What the data for this category looks like
Snack food marketing content data primarily comes from product manuals of partner brands, new product launch press releases, e-commerce platform detail pages, social media recommendation content, temporary promotional event rules, membership benefit descriptions, and exclusive point redemption rules for financial channels. Update frequency fluctuates with marketing cycles: higher during new product launch and holiday promotion periods, lower during routine marketing cycles. Most documents are short texts, with wide variation in individual length. A small number of long-text event rules are included. It is recommended to calculate or test based on internal sample data. Fields include product SKU, flavor, specification, selling price, event time, applicable channels, etc. Units include grams, bags, servings, yuan, etc.
What constraints these characteristics impose on knowledge base retrieval and recall
A high proportion of short texts and many precise identification fields require the retrieval system to balance semantic recall and precise matching, avoiding irrelevant results from short text semantic drift. Multiple structured fields require support for field-based filtered retrieval, such as filtering results by product flavor or event time. Fluctuating update frequency requires support for incremental synchronization and scheduled trigger updates, avoiding repeated full uploads. Time-sensitive marketing content requires recall results to be filterable by time dimension, displaying only recently valid content. Exclusive financial channel rules require support for filtering matching results based on user identity or point level.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
segment_length | 800–1200 characters | Snack food marketing content includes short recommendation copy and long event rules. This range balances semantic completeness and recall accuracy |
similarity_threshold | 0.72–0.85 | Short text selling point matching requires a higher threshold to avoid irrelevant results. Long event rules can appropriately relax the threshold to cover relevant content |
recall_count | Top 6–8 results | Marketing content needs to display multiple sets of selling points or event options. Too many results cause information overload and affect judgment |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Some batch-uploaded event rule documents are long. This duration covers the complete parsing process |
enable_full_text_search | Enabled | Snack food marketing content includes many precise matching contents such as brand names and SKU numbers. Full-text search supplements the shortcomings of semantic retrieval |
incremental_sync_trigger_condition | Triggered by file modification time | Most updates to snack food marketing content are temporary events or new product launches. Triggering by modification time accurately synchronizes the latest content |
Three Common Mistakes
- The symptom is that a targeted query on uploaded documents in the workspace returns no relevant results. The cause is that precise retrieval rules are not configured for structured fields. Relying only on semantic recall cannot match SKU numbers or product names in documents.
- The symptom is that the vector database service returns a "Connection error" error. The cause is that the vector database connection address and authentication information are not configured correctly, or the service port is not open.
- The symptom is that the number of createable knowledge bases has reached the upper limit, and new documents cannot be added. The cause is that the vector database storage configuration is not adjusted. The default upper limit for pgvector is 30 knowledge bases. The corresponding parameter needs to be modified to expand capacity.
How to Verify Successful Configuration
- Upload a test document containing product SKU and event rules. Run a targeted query, and check whether returned results include the document content.
- View the vector database connection logs, confirm that there are no "Connection error" related errors, and check whether the connection configuration matches deployment parameters.
- View the knowledge base list, confirm that the createable quantity meets expectations, and verify whether the expanded upper limit takes effect.
- Adjust the segment length parameter, upload marketing copy of different lengths, and check whether parsed segment results fall within the expected range.
The parameter values provided on this page are common 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 sample data before finalizing the configuration.
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.