generative_ai / src /page6.py
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import streamlit as st
# import openai
import replicate
import os
from dotenv import load_dotenv
from streamlit_extras.stylable_container import stylable_container
import streamlit_extras
# load_dotenv()
# REPLICATE_API_TOKEN = os.environ.get("REPLICATE_API_TOKEN")
os.environ['REPLICATE_API_TOKEN'] = 'r8_4fktoXrDGkgHY8uw1XlVtQJKQlAILKv0iBmPI'
replicate = replicate.Client(api_token='r8_4fktoXrDGkgHY8uw1XlVtQJKQlAILKv0iBmPI')
streamlit_style = """
<style>
#MainMenu {visibility: hidden;}
footer {visibility: hidden;}
video{width:200px;}
.css-1wbqy5l {visibility: hidden;}
.css-15zrgzn {visibility: hidden;}
.css-klqnuk {visibility: hidden;}
.en6cib64 {visibility: hidden;}
.css-1u4fkce {visibility: hidden;}
.en6cib62 {visibility: hidden;}
.css-19rxjzo, .ef3psqc11 {
background-color: purple;
text-color: white;
}
div.stButton > button:first-child {
background-color: darkgreen;
text-weight: bold;
}
</style>
"""
def page6():
with stylable_container(
key="title",
css_styles=[
""" span {
text-align: center;
padding-top: 0px;
padding-right: 0px;
padding-bottom: 0px;
padding-left: 0px;
}"""
,
"""
st-emotion-cache-0{
text-align: center;
padding-top: 0px;
padding-right: 0px;
padding-bottom: 0px;
padding-left: 0px;
}""",
"""
.e1f1d6gn0{
text-align: center;
padding-top: 0px;
padding-right: 0px;
padding-bottom: 0px;
padding-left: 0px;
}
""",
],
):
st.markdown("<h3>Image to Text</h3>", unsafe_allow_html=True) #This is under a css style
st.markdown(streamlit_style, unsafe_allow_html=True)
image_file=st.file_uploader("Select Image", type=['jpeg','jpg','png'])
if image_file is not None:
placeholder=st.empty()
col1,col2=placeholder.columns(2)
col1.text("Uploaded Image")
col1.image(image_file)
prompt = st.text_input(label='Ask question related to image')
submit_button = st.button(label='Requestion Answer')
if submit_button:
if prompt and (image_file is not None):
with st.spinner("Recognizing Image...."):
output = replicate.run(
"nateraw/video-llava:a494250c04691c458f57f2f8ef5785f25bc851e0c91fd349995081d4362322dd", input={
"image_path": image_file,
"text_prompt": prompt
}
)
print(output)
col2.text("Response")
col2.markdown(output)