What This Category of Data Looks Like
Data sources include inspection work orders from internal operation and maintenance management systems, pipeline network basic ledgers, safety operation procedures, employee service manuals, and archived customer complaint work orders. Update frequencies include real-time (for inspection and work order types), monthly (for pipeline network parameter updates), and quarterly (for safety specification revisions). Most document structures mix structured fields and unstructured text. Fields include pipeline network ID, inspection time, fault level, gas pressure (unit MPa), and inspection mileage (unit km). Some documents are long-text safety operation guides spanning thousands of characters.
What Constraints These Characteristics Impose on the Vector Models and Indexing Link
Mixed structured and unstructured text data structures require indexes to support both field filtering and vector recall, to accurately match conditions such as pipeline network ID and fault level. Real-time inspection and work order data requires indexes to support incremental update workflows, to avoid resource consumption from full index reconstruction. Long-text safety operation guides require semantic coherence, so the system must adapt to long text chunking logic. Fields include specific units, so units must be retained during embedding to ensure accurate semantic matching. Data sources with multiple update frequencies require configured differentiated synchronization scheduling rules, to avoid index conflicts and data lag.
How to Configure Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
| Chunk Length | 800–1200 characters | Adapts to long text safety operation guides and work order summaries, avoids semantic breaks |
| Overlap Length | 100–150 characters | Retains semantic connection between chunks, prevents key information from being truncated |
| Similarity Threshold | 0.72–0.78, calibrated via actual testing | Fits the semantic similarity range of gas industry terminology, filters low-relevance results |
| Single Search Limit | Top 8 results | Covers recall needs across scenarios such as pipeline network inspections and work orders, avoids redundant results |
defaultToken | 512 token | Serves as the baseline length for short text embedding, adapts to work order summary data |
maxToken | 4096 token | Fits the input length limit of embedding models, ensures valid embedding of long document chunks |
Three Common Misconfigurations
- Phenomenon: After using chunk mode to call the
pushdata APIto upload data, the interface displays the "Indexing" status for an extended period. Cause: The trigger threshold for incremental indexing is not configured, leading to a large volume of chunks piling up without completing indexing. - Phenomenon: The final set of text after question-answering splitting fails to complete indexing, returning empty result fields. Cause: The final set of text exceeds the
maxTokenlimit, resulting in embedding failure. - Phenomenon: The overall relevance of search results is low, and all results show no obvious difference in matching degree. Cause: Field unit information is not retained, leading to deviations in semantic matching during embedding.
How to Confirm Configurations Are Correctly Applied
- Upload an inspection work order data entry with a pipeline network ID field, check whether index logs contain valid records of field filtering rules taking effect.
- Review the parameter configuration of embedding tasks, confirm that long text chunking does not trigger truncation errors.
- Manually input a gas industry technical term, verify whether retrieval results include relevant safety procedures or work order data.
- Incrementally upload a new inspection record, confirm that the new data is visible in retrieval results.
Note: The values listed here are common starting points, and should be validated against samples relevant to the specific deployment.
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.