Multi-turn Dialogue and Prompting for Baijiu Financial

What Data Looks Like for This Category

Baijiu financial report data mainly comes from official disclosure platforms of stock exchanges and official investor relations announcements of listed companies. The update schedule follows A-share disclosure rules: quarterly reports are released within one month after the end of each quarter, semi-annual reports are disclosed by the end of August each year, and annual reports are disclosed by the end of April of the following year. Documents are mostly in PDF format, with structures including financial statements, operating data sections, and management discussion and analysis. Field units are mostly yuan, ten thousand yuan, or hundred million yuan. Sales volume units are mostly kiloliters or tons, and some reports include sub-indicators such as per-ton selling price.

Constraints Imposed on Multi-turn Dialogue and Prompting

The fixed disclosure cycle of baijiu financial reports requires multi-turn dialogue to be limited to publicly available reports, and cannot generate undisclosed forecast data. Long document length and large amounts of structured financial data require multi-turn dialogue to retain historical context to avoid repeatedly specifying analysis dimensions. The large number of sub-fields requires prompts to clearly specify the analysis scope to prevent the model from confusing revenue data of different aroma types. The risk of inconsistent units requires prompts to uniformly agree on units to avoid unit confusion in generated results.

Configuration Settings

Configuration Item	Recommended Range	Rationale
`maxContext`	`8000-12000 characters`	Adapts to the segment length of single baijiu financial report documents, avoids content truncation caused by context overflow
`temperature`	`0.1-0.3`	Financial report analysis requires rigor; a lower temperature parameter reduces the probability of generating fictional data
`recallSimilarityThreshold`	`0.75-0.85`	Accurately matches financial fields in reports with user queries, avoids recalling irrelevant non-financial content
`UPLOAD_FILE_MAX_SIZE`	`50 MB`	Single baijiu listed company financial report PDF generally does not exceed 20 MB, reserves sufficient upload redundancy
`maxHistoryTurns`	`5-8 turns`	Multi-turn dialogue for baijiu financial report analysis usually focuses on 3-5 turns; excessive turns increase context redundancy
`parseChunkSize`	`800-1000 characters`	Adapts to the length of tables and text paragraphs in reports, avoids splitting that destroys the integrity of financial data

The parameter values provided on this page are common recommendations used as a starting point 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

The returned messages array in the conversation record list does not distinguish between user and assistant roles, making it impossible to match questions and replies. Cause: The logFullConversation configuration is not enabled, or the corresponding mapping between role and content is not retained in the interface return.
Global variables modified in the same scenario do not take effect in subsequent conversations. Cause: The persistSessionVariables configuration is not enabled, or the variable scope is limited to a single component and not set as a global conversation.
No configuration entry for the temperature parameter can be found in the dialogue component, making it impossible to adjust generation rigor. Cause: The advanced configuration mode is not switched to, or the temperature parameter item is not expanded in the model configuration panel.

How to Verify Proper Configuration

Upload the annual report PDF of a baijiu listed company, initiate 3 consecutive questions, and check that the role and content fields of each record in the conversation history correspond one-to-one.
Adjust the temperature parameter to 0.2 in the dialogue component, compare the generated content before and after the adjustment after initiating a question, and confirm that the parameter takes effect.
Call the conversation record list interface, check that the returned messages array is sorted by the createdAt field, and the content of each record matches user questions and AI replies.
Attempt to modify the global variable and initiate a new question, confirm that the updated value of the variable is correctly referenced in the generated content.

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.