What this category of data looks like
Advertising and marketing content data comes primarily from advertising creative management libraries, delivery backends, content publishing systems, and user interaction logs. Systems update data near real-time or on an hourly sync schedule. Full daily delivery performance data is aggregated. Most data uses structured fields, including creative ID, material type, delivery channel, target audience, budget amount, impression count, and more. Unstructured material files are also included, such as graphic and short video materials. Fields have clear units: budget amount uses yuan, material dimensions use pixels.
What constraints these characteristics impose on model access and configuration
Structured fields for advertising and marketing data are numerous, with wide gaps between value ranges. For example, budget amounts and impression counts have very different magnitude levels. Configure vector normalization parameters during model access to adapt to the numerical characteristics of different fields. Set up automatic sync mechanisms for near real-time updated materials to prevent the model from calling expired materials. Unstructured graphic and video materials require adaptation to multimodal models. Configure parameters such as video frame extraction and text parsing. Additionally, advertising and marketing content includes short copy and long video materials. Adjust the model context window configuration flexibly to cover input content of different lengths.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
vectorNormalization | Enabled | Advertising and marketing data includes fields with widely varying values such as budget and impression count. Enabling this adapts to non-normalized vector models such as Doubao embedding |
maxContext | 8000–16000 characters | Covers context requirements for analyzing short advertising copy and long video materials, adapts to input of marketing content of different lengths |
toolCallStrategy | auto | Supports models to independently choose whether to call tools such as material extraction and data query, adapts to dynamic requirements for advertising and marketing content generation |
PARSE_VIDEO_FRAME_INTERVAL | 5 seconds | Balances analysis accuracy and computing cost for advertising video materials (mostly 15-60 seconds). Extracting one frame every 5 seconds covers core frame information |
UPLOAD_FILE_MAX_SIZE | 200 MB | Covers upload requirements for high-definition advertising images and short video materials, prevents upload failures caused by oversized files |
modelApiTimeout | 120 seconds | Meets execution duration requirements for multimodal models analyzing video materials or batch advertising copy, prevents task interruption due to timeout |
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 specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Configuration Mistakes
- Symptom: Model stream response is empty, and the interface displays this error. Cause:
vectorNormalizationis not configured correctly. The wide value gaps in advertising and marketing data are not adapted to, leading to vector generation failure. - Symptom: Multimodal visual model calls return an error that images cannot be downloaded. This error appears when using Qwen2.5-vL, for example. Cause: Public access permissions for material storage are not configured, or
UPLOAD_FILE_MAX_SIZEis set too small, leading to incomplete material uploads. This is a common scenario for failed model access in FastGPT 4.9.2. - Symptom: Tool calls do not trigger as expected. The model always generates content directly. Cause:
toolCallStrategyis set tomanual. The logic for the model to independently select tools is not enabled, so it cannot adapt to dynamic tool call requirements for advertising and marketing content generation.
How to Confirm Configuration is Complete
- Navigate to the model management page, check the enabled status of
vectorNormalization, confirm it matches the requirements of the current vector model. For example, Doubao embedding requires this configuration to be enabled. - Upload one advertising and marketing material file, verify that the upload progress and file size match the
UPLOAD_FILE_MAX_SIZEsetting, and confirm materials can be uploaded normally. - Configure a test workflow, input a segment of advertising copy, trigger the tool call logic, observe whether the model independently selects the material extraction tool, and verify that the
toolCallStrategyconfiguration takes effect. - Run a multimodal image analysis task, check whether the returned analysis results are complete, confirm that
modelApiTimeoutis set sufficiently to cover task execution duration, and prevent mid-task timeout.
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.