What the data for this category looks like
Business data sources for mining and mineral processing include electronic exploration archives from mine geology and survey departments, DCS system operation logs from concentrators, production operation ledgers, and safety inspection records. Basic geological exploration data is updated quarterly. Production operation ledgers are updated daily. Inspection records are updated every 8 hours. Two document structure types are used:
- Structured data tables with fields including work area number, equipment number, processing capacity, and operation time. Units include tons per hour, hours, and others.
- Unstructured documents: PDF-format safety regulations and operation guides, with individual documents reaching tens of thousands of characters.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
The large number of structured fields and diverse units require tracking contextually associated field information during multi-turn dialogue to avoid parameter matching errors. Long unstructured document lengths require prompts to limit retrieval scope, preventing redundant information from interfering with generation results. Differing data update frequencies require prompts to explicitly specify the dataset update time range, ensuring the latest business data is referenced. Dispersed data sources require guiding users to clarify their query’s business type during multi-turn dialogue, narrowing the retrieval scope and improving query accuracy.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum context length | 8000–12000 token | The combined length of mining and mineral processing business documents and structured data is large, so this range covers multi-turn dialogue historical context |
variables binding rules | Sync in real time with the current work area | Production data updates with work shifts, so referenced variables must use the latest state |
| Dialogue history storage duration | 30 days | The traceability cycle for mining and mineral processing business is typically monthly, so sufficient historical dialogue must be retained for issue review |
| Prompt template verification switch | Enabled | Business fields in prompts must fully match field names in the system |
messages context truncation threshold | Retain the most recent 10 dialogue turns | Avoids context overflow from excessive historical information while covering recent business scenarios |
Three Common Misconfigurations
- Issue: After modifying the prompt to use variable references, the temperature setting button disappears, and generation parameters cannot be adjusted. Cause: Parameter custom permission was not enabled in the
variablesconfiguration, so the system hides non-essential settings. - Issue: After calling the interface workflow, running data in the dialogue log is empty. Cause: The dialogue context identifier was not bound in the
chatIdconfiguration, so the system cannot associate call logs with the corresponding dialogue. - Issue: When passing code block parameters in the text content extraction module’s prompt, the complete response shows the code block as undefined. Cause: Parsing rules for code blocks were not explicitly specified in the prompt, so the system cannot recognize the incoming code block format.
How to Verify Proper Configuration
- Initiate a multi-turn dialogue, enter a query containing business fields, and confirm returned results associate with the latest production data.
- View the
variablesconfiguration item to confirm all referenced business fields are bound to the current work area’s real-time data. - Check the dialogue log to confirm each dialogue turn’s
messagesare correctly stored and not accidentally truncated. - Trigger a text content extraction operation, and confirm the extraction result matches the incoming code block format.
The values provided here are common starting points and should be evaluated against the reader's own samples.
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.