What This Category of Data Entails
Securities research report data draws from publicly licensed domestic securities research institutions and third-party financial data platforms with authorized public content. Updates follow workday schedules. Real-time reports generate following intraday sudden industry events or listed company earnings releases. Document structures include fields such as title, issuing institution, release date, core logic, industry rating, profit forecast, valuation metrics, and risk warnings. Numeric field units include earnings per share (yuan), price-to-earnings ratio (times), revenue (100 million yuan), and others.
Constraints for Multi-turn Dialogue and Prompt Engineering
Securities research reports are lengthy and contain structured numeric fields. Multi-turn dialogue must retain historical interactions to link subsequent user follow-up questions and avoid repeated inquiries. Ratings and profit forecast values across different reports have time-based differences. Prompts must explicitly require citing sources and release dates to prevent confusion between analysis results from different periods. Real-time updated reports need priority access to the latest data sources. Multi-turn dialogue must not use expired content to answer current queries.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–12000 characters | A single research report’s main body typically exceeds 3000 characters. Multi-turn dialogue requires retaining historical interactions and content from multiple reports to avoid truncating critical information |
recallTopK | Top 8–12 entries | Securities research reports have many segmented dimensions. Too many recalled entries will introduce irrelevant content, while too few will fail to cover information across required industry, rating, and time dimensions |
similarityThreshold | 0.75–0.85 | Filters low-relevance report fragments to avoid interference from reports of unrelated industries or time periods on dialogue logic |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Research reports contain tables, charts, and structured data, which take longer to parse, so sufficient processing time must be reserved |
enableMultiRound | Enabled | Users often follow up with questions about specific values or rating changes in reports, so historical conversation context must be retained to associate subsequent queries |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: After deployment, calling the research report parsing or voice interaction function throws an error stating that ffmpeg dependencies are missing. Attachments or audio input cannot be processed normally. Cause: Containers run by default with non-root privileges. Installing dependencies during runtime fails due to insufficient permissions. Dependencies must be configured during the image build phase.
- Phenomenon: When multiple AI nodes are connected in a workflow, the final output includes all conversation content from preceding nodes. It does not only retain the final result as expected. Cause: The current node’s prompt does not explicitly require only outputting the current node’s response, or the context inheritance switch is not disabled.
- Phenomenon: The configured HTTP search node in the workflow is not triggered. The AI directly generates non-real-time research report responses. Cause: The system prompt does not specify prioritizing calling the HTTP tool to obtain the latest research report data, or the node’s trigger conditions are not correctly bound to keywords from the user’s query.
How to Verify Proper Configuration
- Upload a public securities research report, submit a query that includes specific numeric values, and confirm that the response labels the issuing institution and release date of the research report.
- Submit a multi-turn follow-up query: first ask for a specific brokerage’s rating of a certain industry, then follow up with a query for the corresponding profit forecast value. Confirm that the response associates with the query object from the previous turn.
- Configure an HTTP node and bind it to the research report search interface, submit a query that requires the latest data, and confirm that the result comes from the content returned by the HTTP request, rather than using pre-trained knowledge.
- Adjust the recall count parameter, submit a multi-dimensional query, and confirm that the number of returned research reports falls within the configured value range.
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.