What Data for This Category Looks Like
The work consultation data for this category mainly comes from official operation manuals, after-sales maintenance archives, and local public service work guideline documents of construction machinery complete machine manufacturers. Data updates are synchronized with device firmware version iterations and adjustments to local work rules, with no fixed cycle. Documents are stored classified by device model, fault type, and work process. Core fields include device number, fault code, process node serial number. The unit for processing timeliness is hours, and the maximum length of a single document can reach 12000 characters.
Constraints Imposed by These Characteristics on the Multi-turn Dialogue and Prompt Engineering Link
The detailed characteristics of device model and fault type require that multi-turn dialogue must bind chatId to pass the unique identifier of the current device, preventing confusion of consultation contexts across different construction machinery equipment. The node-based structure of work processes requires that prompt engineering should implement step-by-step confirmation guidance logic to ensure users submit accurate information in accordance with the process. The lack of a fixed cycle for data updates requires that the multi-turn dialogue link must connect to the latest version of the document library, and prompt engineering should include version verification prompts. The long length of single documents requires that the context window be limited to a reasonable range to avoid redundant information disrupting dialogue logic.
How to Configure the Settings
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
chatId | Bind device unique number + user session identifier | Ensure complete isolation of dialogue contexts between different construction machinery equipment and different users, avoiding parameter confusion |
| Maximum context window | 8000–10000 characters | Match the average length of single documents for construction machinery, avoiding exceeding the model's processing limit |
messages | Retain the last 5 rounds of dialogue content | Adapt to the step-by-step guidance logic of work consultation, retaining necessary context while controlling redundant information |
variables | Bind business fields such as device model and fault code | Adapt to professional terminology and exclusive data of construction machinery, optimizing precise matching of prompt engineering |
| Single recall upper limit | Top 3 matching documents | Reduce interference of irrelevant information on multi-turn dialogue, focusing on core consultation content for the current device |
| Question optimization switch | Enabled | Optimize vague user input for scenarios with many construction machinery fault codes and professional terminology |
Three Common Configuration Mistakes
- Phenomenon: Returns an invalid token error when called, and the OneAPI log shows the passed token value is "fastgpt". Cause: The default identifier of the FastGPT platform was mistakenly filled into the token parameter during configuration, and was not replaced with the actual access token from the business side.
- Phenomenon: When initiating multiple consultations with the same
chatId, previous dialogue history is not loaded correctly. Cause: Inconsistent context retention rounds were set for different model nodes in the workflow, failing to uniformly follow the round requirements of the business needs. - Phenomenon: After the user inputs a fault code, the returned work process does not match the device model. Cause: The prompt engineering did not add the context binding logic for device model, and did not guide users to supplement device number information.
How to Confirm Successful Configuration
- Initiate a multi-turn consultation including device number and fault code, verify that
chatIdis bound to the correct device identifier, and that the dialogue context updates with each turn. - View the FastGPT v4.17.0 call log, confirm that the passed token value matches the token configured for the business, with no default identifier remaining.
- Test initiating multiple consultations with the same
chatId, verify that the context retention rounds meet the configuration requirements, with no abnormal truncation. - Trigger the dialogue history export function, verify that the exported records contain complete multi-turn dialogue content.
The configuration values listed above are common starting points, and should be evaluated using local 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.