What the Data for This Category Looks Like
The data sources for coal-electricity integration policy and regulatory basis documents are official policy papers, project approval decisions, and industry technical standard documents published by the National Energy Administration, local energy regulatory authorities, and the State-owned Assets Supervision and Administration Commission. Updates follow a quarterly routine schedule, with ad-hoc updates when industry regulatory changes or new rules are issued. All documents follow a standard structure including release document number, issuing authority, release date, core clauses, and attachment descriptions. Some documents include quantitative indicators such as energy consumption and installed capacity, using standard professional units like grams of standard coal per kilowatt-hour and ten thousand kilowatts.
Constraints for Vector Models and Indexes
Coal-electricity integration policy documents are highly specialized, with a high proportion of long clauses. Chunk length must balance semantic completeness and retrieval granularity to avoid semantic fragmentation from overly short chunks. Policy update frequency is low, so real-time index construction is unnecessary. A scheduled incremental update mechanism can reduce resource consumption. Documents include standardized quantitative fields and professional terminology, so field metadata must be retained for precise retrieval to avoid matching confusion between different policy clauses. The strict nature of policy text also requires a retrieval threshold higher than general scenarios, to filter low-match irrelevant results.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 1000–1500 characters | Balances semantic completeness and retrieval accuracy for coal-electricity integration policy documents, which mostly contain long clauses |
| Overlap Length | 120–180 characters | Prevents semantic breaks when splitting long clauses, and ensures continuity for cross-chunk retrieval |
| Similarity Threshold | 0.78–0.85 | Filters low-match irrelevant retrieval results due to the highly specialized nature of policy text |
| Single Search Limit | Top 6–10 results | Meets the precision requirement for matching policy clauses, and avoids redundant results interfering with retrieval |
maxToken | 8192 | Adapts to context splicing needs for long policy documents, and supports the reasoning length required for professional Q&A |
defaultToken | 4096 | Balances model inference efficiency and retrieval content completeness, and is suited for professional policy scenarios |
Three Common Misconfigurations
- Phenomenon: When repeatedly submitting the same policy query, there is no significant reduction in system response time, and identical retrieval requests appear repeatedly in the vector database query logs. Cause: Query cache configuration is not enabled, and no cache validity period or hit rules are set, resulting in vector retrieval being re-executed for every query.
- Phenomenon: After adding a single policy document to a collection, the knowledge base cannot retrieve the corresponding content, and no error prompt is displayed. Cause: A batch index build was not triggered by creating a training order. Adding single data only completes data upload, and no retrievable vector index is generated.
- Phenomenon: When attempting to select the latest professional embedding model, the corresponding option does not appear in the model list. Cause: The API key and version permissions for the target model were not entered in the FastGPT v4.17.0 model configuration page, or the current version does not support the latest interface specifications for this model.
How to Verify Configurations Are Set Correctly
- Upload one coal-electricity integration policy document, submit a training order creation request, wait for the index status to change to completed, then retrieve professional keywords within the document, and verify that the matching degree of returned results meets the preset threshold.
- Submit two identical policy queries, compare the response times of the two requests, and confirm that the second response time is significantly reduced after cache is enabled.
- Access the management page of the knowledge base collection, review the number of index data entries, and confirm that it matches the total character count of the uploaded documents with no missing data.
- Review the model configuration page, confirm that the target embedding model appears in the optional list, and can be selected and called normally.
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.