What data for this category looks like
E-commerce service marketing content data primarily comes from e-commerce platform merchant backends, third-party marketing tool export files, and store customer service consultation records. Data update timing varies based on content status:
- Product detail content updates in real time as SKU information is adjusted
- Marketing activity content triggers updates when launched, adjusted, or taken offline
- User interaction data is summarized and updated hourly
Each individual marketing content document includes fields such as product SKU code, activity name, delivery channel, effective time period, material format, and target customer group tags. Most field types are string, integer, or numeric. Some associated fields must be bound to the unique identifier of the corresponding product or activity.
What constraints these characteristics impose on tool calling and plugins
Multiple data sources require tool calling to configure cross-platform authentication parameters, to support interfacing with different data sources such as e-commerce backends and customer service systems. Different update timings impose synchronization policy constraints:
- Real-time updated product content must call incremental pull interfaces
- Timed updated activity content must configure fully synchronized tasks triggered on a schedule
The feature of associated field IDs requires plugins to support mapping rules between external fields and FastGPT knowledge base fields. It also requires adding associated ID validity check logic to prevent calling failures caused by empty values or invalid IDs. The diversity of material formats requires the tool chain to adapt to parsing and preprocessing of different types of content such as images, videos, and marketing copy.
How to configure settings
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
rag_retrieve_top_k | 8-12 results | E-commerce marketing content is mostly short text associated with products or activities. Too many retrieved entries will cause redundant context, while too few will fail to cover core marketing information |
similarity_threshold | 0.75-0.85 | Filters low-relevance non-target marketing materials, adapts to the precise matching needs of e-commerce content, and avoids irrelevant information interfering with calling results |
plugin_api_timeout | 300 seconds | E-commerce marketing content may involve pulling data from multiple sources. Sufficient interface response time must be reserved to prevent tool calling interruptions due to timeouts |
file_parse_chunk_size | 800-1200 characters | Most e-commerce marketing materials are formatted copy or product details. This chunk length balances context completeness and model processing efficiency |
global_knowledge_base_id | Fill in the e-commerce marketing knowledge base ID bound to the business | Must match the global knowledge base ID configured in the FastGPT backend, to ensure accurate association with the target knowledge base during API calls |
The parameter values provided on this page are common 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 configuration errors
- An API call returns a "knowledge base does not exist" error, or recall results deviate from target marketing content. Cause: The
global_knowledge_base_idparameter is not configured correctly, and the passed ID does not match the e-commerce marketing knowledge base ID actually bound in the FastGPT backend. - When triggering a workflow to upload marketing materials via API, a "missing field" or "invalid parameter" error is returned. Cause: The FastGPT-specified request format is not followed, the product SKU or activity ID fields associated with the material are not correctly included, or global variables are not correctly mapped to the knowledge base ID.
- Tool calling returns marketing content that only contains isolated information, without showing the association between products and activities. Cause: Relation extraction plugins are not enabled, or field mapping rules are not configured, so the associated IDs of e-commerce content cannot be converted into recognizable relational data.
How to confirm configuration is complete
- Call the preset test interface with e-commerce marketing keywords, and check whether the returned results include product or activity information from the target category.
- View the tool calling logs to confirm that no timeout errors related to
plugin_api_timeoutare triggered, and that interface response data is complete. - Check the knowledge base association configuration to confirm that the
global_knowledge_base_idparameter matches the e-commerce marketing knowledge base ID configured in the FastGPT backend. - Upload a test marketing material file, and check whether the parsed content chunks conform to the preset
file_parse_chunk_sizerules.
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.