What the Data for This Category Looks Like
Baijiu yield rate and market trend data primarily comes from daily trading public information for constituent stocks in the Shanghai and Shenzhen Stock Exchanges’ baijiu sector, plus daily changes to domestic baijiu industry indices. The system completes daily data collection within one hour after market close each trading day, and makes the data available for query the following day. The dataset uses structured JSON or CSV formatting, with fields including target security code, security name, daily average transaction price, daily price change value, industry index change value, and daily trading volume. Units follow these rules: average transaction price is measured in yuan, price change value is measured in yuan, and trading volume is measured in shares. The dataset excludes pre-market real-time information, only covers completed trading day data, and does not provide non-public trading data for unlisted baijiu brands.
Constraints on Multi-turn Dialogue and Prompt Engineering From Data Characteristics
Data characteristics of the baijiu category impose three constraints on multi-turn dialogue and prompt engineering. First, the dataset only updates after market close on trading days. Prompts must clearly inform users that the available query time range includes the previous trading day and earlier historical data. Real-time market data prior to daily market close cannot be provided, to avoid user misunderstanding. Second, the data source covers two core dimensions: multiple listed baijiu targets and the overall industry sector. Prompts must guide users to specify their exact query target, to avoid incorrect results from ambiguous targets. For example, distinguish between individual listed baijiu stocks and the overall baijiu industry sector. Third, the structured data has a fixed number of fields and standardized field names. Multi-turn dialogue must retain context such as the user’s query dimensions and target selection, to avoid repeating the same questions. It must also ensure accurate matching of field names when calling tools, to prevent returning invalid data.
Configuration Settings
| Configuration Key | Recommended Value | Rationale |
|---|---|---|
maxContext | 2000–3000 characters | Multi-turn dialogue for baijiu yield rate queries needs to retain context such as the user’s target selection, query dimensions, and time range. 2000–3000 characters covers standard 3 rounds or fewer of interactive dialogue |
retrieval count | Top 8–10 entries | The baijiu sector has a large number of constituent stocks. 8–10 retrieved results cover query needs for mainstream baijiu targets, while avoiding information overload |
similarity threshold | 0.75–0.85 | Accurate distinction is required between different baijiu target names and codes. This threshold balances semantic matching precision and recall range, preventing confusion between similar-named targets |
PARSE_FILE_TIMEOUT_SECONDS | 60 seconds | The size of a single daily baijiu market data file typically does not exceed 5 MB. 60 seconds is sufficient to complete structured parsing, avoiding field loss due to timeout |
maxToolCall | 3 times | Standard baijiu yield rate query workflows typically include three steps: confirming the target, confirming query dimensions, and confirming the time range. 3 tool calls cover complete interactive flows |
UPLOAD_FILE_MAX_SIZE | 20 MB | Supports users uploading batch historical baijiu data files for up to one month, to meet bulk analysis needs |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume, and business rules. Each scenario requires specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Symptom: Permission error returned when calling market data tools. Cause: A globally shared API key was used. This key only supports basic calls, and cannot access dedicated data sources for industry-specific scenarios.
- Symptom: Some fields for baijiu targets are missing from parsed results after a user uploads a historical data file during multi-turn dialogue. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted, leading to file parsing timeout and failure to correctly extract some fields. - Symptom: The question classification module in the workflow cannot accurately distinguish between "individual listed baijiu stock" and "baijiu industry sector" query requests. Cause: The
similarity thresholdsetting does not meet the matching requirements of this scenario, leading to deviations in semantic matching.
How to Verify Successful Configuration
- Initiate a multi-turn dialogue that includes multiple baijiu targets and query dimensions, and confirm that the fields returned by tool calls match the preset data source fields.
- Upload a batch of historical baijiu data files, confirm the completeness of parsed fields, and adjust
PARSE_FILE_TIMEOUT_SECONDSuntil parsing succeeds. - Test query requests with different target names, confirm that classification results meet expectations, and adjust the similarity threshold until matching accuracy meets requirements.
- Verify that requests initiated using an application-specific API key return no permission 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.