Cv / app.py
Pezh's picture
Update app.py
f1f3052
raw
history blame
2.22 kB
import streamlit as st
from PIL import Image
import google.generativeai as genai
from googletrans import Translator, LANGUAGES
#def translate_to_persian(text):
# Instantiate the Translator object
translator = Translator()
# Translate the text
#translation = translator.translate(text, src='en', dest='fa')
#return translation.text
genai.configure(api_key="AIzaSyBd36RWeqDpLur3E7TTlX3wnyIh_rdhsU8")
# Set up the model
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"
},
]
text_input = st.text_input('Enter some text')
model = genai.GenerativeModel(model_name="gemini-pro",
generation_config=generation_config,
safety_settings=safety_settings)
prompt_parts = [text_input]
response = model.generate_content(prompt_parts)
#to_markdown(response.text)
# Set up the title of the app
st.title('Simple Streamlit App')
# File uploader to allow users to upload images
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
mod = genai.GenerativeModel('gemini-pro-vision')
#res.resolve()
# Display the uploaded image
if uploaded_file is not None:
image = Image.open(uploaded_file)
res = mod.generate_content(["" + text_input, image], stream=True)
res.resolve()
#st.image(image, caption='Uploaded Image', use_column_width=True)
# Button to print "Hey you"
if st.button('Hey Button'):
st.write(res.text)
# Text input
#text_input = st.text_input('Enter some text')
# Button to print the text from input
if st.button('Print Text'):
st.write(translator.translate(response.text, src='en', dest='fa').text)#translate_to_persian("Hello, how are you?"))#response.text))
# Run this with `streamlit run your_script.py`