What this category of data looks like
Data sources cover hot metal and scrap charging records, L2 process control real-time data, laboratory composition test reports, MES production scheduling data, energy medium consumption ledgers, and equipment operation status records. Update cadence includes generating smelting and continuous casting ledgers per heat, synchronizing L2 process parameters in real time, and summarizing full-process process records per shift. Daily documents include heat plans, batching lists, converter smelting records, finished product composition reports, continuous casting process parameter records, and slab quality judgment sheets. Fields include heat number, cast sequence number, hot metal temperature, alloy addition amount, finished product composition proportion, continuous casting pulling speed, and more. Units include ℃, kg, %, m/min, and others.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Data is associated per heat and production unit. Multi-turn dialogue must be bound to the unique identifier of the current heat to avoid cross-heat context confusion. Multiple document types have significant structural differences; prompts require dedicated parsing rules for each document type to accurately extract corresponding fields. Frequently updated real-time parameters require the dialogue context window to be limited to the most recent 3-5 heats to prevent redundant data from interfering with current judgments. The production logic of strong coupling between heats and cast sequences requires prompts to automatically associate process data for heats and their corresponding cast sequences, ensuring responses cover the complete production chain.
How to set configurations
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
| Context Window Size | Conversation and document data from the most recent 3-5 heats, calibrated via actual testing | Data for each heat in iron and steel smelting and continuous casting is closely linked; excessive historical data will interfere with judgments for the current heat |
messages Format | Stored grouped by heat + cast sequence | Ensures dialogue context is bound to the corresponding production unit, avoiding cross-heat confusion |
| Single Document Recall Count | Top 4 entries | Covers three core process document types: smelting, continuous casting, and quality, avoiding redundancy |
| Timeout Setting | 600 seconds | Matches the standard response cycle for heat processing, adapting to waiting requirements in production links |
chatId Generation Rule | Generate a unique identifier using the heat + cast sequence combination | Ensures dialogue context for each production unit is independent |
variables Binding | Bind the exclusive document ID of the current heat | Accurately matches process data for the current production link |
This configuration is adapted for FastGPT v4.17.0.
Three Common Misconfigurations
- No streaming output for dialogue responses. The phenomenon is waiting for the full result to return after calling the API, with no segmented push progress feedback. The cause is that the streaming output switch is not enabled, or the
messagesparameter is not configured with streaming trigger formatting. - Confusion between different users' dialogue contexts. The phenomenon is that different systems using the same API key obtain identical historical dialogue content. The cause is failing to generate a unique
chatIdbased on heat + cast sequence, leading to shared context. - Inability to retrieve uploaded process documents. The phenomenon is that after uploading a batching list or continuous casting record, retrieval results are empty or do not match the content. The cause is failing to specify parsing rules for the corresponding document, or the uploaded format exceeds supported ranges.
How to Verify Proper Configuration
- Initiate a process query targeting the current heat, verify that the dialogue context only includes relevant documents and historical conversations for that heat.
- Test the streaming output function, observe whether dialogue content is returned in segments.
- Generate
chatIds for different heats, initiate identical queries, verify that dialogue contexts under differentchatIds are independent of each other. - Upload a process document in the specified format, verify that retrieval results match the field content within the document.
The values provided here are common starting points and should be measured against the reader's own samples.