Create app.py

app.py

@@ -0,0 +1,52 @@
+import gradio as gr
+import openai
+from openai import OpenAI
+import os
+import base64
+
+# Set API key and organization ID from environment variables
+openai.api_key = os.getenv('OPENAI_API_KEY')
+openai.organization = os.getenv('OPENAI_ORG_ID')
+client = OpenAI(api_key= os.getenv('OPENAI_API_KEY'), organization=os.getenv('OPENAI_ORG_ID'))
+
+# Define the model to be used
+MODEL = "gpt-4o"
+
+def process_text(text_input):
+    if text_input:
+        completion = client.chat.completions.create(
+            model=MODEL,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant. Help me with my math homework!"},
+                {"role": "user", "content": f"Hello! Could you solve {text_input}?"}
+            ]
+        )
+        return "Assistant: " + completion.choices[0].message.content
+
+def process_image(image_input):
+    if image_input is not None:
+        with open(image_input.name, "rb") as f:
+            base64_image = base64.b64encode(f.read()).decode("utf-8")
+        response = client.chat.completions.create(
+            model=MODEL,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant that responds in Markdown."},
+                {"role": "user", "content": [
+                    {"type": "text", "text": "Help me understand what is it"},
+                    {"type": "image_url", "image_url": {
+                        "url": f"data:image/png;base64,{base64_image}"}
+                    }
+                ]}
+            ],
+            temperature=0.0,
+        )
+        return response.choices[0].message.content
+
+def main(text_input="", image_input=None):
+    if text_input and image_input is None:
+        return process_text(text_input)
+    elif image_input is not None:
+        return process_image(image_input)
+
+iface = gr.Interface(fn=main, inputs=["text", gr.inputs.Image()], outputs="text")
+iface.launch()