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import streamlit as st
import time
import os
import sys
from pathlib import Path
# Add the project root to the Python path
project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
if project_root not in sys.path:
sys.path.insert(0, project_root)
# Import model manager using absolute import
from src.models.model_manager import model_manager
# Set page config
st.set_page_config(
page_title="🤖 Agentic Browser",
page_icon="🤖",
layout="wide"
)
# Custom CSS for better styling
st.markdown("""
<style>
.stTextInput > div > div > input {
padding: 12px;
border-radius: 8px;
border: 1px solid #e0e0e0;
}
.stButton > button {
width: 100%;
border-radius: 8px;
padding: 8px 16px;
font-weight: 500;
}
.stMarkdown h1 {
color: #1f2937;
margin-bottom: 0.5em;
}
.stMarkdown h3 {
color: #374151;
margin-top: 1.5em;
}
</style>
""", unsafe_allow_html=True)
# Initialize session state
if 'messages' not in st.session_state:
st.session_state.messages = []
st.session_state.model_loaded = False
st.session_state.current_model = None
def load_model(model_name):
"""Load the selected model."""
try:
with st.spinner(f"Loading {model_name}..."):
model_manager.load_model(model_name)
st.session_state.model_loaded = True
st.session_state.current_model = model_name
st.success(f"Successfully loaded {model_name} model!")
return True
except Exception as e:
st.error(f"Error loading model: {str(e)}")
return False
def generate_response(prompt, model_name, temperature=0.7):
"""Generate a response using the selected model."""
try:
if not st.session_state.model_loaded or st.session_state.current_model != model_name:
if not load_model(model_name):
return "Error: Failed to load model."
# Generate response
response = model_manager.generate_text(
model_name=model_name,
prompt=prompt,
temperature=temperature,
max_length=1024
)
return response
except Exception as e:
return f"Error generating response: {str(e)}"
# Sidebar for settings
with st.sidebar:
st.title("⚙️ Settings")
# Model selection
selected_model = st.selectbox(
"Select Model",
["tiny-llama", "mistral-7b"],
index=0,
help="Select the model to use for text generation"
)
# Temperature slider
temperature = st.slider(
"Temperature",
min_value=0.1,
max_value=1.0,
value=0.7,
step=0.1,
help="Controls randomness in the response generation. Lower = more deterministic, Higher = more creative"
)
# Load model button
if st.button("🔄 Load Model"):
load_model(selected_model)
st.markdown("---")
st.markdown("### About")
st.markdown("""
**Agentic Browser** is an AI-powered web assistant that runs locally on your machine.
It uses open-source language models to provide helpful and contextual responses.
""")
st.markdown("---")
st.markdown("### Models")
st.markdown("""
- **TinyLlama**: Fast but less powerful (1.1B parameters)
- **Mistral-7B**: More powerful but requires more memory (7B parameters)
""")
# Main chat interface
st.title("🤖 Agentic Browser")
st.caption("Powered by local AI models")
# Display chat messages
for message in st.session_state.messages:
with st.chat_message(message["role"]):
st.markdown(message["content"])
# Chat input
if prompt := st.chat_input("Type your message here..."):
# Add user message to chat history
st.session_state.messages.append({"role": "user", "content": prompt})
# Display user message
with st.chat_message("user"):
st.markdown(prompt)
# Generate and display assistant response
with st.chat_message("assistant"):
message_placeholder = st.empty()
full_response = ""
# Generate response
response = generate_response(prompt, selected_model, temperature)
# Display response with streaming effect
for chunk in response.split():
full_response += chunk + " "
time.sleep(0.05)
message_placeholder.markdown(full_response + "▌")
message_placeholder.markdown(full_response)
# Add assistant response to chat history
st.session_state.messages.append({"role": "assistant", "content": full_response})
# Auto-scroll to bottom
st.experimental_rerun() |