Compatible with FastGPT v4.17.0
What Data Looks Like for This Category
This category serves manufacturing enterprise PMC, planning, shop scheduling, and material control departments. Daily processed documents include sales orders, master production schedules, material requirements plans, weekly and daily scheduling sheets, work orders, material shortage lists, and delivery change notices. Data sources include ERP orders and inventory, BOMs and process routes, equipment capacity, staff shifts, work-in-progress, and supplier deliveries. Update frequencies are daily, weekly, or triggered by orders or exceptions. Specific business fields and their corresponding units are included, such as order numbers, material codes, capacity man-hours, and shift headcounts.
What Constraints Do These Characteristics Impose on Tool Invocation and Plugins
Mixed input of multiple types of structured documents requires plugins to support field mapping and parsing for different formats. High-frequency updates triggered by exceptions require tool invocation triggers to sync with data updates. Precise identification of specific business fields requires plugins to adapt to production planning terminology and units. Fluctuating data volume tied to order counts requires tool invocation load adaptation capabilities to match business changes, avoiding redundant loading or invocation failures. The toolChoice configuration must be used to adapt to multi-tool invocation and cover parsing needs for different business documents.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Workflow/API tool selection | Auto-adapt to multiple tools | Adapt to parsing needs for multiple types of business documents such as sales orders and scheduling sheets, matching the data diversity characteristics of this category |
| Workflow/API function-call configuration | Trigger based on document update timing | Match daily or exception-triggered data update rhythms, ensuring tool invocation syncs with data |
| Chunk Length | 1000–1500 characters | Adapt to paragraph lengths of business documents, improving parsing accuracy |
| Single Search Limit | Top 10 entries | Match typical work order counts for shop scheduling, avoiding loading redundant business data |
| Maximum Context | 8000–12000 tokens | Adapt to long document parsing including BOMs and process routes, covering complete business information |
| Invocation Timeout Threshold | 600 seconds | Adapt to synchronization delays of production planning data, avoiding long waits for abnormal data |
Three Common Configuration Errors
- Model channel errors or invocation logs showing data acquisition failures: Caused by failing to configure tool trigger timing according to this category's data update rhythm, leading to reading unsynchronized ERP or scheduling data during invocation.
- Text extraction tool returns
400 Invalid JSON payload received. Unknown nameerror: Caused by failing to configure correct field mapping for production planning-specific fields such as material codes and capacity man-hours, leading to undefined fields in request parameters generated by the plugin. - Scheduling data recall anomalies after upgrading the PgVector plugin: Caused by failing to adapt to this category's data field structure, with the plugin's vector database index not synchronized to the updated field format of business documents.
How to Validate Proper Configuration
- Tool invocation logs can be reviewed to confirm trigger timing matches sales order and scheduling sheet update times.
- Test documents including work orders and material shortage lists can be submitted, and extracted business fields can be verified against document content.
- Exception scenarios such as simulated emergency order insertion can be triggered, confirming that tool invocation can automatically adapt to new business data.
- Plugin running status can be reviewed to confirm that vector database or tool load matches current business data volume.
The values provided are common starting points and should be evaluated against the samples used in the specific deployment.