New features

assistants/call-analysis.mdx

@@ -0,0 +1,148 @@
+---
+title: "Call Analysis"
+sidebarTitle: "Call Analysis"
+description: "At the end of the call, you can summarize and evaluate how it went."
+---
+
+The Call Analysis feature allows you to summarize and evaluate calls, providing valuable insights into their effectiveness. This feature uses a combination of prompts and schemas to generate structured data and success evaluations based on the call's content.
+
+You can customize the below in the assistant's `assistant.analysisPlan`.
+
+## Summary Prompt
+
+The summary prompt is used to create a concise summary of the call. This summary is stored in `call.analysis.summary`.
+
+### Default Summary Prompt
+
+The default summary prompt is:
+
+```text
+You are an expert note-taker. You will be given a transcript of a call. Summarize the call in 2-3 sentences, if applicable.
+```
+
+### Customizing the Summary Prompt
+
+You can customize the summary prompt by setting the `summaryPrompt` property in the API or SDK:
+
+```json
+{
+  "summaryPrompt": "Custom summary prompt text"
+}
+```
+
+To disable the summary prompt, set it to an empty string `""` or `"off"`:
+
+```json
+{
+  "summaryPrompt": ""
+}
+```
+
+## Structured Data Prompt
+
+The structured data prompt extracts specific pieces of data from the call. This data is stored in `call.analysis.structuredData`.
+
+### Default Structured Data Prompt
+
+The default structured data prompt is:
+
+```text
+You are an expert data extractor. You will be given a transcript of a call. Extract structured data per the JSON Schema.
+```
+
+### Customizing the Structured Data Prompt
+
+You can set a custom structured data prompt using the `structuredDataPrompt` property:
+
+```json
+{
+  "structuredDataPrompt": "Custom structured data prompt text"
+}
+```
+
+## Structured Data Schema
+
+The structured data schema enforces the format of the extracted data. It is defined using JSON Schema standards.
+
+### Customizing the Structured Data Schema
+
+You can set a custom structured data schema using the `structuredDataSchema` property:
+
+```json
+{
+  "structuredDataSchema": {
+    "type": "object",
+    "properties": {
+      "field1": { "type": "string" },
+      "field2": { "type": "number" }
+    },
+    "required": ["field1", "field2"]
+  }
+}
+```
+
+## Success Evaluation Prompt
+
+The success evaluation prompt is used to determine if the call was successful. This evaluation is stored in `call.analysis.successEvaluation`.
+
+### Default Success Evaluation Prompt
+
+The default success evaluation prompt is:
+
+```text
+You are an expert call evaluator. You will be given a transcript of a call and the system prompt of the AI participant. Determine if the call was successful based on the objectives inferred from the system prompt.
+```
+
+### Customizing the Success Evaluation Prompt
+
+You can set a custom success evaluation prompt using the `successEvaluationPrompt` property:
+
+```json
+{
+  "successEvaluationPrompt": "Custom success evaluation prompt text"
+}
+```
+
+To disable the success evaluation prompt, set it to an empty string `""` or `"off"`:
+
+```json
+{
+  "successEvaluationPrompt": ""
+}
+```
+
+## Success Evaluation Rubric
+
+The success evaluation rubric defines the criteria used to evaluate the call's success. The available rubrics are:
+
+- `NumericScale`: A scale of 1 to 10.
+- `DescriptiveScale`: A scale of Excellent, Good, Fair, Poor.
+- `Checklist`: A checklist of criteria and their status.
+- `Matrix`: A grid that evaluates multiple criteria across different performance levels.
+- `PercentageScale`: A scale of 0% to 100%.
+- `LikertScale`: A scale of Strongly Agree, Agree, Neutral, Disagree, Strongly Disagree.
+- `AutomaticRubric`: Automatically break down evaluation into several criteria, each with its own score.
+- `PassFail`: A simple 'true' if the call passed, 'false' if not.
+
+### Customizing the Success Evaluation Rubric
+
+You can set a custom success evaluation rubric using the `successEvaluationRubric` property:
+
+```json
+{
+  "successEvaluationRubric": "NumericScale"
+}
+```
+
+## Combining Prompts and Rubrics
+
+You can use prompts and rubrics in combination to create detailed instructions for the call analysis:
+
+```json
+{
+  "successEvaluationPrompt": "Evaluate the call based on these criteria:...",
+  "successEvaluationRubric": "Checklist"
+}
+```
+
+By customizing these properties, you can tailor the call analysis to meet your specific needs and gain valuable insights from your calls.

mint.json

@@ -156,6 +156,7 @@
             "assistants/custom-llm",
             "assistants/persistent-assistants",
             "assistants/dynamic-variables",
+            "assistants/call-analysis",
             "assistants/background-messages"
           ]
         },
@@ -345,6 +346,14 @@
       "source": "/dynamic-variables",
       "destination": "/assistants/dynamic-variables"
     },
+    {
+      "source": "/call_analysis",
+      "destination": "/assistants/call-analysis"
+    },
+    {
+      "source": "/call-analysis",
+      "destination": "/assistants/call-analysis"
+    },
     {
       "source": "/text_message",
       "destination": "/assistants/background-messages"

sdk/web.mdx

@@ -142,6 +142,14 @@ vapi.setMuted(true);
 vapi.isMuted(); // true
 ```
 
+### `say(message: string, endCallAfterSpoken?: boolean)`
+
+The `say` method can be used to invoke speech and gracefully terminate the call if needed
+
+```javascript
+vapi.say("Our time's up, goodbye!", true)
+```
+
 ## Events
 
 You can listen on the `vapi` instance for events. These events allow you to react to changes in the state of the call or user speech.