Update app.py

app.py

@@ -1,8 +1,10 @@
 import requests
+import streamlit as st
+from llama_cpp import Llama
 import os
 
 print(os.getcwd())
-
+#===================Download Model==============================
 url = "https://huggingface.co/ngxson/DeepSeek-R1-Distill-Qwen-7B-abliterated-GGUF/resolve/main/DeepSeek-R1-Distill-Qwen-7B-abliterated-Q4_K_M.gguf?download=true"
 file_name = "DeepSeek-R1-Distill-Qwen-7B-abliterated-Q4_K_M.gguf"
 
@@ -16,14 +18,47 @@ if response.status_code == 200:
 else:
     print("Failed to download. Status code:", response.status_code)
 
-from llama_cpp import Llama
-# url = "https://huggingface.co/ngxson/DeepSeek-R1-Distill-Qwen-7B-abliterated-GGUF/DeepSeek-R1-Distill-Qwen-7B-abliterated-Q4_K_M.gguf"
-model_path = "DeepSeek-R1-Distill-Qwen-7B-abliterated-Q4_K_M.gguf"
+#==================================Streamlit App====================================
+# Set Streamlit page config
+st.set_page_config(page_title="Llama Chatbot", page_icon="🤖")
+
+# Model path (Ensure the model is in the correct directory)
+MODEL_PATH = file_name
+
+# Check if model exists, else download it
+if not os.path.exists(MODEL_PATH):
+    st.warning("Model not found! Please download it first.")
+    st.stop()
+
+# Load Llama model
+st.session_state["llm"] = Llama(model_path=MODEL_PATH)
+
+# Streamlit UI
+st.title("🤖 Llama GGUF Chatbot")
+
+if "messages" not in st.session_state:
+    st.session_state["messages"] = []
+
+# Display chat history
+for message in st.session_state["messages"]:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# User input
+user_input = st.chat_input("Type your message here...")
+
+if user_input:
+    # Display user message
+    st.session_state["messages"].append({"role": "user", "content": user_input})
+    with st.chat_message("user"):
+        st.markdown(user_input)
 
-# Load the model directly from URL
-llm = Llama(model_path=model_path)
+    # Generate response
+    with st.spinner("Thinking..."):
+        response = st.session_state["llm"](user_input)["choices"][0]["text"]
 
-# Generate a response
-output = llm("What is AI?")
-print(output)
+    # Display bot response
+    st.session_state["messages"].append({"role": "assistant", "content": response})
+    with st.chat_message("assistant"):
+        st.markdown(response)