What the data for this category looks like
Nuclear power operation document data mainly comes from operating procedures, safety review reports, emergency response manuals, daily operation and maintenance inspection records, and event ledgers. Data update frequency varies by type: operation and maintenance inspection records are updated daily, while procedure documents are updated synchronously after major equipment changes or regulatory revisions. Most documents use a chapter-based structure, including fields such as equipment number, working condition parameters, operation steps, and responsible positions. Units involve professional metrological identifiers such as megawatts, operating hours, and pascals.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
The long-text structure and specialized field characteristics of nuclear power operation documents require retrieval and recall to balance long-context matching and precise field association. Individual documents are lengthy: if chunks are split too finely, the logical connection of operation steps will be broken. If chunks are too coarse, irrelevant information will be introduced. The presence of specialized metrological fields and equipment numbers requires retrieval to support precise matching with field restrictions, to avoid mixing in unprofessional retrieval results. The frequently updated operation records also require the knowledge base synchronization mechanism to adapt to incremental update frequencies, preventing data lag from affecting drafting accuracy.
How to set the configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Nuclear power documents have high professionalism, so low-match irrelevant content must be filtered to avoid interfering with drafting logic |
limit | Top 8–12 results | Individual nuclear power documents are lengthy. Too many recall results will exceed the context window, while too few will fail to cover all relevant operation steps |
searchMode | vector | Specialized fields and long-text structures are more suitable for semantic matching via vector retrieval, adapting to the professional expression habits of nuclear power documents |
usingReRank | Enabled | The operation steps of nuclear power documents have strong relevance. Reranking can optimize the logical order of recall results, improving reference value during drafting |
datasetSearchUsingExtensionQuery | Enabled | Drafting requirements often imply expansion of specialized terms, such as expanding "main pump" to "reactor coolant pump", improving retrieval accuracy |
collectionIds | Bind to the dedicated nuclear power operation knowledge base collection | Isolate non-nuclear power documents, avoid mixing irrelevant content in retrieval results, and narrow the retrieval scope |
Three common mistakes
- Symptom: When creating a knowledge base, a parent directory is specified, but the final document is still mounted under the root directory. Cause: The parent directory identifier of the
collectionIdsparameter was not correctly carried, or the parameter format does not comply with the hierarchical path rules required by the system. - Symptom: The knowledge base retrieval can return matching results, but there is no output content when calling the large model to generate documents. Cause: The total token count of the recall results exceeds the current context window limit, or the extended query generated after
datasetSearchUsingExtensionQueryis enabled is not correctly associated with the target collection. - Symptom: The retrieval time of a single document exceeds 15 seconds. Cause: Not enabling
usingReRankresults in no result simplification after retrieval, or thelimitvalue is too high, causing a large number of redundant results to participate in matching calculations.
How to confirm the configuration is complete
- One accesses the knowledge base management page, reviews the directory structure of uploaded documents, and confirms whether the specified parent directory is correctly mounted.
- One initiates a simulated retrieval using specialized terms, compares the matching degree and number of retrieval results, and confirms that they comply with the preset configuration value range.
- One tests the large model call process following retrieval, and confirms that the generated document content includes relevant information returned by the retrieval.
- One reviews the retrieval time logs, and confirms that the single retrieval time meets the expected requirements of the business scenario.
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 2026-09-28.