What data for this category looks like
Data sources for this category include raw material quality certificates, heating furnace systems, press collection data, MES systems, non-destructive testing instruments, and customer forging drawings. Data updates follow the rhythm of each forging piece, each batch, or each furnace run. Daily documents cover forging process specifications, cutting cards, heating furnace records, forging process cards, mold life records, heat treatment work orders, and ultrasonic testing reports. Data fields include forging ratio, fiber direction, furnace batch number, forging batch number, defect type, and more. Corresponding units involve weight, temperature, pressure, and dimensional parameters.
What constraints do these characteristics impose on multi-turn dialogue and prompt engineering
The feature that data updates per single furnace run or single batch requires multi-turn dialogue to accurately associate furnace batch numbers with forging batch numbers, to avoid cross-batch confusion. Differences in structure across multiple daily documents require prompt engineering to clearly define field extraction rules for different documents such as process specifications and testing reports. For scenarios combining frequently updated production data and offline documents, use the messages parameter to limit conversation context length, to avoid redundant information interfering with key parameter matching. The need to verify dedicated fields such as forging ratio and fiber direction requires prompt engineering to include category-specific logical verification rules, to prevent missing fields or incorrect values.
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 length of single-segment process descriptions and testing data in forging documents, avoiding information fragmentation within chunks |
| Overlap Length | 150–200 characters | Ensures key information such as furnace batch numbers and forging batch numbers across chunks is not truncated |
| Single Search Limit | Top 8 entries | Matches retrieval needs for multiple furnace runs and batches, covering the typical volume of batch data in production ledgers |
| Maximum Context | 6000 characters | Limits redundant historical information, focusing on ledger data and report generation requirements for the current batch |
| Question Optimization | Calibrated via actual testing | Adapts to category-specific parameter verification logic, avoiding damage to matching accuracy for forging fields from general optimization rules |
variables | Bind furnace batch number and forging batch number variables | Based on core associated fields of business data, enabling accurate context transfer for multi-turn dialogue |
chatId | Bind current production batch ID | Ensures data isolation for multi-turn sessions, preventing confusion between ledger information from different batches |
Three common configuration mistakes
- Symptom: Timeout errors occur when parsing Word documents for forging ledgers larger than 10 MB. Cause: Chunk configuration was not adjusted for the long paragraphs and multi-field structure of category documents, leading to excessively long single chunks that trigger parsing timeouts.
- Symptom: Prompt engineering optimization steps take longer than reasonable during multi-turn dialogue. Cause: The context range for question optimization was not limited, and irrelevant historical testing report data was included, leading to excessive load on optimization logic.
- Symptom: The debug preview interface returns an empty field error after triggering input guidance. Cause: Category-specific furnace batch number and forging batch number variables were not bound in the
variablesconfiguration, causing the guidance logic to fail to obtain necessary business parameters.
How to confirm successful configuration
- Upload a single furnace run's forging ledger document, verify that extracted furnace batch number and forging ratio fields match the original document content after parsing.
- Launch a multi-turn dialogue, sequentially enter the forging batch number and heating furnace temperature parameters, verify that the conversation context can correctly associate and extract ledger data for the corresponding batch.
- Trigger the question optimization function, check that the optimized prompt still retains verification requirements for category-specific fields such as forging ratio and fiber direction.
- Test parsing of Word documents larger than 10 MB, confirm that parsing time meets response expectations for production scenarios, with no timeout errors.
The values provided here are common starting points, and should be evaluated against the reader's own samples.