What Data for This Category Looks Like
Grain reserve business consultation data mainly comes from public ledgers of national and local grain and material reserve management departments, daily operation records of reserve granaries, and policy documents. Data update cadence follows monthly updates for inventory details, quarterly updates for reserve management policies, and annual updates for overall reserve plans. Document structure is divided into three categories: Inventory detail documents include fields such as warehouse number, grain variety, storage weight, storage period, etc. Policy documents cover reserve rotation rules, safe storage standards, and other content. Emergency dispatch documents include transportation procedures, emergency response requirements. Field units are uniformly tons, kilograms, years. Some documents include standardized codes for warehouse numbers and grain varieties.
Constraints on Multi-turn Dialogue and Prompt Configuration
Grain reserve data has many professional terms, clearly segmented fields, and uneven update frequencies, which impose multiple constraints on multi-turn dialogue and prompt configuration. First, professional terms such as rotation cycle and safe moisture content need clear extraction rules specified in prompts to avoid the model confusing similar expressions. Second, inventory data is updated monthly, so multi-turn dialogue must limit the context scope to prevent calling expired data. Third, the two data structures of inventory and policy differ greatly, so retrieval types must be distinguished in the dialogue flow to avoid returning irrelevant content across categories. Finally, the standardized requirements for field units require prompts to unify return formats to prevent mixed unit usage.
How to Configure the Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 800–1200 characters | Adapts to the average length of single grain reserve documents, avoiding exceeding model context limits |
variables | Pre-set three variables: "reserve variety", "storage warehouse number", "query type" | Used to extract core retrieval fields from user conversations and unify parameter formats |
messages | Limit historical conversations to the first 3 turns | Reduces redundant data interference and focuses on current inventory or policy inquiries |
| Question Optimization | Enabled, calibrated based on actual testing | Optimizes user questions for grain reserve professional terms to improve retrieval accuracy |
| Single Search Limit | Top 5 results | Matches the number of single-batch updated entries in reserve data, avoiding returning too many irrelevant contents |
chatId | Bind to current conversation ID | Ensures context and variable persistence across multi-turn conversations |
| Session Timeout | 600 seconds | Prevents excessive resource usage from long conversations |
Three Common Misconfiguration Issues
- A
Cannot read properties of null (reading 'q)error occurs during invocation. The cause is that the historical conversation format of themessagesparameter is not configured correctly, preventing the system from recognizing user question fields. - Low recognition accuracy of the question classification model. The cause is that the prompt is not adjusted for grain reserve professional terms, and the general model cannot match question types in segmented scenarios.
- Global variables cannot be maintained across turns. The cause is that the
chatIdparameter is not correctly bound to the current conversation, causing variables to be reinitialized for each conversation.
How to Confirm Successful Configuration
- Initiate a simulated inquiry, input "Query the wheat inventory of XX reserve granary", and check whether the returned results include the content of the preset
variablesfields. - Launch three consecutive related inquiries, and check whether the global variables retain the reserve granary name specified in the previous round.
- View the conversation log to confirm that the
messagesparameter only retains the most recent 3 rounds of historical conversations with no redundant content. - Test a professional term inquiry such as "rotation cycle", and check whether the optimized retrieval results match documents related to reserve management.
The values provided 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.