Update README.md

readme description still shows simple-chatbot definition hence made more accurate description

examples/canonical-metrics/README.md

@@ -1,12 +1,43 @@
-# Simple Chatbot
+# Chatbot with canonical-metrics
 
-<img src="image.png" width="420px">
+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 communication environment, utilizing various services for text-to-speech and language model responses.
 
-This app connects you to a chatbot powered by GPT-4, complete with animations generated by Stable Video Diffusion.
+## Features
 
-See a video of it in action: https://x.com/kwindla/status/1778628911817183509
+- **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.
+- **Transcription Services**: Captures and transcribes participant speech for analytics.
+- **Metrics Collection**: Sends audio data for analysis via Canonical Metrics Service.
+
+## Requirements
+
+- Python 3.7+
+- `aiohttp`
+- `loguru`
+- `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`
+   - `CANONICAL_API_KEY`
+   - `CANONICAL_API_URL`
+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.
 
-And a quick video walkthrough of the code: https://www.loom.com/share/13df1967161f4d24ade054e7f8753416
 
 ℹ️ The first time, things might take extra time to get started since VAD (Voice Activity Detection) model needs to be downloaded.