Create app2.py

app2.py

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+""" Simple Chatbot
+@author: Nigel Gebodh
+@email: [email protected]
+"""
+import numpy as np
+import streamlit as st
+from openai import OpenAI
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Initialize the client
+client = OpenAI(
+    base_url="https://api-inference.huggingface.co/v1",
+    api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')  # Replace with your token
+)
+
+# Define Llama 3 model
+model_link = "meta-llama/Meta-Llama-3-8B-Instruct"
+model_info = {
+    'description': """The Llama (3) model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n 
+                      It was created by the [**Meta's AI**](https://llama.meta.com/) team and has over **8 billion parameters.** \n""",
+    'logo': 'Llama_logo.png'
+}
+
+# Random dog images for error message
+random_dog = ["0f476473-2d8b-415e-b944-483768418a95.jpg",
+              "1bd75c81-f1d7-4e55-9310-a27595fa8762.jpg",
+              "526590d2-8817-4ff0-8c62-fdcba5306d02.jpg",
+              "1326984c-39b0-492c-a773-f120d747a7e2.jpg"]
+
+def reset_conversation():
+    '''Resets Conversation'''
+    st.session_state.conversation = []
+    st.session_state.messages = []
+    return None
+
+# Create a temperature slider
+temp_values = st.sidebar.slider('Select a temperature value', 0.0, 1.0, (0.5))
+
+# Add reset button to clear conversation
+st.sidebar.button('Reset Chat', on_click=reset_conversation)  # Reset button
+
+# Create model description
+st.sidebar.write(f"You're now chatting with **Llama 3**")
+st.sidebar.markdown(model_info['description'])
+st.sidebar.image(model_info['logo'])
+st.sidebar.markdown("*Generated content may be inaccurate or false.*")
+st.sidebar.markdown("\nRun into issues? \nTry again later as GPU access might be limited.")
+
+# 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"])
+
+# Accept user input
+if prompt := st.chat_input(f"Hi, I'm Llama 3, ask me a question"):
+
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+
+    # Display assistant response in chat message container
+    with st.chat_message("assistant"):
+
+        try:
+            stream = client.chat.completions.create(
+                model=model_link,
+                messages=[
+                    {"role": m["role"], "content": m["content"]}
+                    for m in st.session_state.messages
+                ],
+                temperature=temp_values,
+                stream=True,
+                max_tokens=3000,
+            )
+    
+            response = st.write_stream(stream)
+
+        except Exception as e:
+            response = "😵‍💫 Looks like something went wrong! Try again later.\nHere's a random pic of a 🐶:"
+            st.write(response)
+            random_dog_pick = 'https://random.dog/' + random_dog[np.random.randint(len(random_dog))]
+            st.image(random_dog_pick)
+            st.write("This was the error message:")
+            st.write(e)
+
+    st.session_state.messages.append({"role": "assistant", "content": response})