Upload app.py

app.py

@@ -0,0 +1,78 @@
+import streamlit as st
+import nltk
+import requests
+import speech_recognition as sr
+from rake_nltk import Rake
+
+nltk.download('stopwords')
+nltk.download('punkt')
+
+# Replace with your actual API key and search engine ID
+API_KEY = 'AIzaSyAjwvDJmEdbWhrzWR-17OctIS0ib4zfneU'
+# Replace with your actual Custom Search Engine ID
+SEARCH_ENGINE_KEY = '7564b8c73e277468a'
+
+
+# Function to transcribe speech to text
+def speech_to_text():
+    recognizer = sr.Recognizer()
+    with sr.Microphone() as source:
+        st.info("Listening... Speak into the microphone")
+        audio = recognizer.listen(source)
+        try:
+            text = recognizer.recognize_google(audio)
+            return text
+        except sr.UnknownValueError:
+            st.error("Speech not recognized")
+        except sr.RequestError as e:
+            st.error(f"Could not request results: {e}")
+
+# Function to extract keywords using RAKE
+def extract_keywords(text):
+    r = Rake()
+    r.extract_keywords_from_text(text)
+    keywords_with_scores = r.get_ranked_phrases_with_scores()
+    return [keyword for score, keyword in keywords_with_scores if score > 5]
+
+# Streamlit app
+st.set_page_config(layout="wide")
+
+def main():
+    st.title("Speech to Text Image Search")
+
+    # Button to start speech to text conversion
+    if st.button("Start Speech to Text"):
+        transcribed_text = speech_to_text()
+        if transcribed_text:
+            st.info("Transcription complete:")
+            st.write(transcribed_text)
+
+            # Extract keywords from the transcribed text
+            st.subheader("Extracted Keywords")
+            keywords = extract_keywords(transcribed_text)
+            st.write(keywords)
+
+            # Use the transcribed text as the search query for image search
+            search_query = ' '.join(keywords)
+            url = "https://www.googleapis.com/customsearch/v1"
+            params = {
+                'q': search_query,
+                'key': API_KEY,
+                'cx': SEARCH_ENGINE_KEY,
+                'searchType': 'image'
+            }
+
+            response = requests.get(url, params=params)
+            results = response.json().get('items', [])
+
+            # Display the first two images side by side
+            st.subheader("Image Search Results")
+            if len(results) >= 2:
+                col1, col2 = st.columns(2)
+                col1.image(results[0]['link'], caption="Image 1", use_column_width=True)
+                col2.image(results[1]['link'], caption="Image 2", use_column_width=True)
+            else:
+                st.warning("Not enough images found for display.")
+
+if __name__ == "__main__":
+    main()