Multi-turn Dialogue and Prompt Engineering for White Goods Intelligent Due Diligence Reports

White goods intelligent due diligence report data mainly comes from official brand parameter pages, e-commerce product detail pages, industry

What the data for this category looks like

White goods intelligent due diligence report data mainly comes from official brand parameter pages, e-commerce product detail pages, industry compliance inspection documents, and after-sales repair manuals. Data updates are triggered by new product launches and adjustments to compliance standards, with no fixed cycle. Most single documents use structured table formats. Core fields include product model, energy efficiency rating, rated power, external dimensions, material type, and warranty period. Units mostly use common standards such as watts (W), liters (L), millimeters (mm), and years. Some documents include detailed parameters from disassembly testing.

What constraints do these characteristics impose on multi-turn dialogue and prompt engineering

Dense structured fields require clear guidance to extract specified fields during multi-turn dialogue, avoiding unstructured general descriptions. The non-fixed update cycle of data sources requires adding logic to verify the latest compliance standards in prompts, preventing the use of outdated parameters. For coexisting multiple units, preset unified unit rules in the dialogue flow, requiring returned results to be converted to specified measurement standards. When parameter discrepancies exist across different source documents, use multi-turn follow-up questions to guide users to confirm the preferred data source, ensuring consistency of due diligence reports.

How to configure the settings

Configuration ItemRecommended ValueRationale
maxContextFirst 10-15 turns of dialogueWhite goods parameter documents are mostly short structured content; overly long context will interfere with accurate extraction of specified fields
RECALL_TOP_NFirst 8-10 entriesCovers multi-dimensional parameter data sources including product model, energy efficiency, dimensions, etc., to avoid missing key fields
SIMILARITY_THRESHOLD0.75-0.85Filters low-match non-official and non-compliant documents, retaining valid data sources from official brands and industry inspections
PARSE_FILE_TIMEOUT_SECONDS300 secondsMulti-page product parameter table documents uploaded in batches require sufficient time to complete structured parsing
UPLOAD_FILE_MAX_SIZE500 MBAdapts to the common file size of single official brand parameter manuals
PROMPT_TEMPLATE_TYPEStructured extraction templateFixed guidance for extracting specified fields, adapting to the standardized output requirements of white goods due diligence reports

The parameter values provided on this page are common starting points for configuration setup. 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 against your own samples before finalizing.

Three common errors

  • Phenomenon: Uploading white goods parameter files or text datasets fails, but the template import function can upload files normally. Cause: Common document formats such as PDF and CSV are not added to the UPLOAD_FILE_ALLOWED_EXTENSIONS whitelist, or the uploaded file exceeds the UPLOAD_FILE_MAX_SIZE limit.
  • Phenomenon: Calling the dialogue interface returns a 404 status code (no body). Cause: The specified dataset ID is not correctly associated, or the system prompt references a knowledge base resource path that was not created.
  • Phenomenon: Parameter units in generated due diligence reports are mixed, with multiple measurement standards such as watts, kilowatts, liters, and milliliters appearing at the same time. Cause: No preset unit unified rules are added to the prompt, and no multi-turn dialogue is used to guide conversion to the specified measurement standards.

How to verify the configuration is properly set

  • Upload an official brand white goods parameter document, verify the upload status and parsing results, and confirm no format parsing failure prompts are present.
  • Initiate a test dialogue, input a specified field extraction request, and check whether returned results include preset core parameter fields.
  • Launch 3 consecutive follow-up questions related to parameters, and check whether dialogue context retains historical interaction content normally, with no content loss.
  • Review knowledge base configuration items, confirm UPLOAD_FILE_ALLOWED_EXTENSIONS includes the currently used document format, and confirm SIMILARITY_THRESHOLD value adapts to matching requirements of the current data source.

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.