Add application file

app.py

@@ -0,0 +1,155 @@
+import streamlit as st
+import pandas as pd
+from datetime import datetime
+import swisseph as swe
+import pytz
+from transformers import pipeline
+import numpy as np
+
+# Set page config
+st.set_page_config(
+    page_title="Hindu Astrology Daily Prediction",
+    page_icon="🔮",
+    layout="wide"
+)
+
+# Initialize the text generation pipeline
+generator = pipeline('text-generation', model='gpt2')
+
+
+def calculate_planetary_positions(birth_date, birth_time):
+    """Calculate planetary positions at the time of birth."""
+    # Convert birth datetime to Julian day
+    date_time = datetime.combine(birth_date, birth_time)
+    julian_day = swe.julday(
+        date_time.year,
+        date_time.month,
+        date_time.day,
+        date_time.hour + date_time.minute / 60.0
+    )
+
+    # List of planets to calculate (Sun to Pluto)
+    planets = range(0, 10)
+    positions = {}
+
+    for planet in planets:
+        position = swe.calc_ut(julian_day, planet)[0]
+        positions[planet] = position[0]  # longitude in degrees
+
+    return positions
+
+
+def get_zodiac_sign(longitude):
+    """Convert longitude to zodiac sign."""
+    signs = [
+        "Aries", "Taurus", "Gemini", "Cancer",
+        "Leo", "Virgo", "Libra", "Scorpio",
+        "Sagittarius", "Capricorn", "Aquarius", "Pisces"
+    ]
+    sign_index = int(longitude / 30)
+    return signs[sign_index]
+
+
+def generate_prediction(planetary_positions):
+    """Generate daily prediction based on planetary positions."""
+    # Create a prompt based on planetary positions
+    prompt = "Based on your planetary positions:\n"
+    planet_names = [
+        "Sun", "Moon", "Mercury", "Venus", "Mars",
+        "Jupiter", "Saturn", "Uranus", "Neptune", "Pluto"
+    ]
+
+    aspects = []
+    for i, planet1 in enumerate(planetary_positions):
+        sign1 = get_zodiac_sign(planetary_positions[planet1])
+        prompt += f"{planet_names[i]} in {sign1}\n"
+
+        # Calculate aspects between planets
+        for j, planet2 in enumerate(planetary_positions):
+            if i < j:
+                angle = abs(planetary_positions[planet1] - planetary_positions[planet2])
+                if abs(angle - 120) < 10:  # Trine
+                    aspects.append(f"Trine between {planet_names[i]} and {planet_names[j]}")
+                elif abs(angle - 90) < 10:  # Square
+                    aspects.append(f"Square between {planet_names[i]} and {planet_names[j]}")
+
+    prompt += "\nSignificant aspects:\n" + "\n".join(aspects)
+    prompt += "\nDaily prediction: "
+
+    # Generate prediction using the model
+    prediction = generator(
+        prompt,
+        max_length=200,
+        num_return_sequences=1,
+        temperature=0.7
+    )[0]['generated_text']
+
+    # Clean up the prediction
+    prediction = prediction.split("Daily prediction: ")[-1].strip()
+    return prediction
+
+
+# Streamlit UI
+st.title("🔮 Hindu Astrology Daily Prediction")
+st.write("Enter your birth details to receive your personalized daily prediction.")
+
+# Input forms
+col1, col2 = st.columns(2)
+
+with col1:
+    birth_date = st.date_input(
+        "Date of Birth",
+        min_value=datetime(1900, 1, 1),
+        max_value=datetime.now()
+    )
+
+with col2:
+    birth_time = st.time_input("Time of Birth")
+
+# Time zone selection
+timezone = st.selectbox(
+    "Select Your Time Zone",
+    options=pytz.all_timezones,
+    index=pytz.all_timezones.index('UTC')
+)
+
+if st.button("Get Prediction"):
+    with st.spinner("Calculating planetary positions and generating prediction..."):
+        try:
+            # Calculate planetary positions
+            positions = calculate_planetary_positions(birth_date, birth_time)
+
+            # Display planetary positions
+            st.subheader("Planetary Positions at Birth")
+            planet_names = [
+                "Sun", "Moon", "Mercury", "Venus", "Mars",
+                "Jupiter", "Saturn", "Uranus", "Neptune", "Pluto"
+            ]
+
+            planet_data = []
+            for i, planet in enumerate(positions):
+                sign = get_zodiac_sign(positions[planet])
+                planet_data.append({
+                    "Planet": planet_names[i],
+                    "Sign": sign,
+                    "Degrees": f"{positions[planet]:.2f}°"
+                })
+
+            df = pd.DataFrame(planet_data)
+            st.table(df)
+
+            # Generate and display prediction
+            st.subheader("Your Daily Prediction")
+            prediction = generate_prediction(positions)
+            st.write(prediction)
+
+            # Add disclaimer
+            st.markdown("---")
+            st.caption(
+                "Disclaimer: This prediction is generated using AI and should be taken "
+                "as entertainment only. For accurate astrological readings, please "
+                "consult a professional astrologer."
+            )
+
+        except Exception as e:
+            st.error(f"An error occurred: {str(e)}")