What This Category of Data Looks Like
Data for this category typically originates from code repositories, documentation site build logs, user feedback, and version release records. Updates follow a weekly or per-version release schedule. Daily maintained documentation covers installation guides, API reference documents, migration manuals, and frequently asked questions. Data fields include version identifiers, interface parameters, operation steps, and troubleshooting instructions. Technical writers, maintainers, or developer relations teams compile this data. Content focuses on long-term usable usage guidance. No fixed mandatory format exists, but content must align with the current software version.
Constraints Imposed on Knowledge Base Retrieval and Recall
Since data updates weekly or per version, the knowledge base must support incremental synchronization and automatic filtering of expired content. This prevents returning outdated installation or interface instructions. Multi-source data includes code repository comments, build logs, and user feedback. The system must clean unstructured text to filter invalid logs and redundant feedback. Document types include structured API documents, Q&A pairs, and step-by-step guides. Retrieval must adapt to different text structures: perform precise matching for interface paths, and semantic recall for step-by-step content. The long-term usable attribute requires recall results to link to the current software version, avoiding mixing content across versions.
Configuration Settings
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Meets the precise retrieval needs of technical documentation, filters low-relevance redundant content |
limit | Top 8–12 results | Controls the number of recall results per request, avoids excessively long context that impacts subsequent generation |
searchMode | semantic | Targets the semantic structure of technical documentation, prioritizes matching semantically related professional content |
usingReRank | Enabled | Performs secondary ranking on recall results, improves ranking accuracy for API documents and migration guides |
datasetSearchUsingExtensionQuery | Enabled | Generates extended queries based on user questions, covers synonyms and parameter aliases in technical documentation |
collectionIds | Fill in according to the knowledge base collections associated with the documentation site | Limits the retrieval scope, prevents mixing documentation data from other categories |
Three Common Configuration Errors
- Symptom: An
invalid configuration parameter name "hnsw.max_scan_tuple"error appears during retrieval. Cause: A non-platform-specified configuration item name is used, and FastGPT’s official configuration specifications are not followed. - Symptom: Single knowledge base retrieval takes longer than 3–5 seconds, causing page loading lag. Cause: A reasonable
limitvalue is not configured, leading to recall of excessive redundant document fragments and increased time for subsequent ranking and splicing steps. - Symptom: When retrieving documents converted from scanned PDFs, recall results do not match the intended semantics, and technical content in images cannot be extracted. Cause: No cleaning is performed on OCR-processed scanned text, leaving large amounts of redundant layout characters that degrade semantic embedding performance.
How to Verify Proper Configuration
- Submit a known technical documentation keyword, and check whether the matching degree of returned results meets business expectations.
- Review retrieval logs to confirm only content within the knowledge base collections associated with the documentation site is recalled, with no data from other sources included.
- Submit multiple consecutive technical questions, and verify that extended queries are generated and matching document fragments are returned.
- Simulate a retrieval request, and confirm that single retrieval time meets the performance requirements of the business side.
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.