Multi-turn Dialogue and Prompting for Crop Farming Yield and

What Data for This Category Looks Like

Data related to crop farming yield and returns comes from three primary sources: national agricultural statistics published by the National Bureau of Statistics, fixed monitoring point data from the Ministry of Agriculture and Rural Affairs, and public data from the National Agricultural Wholesale Market Price Information Network. Data update cycles fall into three categories: weekly spot price data for bulk crops in major producing areas, monthly cost and return data for national-level crops, and quarterly survey data for specialty crops. Individual data documents are organized by crop type. Each crop entry includes fields such as input per unit area, yield per unit area, sales revenue per unit area, and net income per unit area. Field units use standard agricultural production units such as yuan/mu and kg/mu. No percentage-derived indicators are included in the data.

Constraints for Multi-turn Dialogue and Prompting

Data sources are scattered and cover different administrative levels. Multi-turn dialogue must first guide users to specify the exact crop type and producing area. This prevents information confusion across crop categories or regions.

Data update cycles vary across data sets. Prompts must clearly state the update cycle of the currently called data. This prevents access to outdated information.

Fields use mu as the core statistical unit. Multi-turn dialogue must standardize unit descriptions. This avoids confusion over different planting area measurement standards.

No percentage-derived indicators are included in the data. Multi-turn dialogue must first confirm whether the user needs comparative analysis based on raw data. By default, only content explicitly requested by the user is returned.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`maxContext`	`8000–12000 characters`	Crop farming yield and returns data includes detailed information across multiple crops and dimensions. A longer context window can fully retain key specified details such as crop type and producing area from multi-turn dialogue, avoiding repeated prompts for supplementary parameters.
`Recall count`	`Top 3–5 results`	Individual crop farming data documents have many core fields. Too many retrieved results will cause context overload. Too few results will fail to cover core data dimensions such as costs, yield, and returns required by users.
`PARSE_FILE_TIMEOUT_SECONDS`	`300 seconds`	Bulk crop farming data documents include details across multiple crop categories. Field splitting and cleaning take significant time. Sufficient time must be reserved for knowledge base parsing to avoid mid-process timeout errors.
`Similarity threshold`	`0.75–0.85`	Field structures are highly similar across different crops in crop farming. A higher threshold can filter irrelevant retrieved data across crop types, preventing category confusion in dialogue.
`system_prompt`	Must include "Current data update cycle is monthly/weekly, and only supports major producing area crops covered by public monitoring"	Crop farming data has varying update cycles. Clearly informing users of this can prevent access to outdated or non-target regional information.

Three Common Misconfigurations

Issue: Dialogue timeout, with 504 Gateway Timeout error displayed in the interface. Cause: The PARSE_FILE_TIMEOUT_SECONDS parameter was not adjusted. Parsing crop farming data or pulling plugin data exceeds the default threshold, causing request interruption.
Issue: Non-target crop returns data is automatically included in multi-turn dialogue, and repeated category specification is required. Cause: Reasonable Similarity threshold and Recall count were not set, and the crop range was not clearly restricted in the system_prompt, leading to retrieval of irrelevant data.
Issue: Knowledge base content is automatically loaded when using standard chat functionality. Cause: The knowledge base association switch for chat was not disabled, or calls to the knowledge base were not explicitly prohibited in the system_prompt, causing the associated configuration to be enabled by default.

How to Confirm Configuration is Correct

A query including a specific crop and producing area may be initiated. Confirm that the returned crop type and producing area match the query parameters.
Knowledge base parsing logs may be reviewed. Confirm that no timeout errors occurred during data parsing, and that all core fields were extracted completely.
Three consecutive rounds of dialogue may be tested. Confirm that the context retains key details such as crop type and producing area from the previous round, eliminating the need for repeated supplementary input.
The Similarity threshold may be manually adjusted. Test changes in the relevance of retrieved data to confirm the current threshold meets business requirements.

The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Each scenario requires targeted analysis. It is recommended to test on your own samples before finalizing settings.

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.