What This Category of Data Looks Like
Data sources for this category include iron melt and scrap data, L2 process control modules, laboratory testing systems, MES, energy medium systems, and equipment status monitoring terminals. Daily generated documents include heat plans, batching lists, converter smelting records, composition reports, continuous casting process records, and slab judgment sheets. Fields include heat number, cast number, iron melt composition proportion, smelting end temperature, continuous casting pulling speed, slab defect type, and others. Units include percentage, degrees Celsius, meters per minute, tons, and more. Data updates occur per heat, in real time, or as a shift summary.
Constraints Imposed on Multi-Turn Dialogue and Prompt Engineering
Data sources for this category are scattered. Update frequencies vary widely. Multi-turn dialogue must strictly bind the heat number corresponding to the current conversation. This avoids calling mismatched documents across heats. Documents contain multiple types of specialized fields with specific units. Prompts must clearly limit usage to only preset fields within the documents. Fabricating unmentioned parameters is prohibited. The strong coupling between heats and casts requires multi-turn dialogue to continuously track their association. This prevents rhythm coordination errors caused by lost context. Real-time updated data requires pulling the latest heat-level documents first when initiating each dialogue. This ensures the timeliness of review basis.
This configuration is based on FastGPT v4.17.0.
How to Set the Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | Adapts to the long context needs of multi-document association for this category, avoiding truncation of key heat information |
| Single search limit | Top 6 entries | Matches the limited number of associated documents per single heat, reducing interference from redundant data |
| Variable binding rule | Force association with the heat number field in variables | Ensures multi-turn dialogue always calls documents corresponding to the current heat, avoiding context confusion |
| Conversation history tracking | Use chatId to achieve session isolation | Prevents interference between review conversations of different heats, ensuring session independence |
| Document chunk length | 1000–1500 characters | Matches the average length of single documents in this category, ensuring complete logic is retained after chunking |
| Conversation message queue limit | Retain the first 20 entries of the messages array | Avoids excessive context resource usage from overly long historical messages |
Three Common Misconfigurations
- Phenomenon: Non-current heat document content appears in dialogue response results. Cause: The heat number field in
variablesis not bound, resulting in called documents that do not match the current review target. - Phenomenon: Dialogue times out or returns no results. Cause: The length of the
messagesarray is not limited, and overly long historical messages cause context overflow beyond the system processing limit. - Phenomenon: Prompt verification fails to identify non-compliant fields. Cause: The prompt does not clearly limit usage to only preset fields within the documents, allowing the model to fabricate unmentioned parameters.
How to Confirm Proper Configuration
- Initiate a dialogue bound to a specified heat number, and verify that all returned documents are from the relevant records of that heat.
- Initiate multiple consecutive dialogues for different heats, and verify that documents across sessions do not interfere with each other.
- Input a query that exceeds the preset fields of the documents, and verify that the model does not fabricate unmentioned parameters.
- View system logs, and confirm that the
chatIdandvariablesparameters are correctly passed in each dialogue.
The values provided are common starting points and should be measured against the reader's own samples.