What the data for this category looks like
Data for commercial vehicle yield rates and daily market reports comes from fleet management system operation logs, real-time freight rate data from freight platforms, and consumption records from energy refueling platforms. Data is aggregated daily at pre-dawn hours for full previous day operational data, with fine-grained operating condition data per vehicle synced hourly. Each daily report document includes fields such as vehicle VIN code, operating route, daily driving mileage, daily revenue, energy consumption cost, allocated maintenance cost, and daily net profit. Driving mileage is measured in kilometers, revenue and costs are measured in Chinese Yuan, and net profit is measured in Chinese Yuan.
What constraints do these characteristics impose on multi-turn dialogue and prompting?
The dispersed nature of data sources requires multi-turn dialogue to first clarify the user’s query scope, including target vehicle, operating route, and time period, to avoid cross-dimensional data confusion. The requirement for multiple fields and unified units means prompts must explicitly specify the required field names and their corresponding units, to prevent the model from generating confusing numerical content. The daily update schedule requires dialogues to mark the data update date, to avoid users using outdated information by mistake. The rule that VIN codes serve as unique vehicle identifiers means initial interactions must guide users to provide vehicle identification information; directly using vague vehicle model names for queries will lead to inaccurate matching.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 token | Commercial vehicle yield rate data has multiple dimensions. Multi-turn dialogue needs to retain more than 3 rounds of interaction context, and this range covers the context storage needs of regular conversations. |
CHAT_FILE_EXPIRE_TIME | 7–30 days | Commercial vehicle daily report data is updated daily. A 7-day expiration window avoids using outdated data, and the 30-day upper limit adapts to scenarios requiring retrospective data older than 7 days. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Commercial vehicle operating data files may include detailed data for multiple routes and vehicles, with long parsing times. 600 seconds covers the complete parsing process for large files. |
Recall count | Top 8 entries | Commercial vehicle yield rate data includes multi-dimensional information such as operations, costs, and revenue. Retrieving 8 entries covers core query needs and avoids information overload. |
Similarity threshold | 0.75–0.85 | Commercial vehicle VIN codes and route information have high recognizability. This threshold can accurately match the vehicle or route data queried by the user, reducing false retrievals. |
maxTokens | 2000–3000 characters | Daily report content needs to include multi-dimensional data summaries. This range can fully output aggregated yield details and avoid content truncation. |
The parameter values provided on this page are common recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three common errors
- Phenomenon: Garbled text with trailing quotation marks appears in AI dialogue output, and the final output reverts to standard quotation marks. Cause: The prompt fails to explicitly specify quotation handling rules for the output format, and the raw data retrieved from the knowledge base contains unescaped quotation mark characters, leading to format conflicts during model generation.
- Phenomenon: After inserting a multi-turn dialogue workflow array into a batch execution node, some nodes do not trigger as expected. Cause: Multi-turn dialogue context transfer parameters are not configured correctly, causing subsequent nodes to fail to obtain context information from previous dialogues.
- Phenomenon: A token limit exceeded error is triggered when calling the dialogue model. Cause: The reasonable value of the
maxTokensparameter is not restricted, and the multi-turn dialogue context is not effectively truncated, causing the token count of a single request to exceed the model's upper limit.
How to confirm proper configuration
- Upload a test file containing commercial vehicle operating data, initiate a yield rate query, and check whether the output content includes the specified fields and their corresponding units.
- Adjust the
CHAT_FILE_EXPIRE_TIMEparameter to 1 day, initiate a historical dialogue request, and check whether the system prompts that the data has expired or cannot load old data. - Initiate a multi-turn dialogue, sequentially query yield rate data for different routes and different vehicles, check whether the context is correctly retained, and whether subsequent replies are associated with previous query information.
- Trigger a batch dialogue task, and check whether all workflow nodes execute in order and return corresponding results.
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.