What data looks like for this use case
Data for plastic injection molding scenarios covers documents such as injection molding process cards, raw material drying records, mold history logs, first-piece inspection forms, patrol inspection forms, and material change and machine cleaning records. Data sources include resin batch property sheets, real-time injection molding machine parameters, mold temperature controller data, MES system records, and dimensional and appearance inspection results. Data updates trigger with production batches, mold or material change operations, and shift schedules. It includes fields like process parameters, material information, and inspection results. Some fields have clear unit identifiers.
What constraints these characteristics impose during model integration and configuration
Injection molding scenario data is multi-source and updates frequently. Model integration and configuration must adapt to structural differences across document types, and avoid losing key process parameters due to context truncation. Format differences across multiple data sources require configuration to support tool calls, to complete cross-system data integration. Exception report drafting requires accurate analysis results. The model’s generation logic must match the strictness requirements of business parameters. Additionally, data updates occur frequently. Configuration must support quick refreshes of context and retrieval of the latest production data.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the total length of multi-source injection molding process documents and inspection data, preventing truncation of critical packing, holding, and cooling window parameters |
maxTokens | 2000–3000 token | Meets the full output requirements for exception report drafting, covering defect type analysis and rectification suggestion content |
| Workflow/API tool selection | auto | Supports automatic selection of tools such as injection molding machine parameter queries and inspection data comparison, adapting to multi-step process analysis scenarios |
temperature | 0.2–0.4 | Ensures accuracy of process parameters and anomaly analysis, reducing irrelevant divergent output |
AIPROXY_API_ENDPOINT | Fill in according to deployment environment | Adapts to model access paths for enterprise intranets or public clouds. FastGPT v4.17.0 and later versions support custom endpoint configuration |
AIPROXY_API_TOKEN | Generate according to enterprise permissions | Ensures security of model interface access, only allowing authorized users to call related functions |
Three common mistakes
- Phenomenon: Knowledge base retrieval returns results that do not match the preset JSON format, and the system prompts a format parsing failure. Cause: No clear output constraints are configured for the multi-field structure of injection molding inspection data, leading to syntax errors or missing fields in JSON generated by the model.
- Phenomenon: Tool calls cannot automatically select the tool matching injection parameter queries, requiring manual triggering. Cause:
toolChoiceis not set to auto, or the business scenario requiring corresponding tool calls is not clearly specified in the prompt. - Phenomenon: After mixing different types of indexing models and text models, the consistency of process parameter matching decreases, and deviation appears in the analysis results of exception reports. Cause: The vector processing logic and output format of the model are not unified, leading to semantic alignment deviations after mixed multi-model use, which affects the analysis accuracy of exception reports.
How to confirm successful configuration
- Submit a complete injection molding process card and a sample of that day’s exception report, then check whether the generated document contains correct process parameters and defect analysis content.
- Initiate a test request that includes an injection molding machine parameter query requirement, then confirm whether the tool call can automatically trigger the corresponding data acquisition step.
- Import a batch of injection molding inspection data with multiple fields, then check whether the result format returned by knowledge base retrieval complies with preset specifications.
- Adjust the
temperatureparameter, compare two generated exception reports, then confirm that the stability of the analysis results meets business requirements.
The values given are common starting points and should be measured against the reader's own samples.