An AI-powered call analysis platform for reviewing and analyzing sales calls.
Developed by Adeel Zafar
- Copy example environment file and configure your keys:
cp .env.example .env
- Create and activate virtual environment:
python -m venv venv
source venv/bin/activate # On Windows: venv\Scripts\activate
- Install dependencies:
pip install -r requirements.txt
- Set up local environment:
# Copy example environment file
cp .env.example .env
# Edit .env.local with your settings
nano .env
# Create development data directory
mkdir -p data
cp your_calls.json data/calls.json
- Run the application:
flask run
app/
: Main application packageapi/
: API endpointsservices/
: Business logictemplates/
: HTML templatesstatic/
: Static files
data/
: Local development dataconfig.py
: Configuration settingstests/
: Test suite
- Built with Flask and Anthropic's Claude API <3
- Frontend using Tailwind CSS
- Comprehensive test suite
- Caching for performance
- Environment-specific configurations
- Flask: Lightweight web framework with excellent extensibility
- Anthropic Claude API: State-of-the-art AI for natural language processing
- Google Cloud Platform: Scalable cloud infrastructure
- Cloud Run for containerized deployment
- Cloud Storage for secure data management
anthropic
: Official Claude AI SDK for intelligent call analysispython-dotenv
: Secure environment configuration managementgunicorn
: Production-grade WSGI serverpytest
: Comprehensive testing framework
-
Intelligent Caching:
- LRU cache for optimized duration formatting
- Time-based cache invalidation for call data
- Environment-specific cache strategies
-
Robust Logging:
- Rotating file handlers with 1MB limit
- Structured logging with line numbers
- Environment-aware log levels
- Comprehensive error tracking
-
Error Handling:
- Graceful API error management
- Rate limiting protection
- Timeout handling
- Detailed error reporting
-
Security:
- Environment-based configurations
- Secure credential management
- Cloud-native security practices
-
Testing:
MIT License