What This Category of Data Looks Like
Ledger data for metal material processing is primarily sourced from real-time production equipment collection systems, offline quality inspection reports, and warehouse inbound and outbound registration systems, and is mostly exported in CSV or Excel format. Data updates are triggered by production batches; each furnace processing run updates the corresponding ledger entry. Individual ledger documents include fields such as furnace number, batch number, material grade, processing temperature, processing pressure, tensile strength, elongation, stored weight, usage records, and more. Units include ℃, MPa, tons and other professional industrial units. Documents are archived by batch number, and the volume of ledger data for a single batch accumulates gradually as processing steps are completed.
Constraints on Multi-turn Dialogue and Prompt Engineering
The multi-field structure, specialized units, batch-based archiving, and structured export characteristics of metal material processing ledgers create multiple constraints for multi-turn dialogue and prompt configuration. First, key identifiers such as furnace number and batch number must be retained in the conversation context messages to prevent data confusion across batches. Second, prompts must explicitly define mapping rules between fields and units to stop the AI from generating results that do not align with industrial standards. Third, since data is updated per batch, conversations must be bound to a single batch context, and batch parameters cannot be switched arbitrarily. Fourth, the use of professional quality inspection terminology must be pre-specified in prompts to ensure the AI correctly understands the meaning of each indicator.
How to Configure Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId session binding | Bind the unique identifier of the current production batch | Ensure contextual consistency for single-batch conversations, avoid opening new sessions for each query |
variables parameter configuration | Pass furnace number, batch number, material grade | Accurately filter ledger data for the target batch, avoid interference from cross-batch data |
messages context retention limit | First 20 rounds of conversation content | Cover the complete conversation flow for a single batch processing, retain key parameters without loss |
| Prompt template configuration | Fixed inclusion of "Only use the ledger data passed this time to generate reports, disable Markdown formatting" | Match user demand for plain text structured reports, avoid format interference with ledger summary |
| Result output trigger rule | Automatically trigger after confirming batch parameters | Align with the batch-based processing logic of metal material processing ledgers, simplify operational workflows |
Three Common Misconfigurations
- Symptom: Conversation results are only displayed in the sidebar, not directly embedded within the dialog box. Cause: The "Direct Display of Conversation Results" setting in FastGPT v4.17.0 is not enabled, or a rule that only outputs to the sidebar is configured.
- Symptom: A new conversation is automatically opened after each query, making continuation of dialogue for the same batch impossible. Cause: The
chatIdparameter is not bound, or the session binding logic is not associated with the current production batch identifier. - Symptom: The AI response forcibly uses Markdown formatting, and adjustment to plain text output is not possible. Cause: The prompt template does not explicitly disable Markdown syntax, or the default output format configuration is not modified to plain text.
How to Verify Successful Configuration
- Initiate a query that includes a specific furnace number and batch number, check whether subsequent conversations retain the batch identifier, and confirm no parameter confusion occurs.
- Submit 3 consecutive queries about ledger data for the same batch, confirm no new conversation is automatically opened, and that context remains consistent.
- Trigger a report generation request, confirm the output contains no Markdown formatting tags, and only includes structured plain text.
- Check that the
chatIdparameter matches the unique identifier of the current production batch, confirming the session binding logic is active.
The values provided here are common starting points, and should be evaluated against samples from the specific deployment.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.