What data belongs to this category
Data for this category comes primarily from customer system interfaces, public API documentation, integration test data, and issue tracking logs. Daily deliverables include interface lists, integration records, field mapping tables, and issue tracking sheets. Data is updated daily or per project phase. Fields include interface addresses, request parameters, return fields, error code definitions, and field mapping rules. Some data includes unit information, such as interface response timeout thresholds and data transmission byte counts.
Constraints imposed by these characteristics on knowledge base retrieval and recall
Data sources include both real-time interface data and static documents. Retrieval must adapt to both structured interface parameters and unstructured document content to avoid disjointed recall results. High-frequency demand for field mapping and standard confirmation requires retrieval and recall to support field-level precise matching, reducing ambiguity caused by fuzzy matching. The daily or per-phase update frequency requires knowledge base recall to quickly synchronize the latest integration records and interface changes, avoiding use of outdated data. A single integration involves a large number of interfaces, so the number of recall results per query must be controlled within a reasonable range to avoid context overload that reduces troubleshooting efficiency.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Matches the precision of interface fields and integration records; the interval covers common standard matching requirements, calibrated based on actual testing |
limit | Top 8–12 entries | A single integration involves a large number of interfaces; controlling the number of recall results avoids context overload, adapting to the information density of integration troubleshooting |
searchMode | vector + fulltext | Balances vector matching for structured interface parameters and full-text retrieval for unstructured documents, covering multiple data types including interface lists and integration logs |
usingReRank | Enabled | Interface-related questions require precise matching of error codes and field names; re-ranking improves the sorting priority of highly relevant results |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands user integration questions, supplementing keywords such as interface names and error codes to improve recall coverage |
collectionIds | Bind exclusive collections per project | Isolates integration data across different customers, preventing interference from irrelevant results across projects |
Three Common Misconfigurations
- Phenomenon: The result returned after calling the configured LLM is unrelated to the knowledge base content. Cause:
datasetSearchUsingExtensionQueryis not enabled, or thesearchModeconfiguration is incorrect, resulting in failure to correctly associate integration-related knowledge base data. - Phenomenon: As knowledge base content increases, question-and-answer response time lengthens and token consumption increases. Cause: The value range of
limitis not restricted, leading to recall of excessive redundant interface documents and integration logs, which causes context length to exceed limits. - Phenomenon: The test model configuration prompts an error, but runs normally after referencing the knowledge base. Cause: The value range of
similarityis unreasonable, causing model verification to fail while the actual retrieval logic remains unaffected.
How to Confirm Correct Configuration
- Upload a test interface list document, initiate a query containing the target interface name, and verify that the recall results include relevant fragments of the uploaded document.
- Adjust the value of
limit, and observe whether the number of recall results per single query matches the configured interval range. - Switch between different project collections, and confirm that recall results only include integration data within the currently bound collection.
- Verify the FastGPT v4.17.0 version information, and confirm that the configuration items are compatible with the current version.
- Upload a single test document with a volume of 120MB, and confirm that the system supports normal import or provides reasonable prompts.
Note: The configuration values listed here are common starting points. Adjust them based on your own specific samples and use cases.
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.