What This Category of Data Looks Like
The data for this category mainly comes from ERP order and inventory systems, BOM lists, process route tables, equipment capacity ledgers, employee shift schedules, work-in-progress inventory, and supplier arrival records. Daily generated documents include sales orders, master production schedules, material requirement plans, weekly and daily scheduling tables, production work orders, material shortage lists, and delivery change notices. Data update frequency varies by business scenario, including daily, weekly, and real-time updates triggered when orders are placed or exceptions occur. Document fields include order number, material code, capacity unit, scheduling time period, material quantity, and more. Each field follows the internal standardized unit and naming rules of the enterprise.
What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompt Words
Dispersed data sources and inconsistent update rhythms require multi-turn dialogue to track the latest business data versions. It must avoid using expired scheduling or material information. Diverse document types with large structural differences require prompt words to clearly specify the current document type being processed. This prevents the model from confusing field rules of different business documents. Fields have standardized units and naming conventions. Prompt words must enforce output matching the enterprise's internal field format. This ensures generated process documents and exception reports can be directly imported into the system. Multi-turn dialogue needs to handle frequent business changes. Key scheduling constraints must be retained during the conversation to avoid repeatedly asking for confirmed parameters.
How to Configure the Setup
This configuration is based on the functional logic of FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Covers core data of a single batch of sales orders, corresponding work orders and scheduling tables, to avoid context overflow |
| Maximum number of single conversation turns | 10–15 turns | Limits loading of redundant historical data to prevent conversation response timeouts |
variables binding rules | Bind the latest daily ERP capacity, inventory and work order data | Ensures the conversation always uses real-time business data, avoiding generation of outdated process documents |
| Exception response configuration | When the model returns an empty result, return "Unable to generate the current scheduling report, please check data binding" | Handles scenarios where the large model returns empty content, replacing the frontend returning a blank page directly |
chatId conversation isolation | Divide independent conversations by production work order ID | Distinguishes conversation contexts for different scheduling tasks to prevent data confusion |
messages history truncation | Retain the most recent 3 turns of conversation records | Filters non-critical historical information to reduce context processing load |
Three Common Misconfigurations
- Excessively long conversation: The symptom is the interface showing request timeout or waiting more than
600 secondswithout returning a result. The cause is failure to limit context length, loading too much historical scheduling data and unrelated documents. - Chart tool returning empty results: The symptom is a blank production scheduling chart returned after calling the chart tool. The cause is failing to explicitly require the use of capacity and work order data from the currently bound
variablesas the chart data source in the prompt words. - Failed conversation content export: The symptom is being unable to export complete scheduling drafting conversation records. The cause is failing to enable persistent storage configuration for conversation context and failing to bind the corresponding
chatIdfor export.
How to Confirm Correct Configuration
- Input a test sales order, verify that the conversation can automatically associate corresponding work orders, material shortage lists and other bound data, and generate a process document draft that conforms to the format.
- Initiate multi-round scheduling adjustment requests, check that the response time meets the reasonable threshold set by the business scenario.
- Trigger a simulated exception scenario, such as inputting material shortage information, verify that the model can generate a qualified exception report.
- Test the conversation export function, confirm that complete conversation history and bound scheduling-related data can be exported.
The values provided here are common starting points and should be measured against the reader’s own samples.