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import requests
import os
import json
import streamlit as st
from datetime import datetime
import pickle
# Page configuration
st.set_page_config(
page_title="AI Assistant",
page_icon="π¬",
initial_sidebar_state="collapsed"
)
# White background
st.markdown("""
<style>
.stApp {
background: white;
}
.main .block-container {
max-width: 800px;
}
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
header {visibility: hidden;}
.stDeployButton {display: none;}
</style>
""", unsafe_allow_html=True)
# File to store chat history
HISTORY_FILE = "chat_history.json"
def load_chat_history():
"""Load chat history from file"""
try:
if os.path.exists(HISTORY_FILE):
with open(HISTORY_FILE, 'r', encoding='utf-8') as f:
return json.load(f)
except Exception as e:
st.error(f"Error loading chat history: {e}")
return []
def save_chat_history(messages):
"""Save chat history to file"""
try:
with open(HISTORY_FILE, 'w', encoding='utf-8') as f:
json.dump(messages, f, ensure_ascii=False, indent=2)
except Exception as e:
st.error(f"Error saving chat history: {e}")
def clear_chat_history():
"""Clear chat history file"""
try:
if os.path.exists(HISTORY_FILE):
os.remove(HISTORY_FILE)
st.session_state.messages = []
except Exception as e:
st.error(f"Error clearing chat history: {e}")
# Initialize session state with saved history
if "messages" not in st.session_state:
st.session_state.messages = load_chat_history()
# Get API key
OPENROUTER_API_KEY = os.environ.get("OPENROUTER_API_KEY")
@st.cache_data(ttl=300)
def check_api_status():
if not OPENROUTER_API_KEY:
return "No API Key"
try:
url = "https://openrouter.ai/api/v1/models"
headers = {"Authorization": f"Bearer {OPENROUTER_API_KEY}"}
response = requests.get(url, headers=headers, timeout=5)
return "Connected" if response.status_code == 200 else "Error"
except:
return "Error"
def get_ai_response(messages, model="openai/gpt-3.5-turbo"):
if not OPENROUTER_API_KEY:
return "No API key found. Please add OPENROUTER_API_KEY to environment variables."
url = "https://openrouter.ai/api/v1/chat/completions"
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENROUTER_API_KEY}"
}
api_messages = [{"role": "system", "content": "You are a helpful AI assistant. Provide clear and helpful responses."}]
api_messages.extend(messages)
data = {
"model": model,
"messages": api_messages,
"stream": True,
"max_tokens": 1000,
"temperature": 0.7
}
try:
response = requests.post(url, headers=headers, json=data, stream=True, timeout=30)
response.raise_for_status()
full_response = ""
for line in response.iter_lines():
if line:
line_str = line.decode('utf-8')
if line_str.startswith('data: '):
line_str = line_str[6:]
if line_str.strip() == '[DONE]':
break
try:
data = json.loads(line_str)
if 'choices' in data and len(data['choices']) > 0:
delta = data['choices'][0].get('delta', {})
if 'content' in delta:
full_response += delta['content']
yield full_response
except json.JSONDecodeError:
continue
except Exception as e:
yield f"Sorry, I encountered an error. Please try again."
# Header
st.title("AI Assistant")
st.caption("Ask me anything")
# Sidebar
with st.sidebar:
st.header("Settings")
# API Status
status = check_api_status()
if status == "Connected":
st.success("API Connected")
elif status == "No API Key":
st.error("No API Key")
else:
st.warning("Connection Issue")
st.divider()
# Model selection
models = [
"openai/gpt-3.5-turbo",
"openai/gpt-4",
"anthropic/claude-3-haiku",
"google/gemini-pro",
"meta-llama/llama-3.1-8b-instruct:free",
"meta-llama/llama-3.1-70b-instruct:free",
"meta-llama/llama-3.2-3b-instruct:free",
"meta-llama/llama-3.2-1b-instruct:free",
"qwen/qwen-2-7b-instruct:free",
"microsoft/phi-3-medium-4k-instruct:free",
"microsoft/phi-3-mini-128k-instruct:free",
"huggingface/zephyr-7b-beta:free",
"openchat/openchat-7b:free",
"gryphe/mythomist-7b:free",
"undi95/toppy-m-7b:free",
"openrouter/auto"
]
selected_model = st.selectbox("Model", models, index=0)
st.divider()
# Chat History Controls
st.header("Chat History")
# Show number of messages
if st.session_state.messages:
st.info(f"Messages stored: {len(st.session_state.messages)}")
# Auto-save toggle
auto_save = st.checkbox("Auto-save messages", value=True)
# Manual save/load buttons
col1, col2 = st.columns(2)
with col1:
if st.button("Save History", use_container_width=True):
save_chat_history(st.session_state.messages)
st.success("History saved!")
with col2:
if st.button("Load History", use_container_width=True):
st.session_state.messages = load_chat_history()
st.success("History loaded!")
st.rerun()
st.divider()
# View History
if st.button("View History File", use_container_width=True):
if os.path.exists(HISTORY_FILE):
with open(HISTORY_FILE, 'r', encoding='utf-8') as f:
history_content = f.read()
st.text_area("Chat History (JSON)", history_content, height=200)
else:
st.warning("No history file found")
# Download History
if os.path.exists(HISTORY_FILE):
with open(HISTORY_FILE, 'rb') as f:
st.download_button(
label="Download History",
data=f.read(),
file_name=f"chat_history_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json",
mime="application/json",
use_container_width=True
)
st.divider()
# Clear controls
if st.button("Clear Chat", use_container_width=True, type="secondary"):
clear_chat_history()
st.success("Chat cleared!")
st.rerun()
# Show welcome message when no messages
if not st.session_state.messages:
st.info("How can I help you today?")
# 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("Ask anything..."):
# Add user message
user_message = {"role": "user", "content": prompt}
st.session_state.messages.append(user_message)
# Auto-save if enabled
if auto_save:
save_chat_history(st.session_state.messages)
# Display user message
with st.chat_message("user"):
st.markdown(prompt)
# Get AI response
with st.chat_message("assistant"):
placeholder = st.empty()
full_response = ""
for response in get_ai_response(st.session_state.messages, selected_model):
full_response = response
placeholder.markdown(full_response + "β")
placeholder.markdown(full_response)
# Add AI response to messages
assistant_message = {"role": "assistant", "content": full_response}
st.session_state.messages.append(assistant_message)
# Auto-save if enabled
if auto_save:
save_chat_history(st.session_state.messages) |