init version (#7)

.gitignore

@@ -158,3 +158,4 @@ cython_debug/
 #  and can be added to the global gitignore or merged into this file.  For a more nuclear
 #  option (not recommended) you can uncomment the following to ignore the entire idea folder.
 #.idea/
+**/ctm/*

app.py

@@ -1,7 +1,165 @@
+import os
 import gradio as gr
+from ctm.ctms.ctm_base import BaseConsciousnessTuringMachine
 
-def greet(name):
-    return "Hello " + name + "!!"
+ctm = BaseConsciousnessTuringMachine()
+ctm.add_processor("gpt4_text_emotion_processor", group_name="group_1")
+ctm.add_processor("gpt4_text_summary_processor", group_name="group_1")
+ctm.add_supervisor("gpt4_supervisor")
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+DEPLOYED = os.getenv("DEPLOYED", "true").lower() == "true"
+
+def introduction():
+    with gr.Column(scale=2):
+        gr.Image(
+            "images/sotopia.jpg", elem_id="banner-image", show_label=False
+        )
+    with gr.Column(scale=5):
+        gr.Markdown(
+            """Consciousness Turing Machine Demo
+            """
+        )
+
+def add_processor(processor_name):
+    print('add processor ', processor_name)
+    ctm.add_processor(processor_name)
+    print(len(ctm.processor_list))
+
+def processor_tab():
+    with gr.Row() as row:
+        button1 = gr.Button("Text Emotion Analyzer")
+        button2 = gr.Button("Text Summary Generator")
+    
+    invisible_input1 = gr.Textbox(
+        value="gpt4_text_emotion_processor", 
+        visible=False
+    )
+    invisible_input2 = gr.Textbox(
+        value="gpt4_text_summary_processor", 
+        visible=False
+    )
+
+    button1.click(
+        fn=add_processor,
+        inputs=[invisible_input1],
+    )
+    button2.click(
+        fn=add_processor,
+        inputs=[invisible_input2],
+    )
+
+
+def forward(query, content, image, state):
+    state['question'] = query
+    ask_processors_output_info, state = ask_processors(query, content, image, state)
+    uptree_competition_output_info, state = uptree_competition(state)
+    ask_supervisor_output_info, state = ask_supervisor(state)
+
+    ctm.downtree_broadcast(state['winning_output'])
+    ctm.link_form(state['processor_output'])
+    return ask_processors_output_info, uptree_competition_output_info, ask_supervisor_output_info, state
+
+
+def ask_processors(query, content, image, state):
+    # Simulate processing here
+    processor_output = ctm.ask_processors(
+        question=query, 
+        context=content, 
+        image_path=None,
+        audio_path=None,
+        video_path=None
+    )
+    output_info = ''
+    for name, info in processor_output.items():
+        output_info += f"{name}: {info['gist']}\n"
+    state['processor_output'] = processor_output
+    return output_info, state
+
+
+def uptree_competition(state):
+    winning_output = ctm.uptree_competition(
+        state['processor_output']
+    )
+    state['winning_output'] = winning_output
+    output_info = 'The winning processor is: {}\nThe winning gist is: {}\n'.format(winning_output['name'], winning_output['gist'])
+    return output_info, state
+
+
+def ask_supervisor(state):
+    question = state['question']
+    winning_output = state['winning_output']
+    answer, score = ctm.ask_supervisor(question, winning_output)
+    output_info = f"The answer to the query \"{question}\" is: {answer}\nThe confidence for answering is: {score}\n"
+    state['answer'] = answer
+    state['score'] = score
+    return output_info, state
+
+
+def interface_tab():
+    with gr.Blocks() as interface_tab:
+        state = gr.State({})  # State to hold and pass values
+
+        with gr.Column():
+            # Inputs
+            content = gr.Textbox(label="Enter your text here")
+            query = gr.Textbox(label="Enter your query here")
+            image = gr.Image(label="Upload your image")
+            audio = gr.Audio(label="Upload or Record Audio")
+            video = gr.Video(label="Upload or Record Video")
+
+            # Processing buttons
+            forward_button = gr.Button("Start CTM forward process")
+
+            # Outputs
+            processors_output = gr.Textbox(
+                label="Processors Output", 
+                visible=True
+            )
+            competition_output = gr.Textbox(
+                label="Up-tree Competition Output", 
+                visible=True
+            )
+            supervisor_output = gr.Textbox(
+                label="Supervisor Output", 
+                visible=True
+            )
+
+        # Set up button to start or continue processing
+        forward_button.click(
+            fn=forward,
+            inputs=[query, content, image, state],
+            outputs=[processors_output, competition_output, supervisor_output, state]
+        )
+
+    return interface_tab
+
+
+def main():
+    with gr.Blocks(
+        css="""#chat_container {height: 820px; width: 1000px; margin-left: auto; margin-right: auto;}
+               #chatbot {height: 600px; overflow: auto;}
+               #create_container {height: 750px; margin-left: 0px; margin-right: 0px;}
+               #tokenizer_renderer span {white-space: pre-wrap}
+               """
+    ) as demo:
+        with gr.Row():
+            introduction()
+        with gr.Row():
+            processor_tab()
+        with gr.Row():
+            interface_tab()
+
+    return demo
+
+
+def start_demo():
+    demo = main()
+    if DEPLOYED:
+        demo.queue(api_open=False).launch(show_api=False)
+    else:
+        demo.queue()
+        demo.launch(share=False, server_name="0.0.0.0")
+
+
+if __name__ == "__main__":
+    start_demo()