What Data for This Category Looks Like
Data for this category comes from design drawings, material quality certificates, welding equipment parameters, filler metal warehouse management systems, non-destructive testing systems, and personnel qualification ledgers. Daily documents include welding procedure qualifications, welding procedure specifications, filler metal issue records, welder qualification records, weld inspection reports, and repair work orders. Updates occur per weld, per batch of workpieces, or per shift of operations. Document fields include weld number, filler metal grade, welding current and voltage, non-destructive testing results, welder certification number, and other standard fields. No custom units are used.
Constraints Imposed by These Characteristics on the "Model Access and Configuration" Workflow
Dispersed data sources linked to weld, batch, and work shift dimensions require model access to support multi-source data association and matching logic. Frequently updated weld and batch data require context loading rules configured for near-real-time calls. Most documents use welding-specific technical terms, so the model must support parsing for this professional domain. Fixed formats exist for repair work orders and non-destructive testing reports, so configure text splitting rules matching these formats to avoid field misalignment. Rigid requirements for personnel qualifications and procedure qualifications mandate that model outputs strictly match compliant fields, with no arbitrary modification of data items.
How to Set Configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
AIPROXY_API_ENDPOINT | Fill in the dedicated access address provided by the deployment service provider | Specifies the network path for model calls, to support cross-system calls for multi-source welding data |
AIPROXY_API_TOKEN | Bind a dedicated secret key to each team | Enables isolated statistics of model costs by team, aligning with permission division and cost accounting needs for this scenario |
maxContext | 8000–12000 token | Matches the total length of all linked documents for a single batch of workpieces, covering full data including welds, filler metals, and personnel qualifications |
temperature | 0.1–0.3 | Reduces output randomness, ensuring accuracy of professional term parsing and compliant field matching |
vision | Enabled | Supports multi-modal parsing of non-destructive testing images and actual weld photos, adapting to image analysis needs for this scenario |
maxTokens | 2000–3000 token | Limits the length of single model outputs, preventing exceeding the standard field parsing scope of repair work orders and inspection reports |
Three Common Configuration Mistakes
- Phenomenon: An
Invalidformat error is returned when calling a multi-modal Embedding model, and the test interface returns a specified error structure. Cause: Thevisionparameter is not enabled, so the model cannot receive and parse welding non-destructive testing image data. - Phenomenon: Model call costs for different projects within the same team cannot be split and counted by dimension. Cause: An independent
AIPROXY_API_TOKENis not configured for each team, and model permission isolation configuration is not enabled. - Phenomenon: After multiple users scan a code to access the same workflow, the returned traceability results have cross data confusion. Cause: A reasonable
maxContextvalue is not configured for single-batch weld data, leading to context coverage exceeding the single-batch boundary.
How to Confirm Configuration Is Complete
- Access the model access configuration page of FastGPT v4.17.0, verify that
AIPROXY_API_ENDPOINTmatches the deployment address, and thatAIPROXY_API_TOKENis not exposed and bound to the corresponding team. - Upload a welding non-destructive testing image as test input, confirm that the model can normally return image analysis results after the
visionparameter is enabled. - Initiate a simultaneous multi-user call test, using
AIPROXY_API_TOKENvalues from different teams, confirm that call results and cost statistics can be isolated by team. - Import all linked documents for a single batch of workpieces, confirm that after configuring
maxContextandmaxTokens, the model can fully load and parse all fields.
The values provided are common starting points and should be measured against the reader's own samples.