File size: 3,317 Bytes
16f50b1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
edbcbab
16f50b1
 
 
 
 
 
 
 
 
 
 
edbcbab
 
 
ba65023
 
c8a4d20
ba65023
edbcbab
 
 
 
 
 
 
 
 
 
 
d11c97f
a7601eb
edbcbab
3664602
edbcbab
 
 
 
 
 
 
 
16f50b1
 
de239da
16f50b1
 
 
 
edbcbab
16f50b1
 
edbcbab
16f50b1
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
edbcbab
16f50b1
 
edbcbab
16f50b1
 
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
from dotenv import load_dotenv
import os
import streamlit as st
from PIL import Image
from transformers import ViltProcessor, ViltForQuestionAnswering
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
from streamlit_extras.add_vertical_space import add_vertical_space
from langchain.llms import OpenAI

load_dotenv()

processor = ViltProcessor.from_pretrained("dandelin/vilt-b32-finetuned-vqa")
model = ViltForQuestionAnswering.from_pretrained("dandelin/vilt-b32-finetuned-vqa")

llm = OpenAI(temperature=0.2)
prompt = PromptTemplate(
    input_variables=["question", "elements"],
    template="""Please generate a structured response using the following information:
        \n\n
        #Question: {question}
        #Response: {elements}
        \n\n
        Your structured response:""",
)

def process_query(image, query):
    encoding = processor(image, query, return_tensors="pt")
    outputs = model(**encoding)
    logits = outputs.logits
    idx = logits.argmax(-1).item()
    chain = LLMChain(llm=llm, prompt=prompt)
    response = chain.run(question=query, elements=model.config.id2label[idx])
    return response

st.set_page_config(page_title="Insightly")
# Sidebar contents
with st.sidebar:
    st.sidebar.image("https://i.ibb.co/bX6GdqG/insightly-wbg.png", use_column_width=True)
    st.sidebar.markdown("<p class='sidebar-link'>๐Ÿ“ˆ <a href='https://insightly-csv-bot.hf.space/'>  CSV Bot</a></p>", unsafe_allow_html=True)
    st.sidebar.markdown("<p class='sidebar-link'>๐Ÿ“š  <a href='https://chandrakalagowda-demo2.hf.space/'>  PDF Bot </a></p>", unsafe_allow_html=True)
    st.sidebar.markdown("<p class='sidebar-link'>๐Ÿ“ธ  <a href='https://insightly-frame-capturer.hf.space/'>  Frame Capturer</a></p>", unsafe_allow_html=True)
    
    st.sidebar.markdown("<div class='vertical-space'></div>", unsafe_allow_html=True)

# Custom CSS to style the link and create vertical space
st.markdown(
    """
    <style>
    .image-container {
        margin-bottom: 60px;
    }
    .sidebar-link {
        display: flex;
        justify-content: left;
        font-size: 28px;
        margin-top: 20px;
        margin-left: 10px;
    }
    .vertical-space {
        height: 20px;
    }
    </style>
    """,
    unsafe_allow_html=True,
)

def main():
    st.title("Chat With Images ๐Ÿ–ผ๏ธ")

    uploaded_file = st.file_uploader('Upload your Image', type=['png', 'jpeg', 'jpg'])

    if uploaded_file is not None:
        
        image = Image.open(uploaded_file)
        st.image(image, caption='Uploaded Image.', width=300)
        
        cancel_button = st.button('Remove this image')
        if cancel_button:
            st.markdown(
                """<style>
                .css-2trqyj:focus,
                .css-2trqyj:active,
                .css-2trqyj:hover {
                outline: 2px solid red;
                outline-offset: 2px;
                }
                </style>""",
                unsafe_allow_html=True
            )
        query = st.text_input('Type your question here')

        if query:
            with st.spinner('Processing...'):
                answer = process_query(image, query)
                st.write(answer)
          
        if cancel_button:
            st.stop()
            
if __name__ == "__main__":
    main()