What the Data for This Category Looks Like
Data for publishing industry research reports originates primarily from legally authorized official publisher databases, public information platforms of industry associations, and self-developed repositories of professional publishing institutions. Update frequency varies by report type: regular reports are updated weekly, monthly, or quarterly, while emergency industry reports can go live immediately. Each complete report includes a title, issuing institution, author, release date, core viewpoints, data appendix, and references. Most individual reports are approximately 10,000 characters in length. Fields include unique report identifiers, industry classifications, target ratings, target prices, core financial data, and more. Data units use standardized financial measurement units such as yuan, 100 million yuan, and percentage.
Constraints on Multi-turn Dialogue and Prompt Engineering
The long-document nature of research reports requires multi-turn dialogue to support segmented context recall and long-text integration, preventing key information loss from context truncation. The standardized fields and issuing institution identifiers of research reports require prompts to guide models to prioritize referencing officially disclosed business fields, avoiding fabrication of non-standardized content. The high-frequency update feature requires the retrieval pipeline to match the latest research report data in real time. During multi-turn dialogue, user follow-up questions about specific report chapters must be tracked, and the source identifier of the corresponding report retained to ensure citation accuracy. The professional content attribute requires the recall threshold to align with industry information professionalism, filtering low-relevance redundant fragments.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
maxContext | 8000–16000 characters | Single publishing research reports often exceed 10,000 characters, so this range accommodates multi-turn dialogue context and recalled report fragments |
Recall Count | Top 8–12 entries | The volume of research report data is large; too many recalled entries will exceed the context window, while too few will miss detailed chapter content |
Segment Length | 1000–1500 characters | Research reports have clear chapter structures, so this segment length supports complete extraction of core content per chapter |
Similarity Threshold | 0.75–0.85 | Research report content has high professionalism, so this range filters low-relevance non-core fragments and retains highly matched report chapters |
prompt_template | Based on the recalled research report content and historical dialogue, answer questions accurately, and prioritize referencing official research report fields such as issuing institution and target rating | Publishing research reports have standardized business fields, so prompts need to guide models to align with the information specifications of publishing industry research reports |
PARSE_FILE_TIMEOUT_SECONDS | 120 seconds | Single research report documents have large file sizes, so sufficient time is required for parsing to avoid timeout interruptions |
The parameter values provided on this page are common recommended starting points 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 Configuration Mistakes
- Phenomenon: Calling the online interface returns empty data or status code 500. Cause: Permission verification for the research report data source is not configured, or the number of recalled entries exceeds the return limit of the data source interface.
- Phenomenon: In version v4.8.10, short-text questions directly output full results without streaming output. Cause: The
stream_responseconfiguration item is not enabled, or the context window setting exceeds the streaming transmission threshold supported by the model. - Phenomenon: The content of code running output cannot be obtained as an AI dialogue variable in the workflow. Cause: The output of the code node is not bound to the global variables of the workflow, or the variable name does not match the calling parameter in the prompt template.
How to Verify Successful Configuration
A single typical research report may be uploaded, the retrieval process triggered, and the release time of the recalled results verified to match the update cycle of the current report library. Two or more related follow-up questions may be initiated, the dialogue history verified to be correctly included in the context, and the response content confirmed to link to the details of the previous question. Short-text questions may be tested, and the output mode verified to conform to the configured streaming or non-streaming requirements. Workflow running logs may be reviewed, the system parameters verified to be correctly passed to global variables, and the code running output confirmed to be correctly captured.
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.