What Data for This Category Looks Like
Data related to fertilizer and pesticide business comes from three main sources: the Ministry of Agriculture and Rural Affairs Pesticide Registration Database, the fertilizer production filing publicity platform, and industry compliance documents. Updates to this data synchronize in real time with new registration approvals and filing changes. Routine filing data updates once per quarter. A single document includes these fields: product common name, registration certificate number, production enterprise, applicable crops, recommended application rate, pre-harvest interval, and implementation standards. Most application rate units use grams/mu or milliliters/hectare. Pre-harvest interval uses days as the unit. Registration certificate numbers follow a fixed format combining letters and numbers.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
The multi-field professional nature of category data requires gradual guidance of users to clarify specific parameters during multi-turn dialogue. This avoids recommended application rate errors caused by unit confusion. The real-time data update feature requires dialogue context to prioritize latest filing data. Old registration information must not be included in session context. The fixed-format registration certificate number field supports multi-turn dialogue verification of user input format compliance. This reduces subsequent query errors. Single documents have high information density. Prompts must clearly specify extraction of only fields related to the current business process. This prevents irrelevant information from interfering with dialogue logic.
Configuration Settings
All following configurations apply to FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Bind to the unique serial number of fertilizer and pesticide business handling | Ensures multi-turn dialogue context for the same business is not disrupted by other sessions |
messages | Retain the most recent 8 rounds of interaction content. Limit single message length to 700 characters | Adapts to the information density of category data, prevents irrelevant information from interfering with dialogue logic |
variables | Preset three global variables: product registration certificate number, applicable crops, recommended application rate unit | Stores core business parameters entered by users, standardizes field verification rules |
| Maximum context length | 10000–12000 token | Balances information completeness and model processing efficiency |
| Context update rule | Only retain field data related to the current business node | Reduces redundant information and speeds up dialogue response |
Three Common Misconfigurations
- Phenomenon: Global variables are not retained after a multi-turn session ends. Users must re-enter parameters when initiating similar business again. Cause:
variablesare not bound tochatId. Variable scope is not limited to the current business process, so variables cannot be reused across sessions. - Phenomenon: Uploading fertilizer and pesticide filing documents fails to enable accurate extraction of recommended application rate unit information. Cause: Prompts do not clearly specify unit verification rules for fields. The model cannot distinguish between grams/mu and kilograms/hectare.
- Phenomenon: Calling an AI dialogue node for business tasks appends node output automatically to the user's dialogue
messagesarray. This interferes with subsequent dialogue logic. Cause: The node's automatic append output configuration remains enabled. Results become mixed into the conversation context.
How to Verify Proper Configuration
- Initiate a simulated business handling process. Enter a product registration certificate number and applicable crops. Check if global variables correctly store the corresponding parameters.
- Run 3 consecutive queries for different fertilizer and pesticide products. Confirm that binding
chatIdprevents context from mixing parameters from other businesses. - Upload a filing document. Trigger a dialogue query. Check if the model only extracts field information related to the current business.
- Call an AI dialogue node to perform a task. Confirm that returned results only output through the interface and do not appear in the user dialogue flow.
The values provided here are common starting points and should be measured against the reader's own samples.
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.