What the data for this category looks like
Condiment yield rate related data primarily comes from publicly monitored datasets released by domestic food and beverage industry associations, and sales movement data reported by offline retail terminal POS systems. There are two update schedules: regional-level sales movement data is updated weekly, and national-level guide price data is updated monthly.
Documents use a structured format. Each record contains fields including product SKU code, brand name, terminal retail unit price, wholesale supply unit price, coverage area, and statistical cycle start date. Unit price fields use units of yuan per kilogram or yuan per 500 milliliters, and there are no additional percentage-based statistical fields.
What constraints do these characteristics impose on model integration and configuration
The differences in update cadence, multi-field structure, and diverse units of condiment data impose multiple constraints on model integration configuration. The dual weekly and monthly update schedules require that scheduled task trigger rules match the update cycles of the corresponding data sources, to avoid calling old data that has not completed updating. The multi-field structured format requires configuring field mapping rules to map external data source fields to the yield rate calculation fields required by the model. The two unit price formats require configuring unit normalization parameters to unify the calculation benchmark. Additionally, in scenarios with a large number of SKUs, a timeout threshold for batch data processing must be configured to avoid single-batch processing timeouts.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
PARSE_FIELD_MAPPING | Associate retail unit price and wholesale unit price fields using SKU code | Structured data sources use SKU as the unique identifier, so the correspondence between external fields and model calculation fields must be clearly defined |
UNIT_CONVERSION_RULE | Unify conversion to yuan per kilogram, using 1000 milliliters equivalent to 1 kilogram for conversion | Condiment unit prices commonly use two units: yuan per 500 milliliters and yuan per kilogram, so the calculation benchmark must be unified |
CRON_EXPRESSION | Configure two rules: 0 0 2 * * 1 and 0 0 4 * * * | Match the schedule where regional weekly data is updated every Monday, and national monthly data is updated on the 4th of each month |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Sufficient processing time must be reserved for multi-SKU batch data parsing to avoid mid-process timeout interruptions |
SIMILARITY_THRESHOLD | 0.75–0.85 | Condiment SKUs have high similarity, so the threshold must be raised to filter irrelevant matching results |
RECALL_TOP_K | Top 8 entries | A single category has a large number of SKUs, so the number of recalled entries must be limited to avoid model overload |
The parameter values provided on this page are all conventional recommendations used as starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to conduct tests on your own samples before finalizing the settings.
Three common configuration mistakes
- Symptom: The large language model returns
model stream response is empty. Cause: Field mapping rules for condiment data are not configured, so the model cannot identify valid fields in the data source, resulting in no valid content available for generating broadcast content. - Symptom: A
408 Request Timeouterror is triggered during batch data parsing. Cause: The value set for thePARSE_FILE_TIMEOUT_SECONDSparameter is less than the time required for actual data processing, failing to match the time consumption requirements of multi-SKU batch processing. - Symptom: The
m3eembedding model cannot be called normally after configuration. Cause: The API address or key verification rules of the embedding model were not updated after a version upgrade, resulting in an interruption of the model access link.
How to confirm the configuration is complete
- Execute a terminal curl command to call the model access interface, and check whether the returned data source fields match the configured mapping rules.
- Trigger a scheduled data synchronization task once, and check whether there are no prompts for field parsing failures or unit conversion exceptions in the task logs.
- Test the yield rate broadcast function, and verify whether the generated content includes correct SKU, unit price, and statistical cycle information.
- View the model call monitoring metrics to confirm that the number of recalled entries and similarity matching results conform to the preset configuration rules.
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.