What data looks like for this category
Data for this category originates from ticketing systems, customer interview records, CRM systems, and product roadmap documents. Daily produced documents include requirement pool lists, requirement evaluation forms, customer feedback records, and version planning descriptions. Data is typically updated weekly, or synchronized with product version iterations. A single data entry typically includes fields such as requirement ID, associated customer identifier, priority tag, submission time, evaluation status, and detailed request content.
Constraints on reranking and hybrid retrieval
Data sources for this category are scattered and have heterogeneous formats. Implementing reranking and hybrid retrieval requires accommodating field differences across multi-source data such as tickets, CRM records, and interview notes. Teams must configure cross-source data alignment rules. Data update frequencies vary. Refresh cycles for retrieval and reranking must match weekly or version-level requirement data update rhythms to avoid using outdated requirement content. Structuredness varies widely across different documents. The reranking process must balance weight configurations for semantic similarity and fields such as priority and submission time. As requirement pool data volume grows, resource usage for retrieval and reranking must adapt to data scale to prevent performance degradation.
How to configure settings
| Configuration Item | Suggested Setting | Rationale |
|---|---|---|
usingReRank | Enabled | Customer requirement pool data includes multi-source heterogeneous customer feedback and ticket content. Enabling reranking filters low-relevance redundant entries and improves the targeting of retrieval results |
limit | Top 15–25 entries | Requirement pool data update cycles are mostly weekly or version-level. This value range covers requirement coverage for most pre-sales and technical support scenarios, while controlling retrieval resource usage |
similarity | 0.72–0.88 | This range balances the rigor and recall rate of requirement semantic matching, adapting to differentiated expression of customer requests |
searchMode | hybrid | Data for this category includes both structured fields and unstructured text. Hybrid retrieval mode matches both semantic similarity and field attributes, adapting to multi-source data characteristics |
| Reranking model video memory quota | Calibrated based on actual testing, no more than 60% of total video memory | Community feedback reports issues where reranking models occupy excessive video memory. This configuration avoids video memory overflow and ensures stable service operation |
Three common misconfigurations
- Retrieval and reranking processes take too long. Single requests take more than 10 seconds to return results, and interface loading times out. Cause typically involves a configured
limitvalue that is too large, or a configuration that does not adapt to requirement pool data scale, leading to redundant data participating in reranking calculations. - Unable to locate the reranking model configuration entry. No rerank-related settings appear on the knowledge base configuration page. Cause involves not accessing the dedicated knowledge base configuration menu for customer requirement pools, or the deployed version does not include this feature.
- Reranking model video memory overflow. The system reports insufficient video memory errors, or processes are forcibly terminated by the system. Cause involves not configuring a reasonable video memory quota, or multiple reranking tasks running simultaneously to occupy resources.
How to confirm correct configuration
- Access the requirement pool knowledge base configuration page for FastGPT v4.17.0, and confirm that the
usingReRanktoggle is enabled. - Submit a simulated pre-sales consultation question, and check whether the number of returned retrieval results matches the configured
limitvalue range. - Check whether retrieval result fields include both semantically matched request content and structured information such as priority and customer identifier, and confirm that
searchModeis set to hybrid mode. - View the system monitoring panel, confirm that video memory usage for the reranking model does not exceed the configured quota, and there are no consecutive overflow errors.
The values provided are common starting points and should be measured against actual deployment samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-10-19.