What the data for this category looks like
Financial report data for the automotive service category targeting the financial sector primarily comes from annual or half-year financial reports of publicly disclosed automotive sales, repair service, and automotive finance enterprises, monthly operating data reports from automotive circulation industry associations, and monthly operating ledgers of stores. Public financial reports are updated quarterly or annually, while industry reports and internal ledgers are updated monthly. Document structures include consolidated revenue, cost details, and operating segment data. Fields cover store-level revenue, customer unit price, repair labor fees, and parts procurement costs, with units uniformly set as Chinese Yuan or ten thousand Yuan, with no additional non-standard units.
What constraints do these characteristics impose on the "citation source and traceability" link
Financial report data for the automotive service sector targeting financial use cases has scattered sources, including publicly disclosed documents, industry association reports, and store internal ledgers. The update cadences of different data sources vary significantly. This requires the citation traceability link to distinguish the timeliness and credibility of data sources, while complying with financial regulatory compliance requirements. Documents include detailed data across multiple business segments, so precise matching to the user’s query business scenario is needed to avoid retrieving irrelevant segment content. The field dimensions are detailed, so the field range of single retrieved content must be limited to prevent redundant information from interfering with responses. Additionally, internal ledgers are non-public data, so the data source type must be clearly marked during traceability to ensure compliance.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall count | Top 8 | The automotive service financial report has multiple business segments, and needs to cover relevant data for scenarios including repair and sales. 8 entries balances retrieval coverage and information redundancy |
similarity threshold | 0.75–0.85 | There are many technical terms in financial report data. This range balances retrieval accuracy for professional semantics and scenario coverage |
reranked return count | Top 5 | Single financial report data has many fields. Limiting the return count avoids information overload while retaining core detailed content |
segment length | 800–1200 characters | The detailed paragraphs of financial report documents are long. This segment length preserves complete business segment data and avoids truncating key information |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large financial report documents takes significant time. 300 seconds covers the parsing needs of most public financial reports and industry reports |
citation template | Mark source + document title + chapter number according to data source | There are multiple types of data sources for automotive service financial reports. Clear marking improves compliance and readability of traceability |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: After multiple consecutive queries, the data sources cited in subsequent queries are unrelated to the business scenario of the previous query, leading to off-topic responses. Cause: Context-aware recall configuration is not enabled, and retrieval is only performed independently based on the current single query, without inheriting the business scenario keywords from the previous query.
- Phenomenon: A
408 Request Timeoutor504 Gateway Timeouterror is triggered when parsing large financial report documents. Cause: ThePARSE_FILE_TIMEOUT_SECONDSconfiguration value is too low, failing to cover the actual parsing time of large financial report documents. - Phenomenon: Retrieved citation content includes irrelevant business segment data that does not match the specific scenario of the user’s query. Cause: No filtering rules based on business segments are configured, or the
similarity thresholdvalue is too low, resulting in retrieval of content with weak semantic association.
How to confirm the configuration is complete
- Upload a public financial report document of an automotive service enterprise, trigger parsing, and view the parsed segmented content to confirm that the segment length matches the preset configuration.
- Initiate a query that includes a specific business scenario, and check whether the number of retrieved citations and data source markings conform to the configuration requirements.
- Initiate multiple consecutive queries, confirm that the citation data source for each query matches the current query’s business scenario, with no cross-scenario irrelevant content.
- View the knowledge base configuration panel, confirm that the values of parameters such as
similarity thresholdandPARSE_FILE_TIMEOUT_SECONDSmatch the preset configuration.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.