What this page covers
- Client industry: Garment cutting and sewing
- Business direction: Drafting process documents and exception reports
- Capability area: HTTP interfaces and external systems
What the data for this category looks like
Daily documents for this category include process sheets, patterns, layout plans, cutting orders, first sample seals, process quality sheets, and packaging and size matching sheets. Data sources include order and size charts, CAD patterns, fabric and accessory inspection records, hanging system data, needle detector test results, and customer sample seal documents. Data is updated once per order, per style, and per batch. Document fields include pattern parameters, process requirements, fabric batch numbers, size ratios, inspection results, and other fields. There are no fixed unified units, and adjustments must be made dynamically based on the order and fabric category.
Constraints on HTTP interfaces and external systems
The multi-batch, multi-style update characteristics of this category require interfaces to support dynamic data pulling by order ID and style number, to avoid full synchronization consuming system resources. Since documents have no fixed units and fields adjust based on orders and fabric categories, interfaces must support flexible parameter mapping to adapt to field differences across orders. The irreversible nature of fabric cut pieces requires exception report interfaces to synchronize test data from needle detection and sewing processes in real time, to prevent batch errors caused by delayed data. Data sources from hanging systems and CAD patterns are scattered, so interfaces must support aggregation of multi-system data and unified output to the process document and exception report drafting workflow.
How to configure
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
Authorization | Carry a Bearer token with a validity period of 7200 seconds | Adapt to the identity verification requirements of external systems, prevent unauthorized access, and comply with FastGPT v4.17.0 interface call specifications |
variables | Bind order ID and style number as dynamic variables | Support pulling process data for the corresponding batch by order, matching the category’s order-based update characteristics |
responseData | Extract process fields and exception test results as core return fields | Simplify the parsing process for downstream process documents and exception reports |
| Timeout period | Set to 30–60 seconds | Adapt to data pull delays from CAD patterns and hanging systems, avoid request interruptions |
| Single return data volume | 800–1200 characters | Adapt to the text length of process sheets and exception reports, avoid data overload |
| Batch request limit | 10–20 data entries per request | Balance interface load and data synchronization efficiency, adapt to processing needs for multi-batch orders |
Three common configuration mistakes
- When using the database connection plugin to connect to PostgreSQL, a workflow validation failure prompt appears. The cause is that required database connection parameters, such as host address and port, are not configured in
variables, leading to validation failure. - After calling the HTTP interface, the
responseDatafield returns empty. The cause is that the mapping between process fields returned by the external system and FastGPT variable bindings was not set correctly, resulting in failed data extraction. - The Human field is null during API conversations. The cause is that user-entered exception description content was not correctly included in the request body, leading to failure to load the context correctly.
How to confirm correct configuration
- Manually trigger an interface request, and check if the returned
responseDataincludes core fields for process sheets and exception reports. - Call the database connection plugin, enter a test order ID, and confirm that fabric and accessory inspection data for the corresponding batch can be pulled normally.
- Initiate an API conversation, enter a preset exception description, and confirm that the Human field is correctly loaded into the context.
- Adjust the
Authorizationtoken to an expired value, and confirm that the interface returns an unauthorized error prompt, verifying that the identity verification logic functions correctly.
The values provided are common starting points and should be measured against the reader's own samples.