What This Category of Data Looks Like
Daily documents for this category include packaging process cards, bonding and molding parameters, wafer incoming material drawings, test program versions, yield reports, and failure analysis reports. Data sources include wafer test maps, MES systems, bonding and molding equipment, ATE test machines, X-ray/SAM detection equipment, and customer specification requirements. Data is updated per production batch, per chip test cycle, and daily. Fields include wafer number, test voltage and current parameters, yield grade identifiers, and more. Units involve volts and milliamps.
What Constraints These Characteristics Impose on Vector Models and Indexing
Multi-source heterogeneous data types and update frequencies require the indexing system to support mixed processing of structured parameter documents and unstructured reports. High-frequency updated production data requires incremental index synchronization strategies to avoid computing resource consumption caused by full reindexing. Professional field units and identifiers must retain contextual associations during chunking to prevent semantic fragmentation that reduces retrieval accuracy. Bid quotation preparation must align with customer specifications and internal production parameters, so index retrieval should prioritize matching customer-specified test programs and yield standards, and retrieve document fragments that are strongly relevant to business needs.
How to Set Configurations
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapt to the single-segment text length of packaging process cards and yield reports, avoid single chunk tokens exceeding model limits |
| Overlap Length | 100–200 characters | Retain contextual association of adjacent chunks, prevent batch information of wafer incoming material drawings from being truncated |
| Similarity Threshold | 0.72–0.85 | Distinguish professional parameters from general descriptions, match semantic similarity distribution in packaging and testing scenarios |
| Maximum Single Search Results | Top 8 entries | Cover single-batch test parameter entries from ATE test machines, avoid retrieving redundant data |
maxToken | 8192 | Adapt to the input length limit of Qwen/Qwen3-Embedding-8B, match long text chunking requirements |
defaultToken | 1024 | Use as the baseline token count for default chunks, balance retrieval accuracy and computing efficiency |
Three Common Misconfigurations
- Phenomenon: After configuring multiple embedding models with the same name, only the last one takes effect, and the model configuration displayed in the interface does not match the actually called model. Cause: The system uses the model name as the unique identification tag, and configurations with the same name will overwrite previous settings, and the multi-model group management function is not enabled.
- Phenomenon: After importing Excel source data with more than 10,000 rows, a single retrieved data chunk contains complete headers and full-row business content, resulting in field redundancy and semantic confusion. Cause: Chunk length and overlap length parameters are not adjusted, the default chunk size is too large, and chunking optimization is not performed for Excel structured data.
- Phenomenon: Truncation errors occur when generating vectors for long-text failure analysis reports, or key content in the latter half of retrieval results is missing. Cause:
maxTokenis not configured to adapt to the model's input length limit, and default parameters are used directly, resulting in forced truncation of long texts, which does not match the long document processing requirements of packaging and testing scenarios.
How to Confirm Configuration Is Correct
- Enter the model configuration page of FastGPT v4.17.0, check that the embedding model name and call path match the preset settings, and confirm there are no overwritten same-name models.
- Upload a single packaging process card and long-text failure analysis report, preview the chunking results, and confirm that the chunk length and overlap length meet the preset parameters.
- Import test Excel source data, view the chunking preview interface, and confirm that single-chunk data does not contain redundant headers or full-row business content.
- Launch a simulated retrieval test, enter the test program version keyword, and check whether the number and similarity of retrieval results match the maximum single search limit setting.
The values listed above are common starting points, and should be evaluated against the specific samples relevant to the deployment context.