What the data for this category looks like
Data sources for coal-electric integration party building study Q&A include official party building documents issued by the group party committee, monthly study ledgers of each party branch, and party building guidance materials from the higher-level state-owned assets supervision and administration commission. Documents have a fixed structure with five fields: topic, issuing unit, release date, core study content, and assessment rules. Release date uses the YYYY-MM-DD format. Most individual core study content pieces range from 800 to 2000 characters. Data update rhythm follows this schedule: monthly sync of party branch study updates, quarterly update of party building assessment norms, and annual review of the latest higher-level policy interpretations.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
Fixed document fields require prompts to explicitly limit the AI to only use fields such as topic and core content from documents when generating responses. This prevents the generation of irrelevant information. The per-document length range requires that the multi-turn dialogue context window be controlled within a reasonable range. This avoids response timeouts caused by loading overly long content. Monthly updated dynamic data requires the dialogue system to support real-time synchronization of the latest party branch study content. Multi-turn dialogue historical context must regularly clean redundant information to avoid old data interfering with current Q&A. Quarterly updates to party building assessment norms require prompts to link to the latest assessment rules. This ensures responses align with current policy requirements.
How to set up configurations
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Context window size | 8000–12000 token | Matches the length of individual documents and the total volume of multi-turn dialogue historical content, to prevent content overflow |
| Historical message retention count | Top 6 turns | Adapts to the multi-turn interaction logic of party building Q&A, retains recent study discussion context |
| Prompt template | Fixed fields first + industry scenario adaptation | Requires the AI to prioritize using fields like topic and core content from documents, and generate responses combined with the scenario of integrating party building into production for coal-electric integration |
| Knowledge base recall count | Top 3 entries | Matches the typical length of individual documents, to avoid recalling too much content and occupying the window |
chatId | Bind to current party branch session | Ensures that multi-turn dialogue context only takes effect within the current party branch session, avoiding cross-session data confusion |
variables | Pass current party branch ID and study cycle | Enables prompts to dynamically adapt to the current party branch's study tasks and latest updated policy content |
Three common mistakes
- Phenomenon: Intermediate generated content from AI conversations is displayed directly on the page without being processed by a text splicing component. Cause: No output interception rule is configured in the workflow, causing AI-generated content to be returned directly to the front-end dialog box.
- Phenomenon: Core party building study knowledge points and assessment requirements cannot be marked in conversation logs. Cause: Custom field mapping for conversation logs is not enabled, and the document's assessment rules field is not synchronized to the log annotation items.
- Phenomenon: After knowledge base retrieval results are passed to AI conversations, the document's release date and topic information cannot be correctly associated. Cause: Retrieval data is not passed in accordance with the document's fixed field format, causing the AI to fail to recognize associated metadata.
How to confirm the configuration is complete
- Launch a session with multi-turn party building study questions, check that only the most recent 6 rounds of dialogue content are retained in the context window, with no redundant historical data.
- Submit a question related to assessment rules, verify that the AI response only uses fixed field content from documents and does not generate irrelevant information.
- View workflow run logs, confirm that AI dialogue output is intercepted by the text splicing component and not returned directly to the front-end dialog box.
- Check conversation log annotation items, confirm that the document's release date and topic fields are synchronized and displayed.
The values provided are common starting points and should be measured against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.