What the Data for This Category Looks Like
Data sources for personal care product research reports include public research reports from third-party industry research institutions, official business disclosure documents from brands, and consumer insight research reports from e-commerce platforms. Regular category research reports are updated quarterly. Research reports related to new product launches are published on demand. Documents typically include overall category overview, segmented product line data, consumer behavior analysis, channel performance, and policy impact modules.
Fields include segmented category revenue, user repurchase frequency, total number of SKUs, unit selling price, and market share. Corresponding units are billion yuan, times/year, pieces, yuan/piece, and similar units.
What Constraints Do These Characteristics Impose on Tool Calling and Plugins
Diverse data sources lead to significant differences in document formats. These range from standardized PDF tables to unstructured web text. Tool calling must support multi-format parsing and structured extraction.
Flexible update rhythms require plugins to support flexible scheduling. Scheduled quarterly pulls for regular reports can be configured, or new product launch events can be bound to trigger incremental updates. Diverse fields and units require tools to support specified field extraction and unit standardization, to avoid statistical bias across data sources. There are many segmented product line dimensions. Tool calling must support filtering retrieval results by sub-category.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Personal care research reports are mostly 50-100 page PDFs. Standard parsing time is under 200 seconds, with reasonable buffer time reserved |
RECALL_TOP_K | Top 10 entries | Personal care research reports have many segmented dimensions. Excessive recall will cause context overload. 10 entries can cover data for major segmented categories |
FIELD_EXTRACT_RULE | Match by specified field names | Personal care research reports include multiple types of business fields. Precise extraction of target fields such as revenue and repurchase frequency is required |
PLUGIN_TRIGGER_MODE | Scheduled trigger + Event trigger | Regular research reports are updated quarterly. New product research reports must trigger pulls alongside launch events |
DOCUMENT_UNIT_STANDARD | Unify to billion yuan, yuan/piece | Units from personal care research report sources vary. Standardization ensures consistency in retrieval and statistics |
MAX_PARSE_CONTENT_LENGTH | 80000 characters | The text volume of a single personal care research report is typically between 50000-70000 characters, with a reasonable upper limit reserved |
The parameter values provided on this page are common recommended 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 Mistakes
- Symptom: A
400 Invalid JSON payload received. Unknown nameerror is returned when calling the text extraction tool. Cause: The submitted request parameters include undefined fields from personal care research report data, or field naming formats do not meet tool requirements. - Symptom: Context cannot be obtained when calling the workflow via API. Cause: The session ID is not included in the
dataparameter of the request, or the workflow's context configuration is not bound to the API call's session. - Symptom: Inconsistent field units in retrieval results lead to errors in statistical analysis. Cause: Document unit standardization configuration is not enabled, and units from different sources of personal care research reports are not unified.
How to Confirm Proper Configuration
- Upload a local personal care research report PDF. Check if the parsed text fully extracts target fields, and confirm that the parse timeout configuration does not trigger timeout errors.
- Call the tool interface. Check that the returned JSON payload only includes fields specified in the configuration, with no unknown fields. Confirm that the field extraction rule is active.
- Trigger a scheduled pull task. Check if the plugin pulls research report data according to the configured scheduling cycle. Confirm that the trigger mode configuration is correct.
- Call the API with a session ID. Check if the workflow can reuse previous session context. Confirm that the context binding configuration is active.
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.