Reference only; verify against the target FastGPT release and deployment documentation.
What the data for this category looks like
The data required for document and material drafting in metal material processing mainly comes from structured ledgers and unstructured quality inspection reports from enterprise manufacturing execution systems (MES) and quality inspection systems. Data is archived and updated per production batch or daily. Documents include core fields such as heat number, alloy grade, processing technology parameters, mechanical performance indicators, batch pass rate, and more. Units include megapascals (MPa), millimeters (mm), tons (t), and some documents include image links associated with on-site rolling and quality inspection steps.
What constraints these characteristics impose on HTTP interfaces and external systems
Data sources rely on internal enterprise systems, so HTTP interfaces must be compatible with the enterprise’s existing authentication framework. Configure the Authorization parameter as a uniformly issued enterprise API key or OAuth2 token to block unauthorized access. Fields include professional units and specific business identifiers, so unit verification and field mapping must be completed when parsing interface responses; general templates cannot be used directly. Data is generated per production batch, so interface calls must be bound to production batch triggers to match the data update rhythm. Some documents include image links, so link fields must be retained during response extraction for subsequent visual content splicing in documents.
How to set the configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
Authorization | Unified enterprise internal API key | Meets the authentication requirements for connecting to existing enterprise production systems, ensuring legitimate interface calls |
variables | Pass heat number, detection date range, up to 5 business fields | Accurately match batch data for metal material processing, narrow the search scope |
responseData | Extract grade, tensile strength, batch pass rate, quality inspection report link | Match core business fields required for document drafting, avoid redundant data occupying context |
| Interface timeout setting | 600 seconds | Process quality inspection reports with multiple fields and associated image data, avoid timeout interruptions |
| Knowledge base chunk length | 800–1200 characters | Adapt to the length of professional terms in metal material processing documents, ensure complete semantics |
Three common errors
- Symptom: Unable to call external models via HTTP interfaces to complete custom inference. Cause: No custom API key added in FastGPT system configuration, only the built-in model call chain was used.
- Symptom: Empty fields are returned after calling the HTTP interface, or metadata is not correctly associated with the corresponding batch. Cause: No business identifier fields such as heat number and detection date were passed in
variables, causing the interface to fail to accurately match the corresponding data for metal material processing. - Symptom: Structured data returned by the HTTP interface is not correctly stored in the knowledge base. Cause: No field extraction rules for
responseDatawere configured, only the original JSON text returned by the interface was retained, and core business fields were not extracted.
How to confirm the configuration is complete
- Initiate a test call, check if the
responseDatareturned by the interface includes the preset core business fields, and verify that the field units comply with industry standards. - Check the authentication configuration in the FastGPT interface, confirm that the
Authorizationparameter matches the authentication key of the internal enterprise system. - Generate a draft document for metal material processing, verify that the referenced mechanical performance parameters and batch information match the data returned by the interface.
- View the knowledge base dataset list, confirm that the structured data returned by the HTTP interface has been correctly imported and associated with metadata.
The values provided here are common starting points and should be evaluated 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.