Hugging Face's logo

Spaces:
Atreyu4EVR
/
Multi-OpenSource
Sleeping

App Files Community
Multi-OpenSource
File size: 4,274 Bytes 
2d5272c
 
 
 
 
 
 
58785bd
2d5272c
 
 
 
 
 
 
 
 
b81ad51
 
2d5272c
 
 
 
 
 
 
11ad555
2d5272c
 
 
 
11ad555
2d5272c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f6e44c1
2d5272c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
2cee2f8
2d5272c
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
 
import numpy as np
import streamlit as st
from openai import OpenAI
import os
import sys
from dotenv import load_dotenv, dotenv_values
load_dotenv()


# initialize the client
client = OpenAI(
  base_url="https://api-inference.huggingface.co/v1",
  api_key=os.environ.get('HUGGINGFACEHUB_API_TOKEN')#"hf_xxx" # Replace with your token
) 

#Create supported models
model_links ={
    "Meta-Llama-3.1-8B": "meta-llama/Meta-Llama-3.1-8B-Instruct",
    "Mistral-7B-Instruct-v0.3": "mistralai/Mistral-7B-Instruct-v0.3"
}

#Pull info about the model to display
model_info ={
    "Meta-Llama-3.1-8B":
    {'description':"""The Llama (3.1) model is a **Large Language Model (LLM)** that's able to have question and answer interactions.\n \
        \nIt was created by the [**Meta's AI**](https://llama.meta.com/) team and has over  **8 billion parameters.** \n""",
    'logo':'BlueLogoBox.jpg'},
}


#Random dog images for error message
random_dog = ["BlueLogoBox.jpg"]


def reset_conversation():
    '''
    Resets Conversation
    '''
    st.session_state.conversation = []
    st.session_state.messages = []
    return 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) #Reset button

# Create model description
st.sidebar.write(f"You're now chatting with **{selected_model}**")
st.sidebar.markdown(model_info[selected_model]['description'])
st.sidebar.image(model_info[selected_model]['logo'])
st.sidebar.markdown("*Generated content may be inaccurate or false.*")

if "prev_option" not in st.session_state:
    st.session_state.prev_option = selected_model

if st.session_state.prev_option != selected_model:
    st.session_state.messages = []
    # st.write(f"Changed to {selected_model}")
    st.session_state.prev_option = selected_model
    reset_conversation()

#Pull in the model we want to use
repo_id = model_links[selected_model]

st.subheader(f'Demo Chatbot')
# st.title(f'ChatBot Using {selected_model}')

# Set a default model
if selected_model not in st.session_state:
    st.session_state[selected_model] = model_links[selected_model] 

# 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"Liahona.AI powered by {selected_model}."):

    # 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_links[selected_model],
                messages=[
                    {"role": m["role"], "content": m["content"]}
                    for m in st.session_state.messages
                ],
                temperature=temp_values,#0.5,
                stream=True,
                max_tokens=3000,
            )
    
            response = st.write_stream(stream)

        except Exception as e:
            # st.empty()
            response = "šŸ˜µā€šŸ’« 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 šŸ¶:"
            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})