Create ai_interpreter.py

ai_interpreter.py

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+# ai_interpreter.py
+"""
+AI interpretation module using Claude API.
+Handles astrological interpretations and user interactions.
+Uses Hugging Face Space secrets for API credentials.
+"""
+
+from typing import Dict, Any
+import streamlit as st
+from anthropic import Anthropic
+
+class AstroAI:
+    """Handles AI-powered astrological interpretations"""
+    
+    def __init__(self):
+        # Get API key from Hugging Face Space secrets
+        api_key = st.secrets.get("CLAUDE_API_KEY")
+        if not api_key:
+            raise ValueError("CLAUDE_API_KEY not found in secrets. Please configure it in your Hugging Face Space settings.")
+        
+        self.client = Anthropic(api_key=api_key)
+        
+    def _format_chart_data(self, chart_data: Dict[str, Any]) -> str:
+        """Convert chart data to a readable format for the AI"""
+        formatted = "Birth Chart Positions:\n\n"
+        
+        # Format planetary positions
+        formatted += "Planets:\n"
+        for planet, data in chart_data['planets'].items():
+            formatted += f"{planet}: {data['degrees']}° {data['sign']} in House {data['house']}\n"
+        
+        # Format house cusps
+        formatted += "\nHouse Cusps:\n"
+        for house, data in chart_data['houses'].items():
+            formatted += f"{house}: {data['degrees']}° {data['sign']}\n"
+            
+        return formatted
+
+    def get_interpretation(self, chart_data: Dict[str, Any], question: str) -> str:
+        """
+        Generate an astrological interpretation based on the chart and user's question
+        """
+        formatted_chart = self._format_chart_data(chart_data)
+        
+        # Construct the prompt
+        prompt = f"""As an astrological AI assistant, provide an interpretation based on the following birth chart data:
+
+{formatted_chart}
+
+User's Question: {question}
+
+Please provide a clear and insightful interpretation focusing specifically on the question asked."""
+        
+        # Get response from Claude
+        try:
+            response = self.client.messages.create(
+                model="claude-3-sonnet-20240229",
+                max_tokens=1000,
+                messages=[{
+                    "role": "user",
+                    "content": prompt
+                }]
+            )
+            return response.content[0].text
+        except Exception as e:
+            error_message = f"Error generating interpretation: {str(e)}"
+            st.error(error_message)  # Display error in Streamlit UI
+            return f"I apologize, but I encountered an error: {error_message}"