Create old2.py

old2.py

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+# app.py
+import streamlit as st
+from huggingface_hub import InferenceClient
+from datetime import datetime
+
+# Configure page
+st.set_page_config(
+    page_title="DeepSeek Chatbot - ruslanmv.com",
+    page_icon="🤖",
+    layout="centered",
+    initial_sidebar_state="expanded"
+)
+
+# Initialize session state
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Sidebar controls
+with st.sidebar:
+    st.title("🤖 Chatbot Settings")
+    st.markdown("Created by [ruslanmv.com](https://ruslanmv.com/)")
+    
+    # Model selection
+    selected_model = st.selectbox(
+        "Choose Model",
+        options=[
+            "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
+            "deepseek-ai/DeepSeek-R1",
+            "deepseek-ai/DeepSeek-R1-Zero"
+        ],
+        index=0
+    )
+    
+    # System message
+    system_message = st.text_area(
+        "System Message",
+        value="You are a friendly Chatbot created by ruslanmv.com",
+        height=100
+    )
+    
+    # Generation parameters
+    max_new_tokens = st.slider(
+        "Max new tokens",
+        min_value=1,
+        max_value=4000,
+        value=512,
+        step=50
+    )
+    
+    temperature = st.slider(
+        "Temperature",
+        min_value=0.1,
+        max_value=4.0,
+        value=1.0,
+        step=0.1
+    )
+    
+    top_p = st.slider(
+        "Top-p (nucleus sampling)",
+        min_value=0.1,
+        max_value=1.0,
+        value=0.9,
+        step=0.1
+    )
+    
+    # Optional HF Token
+    hf_token = st.text_input(
+        "HuggingFace Token (optional)",
+        type="password",
+        help="Enter your HuggingFace token if required for model access"
+    )
+
+# Main chat interface
+st.title("💬 DeepSeek Chatbot")
+st.caption("🚀 A conversational AI powered by DeepSeek models")
+
+# Display chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+        if "timestamp" in message:
+            st.caption(f"_{message['timestamp']}_")
+
+# Chat input and processing
+if prompt := st.chat_input("Type your message..."):
+    # Add user message to history
+    st.session_state.messages.append({
+        "role": "user",
+        "content": prompt,
+        "timestamp": datetime.now().strftime("%H:%M:%S")
+    })
+    
+    # Display user message
+    with st.chat_message("user"):
+        st.markdown(prompt)
+        st.caption(f"_{st.session_state.messages[-1]['timestamp']}_")
+
+    # Create full prompt with system message
+    full_prompt = f"{system_message}\n\nUser: {prompt}\nAssistant:"
+    
+    # Create client and generate response
+    client = InferenceClient(model=selected_model, token=hf_token)
+    
+    # Display assistant response
+    with st.chat_message("assistant"):
+        response = st.write_stream(
+            client.text_generation(
+                full_prompt,
+                max_new_tokens=max_new_tokens,
+                temperature=temperature,
+                top_p=top_p,
+                stream=True
+            )
+        )
+        timestamp = datetime.now().strftime("%H:%M:%S")
+        st.caption(f"_{timestamp}_")
+
+    # Add assistant response to history
+    st.session_state.messages.append({
+        "role": "assistant",
+        "content": response,
+        "timestamp": timestamp
+    })
+
+# Optional debug information
+# st.sidebar.markdown("---")
+# st.sidebar.json(st.session_state.messages)