What the data for this category looks like
Data related to shipbuilding business process guidance comes from ship classification society approval documents, construction process work cards, inspection record forms, and equipment supporting technical documents. Data updates follow staged updates aligned with process nodes within a single project cycle, and are revised per industry standards for new ship type projects. Most documents use a chapter-by-chapter process description structure, with fields including process number, job requirements, acceptance criteria, and required tooling and equipment. Units are mostly engineering units such as millimeters, tons, and hours.
Constraints imposed on model access and configuration by these characteristics
Multi-project, batch-based document structures require that independent datasets are divided by construction project during model access, to avoid cross-project data confusion. The unit specificity of engineering fields requires that unit verification rules are clearly specified in the prompt during configuration, to prevent the model from mixing up size and weight parameters of different processes. Long document lengths require adjusting the context window parameter to accommodate complete process information. Data updated with each project requires configuring timed synchronization trigger rules, to ensure the model calls the latest version of the process documents.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Single chapter of shipbuilding process documents has a long length, requiring space to accommodate complete process information |
maxTokens | 2000–3000 token | Responses for business process guidance must cover complete inspection steps, to avoid truncation |
toolChoice | auto | Allow the model to independently choose whether to call tools to supplement process details |
temperature | 0.2–0.4 | Business processes require rigor, reducing randomness to ensure step accuracy |
AIPROXY_API_ENDPOINT | Fill in per deployment node | Adapt to the proxy configuration requirements of FastGPT v4.17.0 |
AIPROXY_API_TOKEN | Project-specific secret | Isolate call permissions for different construction projects |
Three common configuration errors
- Phenomenon: Model context is lost after calling the MCP tool, and the response has gaps. Cause:
toolChoiceis not configured as auto, and the context retention rule after tool calling is not clearly specified in the prompt, causing the model to reset the context window. - Phenomenon: Single-round call takes more than 60 seconds, and response delay is obvious. Cause:
maxContextis set too large, exceeding the memory threshold of model inference, or call timeout parameters are not properly configured. - Phenomenon: Rearranged model output does not meet expectations, and key process steps are filtered out. Cause: The rearrangement matching rule is not adjusted for the long text and unit characteristics of shipbuilding engineering documents, causing entries with mismatched units to be incorrectly excluded.
How to confirm correct configuration
- Call the process documents in the test dataset, check whether the process steps returned by the model include complete process numbers and unit information.
- Trigger an MCP tool call, check whether the context window retains the previous round of conversation content with no gaps.
- Monitor call logs to confirm that single call time is within the set threshold, with no timeout errors.
- Verify the return results of the rearrangement model to confirm that key process steps are included with no obvious omissions.
The values provided here are common starting points, and should be evaluated against the samples used in the specific deployment.
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.