Create app.py

app.py

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+import streamlit as st
+import os
+from openai import OpenAI
+
+
+class ChatBot:
+    def __init__(self):
+        self.client = OpenAI(api_key=os.environ["OPENAI_API_KEY"])
+        self.history = [{"role": "system", "content": "You are a helpful assistant."}]
+
+    def generate_response(self, prompt: str) -> str:
+        self.history.append({"role": "user", "content": prompt})
+        
+        completion = self.client.chat.completions.create(
+            model="gpt-4o",
+            messages=self.history
+        )
+        
+        response = completion.choices[0].message.content
+        self.history.append({"role": "assistant", "content": response})
+        
+        return response
+
+    def get_history(self) -> list:
+        return self.history
+
+
+st.set_page_config(layout="wide")
+st.title("OpenAI GPT-4o 🤖")
+
+
+with st.sidebar:
+    with st.expander("Instruction Manual"):
+        st.markdown("""
+            ## OpenAI GPT-4o 🤖 Chatbot
+            This Streamlit app allows you to chat with GPT-4o model.
+            ### How to Use:
+            1. **Input**: Type your prompt into the chat input box labeled "What is up?".
+            2. **Response**: The app will display a response from GPT-4o.
+            3. **Chat History**: Previous conversations will be shown on the app.
+            ### Credits:
+            - **Developer**: [Yiqiao Yin](https://www.y-yin.io/) | [App URL](https://huggingface.co/spaces/eagle0504/meta-llama) | [LinkedIn](https://www.linkedin.com/in/yiqiaoyin/) | [YouTube](https://youtube.com/YiqiaoYin/)
+            Enjoy chatting with Meta's Llama3 model!
+        """)
+
+    # Example:
+    st.success("Example: Explain what is supervised learning.")
+    st.success("Example: What is large language model?")
+    st.success("Example: How to conduct an AI experiment?")
+    st.success("Example: Write a tensorflow flow code with a 3-layer neural network model.")
+
+
+    # Add a button to clear the session state
+    if st.button("Clear Session"):
+        st.session_state.messages = []
+        st.session_state["bot"] = None
+        st.experimental_rerun()
+
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+
+# React to user input
+bot = ChatBot()
+if bot:
+    st.session_state["bot"] = bot
+
+
+if prompt := st.chat_input("😉 Ask any question or feel free to use the examples provided in the left sidebar."):
+
+    # Display user message in chat message container
+    st.chat_message("user").markdown(prompt)
+
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    # API Call
+    response = bot.generate_response("What is the weather like today?")
+
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+        st.markdown(response)
+    # Add assistant response to chat history
+    st.session_state.messages.append({"role": "assistant", "content": response})