Multi-turn Dialogue and Prompting for Optoelectronics Yield Data

Data sources for optoelectronics industry market and yield data include public market APIs of the Shanghai and Shenzhen Stock Exchanges, industry

What This Category’s Data Looks Like

Data sources for optoelectronics industry market and yield data include public market APIs of the Shanghai and Shenzhen Stock Exchanges, industry index data sources from China Securities Index Company, and public trading data from sub-sector manufacturers. Update schedule: Real-time market data updates every minute during trading hours on trading days. Full post-market industry daily reports are released after 16:30 each trading day. Data documents use structured table format, including target security code, security abbreviation, affiliated optoelectronics sub-sector, daily closing price, daily trading volume, and daily trading amount. Units: closing price is in yuan, trading volume is in shares, and trading amount is in yuan.

What Constraints These Characteristics Impose on Multi-turn Dialogue and Prompting

Real-time market data updates frequently during trading hours. This requires data calls in multi-turn dialogue to match trading session timeliness. Prompts must explicitly specify the data source’s latest update node to avoid returning expired data. Post-market daily reports follow a fixed update schedule. This requires prompts to guide users to clearly distinguish between real-time market and post-market daily report query needs, to avoid confusing data time periods. Structured data documents include sub-sector fields. Prompts must pre-set mapping rules for sub-sector classifications to ensure accurate matching between user-mentioned sub-categories and corresponding data during dialogue. Fields and units are fixed. Prompts must clearly mark the query format for each field to avoid unit confusion in returned results.

How to Set Configurations

Configuration ItemRecommended ValueRationale
maxContext1500–2000 charactersAdapted for FastGPT V4.9.13. Multi-turn market queries for optoelectronics often involve consecutive time period comparisons. This range covers the context length of conventional multi-turn interactions
Recall counttop 8 entriesThere are a large number of target securities under optoelectronics sub-sectors. Recalling an appropriate number of entries ensures returned results cover the sub-categories mentioned by users
Similarity threshold0.75The names of optoelectronics target securities have similarities. This threshold filters irrelevant target data with low matching accuracy
PARSE_FILE_TIMEOUT_SECONDS300 secondsPost-market optoelectronics industry daily reports have large document sizes. This timeout duration ensures complete parsing of all data
conversation_persistenceisolate storage by userMarket queries from different users need to save conversation records independently to avoid data confusion

The parameter values provided on this page are conventional recommendations used to determine the starting point for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require specific analysis. It is recommended to test on your own samples before finalizing.

Three Common Mistakes

  • Phenomenon: The AI repeatedly returns expired optoelectronics market data during multi-turn dialogue. Cause: Failing to explicitly specify the data source's update node in the prompt, causing the system to call cached old data.
  • Phenomenon: The returned record ID is empty when calling the "Get Conversation Record List" API. Cause: Not enabling the conversation_persistence configuration, so the system does not generate valid conversation record IDs.
  • Phenomenon: The AI confuses optoelectronics target securities from different sub-sectors during multi-turn dialogue. Cause: Not pre-setting sub-sector classification mapping rules in the prompt, leading to matching errors.

How to Confirm the Configuration is Valid

  • Test three consecutive requests for optoelectronics market queries with different time periods. Check if the system retains complete context, and adjust the value of maxContext to meet requirements.
  • Call the "Get Conversation Record List" API. Verify that the returned conversation record IDs exist and are bound to the current user, confirming that the conversation_persistence configuration takes effect.
  • Enter keywords for optoelectronics sub-sectors. Check if the recalled target data matches, and adjust the Similarity threshold to achieve the expected matching accuracy.
  • Upload the post-market industry daily report document. Verify that the parsing completion time is within the set range of PARSE_FILE_TIMEOUT_SECONDS, confirming that the timeout configuration is reasonable.

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.