Integrate Connexity support

examples/connexity-metrics/.gitignore

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+# Byte-compiled / optimized / DLL files
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examples/connexity-metrics/Dockerfile

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+FROM python:3.10-bullseye
+RUN mkdir /app
+COPY *.py /app/
+COPY requirements.txt /app/
+WORKDIR /app
+RUN pip3 install -r requirements.txt
+
+EXPOSE 8765
+
+CMD ["python3", "server.py"]

examples/connexity-metrics/README.md

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+# Chatbot with Connexity-metrics
+
+This project implements a chatbot using a pipeline architecture that integrates audio processing, transcription, and a language model for conversational interactions. The chatbot operates within a daily and twilio communication environment, utilizing various services for text-to-speech and language model responses. It's two different use cases, for daily and twilio separately.
+
+## Features
+
+- **Audio Input and Output**: Captures microphone input and plays back audio responses.
+- **Voice Activity Detection**: Utilizes Silero VAD to manage audio input intelligently.
+- **Text-to-Speech**: Integrates ElevenLabs TTS service to convert text responses into audio.
+- **Language Model Interaction**: Uses OpenAI's GPT-4 model to generate responses based on user input.
+- **Audio Collection**: Getting a link of your audio recording and sends it to Connexity Metric service for analysis 
+
+## Requirements
+
+- Python 3.10+
+- `python-dotenv`
+- Additional libraries from the `pipecat` package.
+
+## Setup
+
+1. Clone the repository.
+2. Install the required packages.
+3. Set up environment variables for API keys:
+   - `OPENAI_API_KEY`
+   - `ELEVENLABS_API_KEY`
+   - `CONNEXITY_API_KEY`
+4. Run the script.
+
+## Usage
+
+The chatbot introduces itself and engages in conversations, providing brief and creative responses. Designed for flexibility, it can support multiple languages with appropriate configuration.
+
+## Events
+
+- Participants joining or leaving the call are handled dynamically, adjusting the chatbot's behavior accordingly.
+
+
+ℹ️ The first time, things might take extra time to get started since VAD (Voice Activity Detection) model needs to be downloaded.
+
+## Get started
+
+```python
+python3 -m venv venv
+source venv/bin/activate
+pip install -r requirements.txt
+
+cp env.example .env # and add your credentials
+
+```
+
+## Run the server
+
+```bash
+python server.py
+```
+
+Then, visit `http://localhost:8765/` in your browser to start a chatbot session.
+
+## Build and test the Docker image
+
+```
+docker build -t chatbot .
+docker run --env-file .env -p 8765:8765 chatbot
+```