Multi-turn Dialogues and Prompt Engineering for Consumer Electronics Financial Report Analysis

Consumer electronics financial report data mainly comes from designated disclosure platforms of securities regulators and company investor relations

What the Data for This Category Looks Like

Consumer electronics financial report data mainly comes from designated disclosure platforms of securities regulators and company investor relations sections. Update schedules are as follows: quarterly reports are released 1-2 months after the end of each quarter, annual reports are released in March-April of the following year, and temporary announcements supplement information on supply chain and new product line changes. Most documents are in PDF format, with structures including consolidated financial statements, management discussion and analysis, product line revenue breakdowns, R&D investment and inventory data. Core fields include revenue, attributable net profit, and R&D investment ratio. Units are usually RMB or USD, and some documents use millions or billions as simplified display units.

What Constraints These Characteristics Impose on Multi-turn Dialogues and Prompt Configuration

The detailed product line breakdowns, high-frequency update nature, and long-text structure of consumer electronics financial reports create clear constraints for multi-turn dialogues and prompt configuration. Detailed product line data requires multi-turn dialogues to support follow-up questions about detailed product categories, while retaining context-specific reporting periods and dimension information. High-frequency updates require prompts to explicitly specify the current financial report period being analyzed to avoid mixing data across periods. Long-text structures require sufficient context window space to prevent key detailed data from being truncated.

Configuration Settings

Config ItemRecommended ValueRationale
maxContext12000-15000 charactersThe post-parsing text of a single consumer electronics annual financial report is usually 8000-12000 characters, leaving sufficient space to handle detailed data from multi-turn follow-up questions
UPLOAD_FILE_MAX_SIZE20 MBSingle consumer electronics financial report PDFs with multi-quarter comparisons usually do not exceed 15 MB, leaving reasonable redundancy
PARSE_FILE_TIMEOUT_SECONDS90 secondsLong documents require extra time to process section tables and product line detail extraction
Number of recalled entriesTop 8 entriesConsumer electronics financial reports cover multiple core dimensions including total revenue, multiple product lines, R&D, and inventory, requiring sufficient recalled content to cover different needs of multi-turn follow-up questions
Similarity threshold0.75It is necessary to distinguish between total financial report data and detailed product line data to avoid irrelevant content being incorrectly recalled
Global context persistenceEnabledSupports retaining key information such as reporting periods and detailed product categories across turns, meeting the continuity requirements of multi-turn follow-up questions

The parameter values provided on this page are general recommendations used as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis, and it is recommended to test on your own samples before finalizing settings.

Three Common Misconfigurations

  • Phenomenon: Empty smart wearable product line revenue data is returned when asking about it in a multi-turn dialogue. Cause: The global context persistence configuration is not enabled, and key context between sessions is not retained.
  • Phenomenon: Parsing failure is returned after uploading a consumer electronics financial report file via the API. Cause: The UPLOAD_FILE_MAX_SIZE value is not adjusted to match consumer electronics financial reports, and the file exceeds system limits.
  • Phenomenon: The execution result of the AI dialogue node is directly mixed into the front-end dialogue flow. Cause: The AI dialogue node is not configured to only execute tasks without outputting to the dialogue response, or the task output fields are not correctly bound.

How to Verify Proper Configuration

  • Upload a single consumer electronics annual financial report PDF, check if the parsed text blocks cover core fields including total revenue, each product line revenue, and R&D investment.
  • Initiate two rounds of dialogue: first ask about current period total revenue, then ask about the same period's smart wearable product line revenue, and confirm that the context retains the reporting period information from the first round.
  • Adjust the similarity threshold, test recall results for different keywords, confirm that irrelevant content is not incorrectly recalled.
  • Upload a file via the API, check if the returned parsing status code is normal, with no timeout or file size exceeded errors.

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.