Create app.py

app.py

@@ -0,0 +1,67 @@
+openai.api_key=os.getenv('openai_appkey')
+# doc is here https://platform.openai.com/docs/guides/chat/chat-vs-completions?utm_medium=email&_hsmi=248334739&utm_content=248334739&utm_source=hs_email
+def get_chatgpt(input_text):
+    chat_completion = openai.ChatCompletion.create(
+    model="gpt-3.5-turbo",
+    messages=[
+        # system message first, it helps set the behavior of the assistant
+        {"role": "system", "content": "You are a helpful assistant."},
+        # I am the user, and this is my prompt
+        {"role": "user", "content": input_text},
+        # we can also add the previous conversation
+        # {"role": "assistant", "content": "Episode III."},
+        ],
+     )
+# let's see the reply
+    #print(chat_completion.choices[0].message.content)
+    return chat_completion.choices[0].message.content
+with gr.Blocks(
+    css="""
+    .message.svelte-w6rprc.svelte-w6rprc.svelte-w6rprc {font-size: 20px; margin-top: 20px}
+    #component-21 > div.wrap.svelte-w6rprc {height: 600px;}
+    """
+) as iface:
+    state = gr.State([])
+    #caption_output = None
+    #gr.Markdown(title)
+    #gr.Markdown(description)
+    #gr.Markdown(article)
+
+    with gr.Row():
+        with gr.Column(scale=1):
+            with gr.Row():
+                with gr.Column(scale=1):
+                    chat_input = gr.Textbox(lines=1, label="VQA Quesiton Input")
+                    with gr.Row():
+                        clear_button = gr.Button(value="Clear", interactive=True)
+                        submit_button = gr.Button(
+                            value="VQA", interactive=True, variant="primary"
+                        )
+                    
+        with gr.Column():
+            caption_output_v1 = gr.Textbox(lines=0, label="CAP+LLM")
+            
+            
+        image_input.change(
+            lambda: ( [],""),
+            [],
+            [  state,caption_output_v1],
+            queue=False,
+        )
+       
+        submit_button.click(
+                        get_chatgpt,
+                        [
+                            chat_input,
+                        ],
+                        [caption_output,gpt3_output_v1,caption_output_v1],
+                    )
+       
+    examples=[['bird.jpeg',"How many birds are there in the tree?"]]
+    examples = gr.Examples(
+       examples=examples,
+       inputs=[image_input, chat_input],
+    )
+
+iface.queue(concurrency_count=1, api_open=False, max_size=10)
+iface.launch(enable_queue=True)