What the data for this category looks like
Paint and ink marketing content data is primarily sourced from internal product databases, marketing material libraries, and compliance test reports. Updates are triggered by product formula adjustments, new SKU launches, or compliance standard updates, with no fixed schedule. Document structures typically include product overview, technical parameters, application scenarios, compliance instructions, and contact information modules. Fixed fields include product number, name, viscosity, applicable substrates, packaging specifications, and test batch number. Viscosity is measured in millipascal-seconds (mPa·s), packaging specifications use kilograms per barrel as the unit, and batch numbers follow a combination of letters and numbers.
What constraints these characteristics impose on model integration and configuration
Technical parameter values are bound to their units. This requires the model to accurately identify and associate parameters with their corresponding units, so context extraction precision configuration must be adjusted. Documents often include nested tables and high-resolution color cards, which increases file parsing time. Sufficient parsing time and upload space must be reserved. There are frequent needs for multi-SKU parameter comparisons, so enough candidate documents must be retrieved to cover the matching scope. A reasonable similarity threshold must also be set to avoid irrelevant matches. Compliance information in marketing content requires accurate verification, so the model must be able to recognize compliance fields and generate compliant outputs.
How to set the configuration
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | A single paint and ink marketing document contains multiple sets of technical parameters and application scenarios. This value balances context completeness and model redundancy |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Documents often include nested tables and high-resolution color cards. Parsing time is longer than general text, so sufficient parsing time must be reserved |
rerank_top_n | Top 6–8 entries | Paint and ink marketing requires comparison of multi-SKU parameters, so enough candidate documents must be retrieved to cover the target product series |
similarity_threshold | 0.72–0.80 | Product parameters have high semantic similarity. This threshold filters irrelevant matches while retaining valid associations for the same product series |
UPLOAD_FILE_MAX_SIZE | 200 MB | Marketing materials may include high-resolution color card images and bulk product data tables, so large file upload support is required |
workflow_step_output_visible | Only visible for the final step | Marketing content processing requires step-by-step execution of parameter extraction and compliance verification. Only the final generated marketing content needs to be displayed |
The parameter values provided on this page are common recommendations for establishing configuration starting points. Actual values are affected by material form, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing.
Three common mistakes
- Phenomenon: The deployed instance cannot extract color card parameters from marketing documents, while the official online instance functions normally. Cause:
UPLOAD_FILE_MAX_SIZEis not configured or the value is too small, resulting in failure to fully upload and parse high-resolution color card images. The official online instance includes default large file upload configuration. - Phenomenon: After configuring multi-step model calls in the workflow, the parameter extraction results of intermediate steps are publicly displayed. Cause: The intermediate step visibility switch for
workflow_step_output_visibleis not disabled, resulting in exposure of non-final results. - Phenomenon: After calling the rerank model, the number of returned results does not match the configuration, or parsing errors occur. Cause: A rerank model incompatible with FastGPT 4.6.7 is used, or
rerank_top_nis not configured to a value matching the model's output dimension.
How to confirm the configuration is complete
- Upload a single paint and ink marketing document containing multiple sets of technical parameters, and verify that the parameter fields extracted by the model are complete and match their units.
- Trigger workflow execution, check that the interface only displays the final generated marketing content, and that intermediate step parameter processing results are not shown.
- Adjust the
similarity_thresholdvalue, and test whether the retrieved SKU documents cover the target product series with no irrelevant matches. - Upload a document containing high-resolution color cards, and verify that the parsed content is displayed normally with no parsing failure error prompts.
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.