What Data for This Category Looks Like
Vehicle industry research reports mainly come from securities research institute automotive industry teams, domestic automotive industry associations, public technical white papers and sales announcements released by vehicle manufacturers. Update cycles follow these rules:
- Securities research reports: Quarterly regular releases, with supplementary temporary reports for major vehicle launches or industry policy adjustments
- Domestic automotive industry association data: Updated monthly
- Enterprise technical documents: Updated irregularly alongside vehicle model iterations
Documents typically include four core modules: core vehicle parameter tables, market sales analysis, technical route breakdown, and competitor comparison. Fields include CLTC range (unit: km), maximum power (unit: kW), maximum torque (unit: N·m), per-vehicle production cost (unit: yuan), plus metadata such as research report publishing institution, publication date, and corresponding vehicle model year.
Constraints Imposed on Tool Calling and Plugins
Parameters with specific units require automatic identification and unified unit formatting during tool calling to avoid power unit confusion. Irregular update frequencies and scattered data sources require scheduled incremental pull plugin configuration to synchronize the latest research reports and data, preventing outdated content returns. Long individual documents with structured tables require chapter-based splitting during parsing to avoid exceeding model context limits. Research report content is strongly tied to specific vehicle models. Tool calling must pass the vehicle model year as a required parameter to accurately match exclusive content from the corresponding data source.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | The segmented length of parsed single vehicle industry research reports is concentrated between 5000-10000 characters, reserving sufficient context for parsed content and query instructions |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Vehicle industry research reports contain multi-dimensional technical tables and parameter comparisons, with higher parsing time than general documents |
Recall count | Top 8–12 results | Core parameters and competitor information in vehicle industry research reports are concentrated; excessive recall will introduce irrelevant general industry discussions |
Similarity threshold | 0.75–0.85 | Technical parameter queries require high matching accuracy to avoid recalling research report content for non-corresponding vehicle models |
Rerank result count | Top 3–5 results | Decision-making only requires the 3-5 most relevant research report conclusions, reducing model processing and context occupancy |
TOOL_CALL_MAX_RETRIES | 2 retries | Set a reasonable number of retries when tool calls fail, avoiding resource occupation from repeated requests |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Mistakes
- Symptom: Segmented vehicle industry research reports exceed the set threshold, and the reranking model is not triggered, resulting in more returned results than expected. Cause: The
Rerank result countparameter is not configured, or the segmented length is set too large, causing the reranking logic to not be triggered before truncation. - Symptom: Custom Python tool calls fail to run code modules normally, returning execution failure prompts. Cause: Python dependency libraries required for research report parsing are not installed in the deployment environment, causing the code module to fail to load the corresponding automotive industry data parsing logic.
- Symptom: Tool calls return a 400 status code, with logs displaying
role 'tool' message missing preceding assistant message. Cause: The context order of tool calls is incorrect, and tool return results are not immediately passed after the model generates the tool call request.
How to Verify Successful Configuration
- Upload a single vehicle industry research report, and check if the parsed segmented length matches the set range of
maxContext. - Initiate a parameter query for a specified vehicle model, and verify that the number of recalled research reports falls within the set interval of
Recall count. - Check the tool call logs to confirm that each tool request includes the vehicle model year parameter, and that returned results have no empty fields.
- Trigger a long document retrieval task, and check if the reranking model is automatically called and results within the
Rerank result countlimit are returned.
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.