Update google.py

google.py

@@ -1,136 +1,136 @@
-import streamlit as st
-import requests
-import json
-import os
-import speech_recognition as sr
-import pandas as pd
-import altair as alt
-from PIL import Image
-from io import BytesIO
-
-# Function to perform Google Search
-def google_search(api_key, cse_id, query, num_results=10):
-    url = "https://www.googleapis.com/customsearch/v1"
-    params = {'key': api_key, 'cx': cse_id, 'q': query, 'num': num_results}
-    response = requests.get(url, params=params)
-    return response.json()
-
-# Initialize search history and data storage for analytics
-if 'search_history' not in st.session_state:
-    st.session_state.search_history = []
-if 'search_data' not in st.session_state:
-    st.session_state.search_data = pd.DataFrame(columns=["Query", "Source", "Timestamp"])
-
-def main():
-    st.title("Enhanced Google Search Application")
-
-    # User inputs for API key, CSE ID, and search query
-    api_key = "AIzaSyBvnTpjwspsYBMlHN4nMEvybEmZL8mwAQ4"
-    cse_id = "464947c4e602c4ee8"
-    query = st.text_input("Enter your search query", "", key='query_input')
-
-    # Voice search feature
-    if st.button("Use Voice Search"):
-        recognizer = sr.Recognizer()
-        with sr.Microphone() as source:
-            st.write("Listening...")
-            audio = recognizer.listen(source)
-            try:
-                query = recognizer.recognize_google(audio)
-                st.write(f"You said: {query}")
-                if api_key and cse_id and query:
-                    results = google_search(api_key, cse_id, query)
-                    update_search_history(query, "Voice")
-                    display_results(results)
-            except sr.UnknownValueError:
-                st.error("Could not understand audio.")
-            except sr.RequestError:
-                st.error("Could not request results from Google.")
-
-    # Trigger search on Enter or when search button is clicked
-    if st.button("Search") or st.session_state.get('query_input'):
-        if api_key and cse_id and query:
-            results = google_search(api_key, cse_id, query)
-            update_search_history(query, "Text")
-            display_results(results)
-        else:
-            st.error("Please enter API Key, CSE ID, and a search query.")
-    
-    # Button to show search history
-    if st.button("Show Search History"):
-        if st.session_state.search_history:
-            st.write("Search History:")
-            for h in st.session_state.search_history:
-                st.write(h)
-        else:
-            st.write("No search history found.")
-
-    # Button to clear search history
-    if st.button("Clear Search History"):
-        st.session_state.search_history.clear()
-        st.session_state.search_data = pd.DataFrame(columns=["Query", "Source", "Timestamp"])
-        st.success("Search history cleared.")
-
-    # Interactive Analytics Dashboard
-    st.subheader("Search Analytics")
-    if not st.session_state.search_data.empty:
-        # Chart of search counts over time
-        search_trends = alt.Chart(st.session_state.search_data).mark_line().encode(
-            x='Timestamp:T',
-            y='count():Q',
-            color='Source:N',
-            tooltip=['Query:N', 'count():Q', 'Source:N']
-        ).properties(width=600, height=300)
-        st.altair_chart(search_trends, use_container_width=True)
-
-        # Most popular queries
-        st.write("**Top Search Queries**")
-        top_queries = (
-            st.session_state.search_data['Query']
-            .value_counts()
-            .head(5)
-            .reset_index()
-            .rename(columns={'index': 'Query', 'Query': 'Count'})
-        )
-        st.write(top_queries)
-
-def display_results(results):
-    if results and 'items' in results:
-        st.session_state.results = results
-        for i, item in enumerate(results['items']):
-            st.write(f"**{i + 1}. {item['title']}**")
-            st.write(f"[Link]({item['link']})")
-            st.write(f"{item['snippet']}\n")
-            
-            # Check if 'pagemap' and 'cse_image' exist and if 'src' is in 'cse_image'
-            if 'pagemap' in item and 'cse_image' in item['pagemap']:
-                image_data = item['pagemap']['cse_image'][0]
-                image_url = image_data.get('src')  # Use .get() to avoid KeyError
-                
-                # Try to load and display the image if 'src' exists
-                if image_url:
-                    try:
-                        response = requests.get(image_url)
-                        img = Image.open(BytesIO(response.content))
-                        st.image(img, width=100)
-                    except Exception as e:
-                        st.write("**Image could not be loaded.**")
-                else:
-                    st.write("**Image source not available.**")
-            else:
-                st.write("No image available for this result.")
-    else:
-        st.write("No results found.")
