What the data for this category looks like
Data sources for consumer building materials research reports include publicly disclosed industry trend reports from domestic building material industry associations, annual and semi-annual operating announcements of listed consumer building material enterprises, and segmented category tracking reports released by third-party industrial research institutions. Update schedule: Public reports are updated in batches quarterly. Enterprise tracking reports are released as needed. Document structure includes five core modules: industry overview, segmented category performance, channel and policy analysis, competitive landscape, and trend forecast. Fields include:
- Segmented category shipment volume (unit: 10,000 square meters / 10,000 sets / 10,000 tons)
- Raw material purchase unit price (unit: yuan/ton)
- Number of terminal storefronts covered
- Total amount of winning bid projects (unit: 10,000 yuan)
What constraints these characteristics impose on multi-turn conversation and prompt engineering
The multi-source update schedule and multi-field unit characteristics of consumer building materials research reports impose multiple constraints on multi-turn conversation and prompt engineering configurations. First, timeliness differences across data sources require prompts to guide the model to prioritize calling the latest updated content. A timeliness confirmation step must be added in multi-turn conversations. Second, multiple segmented fields with different units require clear guidance to users to specify the segmented category in multi-turn conversations, to avoid unit matching errors. Third, the relatively long length of individual research reports requires prompts to limit the length of recalled context fragments, to avoid exceeding the model's context capacity limit. Fourth, the module structure including policy and channel analysis requires multi-turn conversations to support users to add related follow-up questions, and retain context memory to link with previous questions.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recallTopK | Top 8–12 results | Consumer building materials research reports contain multi-dimensional segmented data. Too many recalled results will exceed the context capacity limit, while too few will lose key related information. 8-12 results can cover the associated information of core segmented categories |
similarityThreshold | 0.72–0.78 | The segmented fields of consumer building materials research reports have strong relevance. A threshold that is too low will introduce irrelevant content, while a threshold that is too high will miss matching results for related segmented categories |
responseMaxToken | 1200–1800 characters | The analysis content of consumer building materials research reports includes multiple sections of structured data. An overly long reply will exceed the user's reading limit. 1200-1800 characters can cover core conclusions and key data |
promptTemplate | Prioritize recalling corresponding research report fragments based on the segmented category specified by the user, gradually answer questions combined with historical conversation context, and clearly mark data sources and update times | There are large differences in data sources and update schedules for consumer building materials research reports. It is necessary to guide the model to prioritize matching the category specified by the user, and link historical conversations to avoid repeated questions |
conversationTimeout | 90 seconds | Retrieval and re-ranking of consumer building materials research reports require processing multi-dimensional data. 90 seconds can cover conventional retrieval and model generation processes, and avoid user-side timeouts |
rerankTopN | Top 3–5 results | The segmented content of consumer building materials research reports has high similarity. Retaining 3-5 results after re-ranking can ensure that core information is not lost, while controlling the context length |
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 specific analysis. It is recommended to test on your own samples before finalizing the configuration.
Three common misconfigurations
- Phenomenon: A
504 Gateway Timeouterror is returned during a conversation, or the interface displays "Conversation has been terminated". Cause: TheconversationTimeoutconfiguration is not set to match the duration required for consumer building materials research report retrieval. The default timeout cannot cover the retrieval and generation processes of multi-dimensional data. - Phenomenon: After a user adds a follow-up question about a segmented category, the system only returns fragments of the first answer, with no response in subsequent processes. Cause: Context association logic is not configured in the
promptTemplate, causing the model to fail to carry over key information from previous conversations and triggering workflow interruption. - Phenomenon: It is impossible to configure a dedicated prompt for a single conversation, and the default prompt is applied to all sessions. Cause: The
perConversationPromptconfiguration item is not enabled, or the custom prompt function is not enabled in the session management interface, making it impossible to set dedicated prompt logic for individual conversations.
How to confirm the configuration is correct
- Initiate a single-round test query, specify a specific consumer building materials segmented category and data dimension, and verify whether the data sources and update times of the recalled results meet the configuration requirements.
- Initiate 3 consecutive follow-up questions, and verify whether the model carries over the context of previous conversations, with no repeated questions or workflow interruptions.
- View the conversation log, and verify whether the actual effective values of configuration items such as
conversationTimeoutandrecallTopKmatch the preset values. - Test the custom prompt function, set a dedicated prompt logic for a single session, and verify whether the reply of that session follows the requirements of the custom prompt.
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.