What Data Looks Like for This Category
Data for this category primarily comes from steel coil labels and quality certificates, press and feeder operation data, mold management systems, MES systems, and coordinate measuring machine or fixture inspection data. Daily ledger documents include stamping work instructions, material utilization rate sheets, mold inspection sheets, first and last piece records, dimensional inspection reports, and mold change records. Data updates trigger on each coil of material, each production batch, and each mold change. Fields include material grade, sheet thickness, press pressure, mold change time, dimensional deviation values from inspection, and corresponding units such as millimeters, megapascals, and hours.
Constraints Imposed by These Characteristics on Multi-turn Dialogue and Prompt Engineering Workflows
Multi-source heterogeneous data sources require that dialogue contexts align with field formats across different systems, to avoid analytical deviations from field mismatches. Frequently updated production data rapidly accumulates dialogue history, so the effective range of contexts must be limited to ensure response efficiency. Ledgers for a single production batch may include multiple documents, and large files will occupy excessive context space. Core relevant information must be reasonably split and retained. Mold changes and batch switches alter production parameters, so dialogues must recognize session boundaries to avoid mixing cross-batch data.
Configuration Specifications
This configuration is optimized for ledger processing in stamping and sheet forming scenarios, based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Stamping category ledgers include associated fields such as material grade and dimensional parameters. Excessively long chunks will lose field associations, while excessively short chunks will increase context splicing times |
| Overlap Length | 100–150 characters | Mold change records and material batch information for stamping data often span chunks. Overlap preserves continuous business-related content |
| Maximum Context Length | 15000–20000 tokens | Single-batch stamping data includes multiple ledger documents. Excessively long contexts will cause delayed dialogue responses, while excessively short contexts will lose core analytical information |
variables | Bind material grade, press model, and mold change time variables | Core analytical dimensions for stamping scenarios must be extracted and fixed from ledgers, to allow multi-turn dialogues to focus on business priorities |
messages | Limit retained historical messages to 20–30 entries | Frequently updated mold change and batch data rapidly accumulates contexts. Excessive entries will interfere with the accuracy of current dialogues |
chatId | Bind by production batch | Stamping data for different batches is independent. Cross-batch dialogues must have clear session boundaries to avoid data mixing |
Three Common Misconfigurations
- The symptom is empty fields returned by the dialogue interface after uploading files. The cause is failure to bind
variablesaccording to the ledger field structure for stamping categories, which prevents the AI from recognizing core fields such as material utilization rate and mold change records in the file. - The symptom is incomplete image display in multi-turn dialogue outputs. The cause is failure to limit prompts to only include partial images of stamping mold debugging and dimensional inspection, or failure to specify image resolution to match the layout requirements of ledger reports.
- The symptom is delayed dialogue responses after knowledge base search. The cause is failure to limit the number of historical
messagesentries, leading to excessive context accumulation that exceeds system processing thresholds.
How to Verify Correct Configuration
- Upload single-batch stamping ledger files, initiate a field extraction dialogue, check that extracted fields such as material grade and press pressure match the source files, and adjust chunk length until no fields are missed.
- Initiate cross-batch multi-turn dialogues, check that
chatIdupdates automatically with batch switches, to avoid mixing data from different batches. - Initiate multiple consecutive dialogues, check that response times meet business expectations, and adjust maximum context length until no significant delays occur.
- Use prompt engineering to generate ledger reports, check that images fully display relevant content such as stamping molds and inspection reports, and adjust prompt image restriction requirements as needed.
The values provided are common starting points and should be evaluated against the reader's own samples.