This configuration is based on FastGPT v4.17.0
What Data for This Category Looks Like
Data for this category comes from product 3D models, GD&T, process routes, coordinate measuring machine (CMM) inspection data, on-site trial feedback, and metrology systems. Daily documents include fixture requirement documents, positioning datum schemes, fixture drawings, gauge operation manuals, acceptance reports, calibration records, and change histories. Data updates are carried out per project, triggered by product changes, or executed according to regular calibration cycles. Document fields include positioning datum parameters, clamping force requirements, calibration validity periods, GD&T tolerance values, and change version numbers. Formats are adjusted slightly based on project needs.
What Constraints These Characteristics Impose on the Workflow Orchestration Link
Data for this category updates per project, product change, and calibration cycle, and includes strongly correlated fields such as professional tolerances and inspection values. Workflows must bind exclusive document sets for corresponding projects to avoid cross-project data confusion. Document structures vary widely by project, so workflows need nodes with customizable field extraction rules to adapt to document formats like fixture requirement documents and fixture drawings for different projects. The accuracy of professional data directly affects clamping and inspection results, and may even cause batch machining out-of-tolerance or gauge misjudgment. Therefore, workflows must add a pre-check link to ensure called documents are the latest version. Multi-turn conversations must retain project-related context to avoid parameter confusion across questions.
How to Configure the Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Max Context | First 6 conversation records | This category requires retaining project-related context such as positioning datum and tolerance parameters to avoid losing key project information in multi-turn conversations |
| Chat History Count | 6 entries | Matches the common interaction length of multi-turn process discussions for this category, avoids context overload |
| Text Content Extraction | Extract GD&T tolerance and calibration validity period fields | Adapts to the core professional field requirements of documents for this category, facilitating subsequent verification and calling |
| Node Timeout | 300 seconds | Reserves sufficient time to process CMM data, parsing and verification of complex fixture drawings |
variables | Bind current project document set | Ensures the workflow calls the latest fixture and gauge data for the corresponding project, avoiding cross-project data misuse |
nodeId | Bind verification node ID | Ensures text extraction results pass verification before entering subsequent links, improving data accuracy |
Three Common Configuration Errors
- Phenomenon: Workflows cannot support multi-turn conversations, and subsequent questions reuse previously selected product categories. Cause: The chat history count parameter is not configured correctly, or the context count is set to 0, resulting in failure to retain key information from previous interactions.
- Phenomenon: Text content extraction nodes return empty results. Cause: Extraction rules are not configured for exclusive fields of documents in this category such as GD&T tolerances and calibration validity periods, and only general extraction templates are used.
- Phenomenon: Workflows time out and interrupt. Cause: The node timeout parameter is not adjusted, or an overly large document set is bound, resulting in the time required to parse complex fixture drawings and CMM data exceeding the default threshold.
How to Confirm Successful Configuration
- Trigger a conversation that includes a query about positioning datum, check whether the workflow logs retain context content from previous interactions.
- Upload a fixture drawing or gauge operation manual for this category, verify whether the text content extraction node can extract preset professional fields.
- Trigger a conversation with multiple rounds of process adjustments, confirm that subsequent answers do not reuse previously incorrect product categories or parameters.
- Test calling document sets from different projects multiple times, confirm that cross-project data confusion does not occur in the workflow.
The values provided here are common starting points and should be measured against the reader's own samples.