-
-def update_search_history(query, source):
-    # Update search history and analytics data
-    st.session_state.search_history.append(query)
-    new_data = pd.DataFrame({
-        "Query": [query],
-        "Source": [source],
-        "Timestamp": [pd.Timestamp.now()]
-    })
-    st.session_state.search_data = pd.concat([st.session_state.search_data, new_data], ignore_index=True)
-
-if __name__ == "__main__":
-    main()
+api_key = "AIzaSyBvnTpjwspsYBMlHN4nMEvybEmZL8mwAQ4"
+cse_id = "464947c4e602c4ee8"
+ import streamlit as st
+import requests
+import speech_recognition as sr
+import pandas as pd
+import altair as alt
+from PIL import Image
+from io import BytesIO
+
+# Ensure set_page_config is the first Streamlit command
+st.set_page_config(page_title="Google Search App", layout="wide")
+
+# Function to perform Google Search
+def google_search(api_key, cse_id, query, num_results=10):
+    url = "https://www.googleapis.com/customsearch/v1"
+    params = {'key': api_key, 'cx': cse_id, 'q': query, 'num': num_results}
+    response = requests.get(url, params=params)
+    return response.json()
+
+# Initialize search history and data storage for analytics
+if 'search_history' not in st.session_state:
+    st.session_state.search_history = []
+if 'search_data' not in st.session_state:
+    st.session_state.search_data = pd.DataFrame(columns=["Query", "Source", "Timestamp"])
+
+def main():
+    st.title("Enhanced Google Search Application")
+
+    # User inputs for API key, CSE ID, and search query
+    api_key = st.secrets["GOOGLE_API_KEY"]  # Use Streamlit secrets for security
+    cse_id = st.secrets["CSE_ID"]
+    
+    query = st.text_input("Enter your search query", "", key='query_input')
+
+    # Voice search feature
+    if st.button("Use Voice Search"):
+        recognizer = sr.Recognizer()
+        with sr.Microphone() as source:
+            st.write("Listening...")
+            audio = recognizer.listen(source)
+            try:
+                query = recognizer.recognize_google(audio)
+                st.write(f"You said: {query}")
+                if api_key and cse_id and query:
+                    results = google_search(api_key, cse_id, query)
+                    update_search_history(query, "Voice")
+                    display_results(results)
+            except sr.UnknownValueError:
+                st.error("Could not understand audio.")
+            except sr.RequestError:
+                st.error("Could not request results from Google.")
+
+    # Trigger search when clicking the search button
+    if st.button("Search") and query:
+        if api_key and cse_id:
+            results = google_search(api_key, cse_id, query)
+            update_search_history(query, "Text")
+            display_results(results)
+        else:
+            st.error("Please enter API Key, CSE ID, and a search query.")
+    
+    # Show search history
+    if st.button("Show Search History"):
+        if st.session_state.search_history:
+            st.write("Search History:")
+            for h in st.session_state.search_history:
+                st.write(h)
+        else:
+            st.write("No search history found.")
+
+    # Clear search history
+    if st.button("Clear Search History"):
+        st.session_state.search_history.clear()
+        st.session_state.search_data = pd.DataFrame(columns=["Query", "Source", "Timestamp"])
+        st.success("Search history cleared.")
+
+    # Interactive Analytics Dashboard
+    st.subheader("Search Analytics")
+    if not st.session_state.search_data.empty:
+        search_trends = alt.Chart(st.session_state.search_data).mark_line().encode(
+            x='Timestamp:T',
+            y='count():Q',
+            color='Source:N',
+            tooltip=['Query:N', 'count():Q', 'Source:N']
+        ).properties(width=600, height=300)
+        st.altair_chart(search_trends, use_container_width=True)
+
+        # Most popular queries
+        st.write("**Top Search Queries**")
+        top_queries = (
+            st.session_state.search_data['Query']
+            .value_counts()
+            .head(5)
+            .reset_index()
+            .rename(columns={'index': 'Query', 'Query': 'Count'})
+        )
+        st.write(top_queries)
+
+def display_results(results):
+    if results and 'items' in results:
+        for i, item in enumerate(results['items']):
+            st.write(f"**{i + 1}. {item['title']}**")
+            st.write(f"[Link]({item['link']})")
+            st.write(f"{item['snippet']}\n")
+            
+            # Display image if available
+            if 'pagemap' in item and 'cse_image' in item['pagemap']:
+                image_data = item['pagemap']['cse_image'][0]
+                image_url = image_data.get('src')  
+                
+                if image_url:
+                    try:
+                        response = requests.get(image_url)
+                        img = Image.open(BytesIO(response.content))
+                        st.image(img, width=100)
+                    except Exception:
+                        st.write("**Image could not be loaded.**")
+                else:
+                    st.write("**Image source not available.**")
+            else:
+                st.write("No image available for this result.")
+    else:
+        st.write("No results found.")
+
+def update_search_history(query, source):
+    st.session_state.search_history.append(query)
+    new_data = pd.DataFrame({
+        "Query": [query],
+        "Source": [source],
+        "Timestamp": [pd.Timestamp.now()]
+    })
+    st.session_state.search_data = pd.concat([st.session_state.search_data, new_data], ignore_index=True)
+
+if __name__ == "__main__":
+    main()