What Data Looks Like for This Category
Data for this category comes from resin batch property sheets, injection molding machine operating parameters, mold temperature controller data, MES systems, dimensional and appearance inspection records, injection molding process cards, raw material drying records, mold history logs, first-piece inspection forms, patrol inspection forms, and material change and machine cleaning records. Data updates trigger with each production batch, each mold or material change, and each shift change. Most documents use fixed-field form formats. Fields include resin grade, drying temperature, holding pressure time, mold temperature, and dimensional tolerances. Corresponding units include degrees Celsius, seconds, megapascals, and millimeters.
Constraints for Model Connection and Configuration
Multi-source, high-frequency updated data for this category requires model connections to support bulk synchronization of multi-format documents. This avoids deviations in review results caused by delayed data updates. The fixed-field structure of form-based documents requires configuration to support accurate extraction of structured data. This avoids errors from unstructured parsing. The tight association of single-batch data requires context configuration to retain all associated information within the batch. It also requires controlling per-round processing load to prevent timeouts caused by excessive data volume. Additionally, security and quality-related review requirements require configuration to lock in high-confidence data source association rules. This explanation uses the configuration logic of FastGPT v4.17.0.
How to Set Configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Matches the total length of multiple documents associated with a single batch of injection molding production, to avoid truncation of critical associated information within the batch |
maxTokens | 4000–6000 token | Adapts to the output requirements of single-round review, covering complete conclusion generation for process parameter verification and defect analysis |
temperature | 0.1–0.3 | Reduces random output, ensuring consistency of results for defect determination and parameter compliance review |
AIPROXY_API_TOKEN | Exclusive key assigned by the platform | Ensures security of access permissions, preventing unauthorized access from affecting production data review |
quoteMaxToken | 1500–2000 token | Limits the length of recalled document fragments, focusing on core process and inspection data within a single batch |
| Workflow/API tool selection | auto | Allows the model to automatically choose whether to call the document retrieval tool, adapting to cross-verification requirements for multi-source data |
Three Common Misconfigurations
- Phenomenon: Injection molding process documents uploaded via the chat window are not included in review analysis, and the output results do not reference uploaded file content. Cause: The
maxContextparameter is not configured to cover the context length of uploaded documents, causing the system to automatically truncate or ignore newly uploaded data. - Phenomenon: After deploying a 70B large model, review response time exceeds 30 seconds, and some batch data processing times out. Cause: The
maxContextandmaxTokensparameters are not adjusted to adapt to the large model's load, or the number of recalled documents is not limited, leading to input token overload. - Phenomenon: The review page embedded via iframe cannot display properly in a mini-program environment, and a domain verification-related prompt pops up. Cause: The platform's supported mini-program adaptation access logic is not used, and a general iframe embedding solution is still adopted.
How to Confirm Proper Configuration
- Upload a single batch of injection molding process cards and inspection records, trigger a review task, and check whether the output results include specific parameters and inspection data from the uploaded documents.
- View the platform's token usage logs to confirm that the input token count does not exceed the configured
maxContextandmaxTokensthresholds. - Test uploading documents with different update frequencies, confirm that the system can automatically synchronize the latest material change and machine cleaning records and mold history data.
- Simulate a review scenario with full single-batch data, check whether the response time meets the requirements of the business scenario.
The values provided are common starting points and should be measured against the reader's own samples.