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Browse files- .env +1 -0
- app.py +61 -0
- requirements.txt +4 -0
.env
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GOOGLE_API_KEY = "AIzaSyCbeXGU_7qWtmY6pXZoff-T_-aNli25x3Y"
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app.py
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from dotenv import load_dotenv
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import streamlit as st
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from pdf2image import convert_from_bytes
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import os
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import google.generativeai as genai
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from PIL import Image
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load_dotenv()
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genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
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def get_gemini_response(input,image,query=None):
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model = genai.GenerativeModel("gemini-pro-vision")
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if query is not None:
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response = model.generate_content([input,image,query])
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else:
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response = model.generate_content([input,image])
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return response.text
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def input_resumedata(uploaded_file):
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if uploaded_file is not None:
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pdf_bytes = uploaded_file.read()
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images = convert_from_bytes(pdf_bytes, first_page=1, last_page=1)
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return images[0]
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else:
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raise FileNotFoundError("No file uploaded")
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st.set_page_config(page_title="Resume Data Extractor")
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st.header("Resume Data")
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uploaded_file = st.file_uploader("Choose a file...", type=["pdf"])
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image_data = None
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if uploaded_file is not None:
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image_data = input_resumedata(uploaded_file)
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st.image(image_data, caption='Resume', use_column_width=True)
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query = st.text_input(label="What details you want from the resume?")
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query_button = st.button("Get Answer")
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submit = st.button("Extract all data")
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input_prompt = """
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You are a resume analyzer. You have to extract the data from the resume image.
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You will have to answer the questions based on the input resume image.
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"""
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if submit and image_data is not None:
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response = get_gemini_response(input_prompt,image_data)
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st.subheader("The response is:")
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st.write(response)
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if query_button and image_data is not None:
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response = get_gemini_response(input_prompt,image_data, query)
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st.subheader("The response is:")
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st.write(response)
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requirements.txt
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streamlit
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google-generativeai
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python-dotenv
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pdf2image
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