What the Data for This Category Looks Like
The data for livestock and poultry farming financing daily reports mainly comes from the Ministry of Agriculture and Rural Affairs’ Livestock and Poultry Industry Monitoring Database, local financial institutions’ agricultural-related financing reporting systems, and daily submission data from livestock and poultry industry associations. The update schedule is daily updates of the previous day’s financing application, approval, and disbursement data. The document structure of a single record includes the subject’s unified social credit code, breeding category, inventory scale, daily financing application amount, approval progress, and corresponding guarantee institution information. For field units: inventory scale is measured in head (for pigs, beef cattle) or feather (for broilers, laying hens), financing amount is measured in ten thousand yuan, and the date format is YYYY-MM-DD.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
Since the data includes multiple breeding categories and inventory scales with different units, the prompt must clearly specify unit conversion and category association rules to prevent the AI from confusing financing data for different livestock and poultry. The daily update feature requires multi-turn dialogue to support context memory for date filtering, and the system must retain the user’s most recent date instruction. There are many data fields, so the prompt must restrict the AI to only output fields within the specified range to avoid redundant content. Additionally, financing data is sourced from multiple systems, so multi-turn dialogue must support users adding supplementary filtering conditions, and the system must be able to parse subsequent supplementary instructions.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The livestock and poultry farming financing daily report has many fields per record. Multi-turn dialogue needs to retain the context of the last 3 rounds of filtering instructions to avoid exceeding window limits |
system_prompt_template | Preconfigured as the template "Output financing daily reports categorized by breeding category, strictly use specified fields and units, do not output irrelevant content" | Clearly constrain the AI’s output format to avoid unspecified redundant information and formatting errors |
ENABLE_TOKEN_STATS | Enabled | Supports displaying the number of input and output tokens to facilitate troubleshooting of context overflow or call cost issues |
retrieval_top_k | Top 8–12 entries | The single-batch return volume of financing daily report data is moderate. Recalling 8-12 entries can cover most users’ filtering needs |
tool_call_max_retry | 2 times | Financing daily reports need to associate breeding categories with financing data. A maximum of two tool calls can complete data retrieval and classification, avoiding invalid retries |
The parameter values provided on this page are general recommendations for establishing a starting point 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 test on your own samples before finalizing.
Three Common Mistakes
- Phenomenon: After calling the tool to retrieve financing daily reports, the AI output contains Markdown syntax symbols (such as #, *) and does not present the corresponding formatting effect. Cause: The prompt template does not clearly require the AI to convert Markdown syntax into natural formatting instructions, or the formatting rendering configuration for dialogue content is not enabled.
- Phenomenon: After initiating a multi-turn dialogue to filter financing daily reports, the returned result is empty or does not match the specified conditions. Cause: The previous round of filtering instructions is not correctly passed in the multi-turn dialogue context, or the
retrieval_top_kvalue is set too low, resulting in no matching data being recalled. - Phenomenon: After the tool call returns financing daily report data, the AI additionally generates irrelevant dialogue explanation content. Cause: The
system_prompt_templatedoes not restrict the AI to only output structured data returned by the tool, and the automatic dialogue supplement switch is not turned off.
How to Verify Successful Configuration
- Initiate a multi-turn dialogue that includes the specified breeding category and date, and check whether the fields output by the AI match the preset fields of the financing daily report.
- View the statistics area of the dialogue interface to confirm that the number of input and output tokens is displayed separately.
- Test the tool call process to confirm that only structured financing daily report data is returned, with no additional redundant content.
- Adjust the filtering conditions and check whether the returned results match the subsequent supplementary dialogue instructions.
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.