What this type of data looks like
Financial institutions’ tourist attraction research reports for cultural and tourism industry analysis are mainly sourced from public information released by cultural and tourism authorities, monthly operation reports from scenic spot operators, and special research results from third-party cultural and tourism consulting institutions. The regular update cycle is monthly or quarterly. Temporary research reports on passenger flow forecasts are released around statutory holidays. Document structures typically include core operation indicators, regional cultural and tourism policy interpretations, analysis of surrounding business linkages, and competitor benchmarking content. Fields mostly involve visitor trips, revenue amount, floor area, opening hours, and similar metrics. Common units are trips, ten thousand yuan, square kilometers, and hours.
What constraints do these characteristics impose on model access and configuration
The multi-source nature, non-fixed update cycles, varied document structures, and diverse field units of tourist attraction research reports for cultural and tourism industry analysis create multiple constraints for model access and configuration. Data sources include multiple formats such as public PDFs, operation Excel files, and web public notices. Preprocessing rules for models that support multi-format parsing must be configured. The temporary update frequency is relatively high, so an on-demand pull synchronization mechanism must be configured to adapt to sudden update requirements. Field names and units vary across research reports from different scenic spots. Custom field mapping and unit normalization preprocessing must be configured to ensure consistent model input formats.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Tourist attraction research reports often contain long tables and multi-page content, with relatively long regular parsing times. 300 seconds covers the parsing needs of most documents |
maxContext | 8000–12000 characters | Tourist attraction research reports include multi-dimensional operation data and analysis content, requiring sufficient context to ensure the model understands the complete logic |
| Recall Count | Top 8–10 entries | Core information of tourist attraction research reports is concentrated in a small number of paragraphs. Excessive recall will introduce irrelevant content that interferes with model output |
| Similarity Threshold | 0.75–0.85 | Tourist attraction research reports cover multiple distinct scenarios. A threshold that is too low will include irrelevant research reports, while a threshold that is too high will miss relevant content |
| Rerank Return Count | Top 3–5 entries | Core conclusions of tourist attraction research reports are usually concentrated in a small number of entries. Streamlining these results can improve model response efficiency |
UPLOAD_FILE_MAX_SIZE | 500 MB | Large scenic spot research reports may contain multi-page high-definition images and detailed data tables. 500 MB covers the needs of most single documents |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: After upgrading to version 4.8.20, the knowledge base can normally recall data, but the model outputs no results. Cause: Dependent parameters for the rerank model are not configured correctly, or the
maxContextparameter for the rerank model is set beyond the resource limits of the current deployment. - Symptom: When deploying the rerank model offline, setting
Rerank Return CounttoTop 6 entriescauses deployment failure. Cause: The offline rerank model has a single return limit of 5 entries. Exceeding this limit triggers a configuration verification error. - Symptom: When connecting a custom model, the
API_KEYparameter is not configured, resulting in a 401 status code returned by model calls. Cause: The model access key is not filled in correctly, so interface authentication cannot be completed. In some scenarios, even if the One API service is not used, a dedicated access key must be configured.
How to Confirm Configurations Are Correct
- A local tourist attraction research report document is uploaded, and the parsing task status is checked to confirm whether it shows "Completed". If failed status is displayed, the parsing timeout configuration and file size limits are reviewed.
- A question-and-answer test related to research reports is initiated, and the model's returned content is observed to confirm whether it includes core operation data and analysis conclusions from the recalled documents.
- Model call logs are reviewed to confirm that the interface returns a 200 response code, and that the request parameters include the correctly configured
API_KEYandAPI_BASE_URL. - The recall count and similarity threshold are adjusted, the number of recall results under different configurations is tested, and the configuration parameters are confirmed to take effect normally.
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.