placed if conditions to change UI on gradio depending on mode

app.py

@@ -137,29 +137,20 @@ def check_cuda_availability():
 
 mode = ""
 
-# # Handling Gradio UI depending on mode
-# def mode_gradio(text: str):
-#     """
-#     Handles the interface gradio will output depending what mode
-#     it's in. It stores the mode in a dictionary that was placed by
-#     a condition inside bot_comms and switches the behaviour in gradio.
-#     """
-
-#     # Mode active
-#     mode_selected = text
-#     return
+# Handling Gradio UI depending on mode
+def mode_gradio(text: str):
+    """
+    Handles the interface gradio will output depending what mode
+    it's in. It stores the mode in a dictionary that was placed by
+    a condition inside bot_comms and switches the behaviour in gradio.
+    """
+
+    # Mode active
+    mode_selected = text
+    return
     
-# # Image created from diffusing
-# image_created = {}
-
-# # Generate An Image from PIL Image grabbed from diffusing
-# def create_image(image):
-#     """
-#     Generates the image using the Image positions
-#     grabbed from PIL in the diffusing.
-#     """
-#     draw = ImageDraw.Draw(image)
-#     retu
+# Image created from diffusing
+image_created = {}
 
 @spaces.GPU(duration=120)
 def bot_comms(message, history):
@@ -172,26 +163,25 @@ def bot_comms(message, history):
 
     if message == "check cuda":
         logger.debug("Checking CUDA availability.")
-        return check_cuda_availability(), None
+        return check_cuda_availability()
     
     if message == "imagery":
         logger.debug("Switching to imagery mode.")
         mode_manager.set_mode("imagery")
-        return "Imagery On! Type your prompt to make the image 🖼️", None
+        return "Imagery On! Type your prompt to make the image 🖼️"
     
     if message == "chatting":
         logger.debug("Switching to chatting mode.")
         mode_manager.set_mode("chatting")
-        return "Imagery Off. Ask me any questions. ☄️", None
+        return "Imagery Off. Ask me any questions. ☄️"
     
     if mode == "imagery":
         logger.debug("Processing imagery prompt.")
         message = message["text"]
         image = diffusing(message)
         # mode_gradio("imagery")
-        # image_created["Image"] = image
-        # yield ("Generated Image:", image)
-        return "", image
+        image_created["Image"] = image
+        return image
         
     buffer = ""
     gpt_outputs = []
@@ -205,7 +195,7 @@ def bot_comms(message, history):
                     # print(f"text recieved inside the stream:\n{text}")
                     gpt_outputs.append(text)
                     buffer += text
-                yield "".join(gpt_outputs), None
+                yield "".join(gpt_outputs)
 
 
 with gr.Blocks(fill_height=True) as demo:
@@ -213,38 +203,44 @@ with gr.Blocks(fill_height=True) as demo:
     
     chatbot = gr.Chatbot(height=600, label="Chimera AI")
     chat_input = gr.MultimodalTextbox(interactive=True, file_types=["images"], placeholder="Enter your question or upload an image.", show_label=False)
-    image_output = gr.Image(type="pil", label="Generated Image")
+    # image_output = gr.Image(type="pil", label="Generated Image")
     
-    def process_response(message, history):
-        response = bot_comms(message, history)
-        if isinstance(response, tuple) and len(response) == 2:
-            text, image = response
-            return text, image
-        return response, None
-
-    chatbot_output = gr.Chatbot(height=600, label="Chimera AI")
-
-    chat_input.submit(process_response, inputs=[chat_input, chatbot], outputs=[chatbot_output, image_output])
-    # if mode_gradio == "imagery":
-    #     gr.Interface()
-    # Customize chatinterface to handle tuples
-    # def custom_fn(*args, **kwargs):
-    #     result = list(bot_comms(*args, **kwargs))
-    #     output = []
-    #     for item in result:
-    #         if isinstance(item, tuple) and isinstance(item[1], Image.Image):
-    #             output.append((item[0], None))
-    #             output.append((None, item[1]))
-    #         else:
-    #             output.append(item)
-    #     return output
-    # gr.ChatInterface(
-    #     fn=bot_comms,
-    #     chatbot=chatbot,
-    #     fill_height=True,
-    #     multimodal=True,
-    #     textbox=chat_input,
-    # )
+    # def process_response(message, history):
+    #     response = bot_comms(message, history)
+    #     if isinstance(response, tuple) and len(response) == 2:
+    #         text, image = response
+    #         return text, image
+    #     return response, None
+
+    # chatbot_output = gr.Chatbot(height=600, label="Chimera AI")
+
+    # chat_input.submit(process_response, inputs=[chat_input, chatbot], outputs=[chatbot_output, image_output])
+    if image_created:
+        gr.Interface(
+            fn=bot_comms,
+            inputs='text',
+            outputs='image',
+            fill_height=True,
+        )
+        # Customize chatinterface to handle tuples
+        # def custom_fn(*args, **kwargs):
+        #     result = list(bot_comms(*args, **kwargs))
+        #     output = []
+        #     for item in result:
+        #         if isinstance(item, tuple) and isinstance(item[1], Image.Image):
+        #             output.append((item[0], None))
+        #             output.append((None, item[1]))
+        #         else:
+        #             output.append(item)
+        #     return output
+    else:
+        gr.ChatInterface(
+            fn=bot_comms,
+            chatbot=chatbot,
+            fill_height=True,
+            multimodal=True,
+            textbox=chat_input,
+        )
 
 if __name__ == "__main__":
     demo.launch()