What the Data for This Category Looks Like
Financial leasing investment research data sources include internal leasing project ledgers, rent calculation documents, lessee credit reports, industry regulatory policy documents, and public research reports. Data update timing shifts with project initiation, rent adjustments, and policy updates, with no fixed cycle. Most documents mix structured tables and unstructured text, containing fields such as lease asset specifications, rent calculation parameters, and lessee financial indicators. Units involved include monetary amounts, lease term units, equipment model codes, and similar categories.
What Constraints Do These Characteristics Impose on Knowledge Base Retrieval and Recall?
Mixed structured and unstructured document structures require distinguishing weights between core business fields and auxiliary explanatory text during retrieval, to avoid irrelevant fields interfering with recall results. Multi-field and multi-unit characteristics require recall logic to support filtering by field tags, ensuring matching content aligns with query scenarios. Data sources with no fixed update cycle require the retrieval link to support on-demand incremental knowledge base refresh, preventing stale data from being recalled. The high proportion of long text paragraphs requires chunking strategies to retain business logic connections, avoiding splitting that destroys business integrity.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Financial leasing documents often contain long rent calculation tables and lease asset detail paragraphs. This range retains business logic connections and avoids splitting to break complete business units |
similarityThreshold | 0.75–0.85 | Structured business fields account for a high proportion, requiring high matching accuracy to filter low-relevance non-core content |
recallTopK | Top 8–10 results | Investment research scenarios require covering multi-dimensional business data. Too many results increase context redundancy, while too few fail to cover complete business scenarios |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | A single leasing project document may contain multiple attachments. A longer timeout ensures all associated files are fully parsed |
enableFieldWeight | Enabled | Core business fields such as lease asset models and rent amounts require higher matching weights to improve recall accuracy |
incrementalRefresh | Triggered by file modification time | Financial leasing project document updates have no fixed cycle. Triggering by modification time enables on-demand refresh of incremental knowledge base content |
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 specific analysis. It is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Symptoms include 504 timeout errors returned by knowledge base retrieval, or retrieval request timeout logs displayed in the console. The cause is failure to adjust the
PARSE_FILE_TIMEOUT_SECONDSparameter. The parsing duration of a single large leasing project document exceeds the default threshold. - Symptoms include long rent calculation tables being split into multiple unrelated chunks, making it impossible to match complete calculation logic during retrieval. The cause is failure to follow the chunking logic of version 4.8.10, with no retention of context connections for business paragraphs during splitting.
- Symptoms include retrieved question-answer pair replies being rewritten by the model, with no direct return of the original text. The cause is failure to enable the configuration item for forced use of knowledge base original text, or failure to correctly configure the recall priority of question-answer pairs.
How to Confirm Proper Configuration
- Upload a typical leasing project document, view the parsed chunk content, confirm that chunks do not destroy the integrity of core business paragraphs, and adjust the
chunkSizeparameter based on the results. - Enter a query containing lease asset models and rent amounts, view the field matching degree of recall results, and adjust the
similarityThresholdparameter based on matching accuracy. - Import a set of test question-answer pairs, confirm that the returned reply is completely consistent with the knowledge base original text after initiating a query, and verify whether the forced original text configuration is effective based on the results.
- Upload a modified leasing document, view the trigger status of knowledge base incremental refresh, and confirm that the update logic meets configuration requirements.
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.