What the data for this category looks like
The main entities in this category are automotive component suppliers for braking, steering, chassis, interior and exterior trim, and powertrain systems. Daily generated documents include control plans, process flowcharts, work instructions, first-piece and patrol inspection records, SPC reports, PPAP materials, and 8D reports. Data sources include customer drawings and special characteristic lists, ERP/MES systems, measurement and inspection tool data, equipment process parameters, and supplier quality certificates. Data is updated continuously per batch and shift; some project documents such as PPAP materials are updated synchronously with customer changes. Documents include both structured parameter reports and unstructured process text, with fields including dedicated identifiers such as part numbers, process parameters, and anomaly record numbers.
What constraints do these characteristics impose on the knowledge base retrieval and recall workflow?
The multi-source and high-frequency update document characteristics of this category require the retrieval system to adapt to mixed retrieval needs for structured parameters and unstructured process text. Data updated per batch and shift needs to support incremental recall to avoid reloading full historical data. Dedicated fields such as part numbers and special characteristic parameters must be used as retrieval weighting items to ensure accurate matching of customer-specified quality standards during audits. At the same time, subject to strict constraints from vehicle customers, retrieval results must be strictly associated with documents of corresponding processes to prevent irrelevant content across batches from interfering with audit judgments.
How to Configure the Setup
This configuration is based on FastGPT v4.17.0.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Filter low-relevance redundant documents to ensure recalled content is strongly linked to automotive component quality audit queries |
limit | Top 10 entries | Cover the multi-dimensional documents required for high-volume manufacturing audits, including process records, quality certificates, and anomaly reports |
searchMode | mixedRecall | Adapt to the mixed document structure of structured parameter reports and unstructured process text |
usingReRank | Enabled | Perform secondary ranking on recalled results to prioritize matching core audit fields such as special characteristics and process parameters |
datasetSearchUsingExtensionQuery | Enabled | Expand retrieval to include cross-reference documents such as supplier quality certificates and PPAP materials |
collectionIds | Configured by document type | Distinguish different business data sets such as control plans, SPC reports, and 8D reports to precisely target retrieval scope |
Three Common Configuration Errors
- Phenomenon: After increasing
limitto 2000, the large language model does not reference any recalled content. Checking details shows recalled data exists. Cause: Thesimilaritythreshold is set too low, so the relevance of recalled content to audit queries is insufficient, and the large language model cannot identify it as valid reference material. - Phenomenon: After importing Word-format control plan documents, chapters are not split by table of contents, resulting in cross-chapter content blocks. Cause: The document directory-based segmentation rule is not enabled, and only the default fixed character length segmentation is used, which does not adapt to the hierarchical structure of automotive component documents.
- Phenomenon: An unauthorized error is returned when calling the knowledge base API with an API key. The error persists after verifying the key is correct. Cause: API access permissions for the data set are not configured, or the application bound to the key is not associated with the currently used knowledge base collection.
How to Confirm the Configuration is Complete
- Upload a typical SPC report document, verify that the segmentation results are split by process groups within the report, with no cross-process content blocks.
- Submit a retrieval query for "process anomaly handling flow for a certain chassis component", check that the recalled results include the corresponding work instructions, 8D reports, and measurement and inspection tool records.
- Call a valid API interface, pass the configured data set ID and valid API key, verify that the returned results include expected recalled document fragments.
- Adjust the
similaritythreshold to 0.8, confirm that the recalled results only contain content strongly relevant to the audit query, with no low-relevance redundant documents.
The values given are common starting points and should be measured against the reader's own samples.