What the data for this category looks like
The data for auto service financing daily reports comes from financing application ledgers of auto dealers, auto loan approval systems of partner financial institutions, and settlement records of supply chain finance platforms. Data is updated daily: full business data from the previous day is synced at midnight. The data structure is a standardized two-dimensional table, including fields such as dealer ID, dealer name, vehicle model series, number of financing applications, single financing amount range, actual received amount, number of overdue items, repayment date distribution, and number of partner financial institutions. The unit for amount fields is Chinese Yuan. Date fields follow the YYYY-MM-DD format. Vehicle model series are fixed enumeration-type names.
What constraints these characteristics impose on model access and configuration
The daily updated data source requires configuring a scheduled trigger task node to avoid data delays caused by manual synchronization. Mixed multi-field structured data requires configuring structured data parsing rules to ensure the model correctly identifies the association between enumeration fields, numeric fields, and date fields. The wide range of amount fields requires configuring vector normalization parameters to avoid impacts on retrieval accuracy from different magnitude values. The large number of fields per data entry requires configuring appropriate context truncation parameters to prevent exceeding the model's token limit.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
embedding_normalization | Enabled | Financing daily reports include amount fields with wide ranges. Enabling this unifies the vector value range and improves retrieval matching accuracy. This corresponds to the vector model normalization configuration capability added in version 4.8.23. |
schedule_interval | 86400 seconds | Financing daily reports are daily updated business data. The scheduled synchronization interval matches the data update frequency to ensure the model uses the latest business information. |
tool_choice | auto | Allows the model to independently determine whether to call the structured data parsing tool, adapts to the multi-field association query requirements of financing daily reports, and resolves issues where the model cannot independently call tools. |
max_token_per_chunk | 1000-1200 characters | Each dealer data entry includes multiple fields. Chunking within this range retains core business information while avoiding exceeding the model's context limit. |
parse_structured_data | Enabled | Financing daily reports are standardized two-dimensional tables. Enabling this automatically extracts field association relationships and improves the model's efficiency in understanding structured data. |
image_analysis_enabled | Disabled | Financing daily reports are text-structured data. Multimodal visual analysis is not required, which avoids triggering unnecessary image download and parsing processes. |
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 on-site analysis. It is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: The model stream response is empty, and the interface prompts "Model stream response is empty, please check model stream output". Cause:
embedding_normalizationis not enabled, and the wide range of amount fields causes abnormal vector generation, triggering model response truncation. This is a common issue for some model access failures in version 4.9.2. - Phenomenon: The multimodal visual model calls the interface with an error, and image analysis cannot be completed. Cause:
image_analysis_enabledis enabled, but no valid image download whitelist is configured, or the image links in the data source cannot be accessed by the platform. This matches the Qwen2.5-vl call error scenario reported by users. - Phenomenon: The model does not independently call tools in the workflow, and only returns text results directly. Cause:
tool_choiceis configured as a fixed tool name instead ofauto, which restricts the model's authority to independently select tools based on query requirements.
How to confirm the configuration is complete
- Manually trigger a data synchronization task, and check whether the field mapping after structured data parsing matches the field names and units of the original daily report.
- Initiate a query that includes amount fields, and confirm that the amount values in the model's returned results match the original data, and no unit confusion occurs.
- View the scheduled task logs of the workflow, and confirm that the task is automatically triggered at the set interval with no timeout or failure records.
- Test a query requirement that includes multi-field association, and confirm that the model independently chooses whether to call the structured data parsing tool based on the query content.
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.