https://github.com/garbii1/voice-assistant-chatapp
🤖 An intelligent voice assistant powered by OpenAI GPT and IBM Watson Speech. Built with Python, Flask, and Docker. 🎤
https://github.com/garbii1/voice-assistant-chatapp
ai-powered api chatbot docker flask full-stack gpt gpt-3-5-turbo html-css-javascript ibm-watson openai openai-api python speech-to-text text-to-speech voice-assistant
Last synced: 4 months ago
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🤖 An intelligent voice assistant powered by OpenAI GPT and IBM Watson Speech. Built with Python, Flask, and Docker. 🎤
- Host: GitHub
- URL: https://github.com/garbii1/voice-assistant-chatapp
- Owner: Garbii1
- Created: 2025-06-11T18:26:37.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-06-11T21:49:13.000Z (4 months ago)
- Last Synced: 2025-06-11T22:40:37.885Z (4 months ago)
- Topics: ai-powered, api, chatbot, docker, flask, full-stack, gpt, gpt-3-5-turbo, html-css-javascript, ibm-watson, openai, openai-api, python, speech-to-text, text-to-speech, voice-assistant
- Language: JavaScript
- Homepage:
- Size: 27.3 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Voice Assistant with OpenAI GPT-3 & IBM Watson
## Conversational AI web app: Speak, listen, and chat with GPT-3, powered by IBM Watson Speech Services
[Features](#-features) • [Tech Stack](#-tech-stack) • [How It Works](#-how-it-works) • [Screenshots](#-screenshots) • [Prerequisites](#-prerequisites) • [Getting Started](#-getting-started) • [Learning Objectives](#-learning-objectives) • [Acknowledgements](#-acknowledgements)
---
## 🎯 Objectives
- Integrate OpenAI GPT-3 with a web application
- Use IBM Watson APIs for speech recognition and synthesis
- Build a full-stack app with Flask and modern frontend tools
- Containerize and deploy with Docker
---
## ✨ Features
- 🎤 **Voice Interaction:** Speak to the assistant and hear its responses.
- 🧠 **Intelligent Responses:** Powered by OpenAI's `gpt-3.5-turbo` model for natural and coherent conversations.
- 🗣️ **High-Quality Speech Services:** Utilizes IBM Watson for fast and accurate Speech-to-Text and Text-to-Speech conversion.
- 🌐 **Responsive Web Interface:** Clean, modern UI with HTML, CSS, and JavaScript.
- 🎨 **Light & Dark Modes:** User-friendly theme switching for comfort.
- 📦 **Containerized:** Includes a `Dockerfile` for easy setup and deployment.
- 🐍 **Python Backend:** Built on the lightweight Flask web framework.
---
## 🛠️ Tech Stack
- **Backend:** Python, Flask
- **Frontend:** HTML, CSS, JavaScript, JQuery, Bootstrap, Font Awesome
- **AI Services:**
- OpenAI API (`gpt-3.5-turbo`)
- IBM Watson Speech to Text
- IBM Watson Text to Speech
- **Containerization:** Docker
---
## 🧩 How It Works
1. **Frontend (JavaScript):** Captures microphone audio when the user clicks the record button.
2. **Speech-to-Text:** Audio is sent to Flask backend's `/speech-to-text` endpoint, which uses IBM Watson Speech-to-Text API.
3. **User Prompt:** Transcribed text is returned and displayed as the user's message.
4. **Process Prompt:** Frontend sends the text to backend's `/process-message` endpoint.
5. **OpenAI GPT-3:** Backend sends the prompt to OpenAI API for a response.
6. **Text-to-Speech:** OpenAI's response is sent to IBM Watson Text-to-Speech API for audio synthesis.
7. **Final Response:** Backend returns the text and audio (base64) to the frontend.
8. **Playback:** Frontend displays the assistant's response and plays the audio.
---
## 🚀 Prerequisites
- **Docker:** Ensure Docker is installed.
- **Git:** To clone the repository.
- **API Keys:**
- **OpenAI:** Create an account and get an API key.
- **IBM Cloud:** Provision Speech to Text and Text to Speech services, get their URLs and API keys.
---
## 🏁 Getting Started
### 1. Clone the Repository
```bash
git clone https://github.com/ibm-developer-skills-network/bkrva-chatapp-with-voice-and-openai-outline.git
mv bkrva-chatapp-with-voice-and-openai-outline chatapp-with-voice-and-openai-outline
cd chatapp-with-voice-and-openai-outline
```
### 2. Configure the Services
Edit `worker.py` to add your API keys and service URLs:
- **IBM Watson Speech-to-Text:** In `speech_to_text`, update `base_url` with your service URL.
- **IBM Watson Text-to-Speech:** In `text_to_speech`, update `base_url` with your service URL.
- **OpenAI:** Ensure your API key is set (typically via environment variable).
Example:
```python
# worker.py
def speech_to_text(audio_binary):
base_url = 'https://YOUR-WATSON-STT-URL' # <-- REPLACE WITH YOUR URL
api_url = base_url + '/speech-to-text/api/v1/recognize'
# ...
def text_to_speech(text, voice=""):
base_url = 'https://YOUR-WATSON-TTS-URL' # <-- REPLACE WITH YOUR URL
api_url = base_url + '/text-to-speech/api/v1/synthesize?output=output_text.wav'
# ...
```
### 3. Build and Run with Docker
```bash
# Build the Docker image
docker build . -t voice-chatapp-powered-by-openai
# Run the container, mapping port 8000
docker run -p 8000:8000 voice-chatapp-powered-by-openai
```
> **Tip:** If you make code changes, stop the container (Ctrl+C), rebuild, and rerun.
### 4. Test Your Assistant
Open your browser and go to [http://localhost:8000](http://localhost:8000) to interact with your voice assistant!
---