File size: 3,362 Bytes
7d415c5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 |
""" 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})
|