File size: 5,313 Bytes
2991a67 9c31040 2991a67 9c31040 2991a67 |
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 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 |
import numpy as np
import streamlit as st
from openai import OpenAI
import os
import json
from dotenv import load_dotenv
load_dotenv()
# Initialize the client
client = OpenAI(
base_url=os.environ.get('BASE_URL'), # Fetch base_url from environment variables
api_key=os.environ.get('API_KEY') # Fetch API key from environment variables
)
# Create supported models
model_links = {
"Mixtral-8x7B-Instruct-v0.1": "mistralai/Mixtral-8x7B-Instruct-v0.1",
}
# 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",
"42a98d03-5ed7-4b3b-af89-7c4876cb14c3.jpg",
"8b3317ed-2083-42ac-a575-7ae45f9fdc0d.jpg",
"ee17f54a-83ac-44a3-8a35-e89ff7153fb4.jpg",
"027eef85-ccc1-4a66-8967-5d74f34c8bb4.jpg",
"08f5398d-7f89-47da-a5cd-1ed74967dc1f.jpg",
"0fd781ff-ec46-4bdc-a4e8-24f18bf07def.jpg",
"0fb4aeee-f949-4c7b-a6d8-05bf0736bdd1.jpg",
"6edac66e-c0de-4e69-a9d6-b2e6f6f9001b.jpg",
"bfb9e165-c643-4993-9b3a-7e73571672a6.jpg"
]
history_file = 'chat_histories.json'
def load_history():
if os.path.exists(history_file):
with open(history_file, 'r') as f:
return json.load(f)
return {}
def save_history(histories):
with open(history_file, 'w') as f:
json.dump(histories, f)
def reset_conversation():
'''
Resets Conversation
'''
st.session_state.messages = []
st.session_state.current_chat_name = None
return None
# Set up the Streamlit page configuration
st.set_page_config(page_icon="π", layout="wide", page_title="GPT-CHATBOT.ru")
# Display the header
st.title("GPT-CHATBOT.ru")
# Initialize session state attributes
if "messages" not in st.session_state:
st.session_state.messages = []
if "chat_histories" not in st.session_state:
st.session_state.chat_histories = load_history()
if "current_chat_name" not in st.session_state:
st.session_state.current_chat_name = None
# Define the available models
models = [key for key in model_links.keys()]
# Create the sidebar with the dropdown for model selection
selected_model = st.sidebar.selectbox("Select Model", models)
# 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)
# Create a chat history dropdown
chat_history = st.sidebar.selectbox("Select Chat History", ["Current Chat"] + list(st.session_state.chat_histories.keys()))
if chat_history != "Current Chat":
st.session_state.messages = st.session_state.chat_histories[chat_history]
else:
if selected_model not in st.session_state:
st.session_state[selected_model] = model_links[selected_model]
# Create a system prompt input
system_prompt = st.sidebar.text_input("System Prompt", value="", help="Optional system prompt for the chat model.")
# Display chat messages from history on app rerun
for message in st.session_state.messages:
avatar = "π" if message["role"] == "assistant" else "π§βπ»"
with st.chat_message(message["role"], avatar=avatar):
st.markdown(message["content"])
# Accept user input
if prompt := st.chat_input(f"Hi I'm {selected_model}, ask me a question"):
with st.chat_message("user", avatar="π§βπ»"):
st.markdown(prompt)
st.session_state.messages.append({"role": "user", "content": prompt})
try:
# Construct the list of messages with an optional system prompt
messages = [{"role": m["role"], "content": m["content"]} for m in st.session_state.messages]
if system_prompt:
messages.insert(0, {"role": "system", "content": system_prompt})
# Make the API request
stream = client.chat.completions.create(
model=model_links[selected_model],
messages=messages,
temperature=temp_values,
stream=True,
max_tokens=3000,
)
response = st.write_stream(stream)
except Exception as e:
response = "π΅βπ« Looks like someone unplugged something!\
\n Either the model space is being updated or something is down.\
\n\
\n Try again later. \
\n\
\n Here's a random pic of a πΆ:"
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})
# Automatically name and save chat history
if not st.session_state.current_chat_name:
st.session_state.current_chat_name = f"Chat_{len(st.session_state.chat_histories) + 1}"
st.session_state.chat_histories[st.session_state.current_chat_name] = st.session_state.messages
save_history(st.session_state.chat_histories)
st.sidebar.write(f"You're now chatting with **{selected_model}**")
st.sidebar.markdown("*Generated content may be inaccurate or false.*")
st.sidebar.markdown("\n[TypeGPT](https://typegpt.net).")
|