What This Category's Data Looks Like
Policy and regulatory basis data for power generation groups comes from official red-headed documents released by various functional departments of the group headquarters, implementation rules from subordinate power plants, and supporting policy implementation documents issued by the National Energy Administration. Data updates are tied to adjustments to national energy policies or revisions to internal group systems, with an irregular frequency. A single update covers one or multiple complete documents. Most documents are in PDF or structured Word format, and include fields such as document number, issuing unit, effective date, applicable business scenarios, and chapter and clause content. The minimum storage unit is a single policy clause, divided by chapter and clause.
Constraints on Vector Models and Indexing
Policy texts for power generation groups are often long, precisely worded paragraphs. Core clauses cannot be arbitrarily truncated during chunking, as this will damage policy integrity and precision. Updates have no fixed cycle, and a single update may cover multiple documents. Incremental indexing by document number or release date is required to avoid resource consumption from full index rebuilding. Documents include metadata such as applicable scenarios and effective dates. Indexing must bind metadata to text content to ensure recall results match the corresponding business scenarios. The minimum storage unit is a single clause, so recall results must be returned at the clause level to avoid semantic confusion from cross-clause mixing.
How to Configure Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the paragraph length of single clauses in power generation group policy documents, avoids splitting core clauses |
| Overlap Length | 50–100 characters | Retains contextual association between adjacent clauses, prevents semantic breakage across chunks |
| Similarity Threshold | 0.75–0.85 | Adapts to the precision requirements of policy texts, filters low-relevance search results |
| Single Search Limit | Top 10 results | Covers conventional retrieval needs for group policies, controls redundancy of returned results |
maxToken | 8000 | Carries contextual content of long policy texts, complies with model parameter limits for FastGPT v4.17.0 |
| Reranking | Enabled | Performs secondary sorting on initial recall results to correct semantic matching deviations from vector recall |
Three Common Configuration Errors
- Phenomenon: When configuring OneAPI as an Embedding proxy, the call returns an "invalid endpoint" error. Cause: The exclusive proxy address for OneAPI was not correctly configured, and the general interface path was mistakenly filled as the retrieval address for power generation group policy data.
- Phenomenon: After enabling reranking, the result ranking of the online recall test does not change, and the number of results is the same as when it is disabled. Cause: The reranking option was only enabled in the global settings, and was not synchronously checked in the index configuration of the target knowledge base, resulting in the configuration not taking effect.
- Phenomenon: When attempting to add the Tongyi Multimodal Embedding Model, the OpenAI-compatible call mode cannot be selected. Cause: The custom multimodal model adaptation switch was not enabled in the FastGPT vector model management page, and format parameters for multimodal input were not supplemented.
How to Verify Configuration Is Correct
- Navigate to the configuration page of the target knowledge base, and verify that the chunk length and overlap length settings match the preset configuration.
- Run an online recall test using policy keywords, and check whether the result sorting logic conforms to the behavior after reranking is enabled.
- Review system logs to confirm that there are no connection errors or parameter verification failure records when the Embedding model calls OneAPI.
- On the FastGPT v4.17.0 vector model management page, confirm that the custom multimodal model adaptation switch is enabled.
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.