What the Data for This Category Looks Like
The data sources for meeting minutes organization include three types: meeting recording transcription text, handwritten notes taken by attendees offline, and chat logs exported from online meeting platforms. An initial version is generated after a single meeting concludes, with subsequent revisions made based on supplementary meeting notices and follow-up records of resolutions. The fixed document structure includes six core fields: meeting topic, holding time, list of attendees, discussion topics, resolution items, and follow-up items. Each field uses scenario-appropriate units, such as number of attendees in people, discussion topics in items, and follow-up items in responsible persons.
What Constraints These Characteristics Impose on the "Multi-turn Dialogue and Prompt Engineering" Link
Diverse data sources result in input text that may be colloquial, contain errors or omissions, or be fragmented. This requires multi-turn dialogue to first complete text normalization, and the prompt must include pre-set text organization rules. The fixed field structure requires the prompt to clearly specify the extraction format for each field to avoid chaotic output. The flexible update cycle means multi-turn dialogue must support appending supplementary content, and the messages parameter must splice newly input content in chronological order. Associations exist between fields — for example, resolution items correspond to discussion topics — which requires multi-turn dialogue to retain contextual associations and not isolate single-turn input content.
How to Set Up the Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Approach | Rationale |
|---|---|---|
messages | Splice segmented text in chronological order of meeting discussions, retain original speaker identifiers | Aligns with the message flow logic of multi-turn dialogue, retains contextual associations |
| Prompt Template | Fixed prefix including text normalization and field extraction rules, with a length of 800–1200 characters | Matches the fixed structure of meeting minutes, clearly guides the model to output in a specified format |
variables | Bind variables for meeting minutes original file ID and list of attendees | Enables dynamic content replacement, avoids repetitive input of fixed information |
| Message History Retention Count | Top 10 entries | Covers the complete discussion and resolution process of a single meeting, avoids context overflow |
| Timeout Setting | 600 seconds | Adapts to the text processing and model inference duration for long meeting minutes |
Three Common Misconfigurations
- After orchestrating an HTTP request, the configured
variablesoutput fields are empty and not displayed in dialogue results. The cause is failing to correctly bind the reference path of the output variable in themessagesparameter. - When configuring multi-turn dialogue, only a single segment of meeting text is passed, and
messagesare not spliced in discussion order, leading to missed associated content from prior discussions when extracting resolution items. - After local deployment, uploaded meeting recording transcription files cannot be read in the dialogue. The cause is failing to enable the real-time file parsing call switch, which only supports files pre-uploaded to the knowledge base.
How to Confirm Proper Configuration
- Initiate a test dialogue, input the core discussion topics of the meeting minutes, and check whether the returned dialogue content includes the preset field extraction results.
- View the dialogue log associated with the
chatIdto confirm that the text in themessagesparameter is correctly spliced in chronological order. - Check whether the variables bound via
variablesare correctly replaced with actual meeting information in the dialogue interface. - Simulate inputting supplementary meeting resolution content, and confirm that the multi-turn dialogue context does not lose prior discussion content.
The values provided here 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.