What This Category of Data Looks Like
This category of data comes from the full production process of machining workshops in machine tool factories, precision parts factories and equipment enterprises. It covers documents such as process routes, operation cards, tool lists, CNC programs, first-piece inspection records, patrol inspection forms, and measuring tool calibration records. Data sources include product drawings and 3D models, CAPP/CAM systems, machine tool collection data, tool management systems, MES systems, and measuring and inspection tool data. Updates trigger with each work order, each workpiece, sampling inspection, or tool replacement. Documents include clear professional fields such as process parameters, dimensional tolerances, tool numbers, and machine tool models.
What Constraints Do These Characteristics Impose on Vector Models and Indexing
This category of data includes professional content such as CNC program code and precision tolerance values, and has a high update frequency. Indexes must quickly synchronize newly generated process documents. Multiple types of documents are stored together. It is necessary to distinguish between process parameter text and structured content such as CNC code to avoid semantic deviation in vector encoding. The length of individual documents varies significantly. CNC programs may reach thousands of characters, while operation cards only have hundreds of characters. This requires adapting chunking logic for different text lengths. Data has strong business associations. For example, tool lists and corresponding operation cards need associated indexes to prevent business logic from being disconnected during retrieval. Index redundancy must also be controlled to avoid recalling outdated invalid process data.
Configuration Settings
These configurations follow the standard specifications for FastGPT v4.17.0:
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the typical length of conventional documents such as operation cards and process routes, and avoids cutting CNC program code that would break its syntax structure |
| Overlap Length | 50–100 characters | Retains contextual association between chunks, and prevents continuous logic of CNC programs from being truncated |
| Similarity Threshold | 0.75–0.85 | Filters low-match general text, and accurately recalls professional content such as process parameters and tolerance requirements |
| Single Search Limit | Top 8 entries | Covers multi-step associated information of machining processes, and avoids recalling too many irrelevant documents |
maxToken | 4000 token | Adapts to the long text content of CNC programs, and ensures complete recall of professional code segments |
| Reranking | Calibrated based on actual measurements | Optimizes sorting logic for documents dense with professional terms, and improves retrieval accuracy |
Three Common Misconfigurations
- Individual CNC program files remain in the index for an extended period. The cause is that a reasonable chunk length was not set, and overly long code segments triggered the platform's chunk processing restrictions.
- A 60-second timeout error occurs when the knowledge base switches indexes. The cause is that timeout parameters adapted for batch synchronization were not adjusted, and the business scenario of simultaneous indexing of multiple documents was not considered.
- Vector model selection only focuses on embedding dimension consistency and does not configure knowledge base priority. The cause is that the semantic encoding capability for professional terms was ignored, and retrieval priority rules were not set, leading to retrieval results that do not meet business expectations.
How to Verify Proper Configuration
- Upload a typical CNC program file, and check whether the indexing progress completes within a reasonable interval without abnormal stagnation.
- Retrieve process questions containing specific tool numbers, and verify whether the recalled results include associated documents such as corresponding operation cards and tool lists.
- Adjust the chunk length parameter, then compare retrieval recall effects under different parameters to confirm that they meet business retrieval requirements.
- Check the platform's indexing logs to confirm that there are no frequent chunk failure or timeout error records.
The values provided here are common starting points, and should be evaluated against the reader's own samples.