What the data for this category looks like
Data sources for hotel and catering investment research cover store operations, supply chains, industry research, and competitor analysis. Store operations data comes from POS systems and reservation management systems. It includes fields such as real-time foot traffic, revenue, and average order value. Supply chain data comes from ingredient supplier quotes and inventory management systems. It includes fields such as ingredient names, purchase prices, and inventory levels. Industry data comes from regional consumption trend reports and customer review platforms. It includes content such as category preferences and regional popularity. Update rhythms vary significantly. Store POS data updates daily or hourly. Supply chain quotes update weekly. Industry reports update monthly or quarterly. Menu and new product information updates irregularly alongside store operations. Document formats include structured reports, semi-structured PDF menus, and unstructured review text. Field units use standard metrics such as yuan, people, and kilograms.
What constraints these characteristics impose on deployment and upgrade
Multi-source, heterogeneous data formats and differentiated update rhythms create multiple constraints for deployment and upgrade. Structured store operations data has high write frequencies. Deployments must configure storage solutions that support high-frequency read and write operations. Semi-structured menu PDFs and long-text industry reports require pre-configuring long-document parsing parameters during deployment. This prevents parsing failures after upgrades. Differing update cycles across data sources require retaining configurable incremental sync tasks during upgrades. This avoids excessive resource usage from full sync operations. Additionally, multi-instance data access across multiple stores and suppliers requires pre-configuring unified data cleaning and mapping rules during deployment. This prevents data loss from format conflicts after upgrades.
How to set configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Hotel and catering menu PDFs and annual revenue reports are typically lengthy. A too-short timeout will cause parsing interruptions |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Annual operational datasets for store clusters and regional consumption trend reports have large file sizes. This setting supports large file uploads |
maxContext | 800–1200 characters | Investment research scenarios require accurate recall of core business fields. Overly long context introduces irrelevant information and reduces retrieval precision |
Number of recall results | Top 8 results | Balances multi-dimensional investment research needs across stores, supply chains, and competitors. Too many results exceed the conversation context window |
Similarity threshold | 0.75–0.85 | Filters low-relevance non-local reports and unrelated customer reviews, while retaining sufficient valid retrieval data |
RE_RANK_TOP_N | Top 3 results | Performs secondary ranking on recall results to focus on core investment research information, avoiding redundant content interfering with analysis |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material formats, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- After uploading a hotel and catering menu PDF, the data processing stage returns empty content. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. Long document parsing timed out and was forcibly terminated. - After deployment, a MongoDB connection error occurs, prompting that a replica set configuration is required. Cause: The MongoDB replica set was not enabled as required. Some versions enforce replica set mode by default to ensure data reliability.
- After migrating a deployment instance from Sealos to a local environment, the knowledge base cannot sync existing data. Cause: Cross-environment storage volume mount paths were not configured. Local services cannot access original document index files.
How to confirm configurations are properly set
- Upload a typical hotel and catering menu PDF. Check if the processed fields are complete, and verify that parsing time matches the preset
PARSE_FILE_TIMEOUT_SECONDSvalue. - Run an incremental sync task. Check if new investment research data entries are generated in MongoDB, and confirm that the replica set configuration is working correctly.
- Initiate an investment research topic conversation. Check if the number of recall results and similarity score fall within the preset threshold range, and verify the ranking logic of reranked results.
- Restart the service after adjusting any configuration item. Check system logs for errors related to parameter loading failures, and confirm all configurations were loaded correctly.
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.