Create app.py

app.py

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+import streamlit as st
+import requests
+
+from langchain.utilities import ApifyWrapper
+from langchain.document_loaders.base import Document
+
+# Initialize ApifyWrapper and other environment variables
+os.environ["OPENAI_API_KEY"] = "Your OpenAI API key"
+os.environ["APIFY_API_TOKEN"] = "Your Apify API token"
+
+APIFY_WEATHER_KEY = "91b23cab82ee530b2052c8757e343b0d"
+apify = ApifyWrapper()
+
+def get_website_summary(website_url):
+    # For now, return a dummy summary. Replace this with the API logic you have
+    return "This is a dummy summary for " + website_url
+
+def get_google_reviews(website_url):
+    # Return dummy Google Maps reviews for now.
+    # Replace this with the logic to get reviews summary using GPT-3.5 and Google Maps API.
+    return {
+        "pros": ["Great ambiance", "Friendly staff", "Tasty food"],
+        "cons": ["A bit pricey", "Long waiting times on weekends", "Limited parking"]
+    }
+
+def get_peak_times(website_url):
+    # Dummy data for peak times.
+    # Replace this with the logic to fetch peak times using Google Maps API.
+    return {
+        "Monday": [10, 20, 30, 40, 30, 20, 10],
+        "Tuesday": [15, 25, 35, 45, 35, 25, 15],
+        # ... add other days
+    }
+
+def get_images(website_url):
+    # Return dummy image URLs.
+    # Replace this with logic to fetch place images using Google Maps API.
+    return [
+        "https://via.placeholder.com/150",
+        "https://via.placeholder.com/150",
+        "https://via.placeholder.com/150",
+        "https://via.placeholder.com/150",
+        "https://via.placeholder.com/150",
+    ]
+
+def get_map_widget(website_url):
+    # Return dummy map coordinates (for New York City).
+    # Replace this with the logic to fetch actual coordinates of the place using its website URL.
+    return {
+        "lat": 40.730610,
+        "lon": -73.935242
+    }
+
+def get_weather_data(lat, lon):
+    BASE_URL = f"https://api.openweathermap.org/data/3.0/onecall"
+    params = {
+        "lat": lat,
+        "lon": lon,
+        "exclude": "hourly,daily,minutely",
+        "appid": APIFY_WEATHER_KEY,
+        "units": "metric"
+    }
+    response = requests.get(BASE_URL, params=params)
+    if response.status_code == 200:
+        return response.json()
+    else:
+        return None
+
+def process_website(website_url):
+    website_summary = get_website_summary(website_url)
+    reviews = get_google_reviews(website_url)
+    peak_times = get_peak_times(website_url)
+    images = get_images(website_url)
+    map_widget = get_map_widget(website_url)
+    
+    weather_data = get_weather_data(map_widget["lat"], map_widget["lon"])
+    if weather_data:
+        temp = weather_data["current"]["temp"]
+        weather_desc = weather_data["current"]["weather"][0]["description"]
+        weather_widget = f"It's {temp}°C with {weather_desc}."
+    else:
+        weather_widget = "Unable to fetch weather data at the moment."
+    
+    return website_summary, reviews, peak_times, images, map_widget, weather_widget
+
+# Streamlit UI
+st.title("Website Information Extractor")
+
+website_url = st.text_input("Enter a website/company name:")
+
+if website_url:
+    summary, reviews, peak_times, images, map_data, weather_info = process_website(website_url)
+
+    st.subheader("Website Summary")
+    st.write(summary)
+
+    st.subheader("Google Reviews")
+    st.write("Pros:")
+    for pro in reviews["pros"]:
+        st.write(f"- {pro}")
+
+    st.write("Cons:")
+    for con in reviews["cons"]:
+        st.write(f"- {con}")
+
+    st.subheader("Peak Times")
+    for day, times in peak_times.items():
+        st.write(f"{day}: {times}")
+
+    st.subheader("Images")
+    for image in images:
+        st.image(image)
+
+    st.subheader("Location")
+    st.map({"lat": map_data["lat"], "lon": map_data["lon"]})
+
+    st.subheader("Current Weather")
+    st.write(weather_info)