Update app.py

app.py

@@ -1,42 +1,36 @@
 import streamlit as st
-from transformers import pipeline
-from pydub import AudioSegment
-import io
-
-# Load the audio classification pipeline
-audio_classification_pipeline = pipeline("audio-classification", model="MIT/ast-finetuned-audioset-10-10-0.4593")
-
-def convert_mp3_to_wav(audio_bytes):
-    # Convert MP3 bytes to WAV format
-    audio = AudioSegment.from_file(io.BytesIO(audio_bytes), format="mp3")
-    wav_bytes = audio.export(format="wav").read()
-    return wav_bytes
-
-def classify_audio(wav_bytes):
-    # Perform audio classification
-    results = audio_classification_pipeline(inputs=wav_bytes)
-    return results
-
-def main():
-    st.title('Hugging Face Audio Classification')
-
-    # File uploader for audio file
-    st.subheader('Upload Audio File:')
-    audio_file = st.file_uploader("Choose an MP3 file", type=["mp3"])
-
-    # Check if audio file is uploaded
-    if audio_file is not None:
-        st.audio(audio_file, format='audio/mp3')
-
-        # Button to classify audio
-        if st.button('Classify'):
-            with st.spinner('Classifying...'):
-                # Convert MP3 to WAV and classify
-                wav_bytes = convert_mp3_to_wav(audio_file.read())
-                results = classify_audio(wav_bytes)
-            st.success('Classification complete!')
-            st.write("Prediction:", results)
-
-if __name__ == '__main__':
-    main()
-
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import requests
+
+# Initialize the tokenizer and model
+tokenizer = AutoTokenizer.from_pretrained("PawanKrd/CosmosRP-8k")
+model = AutoModelForCausalLM.from_pretrained("PawanKrd/CosmosRP-8k")
+
+st.title("CosmosRP-8k Roleplay Chatbot")
+
+user_input = st.text_input("You:", "")
+
+if st.button("Generate Response"):
+    if user_input:
+        # Define the endpoint and payload
+        endpoint_url = "https://api.pawan.krd/cosmosrp/v1/chat/completions"
+        headers = {
+            "Content-Type": "application/json"
+        }
+        data = {
+            "model": "cosmosrp",
+            "messages": [
+                {"role": "system", "content": "You are a roleplay assistant."},
+                {"role": "user", "content": user_input}
+            ]
+        }
+        
+        # Make the request to the API
+        response = requests.post(endpoint_url, headers=headers, json=data)
+        result = response.json()
+        
+        # Extract and display the response
+        generated_response = result['choices'][0]['message']['content']
+        st.text_area("CosmosRP-8k:", generated_response)
+    else:
+        st.warning("Please enter some text.")