What the Data for This Use Case Looks Like
The data for rural commercial bank research report retrieval comes primarily from two sources: internal research department documents including regional financial analysis reports and agricultural credit tracking reports, plus publicly available policy interpretation documents for the agricultural and rural sector and peer regional financial research reports. All documents follow a fixed structure: publishing entity, publishing date, applicable county scope, core business data fields, policy summary, and risk warning items. Internal documents are updated weekly, while publicly synchronized documents are updated quarterly. The core business data fields include agricultural loan balance, rural household credit account count, and county micro and small enterprise credit limit, with units of 100 million yuan, accounts, and 10,000 yuan respectively.
Constraints for Deployment and Upgrade Posed by These Characteristics
Field restrictions tied to specific regions require configuring regional dimension retrieval filtering rules during deployment, to ensure returned results match target county business scenarios. Differences in update cadences across multiple data sources require configuring differentiated scheduled synchronization tasks, to avoid system resource contention between high-frequency internal data syncs and low-frequency public data syncs. The presence of business-specific fields requires adjusting vector recall field weights during deployment, to raise retrieval priority for content related to core business metrics. Permission controls for internal documents require configuring data source access whitelists during deployment, and compatibility with new permission verification logic during upgrades. Additionally, fixed risk warning modules included in documents allow configuring keyword extraction rules during deployment, and adding regular expression matching templates for module recognition during upgrades.
Configuration Recommendations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Rural commercial bank research report documents are often lengthy, with some internal reports reaching tens of thousands of characters, requiring sufficient parsing time |
RECALL_TOP_K | Top 10 results | Retrieval needs for rural commercial bank research reports focus on regional and agricultural business scenarios. Too many recall results increase screening costs; 10 results cover core relevant content |
SIMILARITY_THRESHOLD | 0.75–0.85 | Semantic matching accuracy requirements for business fields are high. A threshold that is too low introduces irrelevant content, while a threshold that is too high misses relevant research reports |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Internal research reports may include attached tables and charts, resulting in large individual document sizes |
SCHEDULER_CRON_EXPRESSION | 0 0 2 * * * (2 AM daily) and 0 0 4 * * 1 (4 AM every Monday) | Internal data updates weekly, public data updates quarterly. Configuring synchronization tasks in batches avoids resource conflicts |
MODEL_EMBEDDING_DIM | Set based on actual testing | Vector dimensions for business fields must match retrieval engine configurations, to avoid recall errors caused by dimension mismatches |
The parameter values provided on this page are common recommended 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 settings.
Three Common Misconfiguration Issues
- Symptom: Docker container status shows up, but accessing port 3000 fails to log into the system. Logs indicate a MongoDB connection failure. Manual login to MongoDB using the configured account and password also fails. Cause: MongoDB connection address and authentication parameters are not correctly configured in environment variables, or the MongoDB instance does not enable remote access permissions.
- Symptom: Local development environment starts successfully, but access to the oneAPI configuration interface fails, with no corresponding entry found. Cause: OneAPI-related configuration items are not enabled, or relevant front-end resources are not loaded into the development environment runtime path.
- Symptom: After adding a custom index model in version v4.8.22, retrieval errors indicate a model dimension mismatch. Cause: The model's vector dimension parameters are not aligned with retrieval engine configuration items, or the vector format returned by model calls does not meet system requirements.
How to Verify Proper Configuration
- Run database connectivity test scripts to verify connection status of MongoDB and the retrieval engine, and confirm that configured connection parameters match the actual deployment environment.
- Upload a sample rural commercial bank research report to trigger a parsing task, and confirm that parsed fields include preset business fields, and parsing duration does not exceed the configured timeout threshold.
- Initiate a regional filter retrieval test to confirm that returned results match the preset county scope, and the number of retrieval results conforms to the configured recall limit.
- Check scheduled synchronization task run logs to confirm that multi-source data completes synchronization according to configured time rules, with no synchronization failure records.
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.