Add application file

app.py

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+# Import the necessary libraries
+import streamlit as st
+from openai import OpenAI  # TODO: Install the OpenAI library using pip install openai
+
+st.title("Mini Project 2: Streamlit Chatbot")
+
+# TODO: Replace with your actual OpenAI API key
+openai_key = "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"
+client = OpenAI(api_key=openai_key)
+
+# Define a function to get the conversation history (Not required for Part-2, will be useful in Part-3)
+def get_conversation() -> str:
+    # return: A formatted string representation of the conversation.
+    conversation = ""
+    for message in st.session_state.messages:
+        role = message["role"]
+        content = message["content"]
+        conversation += f"{role}: {content}\n"
+    return conversation
+
+# Check for existing session state variables
+if "openai_model" not in st.session_state:
+    st.session_state["openai_model"] = "gpt-3.5-turbo"  # Initialize model
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []  # Initialize messages as an empty list
+
+# Display existing chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Wait for user input
+if prompt := st.chat_input("What would you like to chat about?"):
+    # Append user message to messages
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    # Display user message
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Generate AI response
+    with st.chat_message("assistant"):
+        # Send request to OpenAI API
+        response = client.chat.completions.create(
+            model=st.session_state["openai_model"],
+            messages=[{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]
+        )
+        ai_response = response.choices[0].message.content
+
+        # Display AI response
+        st.markdown(ai_response)
+
+    # Append AI response to messages
+    st.session_state.messages.append({"role": "assistant", "content": ai_response})