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https://github.com/terilios/bch-ai-meeting-notes
🤖 Enterprise-grade meeting minutes generator powered by Azure OpenAI. Transforms meeting transcripts into structured documentation with automated analysis, multiple export formats (MD, DOCX, PDF), and intelligent visualization using Mermaid diagrams.
https://github.com/terilios/bch-ai-meeting-notes
ai automation azure-openai docker documentation meeting-minutes mermaid nlp python streamlit
Last synced: 13 days ago
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🤖 Enterprise-grade meeting minutes generator powered by Azure OpenAI. Transforms meeting transcripts into structured documentation with automated analysis, multiple export formats (MD, DOCX, PDF), and intelligent visualization using Mermaid diagrams.
- Host: GitHub
- URL: https://github.com/terilios/bch-ai-meeting-notes
- Owner: terilios
- License: mit
- Created: 2024-10-29T20:32:05.000Z (14 days ago)
- Default Branch: main
- Last Pushed: 2024-10-29T20:36:18.000Z (14 days ago)
- Last Synced: 2024-10-29T22:49:54.652Z (14 days ago)
- Topics: ai, automation, azure-openai, docker, documentation, meeting-minutes, mermaid, nlp, python, streamlit
- Language: Python
- Homepage:
- Size: 21.5 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# BCH AI Meeting Notes Generator
An intelligent meeting minutes generator powered by Azure OpenAI and Streamlit. This application transforms meeting transcripts into well-structured, actionable documentation with automated analysis and multiple export formats.
## Features
- **Multiple Input Formats**: Support for TXT, PDF, DOCX, and MD files
- **Intelligent Processing**: Uses Azure OpenAI for content generation and analysis
- **Rich Output Formats**: Export as Markdown, DOCX, or PDF
- **Meeting Analysis**: Automated scoring across multiple dimensions:
- Meeting Effectiveness
- Participation & Engagement
- Action Item Management
- Risk Management
- Communication Quality
- **Visual Documentation**: Automated generation of Mermaid diagrams for:
- Process flows
- System architectures
- Timeline representations
- Organization structures
- Project dependencies
## Prerequisites
- Python 3.8+
- Pandoc (for document conversion)
- Mermaid-filter (for diagram generation)
- Azure OpenAI API access
## Environment Setup
1. Clone the repository:
```bash
git clone https://github.com/yourusername/bch-ai-meeting-notes.git
cd bch-ai-meeting-notes
```
2. Create and activate a virtual environment:
```bash
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
```
3. Install dependencies:
```bash
pip install -r requirements.txt
```
4. Install system dependencies:
```bash
# On macOS
brew install pandoc
npm install -g mermaid-filter
# On Ubuntu/Debian
sudo apt-get install pandoc
npm install -g mermaid-filter
# On Windows
choco install pandoc
npm install -g mermaid-filter
```
5. Create a `.env` file with your Azure OpenAI credentials:
```env
AZURE_OPENAI_API_KEY=your_api_key
AZURE_OPENAI_API_VERSION=your_api_version
AZURE_OPENAI_API_BASE=your_endpoint
AZURE_OPENAI_DEPLOYMENT_NAME=your_deployment_name
```
## Running the Application
### Local Development
```bash
streamlit run main.py
```
### Docker Deployment
1. Build the Docker image:
```bash
docker build -t bch-ai-meeting-notes .
```
2. Run the container:
```bash
docker run -p 8501:8501 --env-file .env bch-ai-meeting-notes
```
Access the application at http://localhost:8501
## Usage
1. Choose input method:
- Upload a transcript file (TXT, PDF, DOCX, MD)
- Paste text directly
2. Click "Generate Minutes"
3. Review the generated minutes and analysis
4. Download in your preferred format (MD, DOCX, PDF)
## Project Structure
```
bch-ai-meeting-notes/
├── main.py # Main application file
├── schema.json # Analysis schema definition
├── requirements.txt # Python dependencies
├── .env # Environment variables (not in git)
├── Dockerfile # Docker configuration
├── docker-compose.yml # Docker Compose configuration
└── images/ # Application images
├── bch.png
├── user.png
└── user.svg
```
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.