What Data for This Category Looks Like
Data sources for professional chain investment research cover store operation ledgers, supply chain inventory reports, regional consumer research summaries, franchisee performance data, and competitor store trends. Data update frequencies vary. Real-time operation data such as store foot traffic and per-square-meter daily sales are updated daily. Supply chain inventory data is synced in batches. Industry research reports and new product launch information are updated when events occur. Document structures include structured tables (such as weekly single-store revenue reports), semi-structured inspection reports with photo attachments, and unstructured text summaries. Most fields have clear units, for example "daily average store foot traffic (person-times)", "per-square-meter daily sales (yuan/square meter/day)", "new product launch cycle (days)". Some fields require classification labeling by region and store hierarchy.
Constraints for Knowledge Base Retrieval and Recall
Multi-source and heterogeneous data structures require the retrieval link to support weight adaptation across document types. This prevents field information in structured tables from being diluted by unstructured text. Data sources with different update frequencies need matching index refresh strategies. Full refreshes of frequently updated store data will increase retrieval latency. Business fields with units require matching both numerical values and units during retrieval. Otherwise, confusing results such as "per-square-meter daily sales (yuan/day)" and "per-square-meter daily sales (yuan/square meter/day)" may be returned. Cross-store and cross-region investment research analysis requires retrieval to support range filtering by store ID and region. This avoids irrelevant data interfering with core conclusions.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_top_k | Top 15-20 results | Professional chain investment research has many data dimensions. Sufficient candidate sets must be retained for subsequent reranking to avoid missing core information |
chunk_size | 800-1200 characters | Store operation documents mostly consist of short tables paired with explanatory text. This segment length preserves field relationships and prevents loss of business context after splitting |
similarity_threshold | 0.75-0.85 | Investment research scenarios require precise matching of business terms and field units. A threshold that is too low will include non-target data from unrelated stores |
rerank_top_n | Top 5-8 results | Investment research reports must prioritize core business conclusions. Excessive redundant results will reduce decision-making efficiency |
incremental_update_interval | Every 6 hours | Frequently updated data such as store foot traffic and inventory requires regular index refreshes. Full updates will lead to excessive retrieval latency |
enable_field_extract | Enabled | Structured operation data requires field extraction for precise retrieval, such as filtering results by fields like "per-square-meter daily sales" and "franchisee performance rate" |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, 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: No results are returned when invoking a variable to reference a specified knowledge base, and the corresponding field is empty. Cause: The permission scope of the knowledge base bound to the variable was not configured in the retrieval node, so documents matching the corresponding store ID cannot be retrieved.
- Symptom: Knowledge base retrieval responses time out, returning a
504 Gateway Timeoutstatus code. Cause: An incremental update strategy was not configured. Each retrieval performs a full scan of all store operation documents, causing latency to exceed thresholds. - Symptom: Image links in retrieval results are truncated, showing only partial paths. Cause: Document parsing did not extract the complete image storage domain name, only retaining relative paths, and no global domain name configuration was added.
How to Verify Proper Configuration
- Submit a test dataset containing structured store data, semi-structured inspection reports, and unstructured research reports. Run a retrieval test and confirm that the segment length of returned results matches the configured
chunk_sizerange. - Invoke the retrieval interface with a variable specifying a store ID. Confirm that returned results only include documents for the corresponding store, with no cross-store irrelevant data.
- Upload an image document containing complete external links. After retrieval, confirm that image links are displayed fully with no truncation.
- Simulate high-concurrency retrieval requests. Confirm that response times meet business expectations, with no timeout errors.
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.