What the Data for This Category Looks Like
Special steel enterprise financial report data comes primarily from periodic reports disclosed by domestic and overseas stock exchanges, and operating announcements officially released by enterprises. Update frequency follows this schedule: annual reports once per year, semi-annual reports once every six months, and quarterly reports once per quarter. Document structure includes core financial statements, special steel production and sales data, raw material purchase details, capacity utilization rate and other modules. Fields covered include the proportion of special steel revenue in total revenue, gross profit margin of special products, alloy raw material purchase costs, ten-thousand-ton capacity data and more. Units include ten thousand yuan, ten thousand tons, kg standard coal per ton and others.
Constraints on Multi-turn Dialogue and Prompt Engineering
The segmented fields and long document characteristics of special steel financial reports create multiple constraints for multi-turn dialogue and prompt engineering workflows. First, the low update frequency requires limiting the time range of context in multi-turn dialogue to avoid associating with outdated non-current financial report data. Second, segmented fields such as special steel revenue proportion and alloy purchase cost require prompts to clearly specify extraction of indicators strongly related to the special steel category. Generalized manufacturing financial fields should not be extracted. In addition, the long length of single financial report documents requires multi-turn dialogue context windows to adapt to long text processing, preventing truncation of key information. Finally, multi-turn interactions must guide users to focus on analysis questions related to special steel business, avoiding off-topic content.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000-12000 characters | Single special steel financial report document has a long length, needs to accommodate multi-turn interaction history and complete financial report fragments |
recall_top_k | Top 6-8 entries | There are many segmented fields in special steel financial reports, needs to recall enough relevant fragments to cover indicators such as special products and capacity |
prompt_template | Fixedly limit the analysis object to the current financial report of special steel enterprises, extract segmented fields including special steel revenue, gross profit margin, capacity utilization rate, etc., only answer financial and business questions directly related to special steel business | Special steel financial reports have segmented business indicators, need to clearly define the analysis scope of the prompt to avoid returning general data |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Special steel financial reports contain a large amount of long text and tabular data, which takes longer to parse |
multi_round_turn_limit | 10-15 turns | Need to avoid context overload in multi-turn interactions, while covering users' continuous questioning needs |
similarity_threshold | 0.75-0.85 | Special steel segmented fields have high matching accuracy requirements, need to filter low-relevance recalled content |
The parameter values provided 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 specific analysis, and it is recommended to test on your own samples before finalizing.
Three Common Misconfigurations
- The workflow only supports single queries, and cannot trigger multi-turn follow-up questions or continuous Q&A. The cause is that the multi-turn dialogue linkage configuration of the workflow is not enabled, and only a single AI call node is bound.
- After the workflow runs, the responses of all
<ai对话>nodes are displayed in the workflow's chat window. The cause is that the output hiding rule for the nodes is not configured, and the return content of all nodes is pushed to the dialogue context by default. - The financial report data returned in multi-turn dialogue includes non-special steel related indicators such as general steel revenue and ordinary manufacturing costs. The cause is that the prompt does not clearly limit the analysis scope to special steel business, and does not specify the extraction of segmented fields.
How to Verify Correct Configuration
- Upload a special steel enterprise financial report document, initiate the first query, and check whether the returned content includes segmented indicators related to special steel business, and does not include general manufacturing data.
- Initiate consecutive progressive queries, and check whether the dialogue context retains historical interaction content, and no key information is truncated.
- Configure a workflow with multiple AI dialogue nodes, test the run, and check that only the output content of the specified nodes is displayed in the chat window.
- Adjust the similarity threshold, compare the relevance of the recalled document fragments, and confirm that the matching accuracy meets the analysis requirements.
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.