What Data Looks Like for This Category
The data for this category comes from product digital models and GD&T, process routes, coordinate measuring machine data, on-site trial feedback, and metrology systems. Daily produced documents include fixture requirement documents, positioning datum schemes, fixture drawings, gauge operation manuals, acceptance reports, calibration records, and change histories. Data updates are performed per project milestones, each product change, or regular calibration. Documents include fields such as datum parameters, tolerance values, measurement results, and calibration cycles. Units are mostly industrial metrology standard units like millimeters and newtons.
Constraints on Multi-turn Dialogue and Prompt Engineering
Data sources for this category are scattered but closely linked. Multi-turn dialogue must gradually integrate information from different dimensions such as product digital models and coordinate measuring machine data to avoid overload from single input. Data updates have no fixed cycle. Prompts must adapt to temporary product changes and calibration updates to ensure access to the latest change histories and calibration records. Documents include professional metrology fields. Prompts must strictly limit output formats to avoid non-industry standard expressions. Additionally, since errors directly relate to batch machining deviations, multi-turn dialogue must add a result verification step to confirm the accessibility and error range of positioning and clamping schemes.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Result Format Control | Disable Markdown syntax, only output plain text and industry-standard tables | Documents for this category must follow internal enterprise metrology specifications to avoid non-standard formats disrupting fixture and gauge review processes |
| Maximum Context | 8000–12000 characters, calibrated via actual testing | Must accommodate multiple document contents such as fixture drawing parameters, coordinate measuring machine data, and change histories integrated during multi-turn dialogue |
| Session History Retention Duration | 7 days | Matches the full lifecycle of a single fixture project from design to acceptance |
variables Binding | Bind fixture project ID and calibration cycle parameters | Accurately call the process route and latest calibration records for the corresponding project |
messages Context Truncation | Retain the most recent 10 dialogue turns | Avoid redundant historical information interfering with current process document or exception report drafting logic |
chatId Session Isolation | Assign independent session IDs per single fixture project | Prevent confusion between document data and dialogue records from different projects |
Three Common Mistakes
- Issue: AI output includes Markdown bold and table syntax, which cannot be directly imported into enterprise document management systems. Cause: Failed to explicitly disable non-industry standard formats in prompts, and did not configure the result format control parameter.
- Issue: Dialogue data from different fixture projects cross over, and non-current project calibration records and process routes are called. Cause: Did not assign independent
chatIdper project dimension, and session isolation configuration is missing. - Issue: The exception report drafting workflow enters an infinite loop after the AI returns results, stuck on the problem classification node. Cause: The output jump logic of the dialogue node was not set correctly in the workflow, and the problem classification step was not skipped.
How to Verify Proper Configuration
- Initiate a test dialogue requesting a draft gauge operation manual, and check that the output does not contain Markdown syntax.
- Create independent sessions for two different fixture projects, and call calibration records for each to confirm no data crossover occurs.
- Run the configured workflow, and observe whether the dialogue node proceeds directly to the result export step after completion, without triggering problem classification.
- Check that the
variablesparameter is bound to the exclusive identifier of the current project, to ensure called data matches the requirements of the current fixture project.
The values provided are common starting points and should be measured against the reader's own samples.