What the Data for This Category Looks Like
The marketing content data for investment platforms primarily originates from official investment research reports, product manuals, user FAQ libraries, and event rule documents. The data update rhythm aligns with operational activities. Regular investment research content is updated quarterly or monthly. Event-related content is frequently added or modified during event preparation phases. Document structures fall into three categories: long-text analysis, structured product parameter tables, and short marketing copy. Fields include product code, risk level, expected return range, applicable investor type, and other relevant items. Units include percentage, yuan, annualized yield, and similar units.
What Constraints Do These Characteristics Impose on Deployment and Upgrade?
The data sources for investment platform marketing content are scattered, and update frequencies fluctuate. Deployment requires compatibility with multi-format document parsing. Upgrades need to adapt to newly added data source field mapping rules. Parsing long-text investment research reports takes significant time, so sufficient processing duration must be reserved. Specific format requirements for structured fields require retaining the original index mapping logic after upgrades, to avoid damaging historical data associations. For offline investment operation scenarios, support for version upgrades and model deployment without a network environment is required, to reduce reliance on external networks.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 1000 MB | Adapts to the upload requirements of long investment research report documents for investment platforms |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Covers the parsing time required for long-text investment research reports |
maxContext | 8000–12000 characters | Matches the context length of investment research reports, preserving complete marketing information |
Recall count | Top 8–12 entries | Covers the associated display requirements for multi-product marketing content |
Similarity threshold | 0.75–0.85 | Filters low-relevance non-marketing documents, improving content accuracy |
LOCAL_MODEL_API_BASE | http://localhost:11434/v1 | Connects to locally deployed Ollama models |
Three Common Mistakes
- An
ETIMEDOUTerror occurs during upgrade, preventing completion of offline upgrade. The cause is failure to download the offline image package in advance, leading to failure to pull images via external networks. - After upgrading to v4.9.0, the document parsing enhancement function cannot be enabled, and the interface displays a function unauthorized prompt. The cause is failure to complete commercial version permission configuration or failure to synchronize permission mapping rules after upgrade.
- When connecting to a locally deployed deepseek model via Ollama, a test error returns a
500 Internal Server Error. The cause is incorrect model API address configuration or unopened local ports.
How to Confirm Configuration Is Successful
- Upload an official investment research report, and check whether the parsed result includes preset fields such as product code and risk level.
- Run the offline upgrade script, confirm that the image loading is completed, and there are no network pull-related error logs.
- Initiate a model test call, and check that the returned result is associated with correct marketing content information.
- View the system operation logs, confirm that the
PARSE_FILE_TIMEOUT_SECONDSparameter takes effect, and there are no parsing timeout warning alerts.
The parameter values provided on this page are all conventional recommendations, serving as starting points for configuration determination. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis. Actual testing on the target platform's own samples is recommended before finalizing values.
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.