What this category of data looks like
This category of data mainly comes from customer system interfaces, API documentation, test data, and integration logs. The core documents for daily maintenance include API lists, integration records, field mapping tables, and issue tracking sheets. Data update frequency is daily or aligned with project phases. Data fields include API addresses, request parameter rules, response status codes, and field mapping relationships. Some fields have units: for example, API call duration is measured in milliseconds, and request body size is measured in bytes. Different projects have significant differences in API field formats. Alignment requires reliance on dedicated documentation.
What constraints do these characteristics impose on knowledge base retrieval and recall
Data sources for this category are scattered and updated frequently. Knowledge base retrieval must support synchronized recall across multiple data sources to avoid missing latest integration logs and API changes. API fields have strong personalized traits. Retrieval must prioritize matching field mapping relationships and standard field definitions; general recall rules are prone to matching deviations. Daily operations require quick location of issues corresponding to abnormal codes. Retrieval accuracy directly affects troubleshooting efficiency, and expired API configuration data must not be recalled. Additionally, different projects have large differences in document structures. Retrieval configuration must adapt to multi-format API documents and integration records.
How to set configurations
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | High precision is required for API field matching to avoid recalling irrelevant old API configurations |
limit | Top 8–12 entries | Balances recall coverage for multiple document types including integration logs and API lists, while controlling context length |
searchMode | Semantic retrieval + keyword matching | Adapts to precise matching of API fields and keyword positioning needs for integration records |
usingReRank | Enabled | Re-ranks recall results by relevance to prioritize returning latest integration logs and updated API information |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands search terms to cover matching for API aliases and synonyms of common abnormal codes |
Three common misconfigurations
- Phenomenon: Retrieval results include external API information not present in the knowledge base. Cause: Forced only knowledge base retrieval configuration is not enabled, causing the model to call external data sources.
- Phenomenon: Knowledge base query response is slow and fails to meet real-time response requirements for operational on-call. Cause: Retrieval cache configuration is not enabled, or the number of recall entries for the
limitparameter is not restricted, leading to repeated execution of high-overhead retrieval tasks. - Phenomenon: Model output language does not match the language of knowledge base documents. For example, the knowledge base contains English API documents but the model only returns Chinese responses. Cause: Post-retrieval answer language matching rules are not configured, or prompt and knowledge base language requirements are not aligned.
How to confirm the configuration is correct
- Upload a latest integration log and API list to the dedicated dataset, perform retrieval testing, and verify that the recall results include the latest field mapping content.
- View retrieval logs to confirm that the number of recall entries matches the range set by the
limitparameter, with no abnormal timeout records. - Test retrieval of English API documents to verify that the model output language matches the document language, with no cross-language deviations.
- On the FastGPT v4.17.0 backend configuration page, confirm that the values of parameters such as
similarityandusingReRankmatch the preset configuration.
The values provided here are common starting points and should be evaluated 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.