What Data for This Category Looks Like
Grain reserve business data comes from inventory ledgers, inbound and outbound documents, rotation plan documents, and official supervision reports from grain depots at all levels. Data update frequency aligns with business nodes. Real-time inventory data syncs daily. Rotation plans update quarterly. Inbound and outbound documents generate alongside handling processes. Single documents are mostly structured tables or standardized forms, with fixed fields including grain variety, storage grade, inventory quantity (unit: ton/kilogram), warehouse number, handling node, approval status, and other relevant details.
Constraints for Multi-turn Dialogue and Prompt Engineering
The large number of structured fields with clear units requires multi-turn dialogue to strictly match field formats. Avoid mixing unit differences such as tons and kilograms to prevent incorrect handling guidance. Hierarchical data update frequencies require distinguishing calls for real-time inventory and quarterly rotation plans during dialogue. This avoids returning outdated information. Standardized document structures require prompts to guide users to provide information in fixed node order. First confirm the handling type, then add required details like grain variety and quantity. This reduces ineffective interactions. Multi-node handling processes require dialogue to advance step-by-step through links. Skipping key approval steps must be avoided.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 8000–12000 characters | Grain reserve business documents are mostly structured tables with moderate single-document length; overly long context increases inference latency |
| Single Search Limit | Top 6 results | Reserve business data has fixed fields; a small number of recalls can cover required handling information |
| Question Optimization Switch | Enabled | User input may simplify business terminology; optimization enables precise matching of structured fields |
messages Parameter Configuration | Retain the first 10 interaction rounds | Historical interactions in multi-turn handling processes clarify the current node; excessive rounds interfere with current inference |
variables Binding Rules | Bind business variables corresponding to the target grain variety | Accurate calling of inventory and document data for the corresponding variety is required to avoid mixing information from different grain varieties |
chatId Transmission Rule | Automatically carry with each round of conversation | Ensures coherent context for multi-turn dialogue, avoiding session interruption or context loss |
Three Common Misconfigurations
- Symptom: An error occurs when uploading any structured document, while text input dialogue operates normally. Cause: Grain reserve business documents use fixed-format tables, and field separators are not correctly recognized during upload, causing the system to fail to parse content.
- Symptom: An
Unexpected end of JSON inputerror appears during dialogue when using the chatglm2 model. Cause: The context transmitted via themessagesparameter in multi-turn dialogue is too long, exceeding the token limit supported by the model, resulting in truncated and incomplete JSON responses. - Symptom: Slow dialogue response. Cause: The single search limit is set too high, and multiple expired rotation plan documents are called simultaneously, increasing retrieval and inference time.
How to Verify Successful Configuration
- Initiate a simulated grain reserve business handling request. Check that dialogue sequentially asks for required fields in the order of handling type, grain variety, inventory quantity, and warehouse number.
- Review knowledge base recall results. Confirm that only relevant data for the current grain variety is returned, with no business information from other varieties mixed in.
- Test uploading a structured table document. Confirm that the system can normally parse and extract field information without error prompts.
- Review session logs. Confirm that the
chatIdparameter is correctly transmitted with each round of dialogue, with no session context loss or confusion.
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.