Create app.py

app.py

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+import streamlit as st
+from PIL import Image
+from phi.agent import Agent
+from phi.model.google import Gemini
+from phi.tools.firecrawl import FirecrawlTools
+import google.generativeai as genai
+from google.generativeai import upload_file,get_file
+import io
+import base64
+
+import time
+from pathlib import Path
+import tempfile
+
+from dotenv import load_dotenv
+load_dotenv()
+
+import os
+
+API_KEY = os.getenv("GOOGLE_API_KEY")
+if API_KEY:
+    genai.configure(api_key=API_KEY)
+
+# Page Configuration
+
+st.set_page_config(
+    page_title="AI Shopping Partner",
+    page_icon="🤖🛍️",
+    layout="centered"
+)
+
+st.title("AI Shopping Partner")
+st.header("Powered by Agno and Google Gemini")
+#st.cache_resource
+
+def get_gemini_response(api_key,prompt,image):   
+    model=genai.GenerativeModel(model_name="gemini-2.0-flash-exp")
+    response= model.generate_content([prompt,image])
+    return response.text
+
+def initialize_agent():
+    return Agent(
+
+        name="Shopping Partner",
+        model=Gemini(id="gemini-2.0-flash-exp"),  
+        instructions=[
+            "You are a product recommender agent specializing in finding products that match user preferences.",
+            "Prioritize finding products that satisfy as many user requirements as possible, but ensure a minimum match of 50%.",
+            "Search for products only from authentic and trusted e-commerce websites such as Google Shopping, Amazon, Flipkart, Myntra, Meesho, Nike, and other reputable platforms.",
+            "Verify that each product recommendation is in stock and available for purchase.",
+            "Avoid suggesting counterfeit or unverified products.",
+            "Clearly mention the key attributes of each product (e.g., price, brand, features) in the response.",
+            "Format the recommendations neatly and ensure clarity for ease of user understanding.",
+        ],
+        tools=[FirecrawlTools()],
+        markdown=True
+        )
+
+#Initialize the Agent
+multimodal_Agent = initialize_agent()
+
+# Define acceptable file types and MIME types
+accepted_mime_types = ["image/jpeg", "image/png"]
+
+#File Uploader
+image_file = st.file_uploader("Upload a image File to Analyse and provide relevant shopping links",type=["jpg","jpeg","png"],help="Upload max 200mb image for AI Analysis")
+image= None
+
+#Prompt
+prompt= "What is in this photo?"
+
+
+
+if image_file is not None:
+    # Convert the uploaded file into a BytesIO stream
+    #image_stream = io.BytesIO(image_file.read())
+    image = Image.open(image_file)
+    
+    try:
+        # Open the image using PIL
+        #image = Image.open(image_stream)  
+
+        # Display the image in Streamlit
+        st.image(image, caption="Uploaded Image", use_container_width=False,width=400)
+        with st.spinner("AI is processing this image and gathering insights..."):
+            response= get_gemini_response(API_KEY,prompt,image)
+            st.write(f"Product Identified using AI: {response}")
+
+    except Exception as e:
+        st.error(f"Error: Unable to open image. {e}")
+
+    # Specify the mime_type if Streamlit cannot auto-detect
+    #mime_type = image_file.type
+
+    #if mime_type:
+        #st.write(f"File MIME type detected: {mime_type}")
+        # Proceed with file processing
+    #else:
+        #st.error("Could not determine MIME type for the uploaded file. Please upload a valid file.")
+
+    #if mime_type in accepted_mime_types:
+        #st.write(f"File uploaded: {image_file.name}")
+        # Process the file as needed
+    #else:
+        #st.error(f"Unsupported file type: {mime_type}")
+
+
+
+    #prompt= st.text_input("Input prompt(e.g., 'What is in this photo?'):",key="input")
+    promptColor= st.text_input("'What Color you are looking for?'",key="inputcolor")
+    promptPurpose= st.text_input("'For what purpose you are looking for this product?'",key="inputpurpose")
+    promptBudget= st.text_input("'What is your budget?'",key="inputbudget")
+    
+    
+
+    user_query= st.text_area("What specific insights are you looking for from the image?",                 
+                 placeholder="Ask any questions related to the image content. The AI agent will analyze and gather more context if necessary",
+                 help="Share the specific questions or details you want to explore from the image."
+                 )
+    
+    if st.button("Search this Product",key="analyse_image_button"):
+        if not user_query:
+            st.warning("Please enter a query to analyse this image")
+        else:
+            try:
+                with st.spinner("AI is Processing this image and gathering insights..."):
+
+                    #Upload and process the video file
+                    #processed_image = upload_file(image_path)                                      
+                    #st.write(f"processed_image: {processed_image}")
+
+                    response= get_gemini_response(API_KEY,prompt,image)
+                    #st.write(f"Product Identified: {response}")
+
+                    
+
+                    #Prompt generation for Analysis
+                    analysis_prompt =(
+                        f"""
+                        I am looking for 
+                        {response}
+                        with the below preferences: 
+                        {promptColor} 
+                        {promptPurpose}
+                        {promptBudget}
+                        Can you provide recommendations. Always make sure that you provide hyperlinks to the product.
+                        {user_query}
+                        """
+                )
+
+                    #AI Agent Processing
+                    response = multimodal_Agent.run(analysis_prompt,image=image)
+
+                    # multimodal_Agent.print_response(
+                    # "I am looking for running shoes with the following preferences: Color: Black Purpose: Comfortable for long-distance running Budget: Under Rs. 10,000. Can you provide recommendations. Also provide links to the product. Search in Myntra"
+                    # )
+
+                #Display the result
+                st.subheader("Relevant search links for the product")
+                st.markdown(response.content)
+                #st.write(response)
+
+            except Exception as error:
+                st.error(f"An error occured during analysis:{error}")
+            finally:
+                #Clean up temporary video file
+                # Path(image_path).unlink(missing_ok=True)
+                st.info("Clean up temporary image file")
+    #else:
+        #st.info("Upload a image file to start the Analysis")
+    
+        #Customize text area height
+    st.markdown(
+        """
+        <style>
+        .stTextArea textarea{
+            height:100px;   
+        }
+        </style>
+        """,
+        unsafe_allow_html=True
+
+    )