What Data for This Category Looks Like
Cosmetics marketing content data sources primarily include official materials from partner beauty brands, planning documents from financial institution marketing teams, and compliance filing documents. Update frequency adjusts based on new product launches and marketing campaign cycles, with no fixed schedule. Document types include product manuals, aggregated recommendation copy, live stream scripts, ingredient list documents, and more. Document structures often mix long efficacy descriptions, structured ingredient tables, product images, and compliance prompt fields. Fields include ingredient names, content percentages, applicable skin types, filing numbers, marketing copy, and more. Units include percentages, milliliters, grams, milligrams, and others.
Constraints for Document Parsing and Chunking
Mixed document structures require parsing tools to support recognition of long text, structured tables, and images simultaneously. This avoids breaking semantic links between ingredients and efficacy claims, ensuring accuracy for financial institution marketing content. Accurate extraction of structured ingredient tables and compliance fields requires the parsing process to retain table row and column structure and the integrity of specific fields. Do not extract only plain text, as this will impact subsequent compliance checks. For scenarios where images are tied to text, parsing tools must associate images with their contextual descriptions to improve the display effect of marketing content. High-frequency material updates demand the parsing process to have sufficient efficiency to match the rapid iteration pace of financial institution marketing campaigns. The presence of compliance fields requires that key information such as filing numbers is not omitted during chunking, to meet compliance requirements for financial platforms.
How to Set Configurations
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
UPLOAD_FILE_ALLOWED_EXT | ["docx", "pdf", "png", "jpg"] | Cosmetics marketing documents often include materials and images in these formats, covering common file types |
PARSE_TABLE_ENABLE | Enabled | Cosmetics marketing documents include structured tables such as ingredient comparisons and efficacy comparisons, requiring retention of row and column structure |
CHUNK_SIZE | 800–1200 characters | Balances semantic completeness of long efficacy descriptions and retrieval accuracy for short ingredient entries and compliance fields |
PARSE_IMAGE_CAPTION | Enabled and associated with context; requires FastGPT 4.9.0 or higher | Product images and ingredient diagrams must be bound to corresponding text descriptions to avoid isolated image information |
PARSE_REFERENCE_ENABLE | Enabled | Some marketing documents include filing references and bibliography fields, requiring complete extraction |
PARSE_TIMEOUT_SECONDS | 120 seconds | Long documents with multiple tables and images require sufficient parsing time to prevent task interruptions |
The parameter values provided on this page are common starting points for configuration setup. Actual values vary based on material format, data volume, and business rules. Each scenario requires individual analysis. It is recommended to test on samples specific to the deployment before finalizing settings.
Three Common Configuration Mistakes
- Phenomenon: The document parsing node returns empty results, or the console displays
FILE_NOT_FOUNDor400 BAD REQUESTstatus codes. Cause: TheUPLOAD_FILE_ALLOWED_EXTwhitelist is not configured. Cosmetics marketing documents often use docx, pdf, and png formats. These formats must be added to the allowed list. - Phenomenon: Ingredient comparison tables in imported Word documents lose row and column structure after parsing, or product images have no associated text labels. Cause: The
PARSE_TABLE_ENABLEandPARSE_IMAGE_CAPTIONconfigurations are not enabled. This causes structured information for tables and images to be ignored. - Phenomenon: Parsed chunked content does not include filing number references or
referencesfield content from the document. Cause: ThePARSE_REFERENCE_ENABLEconfiguration is not enabled, or matching rules are not adjusted to adapt to the reference format of cosmetics marketing documents.
How to Verify Correct Configuration
- Upload a cosmetics marketing document that includes ingredient tables, product images, and compliance references. Check if parsed data retains table row and column structure and image association labels.
- Review parsing task logs to confirm there are no error messages such as
FILE_NOT_FOUNDorPARSE_TIMEOUT. - Extract chunked content to verify that expected ingredients, efficacy descriptions, and
referencesfield content are included. - Test chunked retrieval effectiveness to confirm that long efficacy descriptions are not split incorrectly, and key compliance fields are not missing.
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.