What Data for This Category Looks Like
Automated equipment data comes from three main sources: real-time operating condition data collected by device sensors, ledger data generated from maintenance work orders, and official product specifications and marketing materials. Data updates follow two schedules:
- Operating condition data updates in real time as the device runs
- Maintenance ledgers and marketing documents are adjusted for product iterations or marketing campaigns, with no fixed uniform update cycle
A single marketing document typically includes fields like device model, rated power, operating voltage, protection rating, and applicable scenarios. Common units for these fields are kW, V, and IP protection rating.
Constraints for Multi-turn Dialogue and Prompt Engineering
Prioritize recalling the latest device data linked to the current session for multi-turn dialogue. This meets the real-time requirements of operating condition data and avoids using expired historical information. Define clear field extraction rules and unit matching logic in prompts. This addresses the parameter structure with multiple specialized units and prevents parameter confusion. Restrict the total length of single-round inputs and stored context in the dialogue flow. This mitigates the risk of exceeding input limits from long marketing materials. Save device models and scenario requirements mentioned across conversation turns in the context. This ensures accurate parameter matching during multi-turn interactions.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–16000 characters | Most single automated equipment marketing documents range from 2000 to 5000 characters. Multi-turn dialogue needs to retain context for 3+ interaction turns. This range covers common scenarios. |
INPUT_TOKEN_LIMIT | 12000 tokens | The total tokens for a single device marketing document plus user questions usually do not exceed 10000. This range reserves buffer space to avoid model error triggers. |
CONTEXT_SIMILARITY_THRESHOLD | 0.75–0.85 | Irrelevant device historical data must be filtered. Only parameter information strongly related to the current interaction should be recalled. This range balances recall accuracy and coverage. |
UPLOAD_FILE_MAX_SIZE | 200 MB | Large 3D models and high-definition product manual PDFs for automated equipment usually do not exceed 150 MB. This sets a reasonable upload space reserve. |
DIALOGUE_LOG_ASSOCIATE | Enabled | Each interaction must be linked to a corresponding user identifier. This supports subsequent querying and deletion of conversation records. |
ERROR_INTERCEPT_SWITCH | Enabled | This can intercept inputs that exceed token limits early. It avoids returning meaningless error messages. |
The parameter values listed on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: An "input length exceeded" error or no response occurs after a device parameter document plus a long question is input in a single round. Cause: The
ERROR_INTERCEPT_SWITCHconfiguration is not enabled. Input token total is not verified in advance, leading to direct model error triggers. - Symptom: Conversation logs cannot be linked to corresponding user identifiers. Querying or deleting interaction records for a specific user is not possible. Cause: The
DIALOGUE_LOG_ASSOCIATEconfiguration is not enabled. No unique user identifier field is bound, so logs have no linking dimension. - Symptom: JPG format device image materials cannot be directly accessed in the AI dialogue node. Cause: The
UPLOAD_FILE_ALLOWED_EXTENSIONSconfiguration is not set to allow JPG format uploads, or the file parsing node for adapting image content is not enabled.
How to Verify Proper Configuration
- Running a multi-turn dialogue that asks about device models and specific parameters confirms whether the context retains device information from the previous turn, with no parameter confusion.
- Uploading a single device marketing document that exceeds the preset character threshold allows verification of whether early interception triggers or parsing completes normally.
- Reviewing the conversation log list confirms that each log is linked to an identifiable user identifier field.
- Uploading a JPG format device image allows verification of whether it can be accessed or parsed normally by the AI dialogue node.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.