What Data for This Category Looks Like
Data sources for research knowledge bases include public brokerage research reports, periodic reports of listed companies, industry databases, and real-time trading market APIs. Update frequency varies by data source type. Research reports sync with their release schedules. Financial reports update on fixed cycles. Document structure includes fields such as ticker code, issuing entity, core viewpoints, core operating metrics, and risk warnings. Most metric fields have clear units such as yuan, multiples. Single-document size varies widely; some in-depth research reports have large content volumes.
What Constraints These Characteristics Impose on Deployment and Upgrade
The large, varying single-document sizes of research data and its multi-source heterogeneous nature require adjusting timeout thresholds for file upload and parsing during deployment, to avoid interruptions during long-document parsing. High-frequency updated data sources require deploying incremental synchronization scripts. Upgrades must be compatible with legacy incremental synchronization logic to prevent data duplication or omission. The presence of multiple fields with specific units requires configuring custom field extraction rules during deployment, to ensure unified parsed data formats. The need to connect multiple data sources also requires configuring relevant parameters for multi-source aggregation during the deployment phase in advance, to ensure completeness of subsequent retrieval.
Configuration Recommendations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 2000 MB | Single research report files are often large; this setting prevents upload interruptions |
PARSE_FILE_TIMEOUT_SECONDS | 1200 seconds | Long documents take longer to parse; this prevents the parsing process from timing out and terminating |
maxContext | 800–1200 characters | Research documents have dense content; an appropriate segment length ensures complete context information |
Recall Count | Top 8–12 results | Covers multi-dimensional research information while controlling model input load |
RECALL_SIMILARITY_THRESHOLD | 0.75–0.85 | Filters low-relevance retrieval results to improve matching accuracy for research data |
Incremental Sync Trigger Interval | Every 15 minutes | Adapts to the lack of fixed release schedules for public research reports, ensuring data timeliness |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- After modifying config.json mounted by docker-compose, the model list does not refresh, and configurations in the /app/data/config directory inside the container do not take effect. The cause is failure to restart the deployment container, so configuration changes are not loaded.
- After deploying with the default docker-compose configuration, clicking the knowledge base triggers an error with a 500 status code. The cause is failure to configure connection keys or permissions for internal data sources, preventing the knowledge base from pulling research data.
- When configuring the general aggregation BASE_URI, using the official website's general account KEY as the access key results in a 401 status code for model calls. The cause is that the general account KEY only applies to official website services. Private deployments must use local model keys or custom access configurations.
How to Verify Proper Configuration
- Upload a typical research report, check that parsed document segments match the preset segment length configuration, and no parsing interruption prompts appear.
- Trigger an incremental synchronization, check that the data source update record includes the latest released research reports, and the synchronization cycle matches the preset configuration.
- Initiate a research-related retrieval, check that the number of recalled results matches the preset recall count configuration, and similarity meets the threshold requirements.
- Restart the deployment container, check that modified configuration items take effect in the system settings interface, and the model list loads correctly.
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.