conversations to retain key SKU identifiers to avoid mixing financing data for different footwear styles. The daily update requirement means prompts must clearly limit query scope to that day’s data to prevent redundant historical information from being returned. The variety of fields and units requires prompts to uniformly specify return formats to avoid unit confusion or missing fields. The long document characteristic means dialogue systems must handle large input contexts, and also intercept over-limit inputs to prevent abnormal large language model responses. The detailed attributes of footwear SKUs require multi-turn dialogue to handle user-subdivided sub-questions, gradually clarifying the financing status of specific footwear styles.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | Previous 10 turns of dialogue | Footwear financing questions mostly focus on the current SKU. Excessively long contexts will introduce redundant information that interferes with responses |
prompt_template | Only return that day's footwear financing data, including SKU code, footwear name, shoe size range, financing amount (yuan), payment arrival date | Clearly define the data scope and return fields, adapting to the multi-field characteristics of footwear financing daily reports |
input_token_limit | 8000 characters | Single footwear financing daily report documents have relatively long lengths. It is necessary to limit the number of input characters to avoid triggering the large language model's upper limit |
conversation_memory_max_length | 5 context entries | Retain key SKU identifiers and historical questions to ensure multi-turn dialogue focuses on financing queries for the current footwear style |
enable_citation | Enabled | Add the cite_id field to returned results, associating with specific data source entries |
error_interception_rule | Return "Input content is too long, please split and try again" when the number of input characters exceeds 8000 | Intercept over-limit inputs to avoid directly returning empty results or abnormal error reports |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to conduct actual testing on internal sample datasets before finalizing settings.
Three Common Configuration Errors
- Phenomenon: Multi-turn dialogue fails to recall the financing question for a specific footwear style, and subsequent replies deviate from the target SKU. Cause: The
conversation_memory_max_lengthconfiguration is not enabled, or the context length is set too short to retain key SKU identifiers. - Phenomenon: Calls to the dialogue interface return results without the
cite_idfield. Cause: Theenable_citationconfiguration item is not enabled, or the prompt does not clearly require associating data source citations. - Phenomenon: When input content exceeds the AI input limit, empty results or error reports are returned directly. Cause: The
error_interception_ruleis not configured to intercept over-limit requests, and over-limit content is passed directly to the large language model.
How to Verify Successful Configuration
- Initiate a multi-turn dialogue that includes multiple footwear SKUs, and verify that replies accurately associate financing data with the corresponding SKU.
- Call the dialogue interface, and check that returned results include the
cite_idfield. - Construct an input request that exceeds the preset character limit, and verify that the preset interception prompt is returned.
- View the dialogue history record, and confirm that key contexts are retained and not automatically cleared.
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.