Data Overview for This Category
Data for this category originates from online composition analysis tools, DCS systems, laboratory facilities, kiln and grinding equipment, raw material and fuel ledgers, and energy metering devices. Update frequencies include three categories: real-time, shift-based, and daily. Daily documents cover raw material batching plans, kiln operation records, laboratory reports, quality control notices, equipment inspection records, and energy reports. Each document contains process parameters, equipment status, test values, and metering data for its respective workflow link, with no additional fictional fields.
Constraints Imposed on Multi-turn Dialogue and Prompt Engineering
Scattered data sources and varying update frequencies require multi-turn dialogue to adapt to three time granularities: real-time working conditions, shift records, and daily ledgers. Prompts must clearly define call priorities for each data type. Daily documents hold professional process parameters and metering data, so prompts must restrict calls to only document fragments specific to cement clinker and grinding, to avoid interference from irrelevant information. Business errors directly impact production stability, so multi-turn dialogue must reasonably limit context length. This prevents redundant historical records from disrupting key parameter extraction and quotation preparation logic.
Configuration Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId binding rule | Bind to the unique ID of a single tender project | Ensure multi-turn dialogue for the same tender project shares context, avoid session data confusion, and align with FastGPT v4.17.0 session logic |
messages organization rule | Only retain process data and interaction records for the current project, filter non-project content | Focus on parameters and quotation logic required for tenders, reduce redundant information interference with core calculations |
| Context window size | 8000–12000 token | Cover full content of core documents such as raw material batching plans and kiln operation records, meet multi-turn dialogue information needs |
variables configuration | Bind fixed fields for raw material and fuel composition, energy metering | Quickly retrieve category-specific data, improve efficiency of tender document and quotation preparation |
| Number of retained conversation history entries | Top 3–5 entries | Adapt to scenarios mixing real-time and historical data, avoid excessive old data disrupting current tender calculations |
Three Common Misconfigurations
- Phenomenon: When multiple calls are initiated for the same tender project ID, previous interaction history fails to load correctly. The context of the first model call only retains 1 round of content. Cause:
chatIdis not bound to the tender project ID. Instead, a random or global session ID is used, separating session contexts across different calls. - Phenomenon: Non-category-specific process parameters appear in generated tender documents, with content unrelated to cement clinker production. Cause: The prompt does not explicitly restrict calls to only category-specific documents such as raw material batching plans and kiln operation records.
- Phenomenon: Timeout errors occur during workflow operation, and the returned result is empty. Cause: The context window is set too large, exceeding system processing limits, causing multi-turn dialogue information loading to fail.
How to Verify Correct Configuration
- Initiate a test call, input the process parameters of the current tender project, and confirm the
chatIdmatches the project ID. - Review the
messagesfield content, confirm it only contains interaction records and process data for the current project, with no irrelevant content. - Trigger multi-turn dialogue, verify that context updates incrementally with interactions, and follows the preset number of retained history entries rule.
- Check the binding status of
variables, confirm category-specific raw material, fuel, and energy fields are automatically populated.
The values provided here are common starting points and should be measured against the reader's own samples.