What the data for this category looks like
Crop farming yield rate related data comes primarily from publicly monitored data released by the Ministry of Agriculture and Rural Affairs, plus daily planting ledgers and market purchase price data reported by local agricultural technology extension stations. Data updates occur once per day, covering the full process of crop planting, harvesting, and trading on the current day. Each data document includes fields such as crop type, planting region, daily yield, per-area revenue, core cost components, and market purchase price. Yield is measured in kilograms per mu, revenue and cost are measured in yuan per mu, and purchase price is measured in yuan per kilogram.
What constraints these characteristics impose on model access and configuration
The daily update cadence of crop farming yield rate data requires configuring a scheduled pull task trigger frequency that matches the one-day data generation cycle. The multi-field structure with dedicated units requires clear unit association rules during field mapping, to avoid mixing up yield and purchase price units. Differences in fields across crop types require configuring classification recognition rules to adapt to data source structures for different crops such as grain and vegetables. Additionally, daily data volume is moderate but fields are tightly linked, requiring a reasonable context window configuration to ensure the model can fully associate relationships between cost, revenue, and market prices.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
llmModels | ["qwen2.5-14b-int4", "baichuan2-13b-int4"] | Crop farming yield rate analysis requires understanding agricultural production terminology. Multi-model configuration covers different scenario requirements, and int4 quantization supports lightweight deployment |
maxContext | 8000–12000 characters | Daily crop farming yield rate data documents contain multi-field associated information. This range fully accommodates a single data document and conversation context to avoid truncation |
dataRefreshInterval | 86400 seconds | Crop farming yield rate data is updated daily. This interval matches the data generation cycle to ensure access to the latest same-day data |
fieldMappingRule | Match corresponding fields by crop type | Calculation fields for revenue vary across different crops. Matching by crop type avoids field misalignment |
similarity threshold | 0.85 | Filters low-match historical data to ensure recalled data is strongly relevant to the current analysis scenario |
maxRecallCount | Top 3 entries | Single crop farming data documents have high relevance. A small number of recalls covers the core historical data required for analysis |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis. It is recommended to test on your own samples before finalizing settings.
Three common configuration errors
- A prompt indicates a specified model call failed, but the default model is actually used. Cause: The
llmModelsarray configuration is incomplete. The system only loads the first configured item and fails to recognize subsequent model configurations. - Analysis content returned by the knowledge base is truncated. Cause: The
maxContextconfiguration value is smaller than the total character count of a single crop farming data document and conversation context. Excess content is automatically truncated. - The model channel is verified as normal, but no response is returned after sending a question. Cause: The
dataRefreshIntervalconfiguration does not match the data update cycle, preventing the model from obtaining valid data sources to generate a response.
How to confirm the configuration is complete
- Navigate to the model management interface, verify the array content of the
llmModelsconfiguration item, and confirm it includes all planned access models. - Manually run a data synchronization task, and check if the obtained dataset contains complete fields and correct units related to crop farming yield rates.
- Initiate a single-round test conversation, input a question related to crop farming yield rate analysis, and confirm the returned content is not truncated and relevant to the input question.
- Check the system operation logs to confirm there are no abnormal error reports related to model calls or data source pulling.
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.