What the data for this category looks like
Securities firms source marketing content data from internal compliance-approved script libraries, product manuals, market analysis materials, and regulatory compliance texts. Update frequency aligns with product launches, regulatory policy changes, and marketing campaign plans. No fixed cycle exists. Core compliance script updates occur less frequently. Campaign-specific materials update immediately when campaigns go live. Document structures include unique script ID, applicable scenario classification, compliance approval number, text content, effective date, and expiration date. Text content is measured in characters. Date fields follow standard Gregorian calendar format.
What constraints these characteristics impose on model integration and configuration
Securities marketing content has strict compliance requirements. Data includes strongly validated fields such as compliance approval numbers. Model integration requires configured association logic for field extraction and compliance checks. Marketing materials update immediately with campaigns. Automatic synchronization triggers for data sources must be configured to support dynamic loading of the latest script library. Scripts vary widely across applicable scenarios. Models need accurate matching of scenario classifications. Association filtering rules for scenario tags must be configured for the recall stage. Regulatory policy changes trigger bulk updates to compliance texts. Configuration entries must be reserved to quickly adjust model compliance check logic.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–16000 characters | Securities marketing content includes multiple fields such as compliance numbers and scenario classifications. Long texts require sufficient context to understand compliance requirements |
SIMILARITY_THRESHOLD | 0.75–0.85 | Accurate matching of marketing scenarios is required to avoid recalling irrelevant compliance scripts or outdated materials |
RECALL_TOP_N | 10–15 entries | Marketing scenarios need coverage across multiple scenario scripts. Too many entries cause redundant model inference. Too few entries fail to match precise needs |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Compliance script libraries may include bulk imports of long documents. Sufficient time must be reserved for parsing and compliance checks |
SYNC_DATA_INTERVAL | 1 hour | Marketing-specific materials update immediately with campaigns. Frequent synchronization of latest content is needed to ensure material timeliness |
PROMPT_TEMPLATE | Embed compliance check rules + scenario matching instructions | Securities marketing must strictly comply with regulatory requirements. Models must prioritize validating compliance fields and matching corresponding scenarios |
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 case-by-case analysis. It is recommended to test on internal samples before finalizing values.
Three common configuration errors
- Issue: After deploying version v4.8.21-fix, adding an ollama model test returns
500 Internal Server Erroror an empty interface response. Cause: ollama API access address not configured correctly, or corresponding port not exposed in docker-compose, so FastGPT cannot connect to the model service. - Issue: Internally deploying a vector model via Docker, no recall results appear after importing text. Cause: Local access address of the vector model not configured, or vector model container not added to FastGPT's Docker network, so connection cannot be established.
- Issue: Using bge-large as the vector model, after importing text with the default segment length, the number of recall results does not match expectations. Cause: Segment length not adjusted to fit the field structure of securities marketing content. Short segments cause key fields such as compliance approval numbers to be split, preventing accurate matching by the model.
How to confirm configuration is complete
- View model service connection logs, confirm no connection timeout or authentication failure errors, and verify that the configured API address matches the actual running address of the model.
- Import a test marketing material, check if the vector model's recall results include matching compliance scripts and scenario tags, and confirm that the similarity threshold and recall count configurations are effective.
- Trigger a data source synchronization, check if the background shows synchronization success, and confirm that new marketing materials have been loaded into the knowledge base.
- Submit a compliance check test request, confirm that the model's return results include compliance field check prompts, and verify that the prompt template configuration is effective.
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.