What the data for this category looks like
Condiment research report data mainly comes from domestic public securities research report databases, public monitoring data from food and beverage industry associations, and periodic reports disclosed by listed companies. Update frequency fluctuates with industry events. Dense updates occur during earnings seasons, new product launches, and price adjustment periods. Daily monitoring data updates monthly. Document formats are primarily PDF and DOCX, containing industry trends, production and sales data for segmented product categories, operating information for key enterprises, raw material prices across the industrial chain, and other content. Some structured monitoring data is in CSV format, with fields including segmented product category output, ex-factory price, channel inventory, and raw material purchase price. Units are thousand tons, yuan per kilogram, units, and yuan per ton respectively.
What constraints do these characteristics impose on workflow orchestration
Multi-source heterogeneous data access requires configuring parallel parsing nodes in the workflow to handle unstructured research reports and structured monitoring data separately, preventing single-node blocking of the parsing process. The large number of segmented product categories and fine data granularity require configuring precise filtering rules during recall and extraction stages to avoid mixing in research report data from unrelated categories. Update frequency fluctuates with industry events, requiring the workflow to support a combination of scheduled triggering and event triggering to cover synchronization needs for both regular updates and emergency events. Mixed processing of structured data and unstructured text requires built-in alignment logic in the workflow to associate the statistical cycle of structured data with the analysis content of unstructured research reports, improving the accuracy of subsequent question answering.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
RECALL_FILTER_KEY | Product Category, Statistical Cycle | Core filtering for condiment research reports revolves around segmented product categories and statistical cycles to avoid recalling unrelated industry research reports |
PARSE_FILE_TIMEOUT_SECONDS | 900 seconds | Single securities research report PDF can be 50 to 100 pages long, with long parsing time. Extend the timeout to avoid parsing failure |
WORKFLOW_TRIGGER_MODE | Timed Trigger, Event Trigger | Condiment research report updates fluctuate with earnings seasons and price adjustment events. Combining both trigger modes covers full data update requirements |
EXTRACT_FIELD_LIST | Segmented Category Output, Ex-factory Price, Channel Inventory, Raw Material Purchase Price | Core analysis dimensions of condiment research reports are production and sales, prices, and inventory. Extracting specified fields reduces redundant data |
MAX_RECALL_NUM | Top 12 entries | Condiment segmented product category data is scattered across multiple research reports. Recalling an appropriate number of entries covers core information while avoiding context overflow |
STRUCTURED_DATA_MERGE_MODE | Align by Statistical Cycle | Aligning structured industry data by statistical cycle allows association with analysis content in unstructured research reports, improving question answering accuracy |
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, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- Symptom: Code running nodes in the workflow pass debugging, but think tag content from AI conversation output remains during actual operation. Cause:
AI_RESPONSE_CLEAN_MODEis not configured asremove_think_tag, and code nodes are only run manually during debugging without triggering the complete workflow chain. - Symptom: The workflow includes multiple AI conversation nodes, and the final output contains conversation content from all nodes. Cause:
LAST_NODE_OUTPUT_ONLYis not configured astrue. The default setting retains full-link conversation context and does not only retain the output of the last node. - Symptom: Partial documents fail to parse when batch processing condiment research reports, and the log returns a
PARSE_FAILEDstatus code. Cause:PARSE_PDF_MODEis not configured ashigh_accuracyfor PDF-format research reports, and some research reports with watermarks or complex formats cannot be parsed normally.
How to Confirm Proper Configuration
- Trigger a manual run of the workflow, check if the output result fields include the preset extraction field list, and confirm that field extraction meets business requirements.
- Upload one unstructured research report and one structured data set, check if the workflow automatically aligns the statistical cycles of the two types of data, and confirm that the merge logic takes effect.
- Configure an event trigger rule, simulate an industry-related event to trigger the workflow, check if it starts automatically, and confirm that the trigger mode takes effect.
- Adjust the recall count configuration item, check if the number of recall results matches business requirements after running, and confirm that the filtering rules take effect.
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.