What Data for This Category Looks Like
Documents and materials in the coal chemical industry mainly originate from internal enterprise process specifications, feasibility study reports, safety and compliance documents, monthly production reports, and bidding documents. Data update cycles vary widely by document type. Process specifications are updated only when process routes are adjusted. Production reports are synchronized weekly. Compliance documents are updated alongside changes to national energy regulatory policies. Most documents combine structured and semi-structured content, with fixed fields including equipment number, process parameters, and approval document number. Some technical documents include unit annotations, such as material flow measured in tons per hour and gas concentration measured in milligrams per cubic meter.
How Document Characteristics Impact Vector Models and Indexing
The mixed structured nature of coal chemical industry documents requires the indexing process to support field-based splitting and chunking, to avoid semantic confusion across fields. Different document types with varying update cycles need matching, differentiated indexing update strategies. High-frequency production reports are suited for incremental indexing to reduce resource consumption. Process parameter text with units must retain unit association information during vector modeling, to prevent semantic misjudgment of similar values due to unit differences. Long documents such as feasibility study reports require appropriate chunking thresholds, to ensure single chunks do not exceed model context limits while preserving complete process logic units.
Reference only; verify against the target FastGPT release and deployment documentation.
How to Set the Configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Coal chemical process documents mostly contain continuous parameter descriptions. This range preserves complete process logic units while adapting to the context limits of most localized vector models |
| Overlap Length | 100–150 characters | Prevents chunking from cutting continuous semantics of process parameters, ensuring cross-chunk process logic can be correctly associated |
| Similarity Threshold | 0.72–0.85 | Coal chemical compliance documents have high semantic similarity. This range filters low-match irrelevant documents while retaining precise matching results for compliance clauses |
| Single Search Limit | Top 8 results | Coal chemical documents have high professional terminology concentration. A small number of high-match results can cover core needs, and excessive results increase context load |
maxToken | 4096 | Adapts to the input limits of mainstream localized vector models, avoiding long text chunks exceeding model processing range |
defaultToken | 8192 | Used to configure the context window of large models, adapting to the overall semantic recall needs of long coal chemical industry documents |
Three Common Misconfigurations
- Phenomenon: The capacity value displayed after uploading the knowledge base does not match the actual total document size, and storage requirements cannot be accurately estimated. Cause: Chunking is not split according to the structured fields of coal chemical documents, leading to duplicate or missing chunk counts. A deviation exists between the system-counted capacity and actual vector storage volume.
- Phenomenon: After switching vector databases, historical indexed coal chemical documents cannot be recalled normally. Cause: The index field mapping of the database is not adjusted for the semi-structured characteristics of coal chemical documents, leading to failure of semantic indexing for professional fields.
- Phenomenon: Vector recall speed is slow after local deployment, with a single search taking more than 30 seconds. Cause: Incremental indexing is not enabled for high-frequency updated production report documents of the coal chemical industry. Full index reconstruction occupies excessive GPU resources, leading to response delays.
How to Confirm Proper Configuration
- Upload a single coal chemical process specification document, check that the chunking results retain complete process parameter paragraphs with no cross-field cutting.
- Input a coal chemical professional question, such as "Safety operation procedures for a specific equipment", and verify that the recalled document fragments match the question’s semantic meaning.
- View the vector database storage monitoring to confirm that incremental indexing only triggers when documents are updated, with no full reconstruction occurring.
- Test uploading coal chemical documents of varying lengths, confirm that chunked text does not exceed the configured
maxTokenlimit.
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.