What the data for this category looks like
Business data for hotel and catering comes from store menus, booking systems, review platforms, member consumption records, and offline marketing materials. Update rhythms vary significantly: menus adjust with seasons, holidays, or new product launches; reviews are generated in real time; marketing materials update per single campaign. Documents mostly take the form of structured tables and long text. Common fields include dish name, per capita consumption, arrival time slot, and ingredient inventory. Units include business-specific identifiers such as yuan, person-times, and kilograms. Some marketing documents exceed 10 MB per file, containing multi-page mixed text and image content.
What constraints these characteristics impose on multi-turn dialogues and prompt engineering
- Frequent menu updates require the dialogue system to refresh the knowledge base regularly to avoid recommending outdated dishes.
- Parsing large-volume documents takes longer, so timeout parameters must be adjusted to accommodate this.
- Multi-turn dialogues often involve fields with units such as per capita consumption and number of guests. Prompts must clearly specify field extraction rules to prevent format confusion.
- The large volume of review data requires limiting the number of recalled contexts in multi-turn dialogues to avoid redundant information occupying model processing space.
- Marketing content generation must strictly match the current in-stock products of the store. Prompts must bind the exclusive knowledge base of the corresponding store to prevent incorrect cross-store content.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | Hotel and catering dialogues often involve menus, reviews, and booking information. Long contexts need to carry details of multi-round consumption scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accommodates parsing time for 10 MB-level large Word documents, avoiding mid-process timeout interruptions |
RECALL_TOP_K | Top 8–12 entries | Balances the volume of recalled review and menu information, avoiding excessive redundant content occupying dialogue space |
PROMPT_TEMPLATE | Arranged in the order of "first match the store's current menu, then combine review preferences, and finally output marketing content" | Aligns with the business logic of catering marketing, which requires first clarifying the store's in-stock products and user past preferences |
UPLOAD_FILE_MAX_SIZE | 20 MB | Covers the upload requirements for 10–15 MB catering documents such as menu collections and review summaries |
SIMILARITY_THRESHOLD | 0.75–0.85 | Filters low-relevance review or menu content, ensuring that returned marketing content accurately matches user needs |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Symptom: Empty fields are returned when calling the dialogue interface associated with a knowledge base, and the interface displays "No knowledge base content matched". Cause: Field mapping configurations for catering documents such as menus and review sheets have not been set to a format recognizable by the dialogue interface, so the interface cannot extract valid business data.
- Symptom: A
504 Gateway Timeouterror is triggered when parsing a 10 MB-level Word document. Cause: ThePARSE_FILE_TIMEOUT_SECONDSparameter has not been adjusted to a duration suitable for large-volume documents. The default timeout duration is insufficient to complete long text parsing. - Symptom: "Thinking" separators remain during the dialogue, and the generated marketing content includes dishes not listed by the store. Cause: The prompt does not explicitly specify that the current bound store knowledge base must be prioritized, causing the model to call irrelevant external information.
How to Confirm Configuration Is Complete
- Upload a 10–15 MB catering document, check whether the parsing progress completes within the set timeout period with no error prompts.
- Initiate a multi-turn dialogue, test inputting questions such as "Today's recommended dishes" and "Preferences of guests who visited last week", and check whether the returned content matches the uploaded menus and review data.
- Call the dialogue interface, verify that the returned results include the number of knowledge base recall entries specified by
RECALL_TOP_K, and that the field format meets preset requirements. - Adjust the
SIMILARITY_THRESHOLDparameter to a lower threshold, test inputting low-relevance questions such as "Recommend coffee shop beverages", and check whether a prompt for no matching results is returned instead of irrelevant content.
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.