What this category of data looks like
Data for this category primarily comes from commercial concrete batching plant control systems, project laboratories, quality departments, and scheduling departments. It covers documents including mix proportion notices, opening identifications, production and transport orders, raw material inspection reports, test block records, strength reports, and more. Data updates occur per vehicle production record, per batch raw material inspection result, and daily aggregated ledger. Fields include raw material batch numbers, moisture content values, slump indicators, strength test values, and others. Units include kilograms, cubic meters, megapascals, and more. The content of individual documents updates dynamically throughout the production process.
Constraints on vector models and indexing
The high-frequency, multi-dimensional data characteristics of this category impose multiple constraints on the vector model and indexing workflow. Data updates frequently per vehicle and per batch of raw materials, so indexes must support incremental synchronization to avoid computational overhead from full reindexing. Documents include both structured numerical and unstructured descriptive content. Vectorization rules compatible with mixed fields must be configured to ensure consistent vector representation across all data types. The total data volume of batch production records and inspection reports is large. The total capacity of a single batch index must be limited to prevent server overload. An association index between batch numbers and documents must also be established, to enable quick matching of full production link data during ledger aggregation.
Configuration settings
This configuration applies to FastGPT v4.17.0.
| Configuration Item | Recommended Values | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to the average length of individual documents in ready-mixed concrete production ledgers, avoids including excessive cross-batch data in a single chunk |
| Overlap Length | 100–200 characters | Retains batch number association information for adjacent chunks, prevents loss of production link context during indexing |
| Similarity Threshold | 0.75–0.85 | Distinguishes ledger data from different production batches, avoids incorrect association of similar raw material inspection records |
| Single Search Limit | Top 20 entries | Matches typical daily query data volumes for batching plants, balances retrieval efficiency and result completeness |
defaultToken | 1024 token | Complies with input limits of mainstream vector models, adapts to chunked ledger document length |
maxToken | 4096 token | Ensures sufficient associated document data can be loaded when generating aggregated reports, covers full production batch process information |
Three common configuration errors
- Issue: When uploading raw material inspection reports or production and transport orders larger than 10 MB, some chunks show vectorization errors, and the interface displays a vector generation failure status marker. Cause: Parameters are not configured for the adapted scenario's chunk length, and some chunked content exceeds the 1024 token limit of
defaultToken, preventing the model from completing vectorization. - Issue: For a local vector service deployed on an Ubuntu system, after restarting, the uploaded ready-mixed concrete ledger knowledge base shows as not ready, and the indexing process cannot automatically recover. Cause: Index breakpoint continuation and automatic retry rules are not configured. After a server exception interruption, incomplete indexing progress is not retained, requiring manual reindexing.
- Issue: When aggregating multi-vehicle production ledgers, associated test block records are missing from retrieval results, and the number of retrieved entries does not match the actual matching quantity. Cause: The single search limit is set too low, failing to cover all associated documents for the current production batch, leading to incomplete retrieval results.
How to confirm correct configuration
- Upload a single batch of production and transport order documents, check that each chunk's content length matches the preset chunk parameters, with no over-length chunk prompts.
- Trigger a ledger aggregation task, review vector retrieval link logs to confirm there are no vectorization failure chunk records, and that indexing progress completes normally.
- Retrieve production data for a specific batch number, verify that the number of returned associated documents matches the actual number of generated documents, confirming the association index is active.
- Adjust the
maxTokenparameter, test loading multiple associated documents, confirm that the generated aggregated report covers all associated data with no content truncation.
The values provided here are common starting points and should be evaluated against the reader's own samples.