Hugging Face's logo

Spaces:
HemaAM
/
AI_Chat_Assistant
Runtime error

App Files Community
AI_Chat_Assistant
File size: 4,979 Bytes 
dd3e1e9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
7334a9d
dd3e1e9
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
 
import torch
from transformers import AutoModelForCausalLM, AutoTokenizer

def extract_responses(text):
    """
    Extracts and returns the responses from the text, excluding the parts
    between and including the [INST] tags.

    Args:
    text (str): The input text containing responses and [INST] tags.

    Returns:
    str: The extracted responses.
    """
    import re

    # Split the text by [INST] tags and accumulate non-tag parts
    parts = re.split(r'\[INST\].*?\[/INST\]', text, flags=re.DOTALL)
    cleaned_text = "".join(parts)

    # Return the cleaned and trimmed text
    return cleaned_text.strip()


def generate_html():
  
  return(
      '''
    <!DOCTYPE html>
    <html lang="en">
    <head>
        <meta charset="UTF-8">
        <meta name="viewport" content="width=device-width, initial-scale=1.0">
        <title>Your Gradio App</title>
        <style>
            @import url('https://fonts.googleapis.com/css2?family=Montserrat:wght@300;400&display=swap');

            body, html {
                margin: 0;
                padding: 0;
                font-family: 'Montserrat', sans-serif;
                background: #f9f9f9;
            }

            header {
                background-color: #e8f0fe;
                color: #333;
                text-align: center;
                padding: 40px 20px;
                border-radius: 0 0 25px 25px;
                background-image: linear-gradient(to right, #a7c7e7, #c0d8f0);
                box-shadow: 0 8px 16px 0 rgba(0,0,0,0.2);
                position: relative;
                overflow: hidden;
            }

            .background-shapes {
                position: absolute;
                top: 0;
                left: 0;
                right: 0;
                bottom: 0;
                background-image: linear-gradient(120deg, #a7c7e7 0%, #c0d8f0 100%);
                opacity: 0.6;
                animation: pulse 5s ease-in-out infinite alternate;
            }

            .header-content h1 {
                font-size: 2.8em;
                margin: 0;
            }

            .header-content p {
                font-size: 1.3em;
                margin-top: 20px;
            }

            @keyframes pulse {
                from { background-size: 100% 100%; }
                to { background-size: 110% 110%; }
            }
        </style>
    </head>
    <body>
        <header>
            <div class="background-shapes"></div>
            <div class="header-content">
                <h1>AI Assistant</h1>
                <p>This chatbot is an interactive application which leverages the power of a fine-tuned Phi 2 AI model to provide responses for the given queries. Type your query below and start chatting. </p>
            </div>
        </header>
        <!-- Rest of your Gradio app goes here -->
    </body>
    </html>

  ''')

def generate_footer():
  
  return(
      '''
    <!DOCTYPE html>
    <html lang="en">
    <head>
        <meta charset="UTF-8">
        <meta name="viewport" content="width=device-width, initial-scale=1.0">
        <title>Your Gradio App</title>
        <style>
            @import url('https://fonts.googleapis.com/css2?family=Roboto+Slab:wght@400;700&display=swap');

            body, html {
                margin: 0;
                padding: 0;
                font-family: 'Roboto Slab', serif;
                background: #f9f9f9;
            }

            header, footer {
                color: #333;
                text-align: center;
                padding: 40px 20px;
                border-radius: 25px;
                background: linear-gradient(120deg, #a7c7e7 0%, #c0d8f0 100%);
                background-size: 200% 200%;
                animation: gradientShift 8s ease-in-out infinite;
                position: relative;
                overflow: hidden;
            }

            .header-content, .footer-content {
                position: relative;
                z-index: 1;
            }

            .header-content h1, .footer-content p {
                font-size: 2.8em;
                margin: 0;
            }

            .header-content p, .footer-content p {
                font-size: 1.3em;
                margin-top: 20px;
            }

            @keyframes gradientShift {
                0% { background-position: 0% 50%; }
                50% { background-position: 100% 50%; }
                100% { background-position: 0% 50%; }
            }

            footer {
                margin-top: 40px;
                border-radius: 25px 25px 0 0;
            }
        </style>
    </head>
    <body>

    </body>
    </html>

  ''')



model = AutoModelForCausalLM.from_pretrained(
    "microsoft/phi-2",
    torch_dtype=torch.float32, 
    device_map="cpu",
    trust_remote_code=True
)
model.load_adapter('checkpoint-1100')


tokenizer = AutoTokenizer.from_pretrained('checkpoint-1100', trust_remote_code=True)
tokenizer.pad_token = tokenizer.eos_token