What the Data for This Category Looks Like
Daily documents for this category include raw material batching plans, kiln operation logs, laboratory reports, quality control notices, equipment inspection records, and energy consumption reports. Data sources include online composition analysis systems, DCS systems, laboratories, kiln and grinding equipment, raw and fuel ledgers, and energy metering devices. Data update frequencies fall into three categories: real-time, per shift, and daily. Kiln operation logs and online composition analysis data update in real time. Equipment inspection records are archived per shift. Energy reports and quality control notices are generated daily. Document fields include raw material mixing parameters, firing temperature, grinding specific surface area, strength test values, and more. Corresponding units are none (for parameter items), degrees Celsius, square meters per kilogram, and megapascals.
Constraints on Model Integration and Configuration
Multiple heterogeneous data sources and varied update frequencies require model access configurations to adapt to document segments with different timeliness. This avoids review result deviations caused by delayed context loading. Professional documents contain a large number of proprietary parameters and terms. Corresponding model recognition rules must be configured to ensure accurate matching of core fields related to batching, kilns, and grinding during cross-review. Content lengths vary widely across different documents. The number of tokens for context and reference segments must be reasonably limited to avoid exceeding the model's processing limit. Review results for this category directly relate to clinker quality and equipment operation safety. Configurations must ensure result consistency and accuracy. Parameter fluctuation ranges should not be overly relaxed.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Cement clinker-related documents include multiple segments of batching, kiln, and grinding data, requiring space to hold core segments from multiple inspection and laboratory reports |
temperature | 0.1–0.3 | Professional document cross-review requires consistent results, avoiding professional judgment deviations caused by parameter fluctuations |
quoteMaxToken | 1500–2000 token | Core content length range for a single laboratory report or kiln operation record |
| Workflow/API tool selection | auto | Automatically adapt review logic based on document type, handling different document types such as batching plans, inspection records, and reports |
AIPROXY_API_ENDPOINT | Enterprise internal compliant proxy address | Connect to in-house DCS and laboratory data sources to ensure secure and compliant data access |
AIPROXY_API_TOKEN | Exclusive key generated via enterprise identity authentication | Restrict unauthorized data source access, ensuring permission security for data links |
Three Common Configuration Mistakes
- Symptom: "No available vector model" error during invocation. Cause: The vector model adapted for cement clinker composition analysis was not added to the API channel configuration, or the configuration path is incorrect.
- Symptom: 'KokoroModel' object has no attribute 'mode' error during model testing. Cause: Adaptation parameters for the corresponding model were not enabled in the API channel configuration, causing an abnormal model invocation link.
- Symptom: Empty values returned when extracting parameters from raw material batching plan documents. Cause: Corresponding recognition rules were not configured for proprietary fields, causing the model to fail to match professional parameters in the document.
How to Confirm Successful Configuration
- Access the API Channel Management page of FastGPT v4.17.0, confirm that the configuration status of
AIPROXY_API_ENDPOINTandAIPROXY_API_TOKENshows normal connection. - Upload a single raw material batching plan document to trigger a review, verify that the length of the reference segment returned by the model falls within the
quoteMaxTokenconfiguration range. - Submit multiple documents of different types (inspection records, laboratory reports) to confirm that the model's review logic matches the configuration rules of
toolChoice. - Adjust the
temperatureparameter, submit the same document for two reviews, verify the consistency of the two results to confirm the parameter takes effect.
The values provided are common starting points and should be evaluated against the reader's own samples.