bring the model call in the same space.

app.py

@@ -133,6 +133,43 @@ def capture_image():
     cap.release()
     return image_path
 
+# This is the main logic file that contains hugging face model interaction
+
+# This model is for detecting food in the image.
+# Use a pipeline as a high-level helper
+from transformers import pipeline
+import os
+import openai
+openai.organization = "org-5Z0c3Uk1VG7t3TsczN6M4FCi"
+#openai.api_key = os.getenv("OPENAI_API_KEY")
+openai.api_key_path ="./key.txt" 
+
+def askGPT(prompt="what can I make with potato?"):
+    response = openai.ChatCompletion.create(
+      model="gpt-3.5-turbo",
+      messages=[
+        {
+          "role": "system",
+          "content":prompt 
+        },
+        {
+          "role": "user",
+          "content": ""
+        }      ],
+      temperature=1,
+      max_tokens=256,
+      top_p=1,
+      frequency_penalty=0,
+      presence_penalty=0
+    )
+    result = response["choices"][0]["message"]["content"]
+    return result
+
+def classifyImage(image):
+    pipe = pipeline("image-classification", model="microsoft/resnet-50")
+    result = pipe(image)
+    return result[0]['label']
+
 
 if __name__ == '__main__':
     main()