What Data for This Category Looks Like
Coal mining production policy and regulatory basis data comes primarily from publicly available official documents issued by the National Energy Administration, Ministry of Emergency Management, and provincial coal industry regulatory authorities. It also includes internal systems developed by coal mining enterprises for production safety and operational standards. Data update cycles fluctuate with new policy releases and annual regulatory revisions, with no fixed schedule. Most individual documents are structured text, containing fields such as policy document number, issuing authority, effective date, clause number, and applicable operational scenarios. Content is organized in clause or chapter format, with most individual clauses ranging from several hundred characters in length.
Constraints for Vector Models and Indexing
Policy documents from multiple sources have significant format differences, including PDF scans, Word formatted files, and web-based text. Indexing processes must support multi-format parsing and unified text extraction. Non-fixed update cycles require indexing to support incremental updates, avoiding resource consumption from full reindexing. Built-in metadata such as document numbers and effective dates must be included in the index to support filtering results by regulatory hierarchy and effective time. The clause-based content structure requires chunking that preserves individual clause integrity, preventing disruption of policy logic after splitting.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Matches the average length of individual clauses in coal mining policy documents, avoids splitting that disrupts clause logic |
| Overlap Length | 50–80 characters | Connects context between adjacent chunks, prevents cross-clause policy associations from being truncated |
| Similarity Threshold | 0.75–0.85 | Filters low-match irrelevant policy content, adapts to the professional expression style of policy text |
| Single Search Limit | Top 8 entries | Covers common policy association scenarios in coal mining production scenarios, avoids excessive results interfering with judgment |
maxToken | 8000 | Adapts to the context length limit of large models, accommodates multiple matched policy chunk contents |
defaultToken | Calibrated based on actual testing | Adapts to the call quota of the external embedding model, avoids excessive charges |
Three Common Misconfigurations
- Phenomenon: Calls to the embedding interface return a 404 error. Cause: The access path for the external embedding model is not configured correctly, or model call permissions have not been enabled.
- Phenomenon: A vector model deployed locally in Docker cannot be called by the indexing service. Cause: The model container port is not mapped to the host network, or firewall policies restrict communication links between containers.
- Phenomenon: Exported knowledge base data cannot be imported split by policy type. Cause: Metadata tags for different types of policy documents are not set in advance, and the default export granularity only supports the overall knowledge base dimension.
How to Verify Successful Configuration
- Upload a single coal mining production policy document, check that chunking results retain complete clauses, with no forced truncation or splitting errors.
- Input a test query, verify that returned matching results include policy clauses relevant to the query, and that the number of results matches the single search limit setting.
- Call the embedding interface, confirm that returned vector data has no abnormal errors, and the interface status code matches expected values.
- Manually trigger an incremental indexing task, check the indexing update logs, confirm that newly uploaded policy documents can be properly indexed and included in the retrieval scope.
The values provided here are common starting points, and should be evaluated 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.