What the data for this category looks like
The data for publishing industry intelligent due diligence reports primarily comes from publishing units' topic filing systems, copyright registration platforms, review process records, distribution ledgers, and compliance supervision databases. Data update frequency changes with business nodes. Topic filing data updates in line with declaration cycles. Review records sync in real time with the review process. Copyright data is updated in bulk quarterly. The fixed document structure includes fields: topic name, ISBN number, author qualifications, copyright ownership document number, distribution scope, review opinions, and compliance rating. ISBN is a 13-digit numeric code. Distribution scope is divided by region or audience group. Review opinions are structured text entries.
What constraints these characteristics impose on multi-turn dialogue and prompt engineering
Decentralized data sources and uneven update rhythms require multi-turn dialogue to associate compliance data from different data sources according to business nodes, to avoid calling expired review records or unsynced copyright information. Fixed structured fields require prompts to accurately match specified fields such as topic names and ISBN numbers, to avoid generating non-standardized report content. Real-time updated review records and periodically updated copyright data require multi-turn dialogue to distinguish the call priority of static and dynamic data, to ensure the timeliness of due diligence report data returned matches business requirements. Standardized coding fields such as ISBN require built-in format verification logic in the dialogue process, to avoid entering or returning invalid codes.
How to configure settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
streamResponseInterval | 1000–2000 milliseconds | Publishing due diligence report content is lengthy. This range balances front-end display smoothness and content output coherence, avoiding too short or too long single returned segments |
maxContext | 10000–15000 characters | Multiple rounds of compliance review records and topic data need to be associated. This range covers core context and avoids redundant model calculations |
customIcon | Publishing industry compliance icon (such as ISBN logo) | Matches the attribute of the due diligence report publishing scenario, replacing the default dialogue icon |
mergeDialogueOutput | Concatenate in dialogue turn order, add the separator 「---」 | Avoids content confusion between two dialogue outputs. A fixed separator distinguishes different AI-generated due diligence fragments |
dialogueLogExportEnabled | Enable full export | Meets the compliance archiving requirements of publishing units, supports pulling all dialogue records for audit |
dialogueSimilarityThreshold | 0.75–0.85 | Filters low-relevance historical due diligence data, ensuring that compliance data called in multi-turn dialogue accurately matches the current topic |
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 case-by-case analysis. It is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: Streaming output returns at a fixed 4-second interval, and cannot be adjusted to 1-2 seconds. Cause: The
streamResponseIntervalparameter is not configured correctly, or the value exceeds the reasonable range supported by the system. - Phenomenon: Dialogue log export only returns records from the last 30 days, and cannot pull all historical dialogue records. Cause: The full export switch for
dialogueLogExportEnabledis not enabled, or an export limit with a limited number of entries is configured. - Phenomenon: Content cross-confusion occurs after concatenating two AI dialogue outputs. Cause: No fixed separator is set, directly concatenating two outputs makes context indistinguishable, or content is not concatenated in dialogue turn order.
How to confirm the configuration is complete
- Initiate a streaming dialogue, observe the interval of front-end returned segments, and adjust
streamResponseIntervaluntil the expected display rhythm is achieved. - Enter the dialogue log module, trigger a full export, and confirm that the exported file contains all historical dialogue records.
- Initiate two independent AI dialogue tasks, concatenate the output results, and check that there are clear separation identifiers and no content crossover.
- Enter the custom icon configuration page, upload an icon matching the publishing scenario, and confirm that the icon on the dialogue interface has been updated.
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.