Create app.py

app.py

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+import base64
+import requests
+import streamlit as st
+from io import BytesIO
+from PIL import Image
+
+# Function to encode image into base64
+def encode_image(img):
+    buffered = BytesIO()
+    img.save(buffered, format="PNG")
+    encoded_string = base64.b64encode(buffered.getvalue()).decode("utf-8")
+    return encoded_string
+
+# Function to interact with the Hyperbolic API
+def get_api_response(base64_img):
+    api_url = "https://api.hyperbolic.xyz/v1/chat/completions"
+    api_key = "YOUR_API_KEY"  # Replace with your actual API key
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}",
+    }
+    payload = {
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {"type": "text", "text": "What is this image?"},
+                    {
+                        "type": "image_url",
+                        "image_url": {"url": f"data:image/jpeg;base64,{base64_img}"},
+                    },
+                ],
+            }
+        ],
+        "model": "Qwen/Qwen2-VL-72B-Instruct",
+        "max_tokens": 2048,
+        "temperature": 0.7,
+        "top_p": 0.9,
+    }
+
+    response = requests.post(api_url, headers=headers, json=payload)
+    if response.status_code == 200:
+        return response.json()['choices'][0]['message']['content']
+    else:
+        return "Error: Unable to get response from API."
+
+# Streamlit interface
+def main():
+    st.title("Image to Text AI Application")
+    st.write("Upload an image and get a response based on the image content.")
+
+    # File uploader for image
+    uploaded_file = st.file_uploader("Choose an image...", type=["png", "jpg", "jpeg"])
+
+    if uploaded_file is not None:
+        # Open the uploaded image
+        img = Image.open(uploaded_file)
+        
+        # Display the uploaded image
+        st.image(img, caption="Uploaded Image", use_column_width=True)
+
+        # Encode the image to base64
+        base64_img = encode_image(img)
+
+        # Get response from the API
+        st.write("Processing the image...")
+        response = get_api_response(base64_img)
+
+        # Display the result
+        st.write("API Response: ", response)
+
+# Run the Streamlit app
+if __name__ == "__main__":
+    main()