What the Data for This Category Looks Like
Data for coal transportation and sales declaration material and file review is sourced from transportation approval declaration forms, weighing vouchers, transportation contracts, safety supervision filing documents, and monthly settlement files. Updates follow declaration batches and monthly settlement cycles. Documents include structured fields and unstructured attachments.
Structured fields include transportation order number, mine site name, coal type, approved tonnage, transportation route, approval node, review opinions, and more. Unstructured attachments are mostly PDF contract scans and review opinions. Units involved include tons, kilometers, and batch numbers.
What Constraints These Characteristics Impose on the Vector Model and Indexing Workflow
Coal transportation and sales declaration materials include structured fields and long-text attachments, and updates follow declaration batches and monthly settlement cycles. This creates multiple constraints for the vector indexing process.
Multi-field mixed content requires configuring multiple vector indexes bound with metadata to enable precise filtering. Long-document attachments need to adapt to variable-length chunking rules to avoid truncating key approval content. Incremental updates must match the declaration cycle to prevent indexes from lagging behind business processes. Some numeric fields need to be converted to text embeddings to ensure consistency in vector retrieval.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
maxToken | 8192 | Adapts to the long-text content of coal transportation and sales contracts and files, matching the context limit of mainstream embedding models in FastGPT v4.17.0 |
| Chunk Length | 800–1200 characters | Covers the core content of a single transportation and sales document, avoiding reduced retrieval accuracy caused by overly fragmented or overly long chunks |
| Overlap Length | 100–200 characters | Ensures contextual coherence between adjacent chunks, preventing approval nodes and contract clauses from being split apart |
| Similarity Threshold | 0.72–0.80 | Distinguishes valid review opinions from irrelevant documents, adapting to the text similarity distribution of coal transportation and sales files |
| Single Search Limit | Top 10 entries | Covers the number of associated files for a single declaration batch, avoiding redundant retrieval results that reduce query efficiency |
defaultToken | 2000 | Balances the text length of a single embedding and retrieval efficiency, adapting to the embedding needs of structured fields |
Three Common Misconfigurations
- Phenomenon: After uploading a coal transportation and sales contract, the vector database has no corresponding embedding data, and empty results are returned during retrieval. Cause: No appropriate chunk length is configured for long-text attachments, causing chunks to exceed the token limit of the embedding model, resulting in embedding failure.
- Phenomenon: An "m3e no available channels" prompt pops up during the embedding phase, and vector data for files cannot be generated. Cause: The m3e API channel is not added on the FastGPT custom model configuration page, and the correct access key and address are not configured.
- Phenomenon: When uploading monthly settlement files in batches, the indexing progress of some documents stalls. Cause: No reasonable upper limit for the number of documents uploaded in a single batch is configured, causing excessive resource occupation and triggering a timeout.
How to Confirm Proper Configuration
- Upload a single coal transportation and sales contract, check the embedding task log to confirm there are no token limit exceeded errors, and verify that corresponding embedding entries exist in the vector database.
- Submit a query containing keywords for coal type and transportation route, verify that the retrieval results include matching declaration materials, and confirm that the similarity configuration adapts to the business scenario.
- Upload incremental monthly settlement files, wait for the indexing update to complete, retrieve the new file number, and confirm that the retrieval results include the newly uploaded content.
- Enter the custom model configuration page, confirm that the m3e channel has been added and enabled, and verify that there are no channel unavailable prompts during the embedding phase.
The values listed above are common starting points and should be evaluated against the user’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.