Upload 2 files

app.py

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+import pathlib
+import textwrap
+import streamlit as st
+import google.generativeai as genai
+from PIL import Image
+from IPython.display import Markdown
+from IPython.display import display
+
+genai.configure(api_key='AIzaSyA_XykKxC4aSi0af9VH5uP2eQlp9Nh25Ds')
+model = genai.GenerativeModel(model_name="models/gemini-pro-vision")
+
+def geminin_response(input,image,prompt):
+    response = model.generate_content([input,image[0],prompt])
+    return response.text
+
+st.set_page_config(page_title="Multi Language Text Extractor")
+st.header("Gemini Application")
+input = st.text_input("Input Query :",key='input')
+uploaded_file = st.file_uploader("Choose an image:",type=['.jpg','.pdf','.jpeg','png'])
+
+image=''
+if uploaded_file is not None:
+    format = ['.jpg','.jpeg','png']
+    for form in format:
+        if str(uploaded_file.name).endswith(form):
+            image = Image.open(uploaded_file)
+            st.image(image,caption='Uploaded Image!!!',use_column_width=True)
+        elif str(uploaded_file.name).endswith('.pdf'):
+            st.warning('Please Upload Images !!!', icon="⚠️")
+            break
+
+submit = st.button("Tell me about invoice")
+input_prompt = "We are uploading an image and you will have to answer any questions based on image"
+def input_image_details(uploaded_file):
+    bytes_data = uploaded_file.getvalue()
+    image_parts = [{
+        "mime_type":uploaded_file.type,
+        "data":bytes_data
+    }]
+    return image_parts
+if submit:
+    image_data = input_image_details(uploaded_file)
+    resp = geminin_response(input_prompt,image_data,input)
+    st.subheader("The Response is:")
+    st.write(resp)

requirements.txt

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+langchain
+openai
+huggingface_hub
+python-dotenv
+streamlit
+cassio 
+tiktoken
+datasets
+PyPDF2
+pypdf
+unstructured
+pinecone-client
+chromadb
+!pip3 install -q -U google-generativeai