Upload 2_chatbot.py

pages/2_chatbot.py

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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)
+
+    
+    
+