What the Data for This Category Looks Like
Data for this category covers the entire forging workflow. Sources include raw material quality certificates, furnace heating system data, press collection data, MES systems, non-destructive testing equipment, and customer forging drawings. Daily documents include forging process specifications, cutting lists, furnace heating records, forging process cards, mold life records, heat treatment work orders, and ultrasonic testing reports. Data updates follow a cadence of per forging piece, per batch of materials, or per furnace heat. Fields include forging batch numbers, furnace heat numbers, deformation step parameters, testing defect values, and more. Both structured collection data and unstructured process and testing documents are included.
What Constraints These Characteristics Impose on the Vector Model and Indexing Stage
Data for this category has high-frequency updates, mixed data types, and strong business relevance. This imposes multiple constraints on the vector model and indexing stage. High-frequency updates per piece or furnace heat require indexes to support incremental updates, avoiding the extra time cost of full reindexing. Coexisting structured collection data and unstructured process and testing documents require vector models to adapt to semantic extraction for mixed formats. It also requires association with metadata such as furnace heat numbers and forging batch numbers to enable precise filtering. Fields with strong business relevance require matching logic to combine business primary keys. This prevents the recall of records that are semantically similar but business-unrelated, while meeting high accuracy requirements to avoid risks such as forging scrap.
How to Set Up Configurations
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the single-section content length of forging process specifications and ultrasonic testing reports, avoiding semantic fragmentation |
| Overlap Length | 100–150 characters | Preserves contextual association for cross-chunk process parameters and testing sequences |
| Similarity Threshold | 0.75–0.85 | Matches strongly relevant fields such as forging batch numbers and furnace heat numbers, reducing false matching probability |
maxToken | 4096 token | Accommodates full workflow records and multiple testing reports for a single batch of forgings |
defaultToken | 2048 token | Meets context call requirements for routine inspection and review |
| Single Search Limit | Top 8 entries | Covers associated data for the same furnace heat or batch, avoiding missed key records |
Three Common Mistakes
- Phenomenon: Non-current furnace heat forging records appear in index recall results, with empty business fields. Cause: No dedicated metadata filtering is set for forging batch numbers and furnace heat numbers. Relying only on vector semantic matching leads to false recalls.
- Phenomenon: The target index model cannot be selected in the configuration interface, and a parameter format error prompt pops up. Cause: The legal value range for
defaultTokenandmaxTokenis not configured as required. This triggers platform verification interception. - Phenomenon: Timeout occurs when batch indexing data for a single furnace heat, with single indexing time exceeding 300 seconds. Cause: Chunk length is set too large. This leads to excessive time spent on single-chunk vector generation and index writing, and does not adapt to the high-frequency updated data rhythm.
How to Verify Successful Configuration
- Upload a single forging process card and ultrasonic testing report. Check the index generation log to confirm that the number of chunks matches the expected content length.
- Enter a query statement containing the target furnace heat number or forging batch number. Check the metadata tags of the recall results to confirm that only associated records for the target batch are included.
- Test calling the index interface. Check the field integrity of the returned results to confirm that the
defaultTokenandmaxTokenconfigurations do not truncate key process or testing content. - Simulate batch uploading multiple records for the same batch of forgings. Check the index update status to confirm that the incremental update function works properly.
The values provided are common starting points and should be measured against the reader's own samples.