What the data for this category looks like
Precast concrete component data is sourced from BIM or detailed design documents, reinforcement and concrete batch records, mold table and curing kiln operation data, laboratory test reports, and product QR code traceability systems. Daily documents include component detailed drawings, reinforcement cutting lists, mold inspection records, pouring and vibration records, curing records, and demolding and factory inspection reports. Data is updated per individual component, each batch of materials, and each curing kiln batch. Fields include component number, reinforcement specification, curing duration, demolding strength, and more. Individual document structures have no unified standard, so each must be parsed according to its independent format.
Constraints Imposed on Model Access and Configuration
Precast concrete component data has scattered sources and high update frequency. Individual documents have large structural differences, so fields and content from different documents must be accurately matched. Component errors can lead to on-site installation failures or scrap, so model output accuracy has high requirements, and response randomness must be strictly controlled. Some documents include visual content such as drawings, so visual parsing capabilities must be supported. Data is updated per individual component and each batch, so the context association range must cover the full-process documents for a single component. This avoids configuration deviations caused by missing information.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Adapts to the multi-document associated context requirements of individual precast components, covering full-process data including detailed drawings, curing records, cutting lists, etc. |
maxTokens | 4000 token | Controls the output length of single-round responses, matching the information density requirements of precast component inspection and maintenance Q&A |
quoteMaxToken | 2000 token | Retains sufficient original text fragments to support accurate reference to component drawings and inspection records during maintenance steps |
vision | Enabled | Adapts to parsing visual documents such as component detailed drawings and mold inspection photos, meeting the appearance defect identification needs during inspection |
temperature | 0.3–0.5 | Reduces response randomness to ensure the accuracy of maintenance steps and inspection standards |
AIPROXY_API_TOKEN | Fill in the authentication token generated by the local proxy | Ensures the security of local model access and prevents unauthorized access |
Three Frequently Made Configuration Errors
- The model dropdown list in the interface is empty. Cause:
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENare not configured correctly, and the local proxy service is not properly connected. - A 401 unauthorized error is returned when calling the model. Cause:
AIPROXY_API_TOKENis filled incorrectly, or the local proxy service has not enabled the authentication verification process. - The maintenance steps output by the model do not match the actual parameters of the component. Cause: The value of
maxContextis too small, so complete associated data such as component curing records and cutting lists are not loaded, resulting in missing context information.
How to Verify Successful Configuration
- The model management page of FastGPT v4.17.0 is accessed, and the dropdown list is checked for connected local models.
- A precast component detailed drawing is uploaded, a parsing test is initiated, and the returned results are confirmed to include key annotations and dimension information from the drawing.
- Model call logs are reviewed, and the actual values of parameters such as
maxContextandtemperatureare confirmed to match the configured content. - An inspection question for a specific component is entered, and the returned result is verified to reference corresponding documents such as curing records and cutting lists.
The values provided are common starting points and should be measured against relevant samples.