What this category of data looks like
The data for meeting spirit summaries comes from official formal meeting documents, leaders' speech transcripts, and supporting authoritative interpretation materials. Updates follow the actual schedule of relevant Party building meetings. A single document typically includes structured modules: meeting title, holding time, organizing unit, core speech content, specific deployment requirements, and more. Fields include meeting unique identifier, release date, full body text, and others. Basic measurement units are characters and articles.
What constraints these characteristics impose on the multi-turn dialogue and prompt engineering link
The official source attribute requires multi-turn dialogue to strictly align with authoritative content, and avoid generating unconfirmed interpretations. Therefore, prompts must explicitly limit content generation to only uploaded official meeting materials. The update rhythm tied to meeting schedules requires that dialogue contexts be regularly synchronized with the latest meeting summary data, to ensure responses cover the latest deployment requirements. Structured document modules allow prompts to target specific content, such as core speeches or deployment requirements, and improve the specificity of questions. Fields with unique identifiers can use chatId to associate the dialogue chain of a single meeting, prevent context interference between different meetings, and ensure the accuracy of question and answer.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
| Maximum Context Length | 800–1200 characters | Matches the typical content length of single meeting spirit summaries, avoids truncating core key points, and adapts to the context processing rules of FastGPT v4.17.0 |
| Number of Retained Conversation History Rounds | First 3 rounds | Party building learning questions mostly focus on single meeting content; excessive history will interfere with the accuracy of current questions |
| Prompt Variables | Meeting Name, Release Date | Clearly define the model's response scope, avoid confusing content from different meetings |
messages parameter | Concatenate per single meeting context | Ensures each round of dialogue only associates historical interaction content for the current meeting |
| Timeout Duration | 60 seconds | Adapts to the parsing and content generation speed of official meeting documents, avoids long waiting times |
| Question Optimization Toggle | Enabled | Helps convert vague learning questions into precise meeting-related questions |
Three Common Misconfigurations
- Issue: Calling the dialogue API returns
400 Bad Requestwith the promptmissing required parameter. Cause: Failed to correctly pass thechatIdormessagesparameters, so the system cannot identify the dialogue chain and context content. - Issue: Generated interpretation content deviates from the official meeting original text, with statements inconsistent with meeting spirit. Cause: Did not explicitly limit generation to only uploaded official materials in the prompt, or did not correctly configure the context scope.
- Issue: After switching to a dialogue on a different meeting topic, the response still associates content from a previous meeting. Cause: Did not configure
chatIdper single meeting, leading to mixed contexts from different meetings.
How to Verify Correct Configuration
- Upload a complete meeting spirit summary document, initiate the first question, and confirm that the response is only generated based on the uploaded content.
- Initiate multiple consecutive questions, and confirm that the system associates the context of the current dialogue and does not introduce content from other meetings.
- When calling the dialogue API, check that the passed parameters include required items such as
chatIdandmessages. - Adjust the number of retained conversation history rounds, and confirm that the system retains the specified number of context rounds according to the configuration.
The values provided here are common starting points, and should be evaluated against samples from the respective deployment scenarios.
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.