What data for this category looks like
This category of data covers the full lifecycle of tooling. Sources include product 3D models and GD&T, process routes, coordinate measuring machine (CMM) inspection data, on-site trial feedback, and metrology system calibration records. Daily documents include tooling requirement specifications, positioning datum schemes, fixture drawings, gauge operation manuals, acceptance reports, calibration records, and change histories. Each document contains dedicated fields such as datum parameters, tolerance requirements, and calibration cycles. Data updates follow project cycles, each product change, and regular calibrations. There is no unified batch update schedule. Single-project data volume accumulates gradually as work progresses through processes.
What constraints this category's characteristics impose on multi-turn dialogue and prompt engineering
The professional fields and staged update characteristics of this category impose clear constraints on multi-turn dialogue and prompt configuration. First, bind project-specific context to avoid mixing cross-project data. Second, the prompt must clearly specify parsing rules for professional fields such as GD&T and CMM data to ensure AI output aligns with industry general standards. Third, track version information of change histories and calibration records to keep dialogue content synchronized with current project status. Fourth, limit the document call scope per single dialogue to avoid response delays caused by loading excessive non-project-related data.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chatId | Create an independent chatId per project, bind its lifecycle to the project cycle | This category of data updates per project. Independent chatIds prevent cross-project dialogue confusion, and align with FastGPT v4.17.0 session persistence rules |
messages | Retain the most recent 20 dialogue messages, limit single message length to no more than 1500 characters | Tooling documents are often long texts. This balances context completeness and response speed, and avoids exceeding system memory limits |
variables | Preset three global variables: project number, GD&T version number, calibration cycle | This category of data requires binding project-specific parameters. Global variables simplify field calls during multi-turn dialogue |
| System prompt template | Include tooling document classification, professional field parsing rules, change history tracking requirements | This category has multiple document types and dedicated professional fields. Clear prompt rules improve AI output accuracy |
| Context retrieval scope | Only call knowledge base documents for the project bound to current variables | Avoid loading irrelevant data, improve retrieval efficiency, and adapt to the project-based update data characteristics of this category |
Three common misconfigurations
- Phenomenon: AI prompts that no files have been uploaded, and cannot read the tooling documents bound to the system prompt. Cause: Tooling requirement specifications, fixture drawings and other documents were not correctly mounted to the context binding of
variablesor system prompts. Only temporary files were uploaded without associating them with the corresponding project. - Phenomenon: Dialogue records are lost after refreshing the dialogue page, and a new conversation is displayed. Cause: The binding logic between
chatIdand the project was not configured. The session was not persistently stored in the context queue for the corresponding project. - Phenomenon: Unable to select the knowledge base documents for the corresponding project in real time during dialogue, or no Word export download link is generated at the bottom of the dialogue. Cause: The rule to call the corresponding knowledge base using the project number in
variableswas not configured in the prompt, or the content of themessagesqueue was not associated as the export source in the workflow.
How to verify a correct configuration
- Initiate a query that includes GD&T tolerances and positioning datum parameters. Check whether the AI returned content correctly parses the corresponding professional fields.
- Refresh the dialogue page. Check whether the historical dialogue records are fully retained and match the project information bound to the current
chatId. - Enter the project number in the dialogue. Check whether the AI can automatically associate the calibration records, change histories and other documents for the corresponding project.
- Trigger the dialogue end process. Check whether a properly formatted export link is generated, with content including the core analysis results of this dialogue.
The values provided here are common starting points, and should be evaluated against the reader's own samples.