Form and Interaction for Chemical Fiber Yield Rates

Data related to chemical fiber yield rates is primarily sourced from domestic spot trading platforms, futures exchanges, and industrial chain

What the data for this category looks like

Data related to chemical fiber yield rates is primarily sourced from domestic spot trading platforms, futures exchanges, and industrial chain monitoring institutions. There are two types of data update schedules: spot prices and industry inventory data update full previous-day information every morning. Main futures contract prices are pushed in real time during trading hours. The document uses a structured daily report format, with core fields including product name, daily settlement price, benchmark price change range, and spot average price range. Units are uniformly yuan/ton and percentage. Some segmented categories such as polyester filament are accompanied by upstream raw material price linkage data.

Constraints Imposed on Form and Interaction by These Characteristics

The layered update feature of chemical fiber data requires form interaction to distinguish between real-time market query and historical daily report retrieval logic. This avoids data matching errors caused by mixed calls. Structured fields include segmented varieties, prices, price changes, and more. Precise category dropdown options must be preset in the form to prevent field extraction mismatches caused by generalized selections. Units are uniformly yuan/ton and percentage, so input validation rules must be configured to enforce unit matching. This prevents unit confusion during data parsing. The high-frequency update of real-time market data requires the form to support custom polling intervals. Historical daily reports must be bound to fixed daily update time nodes to adapt to industry data release rhythms.

How to Set Configurations

Configuration ItemRecommended SettingRationale
recall_top_kTop 8 entriesThere are many segmented categories in the chemical fiber industrial chain. Sufficient entries must be recalled to cover mainstream varieties and avoid missing core data
text_extract_prompt"Extract the following fields: product name, daily settlement price, price change range, spot average price, retain units in yuan/ton and percentage"Matches the standard field structure of chemical fiber daily reports to reduce extraction deviation
tool_call_input_filterEnabledFilters similar-looking character errors in input and corrects abnormal conversion of input content
global_var_assign_triggerTriggered when knowledge base selection changesAdapts to the need for switching knowledge bases on demand and automatically completes global variable assignment
parse_timeout300 secondsChemical fiber data documents may contain industrial chain linkage content. Reserve sufficient parsing time to avoid timeout errors
form_field_unit_checkEnabledVerifies unit matching of extraction results or input content to prevent parsing errors caused by unit confusion

The parameter values given on this page are conventional recommendations used as a starting point 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.

Three Common Mistakes

  • Phenomenon: When passing any as the extraction parameter in text_extract_prompt, the full response displays a code block with undefined. Reason: The fields of chemical fiber data have fixed formats and unit requirements. Generalized extraction without specifying specific fields cannot match the field mapping of structured data, leading to extraction failure.
  • Phenomenon: When the user inputs the text "share", the actual content passed after tool call becomes a similarly spelled string. Reason: The tool_call_input_filter configuration is not enabled, so no error correction verification is performed on input characters, leading to abnormal similar-looking character conversion.
  • Phenomenon: Global variables do not update automatically after switching knowledge bases, or variables do not take effect after manual assignment. Reason: The global_var_assign_trigger configuration is not set to the corresponding trigger timing, and the linkage logic between knowledge base selection and variable assignment is not bound, leading to delayed variable updates.

How to Confirm the Configuration Is Complete

  • Initiate a text extraction test, input the sample text of a chemical fiber daily report, and check whether the fields and units of the extraction result match the preset rules.
  • Input easily confused similar-looking characters, trigger the tool call, and check whether the passed content matches the original input.
  • Switch different knowledge base options, and check whether global variables update automatically along with the option changes.
  • Simulate query requests for different time intervals, and check whether the form correctly adapts to the data update rhythm.

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.