What the data for this category looks like
Daily documents for this category include foundry process cards, batching lists, heat records, mold history logs, first-piece inspection records, material test reports, and nonconforming product review forms. Data sources include ERP material master data, melting furnace thermometers, spectrometers, MES heat records, mold management systems, customer drawings, and technical specifications. Update frequency follows per heat, per batch, or daily cycles. Individual documents contain clear fields such as furnace temperature (℃), alloy composition ratio, pouring temperature (℃), holding time (seconds), mold number, and heat number.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Data sources for this category are scattered, and update frequency is high. Multi-turn dialogue must gradually narrow the scope of documents linked to the session to avoid calling expired heat or mold data. Document fields include specialized process parameters, so prompts must explicitly require extraction of specified fields to prevent vague responses. The volume of documents per single heat is limited, so the number of conversation turns and documents in the session context must be restricted to avoid retrieval overload. Errors in process parameters can cause batch scrap, so multi-turn dialogue must support gradual verification of each parameter’s matching status. For example, first confirm the heat number before retrieving corresponding records, then verify batching ratios and furnace temperature data.
Configuration Settings
This page is compatible with FastGPT v4.17.0. The specific configuration is as follows:
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum Context | First 8 turns of conversation + latest 3 documents | Matches the document update rhythm for single heats in this category, to avoid interference from expired data |
chatId | Bind to current heat number | Ensure multi-turn dialogue only associates document data for the corresponding heat, to prevent cross-batch confusion |
messages | Limit to only include process cards and heat records from the current session | Narrow retrieval scope and improve matching accuracy for professional parameters |
variables | Fill in the alloy grade and mold number for the current heat | Further narrow retrieval scope and reduce recall of irrelevant documents |
| Single Reference Recall Count | Top 6 entries | Match the typical number of documents per single heat in this category, to avoid output overload |
| Session Timeout | 600 seconds | Match the typical cycle for foundry heat processing, to avoid mid-session interruptions |
Three Common Misconfigurations
- Phenomenon: Unauthorized error occurs after switching AI models, or existing session context is lost. Cause: The current session’s permissions and context are not bound via
chatId, causing the session state to fail to synchronize after switching models. - Phenomenon: No matching documents are recalled after increasing the reference limit. Cause: The prompt does not explicitly require generating responses based on recalled foundry documents, or the context configuration exceeds the session’s carrying capacity.
- Phenomenon: The dialogue output does not have streaming segmentation. Cause: The corresponding configuration for streaming output is not enabled, or the session timeout is set too short, causing the output to be forcibly terminated.
How to Verify Successful Configuration
- Initiate a query that includes a specific heat number, verify that the documents returned by the session only associate with the batching lists and heat records for the corresponding heat.
- After switching AI models, check that the session context is not lost and no unauthorized error prompts are displayed.
- Initiate a long-text query that includes professional process parameters, confirm that the output is generated as required and includes field references from recalled documents.
- Initiate consecutive multi-turn dialogue, verify that the session context is retained according to the configured number of turns, and no expired data appears.
The values provided here are common starting points and should be measured against the reader's own samples.