What this category's data looks like
Data for this category comes from enterprise ERP systems, BOM lists, process routes, equipment capacity ledgers, staff shift schedules, work-in-progress inventory records, and supplier arrival reports. Daily processed documents include sales orders, master production schedules, material requirements plans, weekly and daily scheduling tables, production work orders, material shortage lists, and delivery change notices. Data fields include order numbers, process codes, capacity man-hours, material codes, work-in-progress quantities, and more. Update frequencies are daily, weekly, or triggered in real time alongside orders or abnormal events.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Data sources for this category are scattered and updated frequently. Multi-turn dialogue must accurately bind exclusive fields such as ERP and BOM to avoid mixing irrelevant data into context. Single scheduling documents have long content. Dialogue context length must be limited to prevent overflow. When abnormal scenarios such as material shortages or order insertion are triggered, multi-round follow-up questions are needed to supplement details such as supplier arrival information and equipment failures. Prompts must clearly specify the types of fields to extract, to ensure interaction logic fits scheduling business needs. Scheduling tasks for different work orders must be isolated independently to prevent context interference from affecting calculation results.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
messages history count limit | Retain the most recent 4 turns of dialogue | Filter redundant interactive content, adapt to the high-frequency update characteristics of this category's data |
variables binding scope | Bind core ERP fields | Automatically import preset scheduling data such as work order numbers and capacity man-hours |
chatId session isolation rule | Isolate by work order dimension | Ensure that contexts of different scheduling tasks do not interfere with each other |
| Maximum context length | 1000–1500 characters | Match the average content length of single documents in this category, avoid context overflow |
| Dialogue timeout threshold | 600 seconds | Adapt to the time-consuming requirements of complex scheduling calculations |
Three common mistakes
- An error of
Cannot read properties of null (reading 'q')appears in the interface. The cause is thatvariablesbinding to ERP fields is not configured correctly, leading to missing core scheduling parameters in the dialogue request. - A prompt indicating insufficient API Key permissions appears during invocation. The cause is using a globally universal API Key, which cannot meet the permission verification requirements of application dialogue.
- The dialogue return result does not match the current scheduling task. The cause is that the
chatIdisolation rule is not configured by work order dimension, leading to context confusion between different tasks.
How to confirm the configuration is correct
This verification process is based on FastGPT v4.17.0.
- Initiate a test dialogue, enter a known work order number, check whether
variablesautomatically import core field data of the corresponding ERP order. - Simulate a material shortage abnormal scenario, enter material shortage information, check whether multi-round follow-up questions are automatically started to supplement necessary parameters such as supplier arrival time and material replacement plans.
- View the session management list, confirm that dialogues of different work orders are correctly isolated via
chatId, with no context interference. - Initiate a test dialogue involving complex scheduling calculations, confirm that the dialogue does not exceed the set timeout threshold, and no timeout errors occur.
The values provided are common starting points and should be measured against the reader's own samples.