About This Page
This content covers deployment and upgrade for hotel and catering industry research report retrieval and question answering.
What this category’s data looks like
Hotel and catering research report data mainly comes from industry association public monitoring data, third-party catering consumption research institution reports, public financial reports of listed catering enterprises, and regional business district catering consumption review documents. Updates follow a regular cycle, with temporary reports added during holidays and new product launch periods. Document structure includes modules such as core business indicators, regional competitor comparison, supply chain cost breakdown, and store operation suggestions. Fields include customer unit price, average daily passenger flow, store area efficiency, and ingredient procurement cost, with units of yuan/person-time, person-times/day, yuan/square meter/day, and yuan/kilogram respectively.
What constraints do these characteristics impose on deployment and upgrade?
The multi-source and scattered nature of hotel and catering research reports requires standardized verification rules for multi-data source docking during deployment, to avoid field format conflicts across different sources. The non-fixed update rhythm requires optimizing incremental index trigger logic during upgrade, to support immediate access to temporary reports without triggering full index operations to save resources. The large content volume of single documents requires adjusting text parsing segmentation thresholds during deployment, to prevent core business data from being truncated. The presence of multiple fields with multiple units requires configuring unified unit mapping rules during upgrade, to ensure correct aggregation of identical indicator data from different sources. When upgrading the parsing engine, compatibility testing for long documents is required, to avoid parsing failures.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Hotel and catering research reports have relatively long length and include multi-dimensional business data. 600 seconds covers the complete parsing process for most documents |
maxContext | 800–1200 characters | Core business indicators and competitor analysis paragraphs of hotel and catering research reports are mostly within this length, which can retain complete context |
Recall count | Top 8–12 entries | Research reports for this category have numerous segmented dimensions. Retrieving 8 to 12 entries can cover multiple types of relevant information including regions, categories, and supply chains |
Similarity threshold | 0.75–0.85 | Competitor information in hotel and catering research reports has high similarity. This threshold can filter redundant content and retain accurately matched results |
UPLOAD_FILE_MAX_SIZE | 2000 MB | A single research report may include batch data from multiple stores, so large file upload support is required |
Rerank result count | Top 3–5 entries | Final display results need to be concise. 3 to 5 entries can cover core user query needs |
Three Common Mistakes
- Phenomenon: After upgrading to a new version, previously queryable research report content cannot be retrieved, and the interface displays no matching results. Cause: Full or incremental index was not re-executed. After the index parsing rules are updated in the new version, old index data is incompatible with the new rules.
- Phenomenon: When uploading a single large research report, the interface displays upload failure, and the backend returns
413 Request Entity Too Largeerror. Cause: TheUPLOAD_FILE_MAX_SIZEconfiguration value is smaller than the actual size of the uploaded file, exceeding the system's allowed upload limit. - Phenomenon: A large number of truncated business data paragraphs appear after parsing the research report. Cause: The
maxContextconfiguration value is too small, causing core content to be truncated during segmentation and losing key information.
How to Confirm Configurations Are Correct
- Upload a standard research report of this category, check the parsed text content, confirm that core business indicators are not truncated, and verify that the
maxContextconfiguration matches the actual retained context length. - Initiate a retrieval for common query scenarios of this category, check the number of retrieved results, and confirm that the
Recall countconfiguration matches the actual number of returned results. - Upload a common large-volume research report of this category, confirm that the upload is successful, and verify that the
UPLOAD_FILE_MAX_SIZEconfiguration covers the file size. - Trigger an incremental index operation, check whether newly uploaded research reports can be retrieved, and confirm that the incremental synchronization cycle configuration matches the expected update rhythm.
The parameter values provided on this page are common recommended starting points for determining configurations. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Testing on local samples is recommended before finalizing settings.
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.