What the Data for This Category Looks Like
Data for this category primarily comes from customer service systems, community forums, app store reviews, and game logs. Daily processed documents include player support tickets, compensation requests, public opinion daily reports, and standardized response scripts. Common fields include player identifiers, feedback content, associated game scenarios, processing progress, and feedback channel identifiers. Data update cycles are typically daily or real-time. Individual document lengths vary widely, ranging from tens of characters of instant player feedback to thousands of characters of public opinion summary reports.
Constraints Imposed by These Characteristics on Reranking and Hybrid Retrieval
The data characteristics of this category create multiple constraints for reranking and hybrid retrieval. Dispersed multi-source data requires hybrid retrieval to adapt to inputs in different formats from customer service systems, community forums, and other sources, ensuring consistent cross-channel recall results. The wide variation in document lengths requires reranking models to handle both short instant player feedback (tens of characters) and long public opinion summary reports (thousands of characters). This prevents truncation of short content or exceeding model context limits for long content. Real-time updated feedback requires the retrieval pipeline to have controllable delay. The reranking step must not significantly increase overall response time. The strong association between support tickets and response scripts requires hybrid retrieval to first recall historical records from the same game scenario. The reranking step must filter irrelevant noise content to prioritize core information.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Reranking Toggle | Enabled | This category requires accurate sorting of multi-source feedback and historical response scripts. Enabling this improves result relevance |
| Similarity Threshold | 0.72–0.85 | Adapts to the short text characteristics of player feedback. Calibrate the threshold based on actual testing to distinguish valid and invalid recall results |
| Maximum Single Search Results | Top 10 | Balances retrieval efficiency and recall coverage, avoiding excessive redundant results that increase the load on the reranking model |
| Retrieval Mode | Hybrid Retrieval Mode | Adapts to multi-source data sources, integrating retrieval results from different channels such as customer service tickets and community comments |
| Reranking Input Length Limit | 1024–2048 token | Adapts to long documents such as public opinion daily reports, avoiding content truncation that affects ranking accuracy |
This configuration is based on FastGPT v4.17.0
Three Common Configuration Errors
- Symptom: Reranking markers in retrieval results are marked false, or reranked sorted results are not displayed. Cause: The reranking toggle is not enabled correctly, or the retrieval pipeline is not bound to a reranking model.
- Symptom: The reranking model is not triggered after retrieving long documents such as public opinion daily reports. Cause: The reranking model input length limit is set too low, exceeding the character count of the long document, so the system automatically skips the reranking step.
- Symptom: Reranking works normally during individual knowledge base retrieval tests, but the reranking function fails in the chat pipeline bound to a large language model. Cause: The retrieval configuration of the chat pipeline does not sync reranking settings, or large language model context truncation affects the passing of reranking parameters.
How to Verify Successful Configuration
- Access the FastGPT knowledge base configuration page. Confirm the reranking toggle is enabled and the retrieval mode is set to Hybrid Retrieval Mode.
- Submit test texts of different lengths, including short player feedback and long public opinion reports, to verify the reranking model is called normally.
- Review retrieval result return fields to confirm the post-reranking sorted priority meets business requirements, with no obvious redundant results.
- Simulate retrieval requests for real-time player feedback to verify pipeline delay meets business requirements.
Note: The configuration values provided here are common starting points. Adjust them based on specific samples and operational requirements for the target deployment.
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.