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from openai import OpenAI
from mistralai import Mistral
from llamaapi import LlamaAPI
import streamlit as st
from IPython.display import display, Math
# Sidebar for model selection
with st.sidebar:
option = st.selectbox(
'Please select your model',
('o3-mini','o3','GPT-5','GPT-4o','GPT-4o-mini','GPT-4.1','o4-mini','Mixtral 8x7B','Mixtral 8x22B', 'Mistral Large 2','Mistral NeMo',
'Llama-3.1-405B','Llama-3.2-3B','Llama-3.3-70B'))
st.write('You selected:', option)
# API Key input
api_key = st.text_input("Please Copy & Paste your API_KEY", key="chatbot_api_key", type="password")
# Reset button
if st.button('Reset Conversation'):
st.session_state["messages"] = []
st.info("Please change your API_KEY if you change model.")
# Title and caption
st.title("💬 AI Chatbot")
st.caption("🚀 Your Personal AI Assistant powered by Streamlit and LLMs")
# Initialize messages if not present in session state
if 'messages' not in st.session_state:
st.session_state["messages"] = [{"role": "assistant", "content": "How can I help you?"}]
# Display messages
for msg in st.session_state.messages:
st.chat_message(msg["role"]).write(msg["content"])
# Chat input
if prompt := st.chat_input():
if not api_key:
st.info("Please add your API_KEY to go ahead.")
st.stop()
# Append user message to session state
st.session_state.messages.append({"role": "user", "content": prompt})
st.chat_message("user").write(prompt)
# Client initialization based on selected model
if option == 'Mixtral 8x7B':
client = Mistral(api_key=api_key)
response = client.chat.complete(model="open-mixtral-8x7b", messages=st.session_state.messages)
elif option == 'Mixtral 8x22B':
client = Mistral(api_key=api_key)
response = client.chat.complete(model="open-mixtral-8x22b", messages=st.session_state.messages)
elif option == 'Mistral Large 2':
client = Mistral(api_key=api_key)
response = client.chat.complete(model="mistral-large-2407", messages=st.session_state.messages)
elif option == 'Mathstral':
client = Mistral(api_key=api_key)
response = client.chat.complete(model="mistralai/mathstral-7B-v0.1", messages=st.session_state.messages)
elif option == 'Mistral NeMo':
client = Mistral(api_key=api_key)
response = client.chat.complete(model="open-mistral-nemo-2407", messages=st.session_state.messages)
elif option == 'o3-mini':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="o3-mini-2025-01-31", messages=st.session_state.messages)
elif option == 'o3':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="o3", messages=st.session_state.messages)
elif option == 'GPT-5':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="gpt-5-2025-08-07", messages=st.session_state.messages)
elif option == 'GPT-4o':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="gpt-4o", messages=st.session_state.messages)
elif option == 'GPT-4o-mini':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="gpt-4o-mini", messages=st.session_state.messages)
elif option == 'GPT-4.1':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="gpt-4-turbo-2024-04-09", messages=st.session_state.messages)
elif option == 'o4-mini':
client = OpenAI(api_key=api_key)
response = client.chat.completions.create(model="gpt-3.5-turbo", messages=st.session_state.messages)
elif option == 'Llama-3.1-405B':
client = OpenAI(api_key=api_key,base_url="https://api.llama-api.com")
response = client.chat.completions.create(model="llama3.1-405b", messages=st.session_state.messages, max_tokens=1000)
elif option == 'Llama-3.2-3B':
client = OpenAI(api_key=api_key,base_url="https://api.llama-api.com")
response = client.chat.completions.create(model="llama3.2-3b", messages=st.session_state.messages, max_tokens=1000)
elif option == 'Llama-3.3-70B':
client = OpenAI(api_key=api_key,base_url="https://api.llama-api.com")
response = client.chat.completions.create(model="llama3.3-70b", messages=st.session_state.messages, max_tokens=1000)
else:
st.error("Selected model is not supported.")
st.stop()
# Process response and update session state
msg = response.choices[0].message.content
st.session_state.messages.append({"role": "assistant", "content": msg})
st.chat_message("assistant").write(msg)
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