What This Data Looks Like
Data for urban commercial bank yield and market daily reports primarily comes from daily deposit and loan, wealth management product revenue calculation results from internal urban commercial bank operation systems, and interbank business listing quotes disclosed on official channels. Data is fully updated at a fixed time each day. The primary presentation format is structured tables, including fields such as product unique code, product type, term range, access threshold, daily revenue calculation value, and effective date. The unit for access threshold is yuan, the unit for term range is calendar days, and daily revenue calculation values use standardized numeric formats.
Constraints on Multi-turn Dialogue and Prompt Configuration
The structured layering, daily update characteristics, and multi-field requirements of urban commercial bank yield data impose multiple constraints on multi-turn dialogue and prompt configuration. First, data is layered by product unique code and type. Prompts must clearly specify field matching rules to avoid result deviations from fuzzy queries. Second, the fixed daily update feature requires multi-turn dialogue to support contextual date filtering, automatically associating today’s valid data to prevent calling expired information. Third, the structured multi-field format requires prompts to strictly limit the range of returned fields. Multi-turn dialogue must also limit context length to prevent model context overflow from excessive fields. Additionally, product types cover deposits and loans, wealth management products, and interbank business. Prompts must preset classification boundaries to prevent cross-category mixed queries.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Urban commercial bank yield data includes multiple fields. Multi-turn dialogue must retain key information such as product codes and terms to avoid context overflow |
contextRetainHours | 24 hours | Urban commercial bank yield data is updated daily. Context older than 24 hours has no reference value, preventing calls to expired data |
promptTemplate | Only return specified fields, prioritize matching product codes mentioned in queries, retain only data from the last 24 hours in context | Clearly define the scope of returned content and data timeliness, matching the update rhythm and structured data characteristics of urban commercial bank daily reports |
maxSearchResults | Top 3 results | The number of products in a single daily report for urban commercial banks is relatively concentrated. Excessive recall increases context load, and querying parties typically only focus on specified or popular products |
imageRecognitionEnabled | Disabled | Urban commercial bank yield data is structured text with no image recognition needs, preventing the model from misjudging non-target content |
logRetentionStrategy | Retain associated with conversations | Logs before deleted conversations must be retained for troubleshooting, meeting business traceability requirements |
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 individual analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Symptom: Associated conversation logs are deleted synchronously after deleting a multi-turn dialogue, making historical query records untraceable. Cause:
logRetentionStrategyis not configured to retain associated with conversations; the default policy clears logs synchronously when a conversation is deleted. - Symptom: Prompts cannot correctly reference product information from multi-turn dialogue, with returned results unrelated to the context. Cause: The prompt template does not clearly specify context calling rules, and does not bind context range parameters.
- Symptom: After enabling multimodal image recognition, uploading yield daily report images fails to return valid content. Cause: Urban commercial bank yield data is structured text, and the processing scope is not limited in the prompt, causing the model to misidentify image content as non-text format.
How to Verify Successful Configuration
- Initiate a single-turn query including a product code, verify that returned results include the preset specified fields to confirm the prompt template is active.
- Initiate two associated queries, such as first querying a specific product followed by an inquiry about its term, verify that the model automatically associates contextual information to confirm the context window and retention duration configurations are correct.
- Delete the current conversation, verify that background logs still retain the historical records of that conversation to confirm the log retention strategy configuration is correct.
- Upload a structured yield daily report image, verify that the model only returns text query results to confirm the multimodal recognition switch 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.