What Data for This Category Looks Like
Bid-related data for mold design and manufacturing mainly comes from client-provided product models, mold flow or forming simulation files, drawings and process files exported from CAD/CAM, machining and measurement records, mold trial reports, and mold modification notices. Data updates follow individual project cycles. Corresponding documents are synchronized each time a mold trial or modification is completed. Daily documents include mold design task sheets, DFM reports, part drawings, machining process cards, mold trial reports, mold modification notices, and mold history records. Fields include material grades, cavity counts, draft angles, machining tolerances, mold trial defect records, and more. Most units use industrial standard measurements such as millimeters, kilograms, and hours.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering
First, data is updated in isolation per individual project. Multi-turn dialogue must bind project-specific unique identifiers to avoid cross-project context confusion. Second, documents include both structured parameters and unstructured defect records. Prompts must distinguish between different types of document content to accurately extract bid-required information such as machining man-hours and material usage. Third, each mold trial or modification generates new modification records. Multi-turn dialogue must retain complete historical interactions and document update information to prevent loss of critical parameters. Fourth, bid documents and quotations must strictly match a project’s inherent data, and cannot rely on generic industry data for generated results. Project-specific data must be passed as fixed variables into the dialogue workflow.
How to Configure Settings
These configuration guidelines are based on FastGPT v4.17.0.
| Configuration Item | Recommended Practice | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current mold project | Ensure complete isolation of dialogue contexts between different projects to avoid data confusion |
messages | Retain the first 20 pieces of dialogue context | Cover complete modification records from multi-round mold trial iterations for mold projects, supporting multi-round communication for quotation adjustments |
variables | Pass preset project parameters including material grades, cavity counts, and machining tolerances | Allow the AI to directly call project-specific data, avoiding generated quotations that do not match actual conditions |
| Maximum context length | 8000–12000 characters | Adapt to the length of mold-related documents containing multiple drawings and report texts, preventing context overflow |
| Prompt optimization | Calibrate based on actual testing | Optimize prompts for professional terminology in the mold industry to improve the accuracy of bid documents and quotations |
Three Common Configuration Mistakes
- Phenomenon: The material usage in the generated bid quotation does not match the mold flow simulation data provided by the project. Cause: Project-specific fixed parameters such as material grades and part weights were not passed via
variables. The model relied on generic industry data to generate incorrect results. - Phenomenon: Only a small number of recent conversations are displayed in the dialogue log, and early mold modification requirement records are lost. Cause: The context retention limit for
messageswas not configured. The default truncation rule overwrote critical historical interaction information. - Phenomenon: The generated content from the AI dialogue in the workflow is directly displayed in the front-end dialog box, and cannot be received and processed by the text splicing component. Cause: The automatic output switch of the AI dialogue module was not turned off, and the component calling logic of the workflow was not followed.
How to Verify Successful Configuration
- Check that
chatIdis bound to the unique identifier of the current mold project, ensuring that dialogue contexts between different projects do not interfere with each other. - Initiate a round of dialogue containing historical mold modification requirements, confirming that the
messagescontext retains complete historical interaction records without critical information truncation. - Pass preset
variablesparameters, verifying that the AI-generated quotation content matches project-specific data such as materials and tolerances, with no incorrect calls to generic industry parameters. - Run a test in the workflow, confirming that the output of the AI dialogue is received by the text splicing component, not directly displayed in the front-end dialog box, and meets workflow design requirements.
The configuration values provided here are common starting points. Adjust them based on your own specific samples and use cases.