Delete app1.py

app1.py

@@ -1,70 +0,0 @@
-import streamlit as st
-import speech_recognition as sr
-from pydub import AudioSegment
-import tempfile
-import os
-
-# Function to format text into SRT format
-def generate_srt(transcriptions):
-    srt_content = ""
-    for i, (start_time, end_time, text) in enumerate(transcriptions, 1):
-        start_srt = f"{int(start_time // 3600):02}:{int((start_time % 3600) // 60):02}:{int(start_time % 60):02},000"
-        end_srt = f"{int(end_time // 3600):02}:{int((end_time % 3600) // 60):02}:{int(end_time % 60):02},000"
-        srt_content += f"{i}\n{start_srt} --> {end_srt}\n{text}\n\n"
-    return srt_content
-
-st.title("🎙️ Audio to Text Transcription App (Google)")
-
-uploaded_file = st.file_uploader("Upload an audio file", type=["mp3", "wav", "m4a"])
-
-if uploaded_file is not None:
-    with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmpfile:
-        file_path = tmpfile.name
-        tmpfile.write(uploaded_file.read())
-
-    st.audio(uploaded_file, format="audio/wav")
-
-    # Convert to WAV
-    audio = AudioSegment.from_file(file_path)
-    audio = audio.set_frame_rate(16000).set_channels(1)
-    audio.export(file_path, format="wav")
-
-    recognizer = sr.Recognizer()
-    transcriptions = []
-    step = 5
-    with sr.AudioFile(file_path) as source:
-        duration = int(source.DURATION)  # Get total duration in seconds
-        
-        # Process in 5-second chunks
-        for i in range(0, duration, step):
-            source = sr.AudioFile(file_path)  # Reopen file for each iteration
-            with source as audio_source:
-                recognizer.adjust_for_ambient_noise(audio_source, duration=0.5)
-                audio_data = recognizer.record(audio_source, offset=i, duration=step)  # Use offset correctly
-            try:
-                text = recognizer.recognize_google(audio_data)
-                transcriptions.append((i, min(i + step, duration), text))  # Store chunk timestamps
-            except sr.UnknownValueError:
-                continue  # Skip if the chunk is not recognized
-            except sr.RequestError:
-                st.error("❌ Google API error. Check internet connection.")
-                break
-
-    # Generate SRT content
-    srt_text = generate_srt(transcriptions)
-
-    # Save SRT file
-    srt_path = file_path.replace(".wav", ".srt")
-    with open(srt_path, "w") as srt_file:
-        srt_file.write(srt_text)
-
-    st.success("✅ Transcription Complete!")
-    st.text_area("Transcribed Text:", "\n".join([t[2] for t in transcriptions]), height=200)
-
-    # Provide SRT file for download
-    with open(srt_path, "rb") as srt_file:
-        st.download_button("📥 Download SRT File", srt_file, file_name="transcription.srt", mime="text/plain")
-
-    # Clean up
-    os.remove(file_path)
-    os.remove(srt_path)