File size: 4,538 Bytes
f60b836
 
 
b01623b
f60b836
 
 
 
 
 
 
 
 
 
 
 
 
e4809e4
 
 
 
f60b836
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b01623b
 
 
f60b836
b01623b
 
 
f60b836
b01623b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f60b836
 
 
 
 
 
 
 
 
 
b01623b
 
f60b836
 
 
 
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
import logging
import os
import PIL
import requests
import streamlit as st
import google.generativeai as genai

from dotenv import load_dotenv


logging.basicConfig(
    level=logging.DEBUG,
    format='%(asctime)s - %(message)s',
)

SUPPORTED_FILE_EXTENSIONS = ['png', 'jpg', 'jpeg']
IMAGE_PROMPT = (
    # 'You are a systems expert.'
    ' The provided image relates to a system.'
    # ' Refuse to answer if the provided image is not related to any system or software in any way.'
    ' The system\'s image could be of any type, such as architecture diagram, flowchart, state machine, and so on.'
    ' Based SOLELY on the image, describe the system and its different components in detail.'
    ' You should not use any prior knowledge except for universal truths.'
    ' If relevant, describe how the relevant components interact and how information flows.'
    ' In case the image contains or relates to anything inappropriate'
    ' including, but not limited to, violence, hatred, malice, and criminality,'
    ' DO NOT generate an answer and simply say that you are not allowed to describe.'
)

GENERATION_CONFIG = {
    "temperature": 0.9,
    "top_p": 1,
    "top_k": 1,
    "max_output_tokens": 2048,
}
SAFETY_SETTINGS = [
    {
        "category": "HARM_CATEGORY_HARASSMENT",
        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
    },
    {
        "category": "HARM_CATEGORY_HATE_SPEECH",
        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
    },
    {
        "category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
    },
    {
        "category": "HARM_CATEGORY_DANGEROUS_CONTENT",
        "threshold": "BLOCK_MEDIUM_AND_ABOVE"
    }
]


@st.cache_resource
def get_gemini_model():
    """
    Get the Gemini Pro Vision model.

    :return: The model
    """

    return genai.GenerativeModel(
        model_name='gemini-pro-vision',
        generation_config=GENERATION_CONFIG,
        safety_settings=SAFETY_SETTINGS
    )


def get_image_description(image: PIL.Image) -> str:
    """
    Use Gemini Pro Vision LMM to generate a response.

    :param image: The image to use
    :return: The description based on the image
    """

    model = get_gemini_model()
    response = model.generate_content([IMAGE_PROMPT, image], stream=False).text
    # print(f'> {response=}')

    return response


# The page
load_dotenv()
genai.configure(api_key=os.getenv('GOOGLE_API_KEY'))

st.title('Sys2Doc: Generate Documentation Based on System Diagram')

uploaded_file = st.file_uploader(
    'Choose an image file (PNG, JPG, or JPEG) that depicts your system,'
    ' for example, architecture, state machine, flow diagram, and so on',
    type=SUPPORTED_FILE_EXTENSIONS
)

st.write('OR provide the URL of the image:')
img_url = st.text_input('URL of the image')
st.markdown('(*If an image is uploaded and a URL is also provided, Sys2Doc will consider the uploaded image*)')

if uploaded_file is not None or (img_url is not None and len(img_url) > 0):
    # Show the uploaded image & related info
    print(f'{img_url=}')
    try:
        if uploaded_file:
            the_img = PIL.Image.open(uploaded_file)
            file_details = {
                'file_name': uploaded_file.name,
                'file_type': uploaded_file.type,
                'file_size': uploaded_file.size
            }
        elif img_url:
            the_img = PIL.Image.open(requests.get(img_url, stream=True).raw)
            file_details = {
                'file_name': os.path.basename(img_url),
                'file_type': the_img.format,
                'file_info': the_img.info
            }

        if the_img.mode in ('RGBA', 'P'):
            the_img = the_img.convert('RGB')

        st.header('Image')
        st.write(file_details)

        st.image(the_img, width=250)
        description = get_image_description(the_img)
        st.header('Description')
        st.write(description)
        logging.debug(description)
        logging.info('Done!')
    except PIL.UnidentifiedImageError as uie:
        st.error(f'An error occurred while loading the image: {uie}')
        logging.debug(f'An error occurred while loading the image: {uie}\n'
                      f'File details: {file_details}')
    except requests.exceptions.MissingSchema as ms:
        st.error(f'Please specify a proper URL for the image.')
    finally:
        st.divider()
        st.write('Sys2Doc is an experimental prototype, with no guarantee provided whatsoever.'
                 ' Use it fairly, responsibly, and with care.')