Create app.py

app.py

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+import os
+import streamlit as st
+import speech_recognition as sr
+from gtts import gTTS
+from groq import Groq
+from dotenv import load_dotenv
+import tempfile
+import base64
+
+# Load environment variables
+load_dotenv()
+GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+# Initialize Groq Client
+client = Groq(api_key=GROQ_API_KEY)
+
+# Function to transcribe voice to text
+def transcribe_audio(audio_file):
+    recognizer = sr.Recognizer()
+    with sr.AudioFile(audio_file) as source:
+        audio_data = recognizer.record(source)
+        try:
+            text = recognizer.recognize_google(audio_data)
+            return text
+        except sr.UnknownValueError:
+            return "Could not understand the audio"
+        except sr.RequestError:
+            return "Error with speech recognition service"
+
+# Function to generate speech from text
+def text_to_speech(text):
+    tts = gTTS(text=text, lang="en")
+    temp_audio_path = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3").name
+    tts.save(temp_audio_path)
+    return temp_audio_path
+
+# Function to get AI insights from LLaMA 3 70B
+def get_ai_response(text):
+    response = client.chat.completions.create(
+        model="llama-3.3-70b-versatile",
+        messages=[
+            {"role": "system", "content": "You are an advanced AI that helps with speech processing."},
+            {"role": "user", "content": f"Analyze this text: {text}"}
+        ]
+    )
+    return response.choices[0].message.content
+
+# Streamlit UI
+st.title("🎙️ AI Voice Converter: Speech-to-Text & Text-to-Speech")
+st.write("Convert voice into text and generate AI-powered speech.")
+
+# Voice-to-Text Section
+st.subheader("🎤 Voice-to-Text")
+audio_file = st.file_uploader("Upload an audio file (WAV format)", type=["wav"])
+
+if audio_file:
+    with open("temp.wav", "wb") as f:
+        f.write(audio_file.getbuffer())
+    
+    st.audio(audio_file, format="audio/wav")
+    
+    if st.button("Transcribe Audio"):
+        transcribed_text = transcribe_audio("temp.wav")
+        st.write("**Transcribed Text:**", transcribed_text)
+
+        # AI insights
+        ai_insights = get_ai_response(transcribed_text)
+        st.write("**AI Analysis:**", ai_insights)
+
+# Text-to-Voice Section
+st.subheader("📝 Text-to-Speech")
+input_text = st.text_area("Enter text to convert into speech")
+
+if st.button("Generate Speech"):
+    if input_text.strip():
+        audio_path = text_to_speech(input_text)
+        
+        # Convert audio file to base64 for download
+        with open(audio_path, "rb") as f:
+            audio_bytes = f.read()
+        b64 = base64.b64encode(audio_bytes).decode()
+
+        # Audio player and download button
+        st.audio(audio_path, format="audio/mp3")
+        st.markdown(f'<a href="data:audio/mp3;base64,{b64}" download="output.mp3">Download Speech</a>', unsafe_allow_html=True)
+    else:
+        st.error("Please enter text to generate speech.")