Update app.py

app.py

@@ -1,51 +1,22 @@
 import streamlit as st
-import sounddevice as sd
-import soundfile as sf
-from faster_whisper import WhisperModel
-import io
-import os
 from langchain_community.llms import Ollama
-import pyttsx3
-# Set environment variable to handle duplicate libraries
-os.environ["KMP_DUPLICATE_LIB_OK"] = "TRUE"
 
-# Initialize WhisperModel and Ollama
-model_size = "base.en"
-model = WhisperModel(model_size, device="cpu", compute_type="int8", num_workers=5)
+# Initialize the language model
 llm = Ollama(model="tinyllama")
 
-# Initialize text-to-speech engine
-engine = pyttsx3.init('sapi5')
-voices = engine.getProperty('voices')
-engine.setProperty('voice',voices[0].id)
-engine.setProperty('rate',180)
+# Streamlit UI elements
+st.title("Language Model Invocation")
+st.write("Enter a prompt to get a response from the language model.")
 
-def speak(audio):
-    engine.say(audio)
-    engine.runAndWait()
+# Text input for prompt
+prompt = st.text_input("Enter a prompt:")
 
-# Record and transcribe audio
-audio_data = st.audio("recorded_audio.wav", format="audio/wav", start_time=0)
-if st.button("Record"):
-    with st.spinner("Recording..."):
-        recorded_audio = sd.rec(int(5 * 44100), samplerate=44100, channels=2, dtype="int16")
-        sd.wait()
-        sf.write("recorded_audio.wav", recorded_audio, samplerate=44100)
-
-    st.audio("recorded_audio.wav", format="audio/wav", start_time=0)
-
-    # Transcribe audio and speak response
-    with open("recorded_audio.wav", "rb") as audio_file:
-        segments,info= model.transcribe(io.BytesIO(audio_file.read()), beam_size=10)
-    for segment in segments:
-        prompt=segment.text
-        print(prompt)
-        st.text(prompt)
+# Button to invoke the model
+if st.button("Submit"):
     if prompt:
+        # Generate the response
         response = llm.invoke(prompt)
-        st.success("Response: " + response)
-        speak(response)
-        st.stop()
+        st.write("Response:")
+        st.write(response)
     else:
-        st.error("Failed to transcribe audio.")
-    
+        st.write("Please enter a prompt.")