What This Category of Data Looks Like
Metal material processing ledger data comes from production execution systems, online quality inspection equipment, warehouse management systems, and equipment operation and maintenance logs. Data is synced either after each production batch is completed, or via daily batch sync of full batch data.
Documents include structured fields and unstructured attachments. Structured fields cover furnace number, material grade, rolling temperature, rolling pressure, inspection hardness, incoming weight, with corresponding professional units of ℃, MPa, HB, and ton. Unstructured attachments include scanned quality inspection reports, electronic process cards, and similar items. Single process-related documents are usually long, and each ledger is associated with multiple auxiliary documents.
Constraints Imposed by These Characteristics on Knowledge Base Retrieval and Recall
Professional terminology and specialized units for metal material processing ledgers require the retrieval link to support semantic matching with units and exact keyword matching. This prevents retrieval failure caused by mismatched units or terminology.
The batch-updated data feature requires a single retrieval to cover multiple types of documents associated with the same batch. This ensures the completeness of ledger summary.
The features of long documents and multiple associated documents require retrieval configuration to balance the integrity of single document segmentation and the coverage of multi-document recall. This avoids destroying field associations or missing auxiliary documents due to segmentation.
Business data isolation requirements require strictly limiting the retrieval scope to a dedicated directory. This prevents cross-category data from mixing into retrieval results.
Configuration Setup
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
similarity | 0.72–0.80 | Metal material processing ledgers contain professional terminology and specialized units. This range filters irrelevant retrieval results and retains associated data of the same material and process |
limit | Top 12 entries | A single batch ledger is associated with multiple types of auxiliary documents. Taking the top 12 entries covers associated data in most scenarios and avoids missing key parameters |
searchMode | hybrid | Supports mixed keyword and semantic retrieval, adapting to the mixed query requirements of structured fields and unstructured process documents |
usingReRank | Enabled | Semantic matching for professional terminology may have deviations. Reranking corrects similarity sorting and prioritizes results with higher matching degrees to ledger fields |
datasetSearchUsingExtensionQuery | Enabled | Ledger summary queries often include extended association requirements. Query optimization can recall hidden fields and auxiliary documents associated with the ledger |
collectionIds | ID of the dedicated directory for metal material processing ledgers | Isolates business data, avoids recalling documents from other categories, and ensures retrieval accuracy |
Three Common Misconfigurations
- Symptom: The model prompts that no available content is in the knowledge base during conversation, but documents can be viewed normally on the knowledge base page. Cause: Index data was not synced correctly, or the correct
collectionIdsparameter was not bound, causing the retrieval engine to fail to load documents from the target directory. - Symptom: Retrieval results include a large number of administrative documents for non-metal material processing or ledger data from other categories. Cause: The
similaritythreshold was set too low, or the mixed retrieval mode ofsearchModewas not enabled, leading to generalized recall of irrelevant content. - Symptom: Uploaded long process documents cannot be retrieved and matched. Cause: The number of single document segmentation chunks exceeds 3000, and the document was not split into multiple sub-files, causing some chunks to not be indexed.
How to Confirm the Configuration Is Correct
- Upload a test ledger document containing furnace number and rolling temperature, initiate a query including "Quality inspection data for [furnace number]", and verify that the returned results include the corresponding fields of this document.
- View the retrieval logs in the FastGPT backend, confirm that the
collectionIdsparameter is bound to the dedicated directory for metal material processing ledgers, and there are no retrieval records of cross-business datasets. - Upload a process document with more than 10,000 characters, confirm that the number of segmentation chunks after upload does not exceed 3000, and initiate a query of "Rolling parameters for this process" to retrieve relevant content.
- Initiate a summary query of "Full associated ledgers for a certain batch", and verify that the returned results cover multiple types of associated documents including work orders, quality inspection, inventory, and similar items.
The values provided are common starting points and should be evaluated 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.