Customer Technical Support and Pre-sales Q&A for Renewal Health Management: Knowledge Base Retrieval and Recall

What the data for this category looks like

Core data for renewal health management typically comes from CRM systems, product usage data, ticket statistics ledgers, and contract archives. Data update cycles follow weekly or monthly intervals. Daily produced documents include customer health reports, renewal forecast sheets, high-risk customer lists, and cross-department meeting minutes. Common data fields include customer unique identifiers, remaining contract periods, recent cycle activity metrics, ticket response times, and risk level tags. There is no unified fixed unit format, and adaptation is required based on document type.

What constraints do these characteristics impose on knowledge base retrieval and recall?

Multi-source heterogeneous data sources require retrieval to support cross-document associated matching, avoiding fragmented information pieces. Weekly or monthly update cycles mean the knowledge base incremental sync cycle should not be too short, balancing real-time performance and computing costs. Mixed scenarios of structured table documents and unstructured meeting minutes require retrieval modes that balance semantic understanding and precise field matching. The business goal focused on renewal retention risk requires recall results to prioritize documents related to high-risk customers, avoiding irrelevant content interfering with decision-making.

How to configure

The following configurations are based on FastGPT v4.17.0.

Three Common Misconfigurations

• Phenomenon: Entering a renewal question that exactly matches a knowledge base chunk fails to recall the corresponding content, but creating a new similar knowledge base allows normal recall. Cause: The datasetSearchUsingExtensionQuery configuration of the original knowledge base was accidentally enabled, causing the originally exact-matched chunk to be overwritten by automatically expanded semantics, losing precise recall capability.
• Phenomenon: In a private deployment environment, after setting limit to 6 via API, the number of retrieval entries cannot be adjusted to a higher value. Cause: The system default configuration limits the maximum number of entries per retrieval, and the corresponding threshold was not modified in the deployment configuration file.
• Phenomenon: After configuring all parameters, the knowledge base never returns recall results. Cause: The similarity threshold is set too high, causing documents that meet business relevance requirements to be excluded from the recall range.

How to Confirm the Configuration is Valid

• View the logs returned by the retrieval interface, confirm that recall results only come from the specified exclusive renewal health management knowledge base, to verify that the collectionIds configuration takes effect.
• Enter a renewal consultation question about a high-risk customer, check whether the recall results include the corresponding high-risk customer list and meeting minutes, to verify the ranking effect of similarity and usingReRank.
• Adjust the similarity threshold, observe changes in the number of recall results, confirm that the threshold setting meets the business precision requirements.
• Call the retrieval interface via API, confirm that the number of returned results matches the configured limit parameter, to verify that the interface parameter takes effect.

The values provided are common starting points and should be measured against the reader's own 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.