What this category of data looks like
The typical subjects of this category are injection molding, stamping, and die-casting mold enterprises, as well as mold centers of manufacturing enterprises. Daily generated documents include mold design task sheets, DFM reports, part drawings, machining process cards, mold trial reports, mold modification notices, and mold records. Data mainly comes from customer product models, mold flow or forming simulation results, CAD/CAM files, machining and measurement data, and trial-molded parts. Data updates are triggered by project milestones, and updates are made after each mold trial or modification. Core documents contain mold-specific process fields such as demolding angle, shrinkage rate, and assembly accuracy requirements.
Constraints on Model Access and Configuration
Mold design and manufacturing data sources cover outputs from multiple professional tools. File formats include CAD structured data, simulation results, process documents, and others, with a relatively long context length for a single document. Data update frequency fluctuates with project iterations; local data is updated frequently during mold trial and modification stages, requiring configuration to support dynamic context loading. There are many mold-specific process terms, and document fields have industry-specific characteristics, requiring configuration of knowledge base embedding rules adapted to this category. At the same time, mold data involves internal enterprise production processes, so data transmission and storage security must be ensured, and the scope of external interface calls must be limited.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Mold-related documents include multi-round data for design, mold trial, and modification. The context length of a single document is long, requiring adaptation to long-text processing requirements |
maxTokens | 2000–3000 token | Process specification and technical standard Q&A requires output of detailed compliance judgments and improvement suggestions, to avoid output that exceeds length limits |
temperature | 0.1–0.3 | Process standards require rigor and consistency. A lower temperature value reduces output randomness and ensures consistency of process recommendations |
| Workflow/API tool selection | auto | Requires the model to independently determine whether to call tools for dedicated scenarios such as process feasibility analysis and assembly accuracy verification |
AIPROXY_API_ENDPOINT | Large model API address deployed within the enterprise | Mold process data is core internal production information for the enterprise. Local API endpoints are required to ensure data security |
AIPROXY_API_TOKEN | Enterprise-specific access key | Restricts access to internal process knowledge bases and model services only to authorized personnel, preventing data leaks |
Three Common Configuration Mistakes
- Trailing symbols displaying rule traces appear in model conversation responses. This occurs when the built-in rule trace display configuration is not disabled in FastGPT v4.17.0, as debug mode output remains enabled by default.
- The model cannot accurately identify mold-specific process terms, such as specific requirements for demolding angle and shrinkage rate. This occurs when knowledge base embedding is not performed for dedicated mold category documents; models trained only on general corpora cannot match industry-specific fields.
- Q&A becomes unresponsive due to failed context loading. This occurs when the
maxContextsetting value is too small to accommodate complete document data for a single mold project, triggering a truncation error.
How to Verify a Successful Configuration
- A complete mold DFM report is uploaded, a Q&A with the query "Does the demolding angle of this part meet process requirements?" is initiated, and the returned result is checked to include specific recommendations compliant with mold industry standards, with no generalized vague statements.
- Model call logs in the FastGPT backend are reviewed, the
maxContextparameter is confirmed to have taken effect, and no context length overrun error prompts appear. - A Q&A with the query "Rectification plan for shrinkage defects encountered in this mold trial" is initiated, and the returned result is confirmed to link to historical project data such as mold trial reports and machining process cards.
- The internal API endpoint configuration is verified, a test call is initiated, and no connection timeout or insufficient permission errors are confirmed.
The values provided are common starting points and should be measured against the reader's own samples.