What the Data for This Use Case Looks Like
Data sources include internal marketing systems, promotional materials submitted by subordinate branches, and script materials from existing customer feedback. Data updates follow marketing campaign schedules, with no fixed update cycle for single campaign materials. Most documents are plain text, containing fields such as marketing theme, target customer group, product ID, activity start and end dates. Activity validity periods are measured in calendar days, and product IDs follow a six-digit numeric format.
Constraints Imposed by These Characteristics on Model Access and Configuration
Marketing content mostly consists of short individual texts that are updated frequently alongside campaigns. This requires the model access workflow to support batch short text parsing and rapid context adaptation. Documents include industry-specific fields such as product ID and activity validity period. Entity extraction rules for the model must be configured to match these non-standard fields. Updates have no fixed cycle, so the model’s context window must support dynamic adjustment to fit new materials of varying lengths. Internal material sources are scattered, so a unified document upload entry must be configured to integrate multi-channel marketing content.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
UPLOAD_FILE_MAX_SIZE | 100 MB | Most regional commercial banking marketing materials are short individual texts. Setting a 100 MB single-file limit for batch uploads balances storage and loading efficiency |
PARSE_FILE_TIMEOUT_SECONDS | 60 seconds | Short text parsing takes little time. A 60-second timeout avoids unnecessary waiting and aligns with the frequently updated material schedule |
Segment Length | 800–1200 characters | Aligns with the typical length of regional commercial banking marketing scripts, avoiding semantic fragmentation caused by over-splitting |
maxContext | 4096 tokens | Matches the base context limit of most general large models, meeting processing requirements for short-text marketing content |
Similarity Threshold | Calibrated via actual testing | Must be adjusted based on the matching needs of regional commercial banking marketing materials to ensure recall results align with business scenarios |
Recall Count | Top 3 entries | Controls the number of returned related marketing materials, preventing information overload that could disrupt marketing script generation |
Three Common Configuration Mistakes
- Phenomenon: The model dropdown list in workflow nodes does not display globally enabled models. Current version: 4.14.4. Cause: The target model has not been associated with the current workflow on the application details page, or the "Workflow Visible" toggle has not been enabled in the global configuration.
- Phenomenon: After uploading TXT-format marketing materials, the large model fails to generate valid summary content. Cause: The
Segment Lengthparameter has not been configured to adapt to the short-text structure, orPARSE_FILE_TIMEOUT_SECONDSis set too short, causing parsing to fail to complete. - Phenomenon: A 500 error is returned when calling a model configured via the AIProxy channel. Cause: Model mapping rules have not been correctly set in the AIProxy configuration, or parsing parameters matching industry-specific fields such as product ID and activity validity period have not been filled in.
How to Verify Successful Configuration
- Navigate to the FastGPT global model configuration page, check if the "Workflow Available" toggle for the target model is enabled, and confirm the application binding relationship is correct.
- Upload a test TXT document of regional commercial banking marketing materials, trigger workflow execution, and verify that the parsed text fragments contain correct product ID and activity validity period fields.
- On the AIProxy configuration page, test calling the configured model and check if the interface return results include expected marketing content summaries.
- Adjust the
Similarity Thresholdparameter, trigger a recall test for related marketing materials, and confirm that the matching degree of returned results aligns with business requirements.
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
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.