Create app.py

app.py

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+import streamlit as st
+from transformers import pipeline
+
+model_id = "meta-llama/Meta-Llama-3-8B"
+
+# Initialize the model pipeline
+pipe = pipeline("text-generation", model=model_id)
+
+# Display the logo and title
+st.image("logo.jpg", width=300)
+st.title("Coach Virtual PRODI")
+
+# Initialize a session state variable for history if it doesn't exist
+if 'history' not in st.session_state:
+    st.session_state['history'] = []
+
+# Function to update the conversation history
+def update_history(user_input, ai_response):
+    st.session_state['history'].append(("User", user_input))
+    st.session_state['history'].append(("AI", ai_response))
+
+# Display the conversation history
+for speaker, text in st.session_state['history']:
+    if speaker == "User":
+        st.text_input("Usuario", value=text, disabled=True)
+    else:
+        st.text_area("PRODI", value=text, height=75, disabled=True)
+
+# Chat input for user prompt
+user_input = st.text_input("¿Cómo te puedo ayudar hoy?")
+if user_input:
+    with st.spinner("Generando respuesta..."):
+        # Get the AI's response
+        ai_response = pipe(user_input, max_length=100, num_return_sequences=1)[0]['generated_text']
+        
+        # Update the conversation history
+        update_history(user_input, ai_response)
+        
+        # Display the AI's response
+        st.write(ai_response)