What the data for this category looks like
Data for fertilizer and pesticide policy and regulatory basis questions comes primarily from official public documents of the Ministry of Agriculture and Rural Affairs, Ministry of Ecology and Environment, Ministry of Industry and Information Technology, and local agricultural law enforcement departments. Updates trigger synchronously with new policy releases, with no fixed cycle. Core documents fall into three categories: departmental regulations, industry standards, and local implementation rules. Individual document lengths range from hundreds to tens of thousands of characters. Fields include document number, issuing authority, effective date, applicable category, penalty clauses, and execution requirements. Field formatting follows standard official document specifications.
What constraints these characteristics impose on tool calling and plugins
Strict formatting requirements for official documents require tool calling nodes to pre-configure official document field matching rules, to avoid extracting invalid content. The wide span of document lengths requires limiting the context token count per single call, to prevent model output interruptions. The lack of a fixed update cycle requires configuring a plugin for timed data source synchronization, to ensure the latest policy content is retrieved during tool calls. Differences in applicable scope across policy documents at different levels require adding regional adaptation checks in tool calling, to avoid returning invalid cross-regional clauses.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
toolChoice | auto | Allows the model to autonomously select tools adapted to fertilizer and pesticide policies, covering different types of Q&A scenarios |
functionCall | enabled | Forces the model to generate responses in standard tool calling format, ensuring output can be parsed |
| Timeout period | 200–300 seconds | Adapts to retrieval and parsing times for official policy documents, avoiding call interruptions |
| Number of results returned per call | Top 3–5 entries | Balances information completeness and output conciseness, aligning with reading habits for policy Q&A |
| Context length limit | 10000–15000 token | Adapts to the average length of most fertilizer and pesticide policy documents, preventing model output interruptions |
| Data source synchronization cycle | 7 days | Adapts to the update frequency of fertilizer and pesticide policies, ensuring the latest content is available during tool calls |
Three Common Mistakes
- Phenomenon: Model output suddenly interrupts during tool calling. Workflow logs show context limit exceeded. Cause: No reasonable context length limit is set. Wide variation in fertilizer and pesticide policy document lengths exceeds the model’s processing capacity.
- Phenomenon: Full fields of tool execution results cannot be obtained when calling the workflow via API. Cause: The
functionCallparameter is not enabled. Tool output is not serialized to standard format, so it cannot be parsed normally. - Phenomenon: Attempting to call local office software fails. The workflow node returns an execution error. Cause: FastGPT v4.17.0 tool calling defaults to only supporting cloud service calls. No local permission mapping is configured, so local programs cannot be launched.
How to Verify Proper Configuration
- Submit test questions containing fertilizer and pesticide policy keywords. Check if the tool calling node triggers and returns corresponding policy document fragments.
- View workflow logs to confirm that the tool calling timeout period does not trigger timeout errors, and the number of returned results matches the preset range.
- Call the API to obtain workflow execution results. Confirm that the
toolChoiceparameter has taken effect, and the tool calling format conforms to standard specifications. - Debug the workflow node to confirm that only one thinking process appears, with no extra steps caused by repeated calls.
All configuration values listed are common starting points, and should be validated against your own specific samples and use cases.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.