What This Category of Data Looks Like
This category of data comes from flow, pressure, and temperature instrument manufacturers and metrology laboratories. Daily documents include assembly and commissioning sheets, calibration procedures, original calibration records, error curves, metrology certificates, and software version logs. Data is sourced from design documents, standard instrument monitoring data, calibration software, laboratory information systems, and customer range requirements. Updates occur after each calibration for every individual instrument. Documents include professional fields such as measurement range, error value, calibration date, and traceability number. Units include metrology-specific units including pascals, cubic meters per hour, and degrees Celsius.
Constraints Imposed on Knowledge Base Retrieval and Recall
High-frequency data updates require the retrieval system to support incremental updates for single-instrument or single-batch documents. This avoids full re-building of the knowledge base. Multiple document types including tables, curves, and long text require the retrieval system to adapt chunking and matching logic for unstructured professional text. Dispersed data sources and strict field unification requirements mean metadata must be bound to instrument type and calibration cycle to narrow retrieval scope. Calibration records are core deliverables. Retrieved content must be traceable, to avoid including non-official documents. Dense professional terminology requires higher retrieval matching accuracy than general scenarios, to reduce deviation transfer risks.
Configuration Settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.82–0.88 | Matches professional terminology in calibration procedures, preventing accidental recall of unrelated error curves or metrology certificates |
limit | Top 6 entries | The number of documents under a single instrument classification is moderate. Limiting recall entries avoids context overflow |
searchMode | fullTextRecall | The query examples emphasize identifiers or specialist terms; test this mode with representative data, not as a product default. |
usingReRank | Enabled | Requires secondary verification of semantic similarity between calibration records and error curves, to improve precise matching accuracy |
datasetSearchUsingExtensionQuery | Disabled | Professional terminology does not require extended queries, to avoid introducing non-standard expressions that interfere with retrieval results |
collectionIds | Bind corresponding collections by instrument type | Stores documents classified by flow, pressure, and temperature instruments, to narrow the scope of a single retrieval |
Three Common Misconfigurations
- Retrieval returns a timeout. The interface displays "Retrieval Timed Out" or returns a
504status code. The cause is failure to bindcollectionIdsby instrument type. The retrieval scope covers the full knowledge base, causing processing time to exceed thresholds. - Imported long calibration procedures have chunking anomalies. Some long paragraphs are forcefully truncated or merged beyond expected lengths. The cause is failure to adapt chunking logic for long tables and error curve text in calibration procedures, and failure to process according to natural segmentation of professional documents.
- Retrieval results do not return the original answer from preset Q&A documents. Non-target content appears. The cause is incorrect configuration of the
similaritythreshold, leading to recall of non-target documents, or failure to enable precise matching mode.
How to Verify Proper Configuration
- Import calibration procedure documents for a single instrument. Retrieve corresponding process keywords. Check that the number and similarity of retrieval results match the configured parameters.
- Trigger a retrieval operation. Observe interface response time. Confirm no timeout errors or abnormal status codes occur.
- Import preset Q&A documents. Retrieve corresponding questions. Check that returned content matches the original text of the preset answer.
- View knowledge base chunking logs. Confirm that long document chunking follows natural segmentation logic for professional documents.
The values provided are common starting points and should be measured against the reader's own samples.