Create app.py

app.py

@@ -0,0 +1,47 @@
+import base64
+import gradio as gr
+import requests
+
+def encode_image(image_file):
+    with open(image_file.name, "rb") as img_file:
+        return base64.b64encode(img_file.read()).decode('utf-8')
+
+def send_to_openai(api_key, image_file):
+    base64_image = encode_image(image_file)
+
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}"
+    }
+
+    payload = {
+        "model": "gpt-4-vision-preview",
+        "messages": [
+            {
+                "role": "user",
+                "content": [
+                    {
+                        "type": "text",
+                        "text": "Answer in three words only, does the image uploaded have a healthy rice leaf - Yes or No , does the image uploaded have a rice leaf with brown spots - Yes or No , does the image uploaded have a rice leaf have yellowish discoloration in some spots - Yes or No , DO NOT RESPOND IN MORE THAN THREE WORDS  "
+                    },
+                    {
+                        "type": "image_url",
+                        "image_url": {
+                            "url": f"data:image/jpeg;base64,{base64_image}"
+                        }
+                    }
+                ]
+            }
+        ],
+        "max_tokens": 300
+    }
+
+    response = requests.post("https://api.openai.com/v1/chat/completions", headers=headers, json=payload)
+    # Extract words from the assistant's response
+    assistant_response = response.json()['choices'][0]['message']['content']
+    words = assistant_response.split('\n')
+    
+    return ' '.join(words)
+
+iface = gr.Interface(send_to_openai, ["text", "file"], "text")
+iface.launch()