examples(twilio-chatbot): update instructions and renames

examples/twilio-chatbot/README.md

@@ -7,6 +7,7 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
 - [Features](#features)
 - [Requirements](#requirements)
 - [Installation](#installation)
+- [Configure Twilio URLs](#configure-twilio-urls)
 - [Running the Application](#running-the-application)
 - [Usage](#usage)
 
@@ -38,11 +39,19 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
     ```
 
 3. **Create .env**:
-    create .env based on .env.example
+    create .env based on env.example
 
 4. **Install ngrok**:
     Follow the instructions on the [ngrok website](https://ngrok.com/download) to download and install ngrok.
 
+## Configure Twilio URLs
+
+1. **Update the Twilio Webhook**:
+    Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
+
+2. **Update the streams.xml**:
+    Copy the ngrok URL and update templates/streams.xml with `wss://<ngrok_url>/ws`.
+
 ## Running the Application
 
 ### Using Python
@@ -57,13 +66,6 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
     ```sh
     ngrok http 8765
     ```
-
-3. **Update the Twilio Webhook**:
-    Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
-
-3. **Update the streams.xml**:
-    Copy the ngrok URL and update your .xml URL to `wss://<ngrok_url>/ws`.
-
 ### Using Docker
 
 1. **Build the Docker image**:
@@ -73,22 +75,8 @@ This project is a FastAPI-based chatbot that integrates with Twilio to handle We
 
 2. **Run the Docker container**:
     ```sh
-    docker build -t twilio-chatbot .                               
     docker run -it --rm -p 8765:8765 twilio-chatbot
     ```
-
-3. **Start ngrok**:
-    In a new terminal, start ngrok to tunnel the local server:
-    ```sh
-    ngrok http 8765
-    ```
-
-4. **Update the Twilio Webhook**:
-    Copy the ngrok URL and update your Twilio phone number webhook URL to `http://<ngrok_url>/start_call`.
-
-5. **Update the streams.xml**:
-    Copy the ngrok URL and update your .xml URL to `wss://<ngrok_url>/ws`.
-
 ## Usage
 
 To start a call, simply make a call to your Twilio phone number. The webhook URL will direct the call to your FastAPI application, which will handle it accordingly.

examples/twilio-chatbot/bot.py

@@ -2,7 +2,7 @@ import aiohttp
 import os
 import sys
 
-from pipecat.frames.frames import LLMMessagesFrame, Frame, AudioRawFrame
+from pipecat.frames.frames import EndFrame, LLMMessagesFrame
 from pipecat.pipeline.pipeline import Pipeline
 from pipecat.pipeline.runner import PipelineRunner
 from pipecat.pipeline.task import PipelineParams, PipelineTask
@@ -10,8 +10,6 @@ from pipecat.processors.aggregators.llm_response import (
     LLMAssistantResponseAggregator,
     LLMUserResponseAggregator
 )
-from pipecat.processors.frame_processor import FrameProcessor, FrameDirection
-
 from pipecat.services.openai import OpenAILLMService
 from pipecat.services.deepgram import DeepgramSTTService
 from pipecat.services.elevenlabs import ElevenLabsTTSService
@@ -32,10 +30,8 @@ async def run_bot(websocket_client):
         transport = FastAPIWebsocketTransport(
             websocket=websocket_client,
             params=FastAPIWebsocketParams(
-                audio_in_enabled=True,
                 audio_out_enabled=True,
                 add_wav_header=False,
-                transcription_enabled=False,
                 vad_enabled=True,
                 vad_analyzer=SileroVADAnalyzer(),
                 vad_audio_passthrough=True
@@ -57,7 +53,7 @@ async def run_bot(websocket_client):
         messages = [
             {
                 "role": "system",
-                "content": "You are a helpful LLM in a WebRTC call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
+                "content": "You are a helpful LLM in an audio call. Your goal is to demonstrate your capabilities in a succinct way. Your output will be converted to audio so don't include special characters in your answers. Respond to what the user said in a creative and helpful way.",
             },
         ]
 
@@ -83,6 +79,10 @@ async def run_bot(websocket_client):
                 {"role": "system", "content": "Please introduce yourself to the user."})
             await task.queue_frames([LLMMessagesFrame(messages)])
 
+        @transport.event_handler("on_client_disconnected")
+        async def on_client_disconnected(transport, client):
+            await task.queue_frames([EndFrame()])
+
         runner = PipelineRunner(handle_sigint=False)
 
         await runner.run(task)

examples/twilio-chatbot/server.py

@@ -1,8 +1,10 @@
-from fastapi import FastAPI, WebSocket, WebSocketDisconnect
-from fastapi.middleware.cors import CORSMiddleware
 import uvicorn
+
+from fastapi import FastAPI, WebSocket
+from fastapi.middleware.cors import CORSMiddleware
 from starlette.responses import HTMLResponse
-from test_bot import run_bot
+
+from bot import run_bot
 
 app = FastAPI()