Data Characteristics and Sources
Financial leasing marketing content data comes from internal product manuals, compliance regulatory announcement documents, past customer engagement records, and customized proposal documents. Updates trigger when product designs or regulatory policies change, with no fixed schedule. Most individual documents use structured formatting, including fields such as product type, financing amount, application term, annualized interest rate, and eligibility requirements. Amounts use ten thousand yuan as the unit. Terms use months or years as the unit. Interest rates are listed as annual percentages. Some long documents include multi-page compliance explanations and case details.
Constraints on Deployment and Upgrade Workflows
Financial leasing marketing content has three key traits: numerous structured fields, no fixed update cycle, and strict compliance requirements. These traits create multiple constraints for deployment and upgrade workflows. Structured fields demand precise field extraction rules during deployment, to prevent retrieved content from mismatching marketing scenarios. No fixed update cycles require upgrade workflows to support incremental synchronization. This eliminates full knowledge base rebuilds each time, reducing downtime. Strict compliance requirements demand separate partitioning of compliance content knowledge base shards, plus configured content review rules. This ensures marketing content aligns with regulatory standards. High volumes of long documents require adjusted long-text parsing parameter thresholds, to avoid content loss from parsing truncation.
Configuration Settings
| Configuration Item | Recommended Value | Basis for This Value |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapt to long document parsing needs, avoid parsing interruptions caused by large document content |
Chunk size | 800–1200 characters | Match the structure of long financial leasing documents, avoid semantic fragmentation after splitting |
Recall count | Top 8-10 entries | Cover multi-dimensional product information in marketing scenarios, avoid insufficient retrieved content |
Similarity threshold | 0.75–0.85 | Filter low-relevance retrieval results, ensure the accuracy of marketing content matching user questions |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapt to the upload needs of large-volume documents such as compliance announcements and customer cases |
Incremental Sync Switch | Enabled | Adapt to content iteration with no fixed update cycle, reduce resource consumption of full synchronization |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on internal test samples before finalizing configuration.
Three Common Misconfigurations
- Phenomenon: After local deployment via Docker Compose, historical conversation records remain after container restart, and cannot be cleared using standard operations. Cause: Cleanup permissions for database persistent volumes are not configured correctly, or conversation data files in the storage directory mounted by the corresponding container are not deleted.
- Phenomenon: After deploying a new version, no directly embeddable frontend page entry can be found, and only API interface calls are available. Cause: The frontend embedding module of the open-source version has been adjusted to an independent deployment package, and does not start synchronously with the core service.
- Phenomenon: Retrieved marketing content includes non-compliant clauses, or compliant content is not retrieved normally. Cause: Compliance knowledge base shards are not separately partitioned, resulting in mixed retrieval of compliance content and general marketing content, triggering abnormal review rules.
How to Verify Correct Configuration
- Upload a standard financial leasing marketing document, verify that the parsed segment results match the configured
Chunk sizeparameter, and adjust parameters until segment semantics are complete. - Initiate a simulated user query, verify that the number of retrieved content entries matches the configured
Recall count, and that the similarity falls within the preset range. - Perform an incremental synchronization operation, confirm that only updated content is synchronized to the knowledge base, and no full reconstruction process is triggered.
- Test the frontend embedding call interface, confirm that a content display page conforming to the marketing scenario can be generated, with no error returns.
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.