Forms and Interactions for Dairy Product Marketing Content

Dairy product marketing-related data primarily comes from enterprise production management systems, supply chain ERP, terminal POS data, and new

What the data for this category looks like

Dairy product marketing-related data primarily comes from enterprise production management systems, supply chain ERP, terminal POS data, and new product filing documents. Data update cadence adjusts based on business nodes. Product basic information is updated when new SKUs are filed. Sales data is synced daily. Consumer survey data is updated monthly. Document structure primarily uses structured tables, with fields including product ID, product name, specification parameters, unit (box, case, liter, etc.), shelf life duration, recommended retail price, ingredient list, and other fields. Some fields must be linked to milk source traceability information.

What constraints apply to forms and interactions

The structured product data and node-specific update cadence for dairy products create clear constraints for form interactions. Fixed attributes for product specifications and units require form fields to preset unit options, preventing users from entering non-standard units. The shelf life field must include unit verification rules, to avoid accidental entry of shelf life days as months. Daily synced sales data requires forms to call the latest inventory and promotional price information in real time, to avoid displaying outdated content. Frequent new product updates require product selection components to support dynamic loading of the latest SKU lists, without manual maintenance of options. The traceability information linking requirement adds a need for credential upload fields in forms, plus file format compliance verification.

How to Set Configuration Values

Configuration ItemRecommended SettingRationale
form_field_unit_restrictionBind the four preset units: box, case, liter, kilogram, to product specification fieldsMatches common sales units for dairy products, prevents non-standard user input
dynamic_sku_load_interval3600 secondsAdapts to the monthly 1-2 new product filing update cadence, refreshes SKU lists regularly
rag_recall_top_kTop 8 entriesDairy product information has many fields, sufficient matching entries must be recalled to cover dimensions including ingredients and shelf life
workflow_ai_prompt_max_length1200 charactersLimits the length of sales and customer service prompts, ensuring the model accurately identifies procurement information verification rules
form_upload_file_max_size100 MBAligns with common uploaded file sizes for traceability credentials and product packaging images
form_submit_timeout30 secondsAvoids form submission failures due to network fluctuations, matches reasonable user wait times for interactions

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 case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Mistakes

  • Phenomenon: Calling the FastGPT API to retrieve interaction results returns a 400 status code, with the prompt "missing callback url". Cause: No backend callback address is bound in the form configuration, so interaction results cannot be pushed to the backend service.
  • Phenomenon: The workflow AI node returns incorrect verification results for product information completeness, failing to detect missing specified fields. Cause: The system prompt does not explicitly list all six required product information items, so the model does not cover all verification checks.
  • Phenomenon: The product selection component in the form loads slowly, exceeding reasonable wait times. Cause: The dynamic_sku_load_interval parameter is set incorrectly, causing frequent interface calls to refresh the SKU list and exceeding interface call limits.

How to Confirm Configuration Is Complete

  • Submit a test form containing dairy product information, verify that field verification blocks non-standard unit input, and confirm the configuration takes effect.
  • Trigger the AI verification node in the workflow, enter preset complete product information, and check that the returned verification results match expectations.
  • View backend service logs, confirm that the backend service receives interaction result data pushed by FastGPT after form submission.
  • Manually trigger a SKU list refresh, verify that the product selection component loads updated new product information.

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.