What the Data for This Category Looks Like
This category's data mainly comes from internal enterprise process specifications, heat batch test reports, and business handling work orders. Updates run per production heat batch, with single heat batch data updated once daily. The data includes fields such as material grade, heat number, heating temperature, holding duration, tensile strength, and others. Fields use units like degrees Celsius, hours, megapascals. The length of a single business data entry falls between 800 and 1200 characters.
Constraints Imposed by These Characteristics on the Multi-turn Dialogue and Prompt Words Link
Multi-turn dialogue for metal material processing business must accurately extract process parameters with specific units and business identifiers, to prevent parameter confusion. The process includes branch logic, such as rework when testing fails. Multi-turn dialogue must record historical status to guide the correct handling path. Overlong dialogue context may mix expired heat batch information, leading to guiding deviations. The handling cycle for a single batch is relatively long, so sufficient dialogue history retention is needed to cover the full process.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context | First 1200-1800 characters | Match the length of single heat batch business data to avoid interference from redundant information |
| Question Optimization | Enabled | Refine core demands for process parameters and process nodes, reduce invalid dialogue |
| Variable Binding | Bind the heat number and material grade fields in variables | Accurately lock business-specific identifiers, avoid parameter confusion |
| Dialogue ID Configuration | Bind the chatId parameter | Ensure correct context association for multi-turn dialogue, prevent cross-talk between conversations |
| Dialogue History Retention Duration | 7200 seconds | Cover the full handling cycle of single-batch metal material processing |
| Single Historical Dialogue Retention | First 3 dialogues | Focus on key information for the current handling link, filter redundant old data |
Three Common Misconfigurations
- Phenomenon: Repeated reference to completed process nodes in dialogue, and debug preview history records include expired heat batch information. Cause: The maximum context retention range is not restricted, leading to old data mixing into the current dialogue context.
- Phenomenon: Prompt words fail to correctly extract material grade or heat number fields, and generated guidance content does not match actual business parameters. Cause: The
variablesparameter is not bound to lock business-specific fields, so the model cannot accurately extract key identifiers. - Phenomenon: The completion reason field from the previous round cannot be referenced in a cyclic process, and subsequent dialogue cannot adjust guidance logic based on prior conclusions. Cause: Fields output in the previous round are not written to the
messagesparameter, leading to key conclusions not being passed in the context.
How to Verify Correct Configuration
- Initiate a simulated business handling dialogue, input specific material grade and heat number, and verify whether the
variablesparameter correctly binds the extracted fields. - Trigger multi-turn process guidance, review debug preview history records to confirm only necessary dialogue content for the current link is retained, with no redundant old data.
- Test cyclic branch logic, confirm the completion reason field from the previous dialogue can be properly referenced by subsequent dialogue components.
- Access application settings in the workspace, clear the dialogue cache for the specified application, and confirm history records have been cleared.
The values provided are common starting points and should be assessed against samples relevant to 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.