Upload 3 files

app.py

@@ -0,0 +1,86 @@
+# 1. Imports and API setup
+from groq import Groq
+import base64
+import streamlit as st
+import pandas as pd
+
+client = Groq(
+    api_key="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",
+)
+
+llava_model = 'llava-v1.5-7b-4096-preview'
+llama31_model = 'llama-3.1-70b-versatile'
+
+# 2. Image encoding
+def encode_image(image_path):
+  with open(image_path, "rb") as image_file:
+    return base64.b64encode(image_file.read()).decode('utf-8')
+
+# 3. Image to text function
+def image_to_text(client, model, base64_image, prompt):
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": prompt},
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{base64_image}",
+                        },
+                    },
+                ],
+            }           
+        ],
+        model=model
+    )
+
+    return chat_completion.choices[0].message.content
+
+# 4. Short story generation function
+def analyzer_generation(client, image_description):
+    chat_completion = client.chat.completions.create(
+        messages=[
+            {
+                "role": "system",
+                "content": f"You are a food and nutrition expert, you analyze Food by Photo: The user takes a photo of a plate of food, and the app describes the ingredients, possible calories, and offers suggestions on how to make the meal healthier or more balanced. Note: Write in Portuguese.",
+            },
+            {
+                "role": "user",
+                "content": image_description,
+            }
+        ],
+        model=llama31_model
+    )
+    
+    return chat_completion.choices[0].message.content
+
+# 5. Streamlit app
+def main():
+    st.image("images.jpg", width=200)
+    st.title("FoodBot - Análisador de Alimentos",  anchor="center")
+    st.write("Conheça o FoodBot, um assistente inteligente que o usuário tira uma foto de um prato de comida, e o app descreve os ingredientes, possíveis calorias, e oferece sugestões de como tornar a refeição mais saudável ou equilibrada.")    
+
+    
+    uploaded_file = st.file_uploader("Carregue uma imagem (png ou jpg)", type=["png", "jpg"])
+    if uploaded_file is not None:
+        # To read file as bytes:
+        bytes_data = uploaded_file.read()
+        base64_image = base64.b64encode(bytes_data).decode('utf-8')
+        prompt = '''
+        Describe this image in detail, including the appearance of the object(s).  Note: Write in Portuguese.
+        '''
+        image_description = image_to_text(client, llava_model, base64_image, prompt)
+
+        st.write("\n--- Image Description ---")
+        st.write(image_description)
+
+        st.write("\n--- Análise do Alimento ---")
+        food_description = analyzer_generation(client, image_description)
+        st.write(food_description)
+
+       
+
+if __name__ == "__main__":
+    main()