What the Data for This Category Looks Like
Commercial vehicle research report data is sourced from publicly disclosed industry association information, official technical documents from original equipment manufacturers, third-party commercial vehicle consulting firm reports, and Ministry of Industry and Information Technology vehicle announcement disclosures. Update cycles primarily follow monthly sales reports and quarterly market analyses, with supplementary special content released during major policy launches or new model releases. Most documents are in PDF format, including modules such as vehicle parameters, market sales volumes, policy interpretations, and supply chain analyses. Fields include wheelbase, rated load, cruising range, and others, with units typically being standard physical units like millimeters, kilograms, and kilometers. Some content uses structures with long paragraphs nested within tables.
Constraints for Multi-turn Dialogue and Prompt Engineering
Differences in data standards exist across commercial vehicle research report sources. Multi-turn dialogue must first align vehicle classifications, statistical cycles, and other standards mentioned by users to avoid confusion between statistical standards of reports from different sources. Documents contain long paragraphs and nested tables. Multi-turn dialogue must guide the splitting of key parameters, and prompt templates must explicitly require extraction of specified fields while retaining corresponding units. Update cycles are primarily monthly and quarterly. Multi-turn dialogue must require users to clearly specify the analysis time interval to prevent mixing of data across cycles. Some reports include special content, and prompt templates must limit retrieval scope to research report content for the corresponding scenario.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Commercial vehicle research reports have longer individual document lengths, so sufficient context must be retained to avoid loss of key parameters and multi-turn dialogue logic |
RECALL_TOP_N | Top 8–12 results | Commercial vehicle research reports contain multiple types of fields such as vehicle parameters, sales data, and policies, so sufficient retrieval results must be covered to support multi-turn follow-up questions |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Commercial vehicle research reports often contain nested tables and long paragraphs, so parsing takes longer than general documents, requiring an extended timeout threshold |
PROMPT_TEMPLATE | Fixed requirement to extract commercial vehicle-specific parameters and label standard units | Commercial vehicle parameter units are uniform and clear, forcing the prompt to return specified units can avoid unit conversion errors |
WORKFLOW_CLASSIFY_MODEL | Calibrated based on actual testing | Different models have varying accuracy in classifying questions for commercial vehicle-specific scenarios, requiring adjustment based on business testing |
MAX_RETRY_TIMES | 2 times | Research report data retrieval may fail due to API fluctuations or temporary unavailability of data sources, appropriate retries can ensure dialogue continuity |
The parameter values provided on this page are common starting points 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 settings.
Common Misconfigurations
- Using a general classification model when configuring
WORKFLOW_CLASSIFY_MODEL, leading to incorrect classification of commercial vehicle-specific questions and triggering non-matching workflow branches. This occurs because general models have not been fine-tuned for terminology associated with commercial vehicle niche categories, and cannot accurately recognize industry-specific queries. - Failing to specify
fileTypeaspdfwhen uploading research report files via API, leading to the system being unable to correctly parse the nested table structure of commercial vehicle research reports. This occurs because the system's default parsing logic does not adapt to the document format of commercial vehicle research reports, requiring explicit specification of the file type to trigger the corresponding parsing rules. - Not enabling the
enableSessionPersistparameter during multi-turn dialogue, leading to global variables not being retained across sessions, requiring repeated input of conditions for each follow-up question. This occurs because session persistence configuration is not enabled, and the system resets the conversation context by default, making it impossible to retain context information for multi-turn dialogue.
How to Verify Successful Configuration
- Initiate a multi-turn dialogue covering commercial vehicle model parameters and sales data, and verify that returned results include fields with specified units and have coherent context logic.
- Upload a commercial vehicle research report in PDF format, and check that parsed text retains key information from nested tables without parsing truncation or format disorder.
- Test the question classification function, input a commercial vehicle-specific query, and confirm that the corresponding research report retrieval workflow branch is triggered.
- Modify global variables after enabling multi-turn dialogue, and verify that subsequent follow-up questions use the updated variable conditions for retrieval.
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.