What the data for this category looks like
Insurance marketing content data comes from four main sources: clause texts in internal product management systems, sales script libraries accumulated by agent teams, compliance documents published by regulatory authorities, and sorted frequently asked questions from past customer consultations. Updates are triggered by new product launches, regulatory policy adjustments, or quarterly marketing campaigns. There is no fixed update cycle, but single update volumes are large.
Documents are divided into three categories: product details, sales script templates, and compliance reminders. Product details include fields such as coverage responsibilities, underwriting rules, and rate parameters. Sales script templates include scenario-adapted lines, referral guidance lines, and similar content. Compliance reminders include fields such as regulatory filing numbers and applicable population restrictions. Some fields require units. For example, payment duration uses years, and payout ratio uses percentage.
Constraints on Deployment and Upgrade
The multi-source, multi-structure nature of insurance marketing content requires the deployment process to support batch import of multi-format files and classified parsing. Parsing rules must be configured separately for product details, sales script templates, and compliance reminders. This prevents field extraction conflicts across different documents.
The large single-update volume requires the upgrade process to support incremental synchronization. This avoids service interruptions caused by full updates.
The requirement for units on some fields means unit validation rules must be configured during deployment. This prevents missing or incorrect units for parameters such as rates and durations.
The strict validation need for compliance-related fields requires integrating sensitive content scanning components during deployment. This filters non-compliant text that violates regulatory requirements in advance.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_MAX_SIZE | 500 MB | Insurance product clause PDFs typically contain multiple pages of detailed content, resulting in large single-file sizes. This value covers most product documents |
maxContext | 8000–12000 characters | Insurance marketing content often includes long clause texts. This range fully loads context information and avoids truncating critical coverage responsibility descriptions |
UPLOAD_BATCH_MAX_COUNT | 20 per batch | The volume of marketing materials updated at one time is usually high. This value balances upload efficiency and service stability |
content_similarity_threshold | 0.75–0.85 | Similarity requirements for insurance marketing content balance precise matching and compliance. This range filters duplicate sales scripts while retaining variant content adapted to different scenarios |
PARSE_TIMEOUT_SECONDS | 600 seconds | Parsing long documents takes significant time. This value prevents parsing processes from being interrupted by timeouts |
enable_sensitive_check | Enabled | Insurance content must meet regulatory compliance requirements. This configuration automatically scans and blocks prohibited content such as exaggerated returns and misleading statements |
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 available samples before finalizing settings.
Three Common Configuration Mistakes
- Issue: After deploying a local large language model, the configured thinking process switch does not take effect, and the interface always displays full reasoning steps. Cause: Corresponding parameters are not correctly configured in the model configuration items, or the parameters are incompatible with the actual deployed model version.
- Issue: During cross-machine deployment, the machine hosting the FastGPT service cannot connect to another deployed large language model, returning a connection timeout error. Cause: Port permissions for the large language model service are not opened, or the correct target machine IP and port address are not filled in the FastGPT model configuration.
- Issue: After batch uploading insurance marketing documents, some compliance fields such as regulatory filing numbers are not correctly extracted. Cause: Parsing rules are not separately configured for compliance documents, and a general parsing template is used, resulting in failed field matching.
How to Verify Successful Configuration
- Upload the largest-sized single insurance product clause document, verify the integrity of the parsed text and field extraction results, and confirm that the parsing configuration takes effect.
- Initiate a batch upload test, verify the upload progress and result prompts, and confirm that the batch upload configuration meets expectations.
- Input a test sales script containing exaggerated return statements, verify whether the system triggers sensitive content blocking, and confirm that the compliance verification configuration takes effect.
- Call the associated large language model interface, verify whether the length of the returned results meets the configuration limits, and confirm that the context parameter configuration takes effect.
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.