What this category of data looks like
Heat treatment inspection and process record review data comes from material grades, customer technical specifications, temperature control instruments, furnace temperature uniformity testing equipment, hardness testers and metallographic equipment, and manufacturing execution systems. Data is updated per furnace charge and per batch. Core documents include heat treatment process cards, charging diagrams, furnace temperature curves, hardness and metallographic reports, equipment inspection forms, and exception handling forms. Data fields include furnace temperature (℃), holding time (hours), hardness value (HV), metallographic structure grade, and more. Each furnace charge corresponds to a unique production batch identifier and associated document set.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
The high-frequency updated data for each independent furnace charge requires multi-turn dialogue to bind a unique identifier, preventing cross-furnace charge context confusion. Mixed input of multiple types of structured documents requires prompts to clearly define the context scope, only calling documents related to the current furnace charge. Data fields with fixed built-in units require prompts to enforce that output results match the corresponding units, to avoid review deviations. Data sources connected to production systems require dialogue to pass parameters such as batch number and furnace number, to quickly locate exclusive business data.
Configuration Settings
These configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind the current furnace charge number plus production batch number | Ensure each furnace charge has independent dialogue context, avoiding confusion between review data from different batches |
messages | Limit the context window to the first 20 messages of the current session | Core heat treatment review dialogues typically do not exceed 20 rounds; overly long contexts may introduce irrelevant historical content |
variables | Preset variables for furnace temperature curve ID and process card number | Quickly locate exclusive business documents for the current furnace charge, reducing ineffective search range |
| Maximum context length | 800–1200 characters | The total length of core review documents for a single furnace charge typically falls within this range, avoiding interference from redundant data on model judgment |
| Single search limit | Top 3 results | Core documents to verify for heat treatment review are process cards, furnace temperature curves, and hardness reports; too many results will distract attention |
| Question Optimization | Enabled | The step-by-step review process can clarify the verification target for each round of dialogue through question optimization, improving review accuracy |
Three Common Misconfigurations
- Dialogue logs fail to export all records, returning empty results. This occurs when the
chatIdparameter is not correctly bound, and the association logic between session storage and the current furnace charge identifier is not configured. - After uploading a furnace temperature curve image, it cannot be interpreted, returning no relevant content. This happens when multimodal configuration is not enabled, or the prompt does not explicitly require identifying temperature values and curve trends in the image.
- Chat history context is lost, and previously verified content is not reflected. This is caused by not limiting the
messagesparameter to the current session scope, and incorrectly introducing context data from other furnace charges.
How to Verify the Configuration is Correct
Initiate a single-furnace-charge review dialogue. Verify that returned context only includes documents such as process cards and furnace temperature curves corresponding to the current furnace number, with no data from other batches. Upload a photographed image of the furnace temperature curve. Validate that the model can extract and verify temperature values in the image match preset process requirements. Initiate a multi-round step-by-step review. Confirm that the session log fully records each round of questions and replies, with no omissions. Call the variables parameter to pass a specified furnace number. Validate that the model can automatically associate data from the equipment inspection form and exception handling form for the corresponding batch.
The values provided here are common starting points and should be measured against the reader's own samples.