What this category of data looks like
Daily documents for general mechanical equipment assembly include assembly process cards, BOMs, torque records, clearance adjustment records, commissioning reports, factory inspection sheets, packing lists, and more. Data sources cover PLM/ERP systems, part inspection data, assembly tool collection terminals, test benches, MES systems, and customer technical agreements. Data updates follow the pace of individual equipment or order completion. Fields include quantified parameters with units, such as torque values (newton meters), clearances (millimeters), coaxiality (micrometers), and others. Document structures and fields vary across different orders.
What constraints do these characteristics impose on the model access and configuration link?
Multiple scattered data sources require configuration to support cross-system data association and unified parsing. The update pace tied to individual equipment requires the context window to adapt to the scale of single-batch documents, avoiding loading redundant or irrelevant data. Structured fields with units and diverse document types require configuration to retain original field formats, ensuring the accuracy of parameter Q&A. The assembly link has clear real-time requirements, requiring reasonable response threshold configuration to avoid affecting on-site debugging progress.
How to set the configuration
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the total length of associated documents such as assembly process cards, BOMs, and inspection records for a single piece of equipment, avoiding context overflow that interrupts Q&A |
temperature | 0.1–0.3 | Process and standard Q&A requires rigor, reducing randomness to ensure answers match fixed content in technical documents |
quoteMaxToken | 1500 token | Retains sufficiently long original document fragments to verify the compliance and accuracy of process steps and parameters |
AIPROXY_API_ENDPOINT | Fill in according to the deployed large model service address | Connection address for docking local or online large models, adapting to requirements of different deployment scenarios |
AIPROXY_API_TOKEN | Exclusive token generated by the deployment platform | Completes interface authentication and ensures the security of data calls |
| Workflow/API tool selection | none | This scenario focuses on text Q&A, no tool calls are required, avoiding unnecessary logical branches |
Three common misconfigurations
- Phenomenon: Returns a parameter mismatch error with status code 400 when calling a local large model. Cause: Failed to distinguish parameter formats between local large models and online APIs, directly reusing configuration logic for online calls.
- Phenomenon: After uploading assembly documents containing torque and clearance parameters, the model cannot accurately extract quantified values. Cause: Failed to set a reasonable
maxContextparameter, resulting in truncation of key document fragments and loss of parameter information. - Phenomenon: Irrelevant part machining content appears in Q&A results. Cause: Failed to limit the context range, introducing document data from non-assembly scenarios, leading the model to generate off-topic responses.
How to confirm correct configuration
- Upload the complete assembly document for a single piece of equipment, verify that the model can accurately return parameter requirements for assembly steps, such as specified torque values and clearance adjustment ranges.
- Call the test interface, pass simulated process questions, check whether the returned results include reference fragments from the original document, confirming that data association is working properly.
- View the FastGPT v4.17.0 interface call log, confirm that the authentication token and API address are configured correctly, with no 401 or 403 authentication errors.
- Adjust the
temperatureparameter, verify that the response to the same question has no obvious random changes, meeting the rigor requirements of process Q&A.
The values provided are common starting points and should be measured against the reader's own samples.