What this category of data looks like
Data for this category originates from the internal ledger systems of equipment lessors, equipment financing filing databases of industry associations, and loan transaction records of financial institutions. Full synchronization of the previous day’s data is completed each day at midnight. Structured tables serve as the core documentation carrier. Each data entry includes equipment identification fields (equipment serial number, model), financing transaction fields (financing amount, financing term, loan date), subject fields (lessee, loan institution), and equipment usage scenario fields. Unified field units apply: financing amount is measured in ten thousand yuan, financing term in natural months, and dates follow the YYYY-MM-DD format.
Constraints imposed by these characteristics during model access and configuration
This category of data has high structural completeness and clear requirements for field formats. The model access link must support parsing and verification of structured data sources to prevent data import failures caused by mismatched field formats. The fixed daily update rhythm requires configuring scheduled daily data source synchronization tasks to ensure the latest financing daily report data can be called by the model in real time. The existence of equipment unique identification fields requires configuring data deduplication logic based on unique keys to prevent duplicate data from entering the knowledge base. At the same time, the specific requirements for field units must be clearly marked in the model prompt to avoid the model confusing the measurement standards of amount and term, which would affect the accuracy of subsequent analysis results.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
sync_cron | 0 1 0 * * ? | Matches the daily midnight synchronization rhythm for this category’s previous day’s data, ensuring timely triggering of data source pulls |
data_parse_strict_mode | Enabled | This category has strict requirements for data field formats. Enabling this mode verifies matching between field types and units, reducing import errors |
rag_retrieve_unique_key | equipment serial number | This field is the unique identifier for equipment financing data, allowing precise location of individual equipment financing records and avoiding redundant recall |
model_prompt_template | Please answer user questions based on the structured data of specialized equipment financing daily reports, following the rules that financing amount is in ten thousand yuan and financing term is in natural months | Clearly marks field measurement standards to avoid model confusion of units and improve the accuracy of analysis results |
api_request_timeout | 600 seconds | Allows sufficient time for batch validation and storage of structured data, preventing synchronization tasks from timing out and terminating |
duplicate_check_enabled | Enabled | Duplicate entries may exist in daily synchronized data. Deduplication based on unique keys prevents redundant knowledge base data |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by data format, data volume and business rules. Each scenario requires individual analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration mistakes
- Symptom: The model returns a
ParameterInvaliderror with the promptField unit mismatch. Cause: Field unit rules are not clearly specified in the model prompt, causing the model to generate non-compliant output that triggers API parameter validation failure. - Symptom: Multiple financing records for the same device appear in the knowledge base. Cause: The
duplicate_check_enabledconfiguration is not enabled, andrag_retrieve_unique_keyis not specified as the equipment serial number, causing duplicate data from daily synchronization to not be filtered out. - Symptom: The scheduled synchronization task times out and terminates, failing to complete the daily financing daily report import. Cause: The
api_request_timeoutconfiguration value is too small, failing to reserve sufficient time for batch validation and storage of structured data.
How to confirm the configuration is complete
- Manually trigger a data source synchronization, check the knowledge base import logs, and confirm there are no field format error prompts.
- Configure a model test call, input a query that includes the device model and financing amount, and verify that the model’s output units comply with the preset rules.
- Check the scheduled task run records to confirm that the daily synchronization task triggers at the preset time and completes data import.
- Retrieve entries in the knowledge base with the same device serial number, and confirm that only one valid record exists.
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.