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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) |