What the data for this category looks like
Publishing industry research report data comes from official releases of professional publishing institutions and authorized access to industry databases. Update cycles primarily follow scheduled special research reports, supplemented by temporary reports for sudden industry events. A single document includes sections such as the release header, industry background, core data tables, rating conclusions, and investment advice. It contains fields including report ID, publishing institution, release date, industry tags, target price, and revenue forecast. Most target prices are quoted in RMB per share, and revenue forecasts are quoted in 100 million yuan.
What constraints these characteristics impose on model access and configuration
Research reports have authorized sources, so the model access link must adapt to exclusive data permission verification logic to prevent unauthorized content from being called. Fixed update cycles and sudden content coexist, so the model caching strategy must support dynamic refresh based on release date. Single documents are long and include structured tables, so the model context window and segmentation configuration must adapt to long text processing. Multiple structured fields require recall and reranking parameters to accurately match semantic associations of professional content, to avoid invalid recall.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
maxContext | 8000–16000 characters | The text length of a single research report mostly falls between 5000 and 12000 characters, with reserved space for splicing retrieval results |
rerankTopK | Top 3–5 results | Research report content is professional and contains relatively redundant information; too many recall results will dilute core arguments |
simThreshold | 0.75–0.85 | Industry tags and core content of research reports have high relevance. A threshold that is too low will introduce irrelevant documents, while a threshold that is too high will miss relevant content |
UPLOAD_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing embedded tables and images in single research report PDFs takes longer than ordinary documents |
MODEL_API_TIMEOUT | 60 seconds | Research report Q&A requires integrating multiple retrieval results, and model inference takes longer than general Q&A scenarios |
RERANKER_MODEL_MEMORY_LIMIT | 6G per GPU card | Adapts to the video memory usage of bge-reranker-style reranking models, to avoid insufficient video memory on a single card or unlimited video memory usage across multiple cards |
The parameter values provided on this page are all conventional recommendations, used as a 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 the settings.
Three Common Misconfigurations
- Phenomenon: After calling the bge-reranker model, GPU video memory quickly grows to 6-7G, and each GPU card shows usage. Cause: The video memory limit parameter for the reranking model is not configured, so the full model weights load to all available graphics cards by default.
- Phenomenon: An invalid token error displays when accessing a domestic model, and the interface functions normally when tested with a third-party interface testing tool. Cause: The API path prefix required by the platform is not specified in the model access configuration, or custom request header parameters are not included.
- Phenomenon: The model configuration entry appears on the password-free access page. Cause: The model configuration node is incorrectly bound to public access permissions, and access rules that only allow internal operation and maintenance personnel to view are not set.
How to confirm the configuration is correct
- Upload a test research report, check whether the parsed text fields fully cover the standard modules of the research report, to confirm that the parsing configuration adapts to the research report structure.
- Initiate a Q&A request targeting specific content in the research report, check whether the returned results accurately associate corresponding fields and arguments, and verify the actual effect of recall and reranking parameters.
- Observe GPU monitoring data, confirm that video memory usage stabilizes within the expected range after the reranking model starts, and that unlimited growth does not occur.
- Initiate a model call request using a forged invalid token, confirm that the system returns a corresponding error prompt, and verify that the token verification logic takes effect.
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.