app.py

import os
from anthropic import Anthropic
import gradio as gr
# ... (your existing imports)

class ClinicalVoiceAnalyzer:
    def __init__(self):
        # Initialize without the API key first
        self.anthropic = None
        self.model = "claude-3-opus-20240229"
        self.api_key = os.getenv('ANTHROPIC_API_KEY')
        
        # Reference ranges remain the same
        self.reference_ranges = {
            'pitch': {'min': 150, 'max': 400},
            'tempo': {'min': 90, 'max': 130},
            'energy': {'min': 0.01, 'max': 0.05}
        }
        
        # Initialize Anthropic client if API key is available
        self._initialize_anthropic()
    
    def _initialize_anthropic(self):
        """Safely initialize the Anthropic client"""
        try:
            if self.api_key:
                self.anthropic = Anthropic(api_key=self.api_key)
                print("Anthropic client initialized successfully")
            else:
                print("Warning: ANTHROPIC_API_KEY not found in environment variables")
        except Exception as e:
            print(f"Error initializing Anthropic client: {str(e)}")
            self.anthropic = None

    def generate_clinical_analysis(self, voice_features):
        """Generate clinical analysis with fallback behavior"""
        if not self.anthropic:
            return self._generate_fallback_analysis(voice_features), {}
        
        try:
            prompt = self._construct_analysis_prompt(voice_features)
            response = self.anthropic.messages.create(
                model=self.model,
                max_tokens=1000,
                messages=[{
                    "role": "user",
                    "content": prompt
                }]
            )
            return response.content, self._parse_clinical_response(response.content)
        except Exception as e:
            print(f"Error in clinical analysis: {str(e)}")
            return self._generate_fallback_analysis(voice_features), {}

    def _generate_fallback_analysis(self, features):
        """Generate basic analysis when Anthropic API is unavailable"""
        pitch_status = "elevated" if features['pitch_mean'] > self.reference_ranges['pitch']['max'] else "normal"
        tempo_status = "elevated" if features['tempo'] > self.reference_ranges['tempo']['max'] else "normal"
        
        return f"""Basic Voice Analysis:
        
Pitch Analysis: {pitch_status} ({features['pitch_mean']:.2f} Hz)
Speech Rate: {tempo_status} ({features['tempo']:.2f} BPM)
Energy Level: {features['energy_mean']:.4f}

Note: This is a basic analysis. For detailed clinical interpretation, please ensure the Anthropic API key is configured."""

    # ... (rest of your ClinicalVoiceAnalyzer methods remain the same)

# Modified analyze_audio function
def analyze_audio(audio_input):
    try:
        # Your existing audio processing code...
        
        # Initialize clinical analyzer with graceful fallback
        clinical_analyzer = ClinicalVoiceAnalyzer()
        clinical_analysis, clinical_insights = clinical_analyzer.generate_clinical_analysis(features)
        
        # Create enhanced summary
        summary = f"""Voice Analysis Summary:

Speech Content:
{transcription}

Voice Characteristics:
- Average Pitch: {features['pitch_mean']:.2f} Hz
- Pitch Variation: {features['pitch_std']:.2f} Hz
- Speech Rate (Tempo): {features['tempo']:.2f} BPM
- Voice Energy: {features['energy_mean']:.4f}

Dominant Emotion: {max(emotion_scores.items(), key=lambda x: x[1])[0]}

Clinical Analysis:
{clinical_analysis}
"""
        return summary, emotion_viz, feature_viz, clinical_insights
        
    except Exception as e:
        error_msg = f"Error in audio analysis: {str(e)}"
        print(error_msg)
        return error_msg, None, None, None

# ... (rest of your existing code)

# Modified Gradio interface
demo = gr.Interface(
    fn=analyze_audio,
    inputs=gr.Audio(
        sources=["microphone", "upload"],
        type="filepath",
        label="Audio Input"
    ),
    outputs=[
        gr.Textbox(label="Analysis Summary", lines=15),
        gr.HTML(label="Emotion Analysis"),
        gr.HTML(label="Voice Feature Analysis"),
        gr.JSON(label="Clinical Insights")
    ],
    title="Advanced Voice Analysis System",
    description="""This system provides comprehensive voice analysis with clinical interpretation. 
                Upload an audio file or record directly through your microphone."""
)