Model Access and Configuration for Auto Parts Yield Rate

What the data for this category looks like

Data for this category comes from three sources: domestic auto parts supply chain finance industry monitoring platforms, public quotation data from regional auto parts trading markets, and supporting supply ledgers from host factories. Data updates daily at midnight, syncing full market information from the previous full trading day. The document uses structured table format. Each row corresponds to a single component's daily market entry, with fields including part_code, part_name, supplier_id, report_date, purchase_price, sale_price, production_cost, and inventory_turnover_days. Price-related fields use yuan per piece as their unit. Turnover-related fields use natural days as their unit.

Constraints Imposed by Data Characteristics on Model Access and Configuration

This category's data characteristics create three clear constraints for model access and configuration:

There are many structured fields with close business correlations. Configure strict validation rules for field mapping to ensure part_code binds correctly to corresponding price and cost fields, and avoid model input mismatches.
Daily full batch data synced at midnight has large volume. Configure batch processing timeout thresholds and sharding rules to prevent task interruptions caused by single batch data overload.
Price-related fields use multiple pricing units. Configure unit normalization preprocessing logic to unify data standards before sending data to the model, ensuring consistent input data.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`batch_process_timeout`	`600 seconds`	The standard processing duration for daily full market data is 5-8 minutes. 600 seconds covers the execution cycle of most batch tasks
`field_mapping_strict_mode`	Enabled	Fields in this category have close business correlations. Strict mode prevents model input errors caused by field mismatches
`data_unit_normalization`	Enabled	Price-related fields have multiple unit formats such as yuan per piece and yuan per ton. Enabling this option automatically unifies pricing standards
`rerank_top_k`	Top 8 entries	There are many associated categories for auto parts. Sufficient candidate entries must be retained for the model to complete association matching
`datasource_priority`	Host factory ledger > trading market data	Host factory ledger data has higher accuracy. Prioritizing it improves the credibility of model output

The parameter values provided on this page are all common 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, and it is recommended to test on your own samples before finalizing the configuration.

Three Common Mistakes

Phenomenon: The number of results returned after rerank model call does not match expectations. Cause: The rerank_top_k parameter is not configured correctly, or the rerank model is not bound to the current knowledge base retrieval link.
Phenomenon: A [failed to get]-type FATAL error occurs when starting the container service. Cause: The server is offline, unable to pull model dependency images or sync market data source configurations.
Phenomenon: The conversation output contains a large number of meaningless punctuation marks such as # and *. Cause: The output content format filtering configuration is not enabled, and the markdown tags generated by the model are not automatically cleaned.

How to Confirm the Configuration is Complete

Upload a single structured market test file, check that the field binding relationship displayed on the field mapping interface matches the preset configuration.
Start a batch processing task, check that the task execution duration does not exceed the configured batch_process_timeout threshold.
Initiate a market daily report generation request, check that there are no redundant format punctuation marks in the output content.
Call the rerank model interface, check that the number of returned candidate entries matches the configured rerank_top_k value.

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.