What this category's data looks like
Precast concrete component-related data comes from BIM detailed design documents, steel bar and concrete batch ledgers, mold table and curing kiln operation records, laboratory test reports, and QR code traceability systems. Daily documents include component detailed drawings, steel bar cutting lists, mold inspection records, pouring and vibration logs, curing parameter records, demolding and factory inspection reports. Data is updated per individual component, each batch of materials, and each curing kiln batch. Fields include component number, steel bar specification, curing temperature, demolding strength value, and others. Units include millimeters, megapascals, degrees Celsius, and additional standard engineering units.
What constraints these characteristics impose on the "multi-turn dialogue and prompt engineering" workflow
Precast concrete component data sources are scattered and updated frequently per individual component, batch, and kiln run. Multi-turn dialogue must bind the current session’s component number and batch information to ensure each follow-up question matches the corresponding set of documents. Daily documents include professional engineering drawings and test data, so prompts must limit calls to category-specific process specifications and technical standard content, excluding irrelevant domain information. Fields include clear engineering units, so dialogue interactions must preserve parameter unit associations to prevent errors from unit confusion. Errors directly lead to component scrapping and project delay, so content verification logic must be strengthened in dialogue interactions.
How to set the configuration
The following configurations are formulated based on the interaction logic of FastGPT v4.17.0.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind the unique identifier of the current component | Ensure multi-turn dialogue context is linked to the exclusive data of the corresponding component |
messages | Retain the first 10 rounds of dialogue content | Cover the full process interaction from detailed design to factory inspection for components |
variables | Pass the current component number, batch number, and curing kiln number | Accurately match documents and test data for the corresponding batch |
| Maximum context length | 8000–12000 characters | Accommodate multiple component documents and complete dialogue history |
| Output format control | Disable Markdown syntax, output plain text | Adapt to the display and entry requirements of on-site factory terminals |
| Session retention duration | 7200 seconds | Cover the full consultation cycle for a single batch of components |
Three Common Misconfigurations
- Symptom:
Unexpected end of JSON inputerror appears in dialogue. Cause: Thevariablesparameter is not correctly bound, resulting in empty component batch information being passed, triggering abnormal model formatting. - Symptom: Dialogue results are not displayed directly in the dialog box and must be viewed manually in the sidebar. Cause: Real-time synchronization logic for the session context is not configured, causing returned content to not be mounted to the current dialogue window.
- Symptom: A new session must be created for each dialogue initiation, and previous interactions cannot be continued. Cause: The
chatIdis not correctly used to bind the unique identifier of the current component, and the system generates a new session by default for each request.
How to Confirm the Configuration is Correct
- Initiate a test dialogue, enter the number of a specific component, and verify that the returned content only relates to the process specifications and test data of that component.
- Initiate 3 consecutive follow-up questions, check whether the dialogue context retains the previous component information and interaction content.
- Adjust the output format configuration, verify that the returned results meet the preset plain text requirements.
- View the session identifier, confirm that dialogues associated with the same component use the same
chatIdeach time.
The values provided are common starting points and should be measured against the reader's own samples.