Summarizer
Description
The Summarizer step connects to a Large Language Model to analyze text. This step accepts input data and generates an intelligent summary of the key information. It captures the core message from sources such as long email threads, message history, document text, etc. The output delivers a clear, condensed version of the original material. The Input tab defines the exact content for processing. This section accepts information from earlier workflow steps or text typed directly into the box. The model uses this data to generate the final summary.
Example using Summarizer step: The process summarizes recorded sales calls and posts key points to the CRM opportunity record. The process performs the following actions:
- Workflow automatically generates a transcript once the sales representative finishes a recorded call with a prospect.
- Summarizer plugin step generates a short, bullet summary of key customer needs, budget discussions, and action items.
- Post the summary directly into the opportunity record in the CRM. The workflow efficiently summarized sales call transcripts and updated the CRM with key insights, streamlining follow-ups and enhancing opportunity management.
Configurations
| No. | Field Name | Description |
|---|---|---|
| 1 | Step name | Specify a unique name for the step. The name helps you identify the step in the workflow and makes it easier to debug or link it with other steps |
LLM Setting tab
For the LLM field details, click LLM setting
Input tab
| No. | Field Name | Description |
|---|---|---|
| 1 | Source data | Specify the input source data to analyze and classify into the defined categories. This data can include plain text, user queries, email content, document text, or output from previous steps. You can press Ctrl + Space to insert a variable or Shift + Space to insert a field. |
Output tab
Use the Output tab to save the results of the AI Agent's execution into variables. You can reference these field name in later steps of your workflow to use the AI's answer or track usage costs.
| No. | Field Name | Description |
|---|---|---|
| 1 | Summary | Specify a name for the variable that stores the AI's final answer. This variable captures the main text reply or the result of a tool execution. For example, if you name this variable AnalysisResult, you can reference it in a later email step to send the answer to a user. Default value: summary |
| 2 | Total tokens | Specify a field name to track the total number of tokens used during the execution. This value is the sum of both input and output tokens, representing the total processing size of the transaction. Default value: totalTokens |
| 3 | Input tokens | Specify a field name to count the tokens sent to the AI model. This count includes your prompts, system instructions, and any attached files or context used to ask the question. Default value: inputTokens |
| 4 | Output tokens | Specify a field name to count the tokens generated by the AI in its reply. This measures the length of the response or answer provided by the model. Default value: outputTokens |