What the data for this category looks like
Historical query record data originates from end-user search interaction logs. It covers natural language search operations in finance, insurance, and wealth management applications. Data is written in real time after each search operation completes. No batch aggregation delay exists. The document structure of a single record uses standardized JSON format. It includes these fixed fields: query time (millisecond-level timestamp), unique user identifier (anonymized string), query text, search latency (in seconds), and associated search result ID. Text length values for each record vary widely. It is recommended to confirm values based on sample statistics or actual testing. No nested complex structures are present.
What constraints do these characteristics impose on the "model integration and configuration" link?
The real-time update feature of historical query records requires the model integration link to support high-frequency, small-batch search requests. This avoids data lag caused by index update delays. The short text attribute of a single record requires the recall model to adapt to short text semantic matching. This prevents semantic deviation. The fields include a unique user identifier. This requires the model integration link to support filtering data by user dimension. This ensures privacy compliance in finance scenarios. The high frequency of search operations requires call frequency limits to align with actual business needs. This avoids triggering quota limits on model APIs.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 800-1200 characters | Single historical query record has short text. This value balances semantic matching accuracy and context resource usage |
Recall Count | Top 3-5 entries | Total historical query records per user are limited. Excessive recall introduces irrelevant history and reduces search accuracy |
Similarity Threshold | 0.75-0.85 | Adapts to the accuracy requirements of short text semantic matching. It effectively filters irrelevant historical query records |
INDEX_MODEL | Determined through actual testing | Historical query records are short text. An index model adapted to short text semantic matching is required. Specific selection must be verified against the business scenario |
API_RATE_LIMIT | 10-20 requests/minute | Aligns with user search frequency in finance scenarios. This avoids triggering the 429 Too Many Requests error from model APIs |
USER_ID_FILTER_ENABLE | Enabled | Ensures privacy and security of user historical query records. Only returns search data for the current user |
The parameter values provided on this page are all common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. Actual testing on samples is recommended before finalizing values.
Three common configuration mistakes
- Phenomenon: Model calls return
401 Unauthorized. The interface displays authorization verification failure. This error occurred when adapting Qwen3 in version 4.9.6, for example. Cause: New authentication logic is not adapted. Some models use token-based authorization, and correct authentication parameters are not filled in the configuration. - Phenomenon: Concurrent calls result in
429 Too Many Requestsbeing returned. Search results are delayed or empty. Cause: Reasonable call frequency limit parameters are not set. Concurrent requests exceed the quota of the model API. - Phenomenon: Search results do not include historical query records for the target user. Cause: The
USER_ID_FILTER_ENABLEconfiguration is not enabled, or the mapping of the unique user identifier field is incorrect.
How to verify a successful configuration
- A test historical query record is submitted. The search results returned by the interface are checked to confirm they include historical data for the corresponding user. The number of results is verified to match the
Recall Countsetting. - Model call logs are reviewed. Errors of type
401 Unauthorizedor429 Too Many Requestsare confirmed to be absent. Authentication parameters are verified to be configured correctly. - The
Similarity Thresholdparameter is adjusted. Changes in the matching degree of search results are observed. The threshold setting is verified to meet business requirements. - Concurrent requests are simulated. Interface calls are checked for triggering frequency limits. The
API_RATE_LIMITparameter is confirmed to take effect.
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.