support pre-commit (#10)

.gitignore

@@ -157,4 +157,4 @@ cython_debug/
 #  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
 #  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/
+#.idea/

.pre-commit-config.yaml

@@ -0,0 +1,27 @@
+repos:
+-   repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v3.2.0
+    hooks:
+    -   id: trailing-whitespace
+    -   id: end-of-file-fixer
+    -   id: check-yaml
+    -   id: check-added-large-files
+-   repo: https://github.com/pre-commit/mirrors-prettier
+    rev: v3.0.1  # Use the sha / tag you want to point at
+    hooks:
+    -   id: prettier
+        types_or: [html]
+-   repo: https://github.com/psf/black
+    rev: 22.12.0
+    hooks:
+    -   id: black
+        args: [--line-length=79]
+-   repo: https://github.com/pycqa/isort
+    rev: 5.12.0
+    hooks:
+    -   id: isort
+        args: ["--profile", "black", --line-length=72]
+-   repo: https://github.com/kynan/nbstripout
+    rev: 0.6.0
+    hooks:
+      - id: nbstripout

app.py

@@ -1,16 +1,17 @@
 import os
-import gradio as gr
 import sys
-sys.path.append('../CTM/')
+
+import gradio as gr
+
+sys.path.append("../CTM/")
 from ctm.ctms.ctm_base import BaseConsciousnessTuringMachine
 
 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")
 
 DEPLOYED = os.getenv("DEPLOYED", "true").lower() == "true"
 
+
 def introduction():
     with gr.Column(scale=2):
         gr.Image(
@@ -22,11 +23,13 @@ def introduction():
             """
         )
 
+
 def add_processor(processor_name, display_name, state):
-    print('add processor ', processor_name)
+    print("add processor ", processor_name)
     ctm.add_processor(processor_name)
     print(len(ctm.processor_list))
-    return display_name + ' (added)'
+    return display_name + " (added)"
+
 
 def processor_tab():
     # Categorized model names
@@ -34,14 +37,14 @@ def processor_tab():
         "gpt4_text_emotion_processor",
         "gpt4_text_summary_processor",
         "gpt4_speaker_intent_processor",
-        "roberta_text_sentiment_processor"
+        "roberta_text_sentiment_processor",
     ]
     vision_processors = [
         "gpt4v_cloth_fashion_processor",
         "gpt4v_face_emotion_processor",
         "gpt4v_ocr_processor",
         "gpt4v_posture",
-        "gpt4v_scene_location_processor"
+        "gpt4v_scene_location_processor",
     ]
 
     with gr.Blocks():
@@ -49,77 +52,100 @@ def processor_tab():
             with gr.Column(scale=1):
                 gr.Markdown("### Text Processors")
                 for model_name in text_processors:
-                    display_name = model_name.replace("processor", "").replace("_", " ").title()
+                    display_name = (
+                        model_name.replace("processor", "")
+                        .replace("_", " ")
+                        .title()
+                    )
 
                     button = gr.Button(display_name)
-                    processor_name = gr.Textbox(value=model_name, visible=False)
-                    display_name = gr.Textbox(value=display_name, visible=False)
+                    processor_name = gr.Textbox(
+                        value=model_name, visible=False
+                    )
+                    display_name = gr.Textbox(
+                        value=display_name, visible=False
+                    )
                     button.click(
                         fn=add_processor,
                         inputs=[processor_name, display_name, gr.State()],
-                        outputs=[button]
+                        outputs=[button],
                     )
 
             with gr.Column(scale=1):
                 gr.Markdown("### Vision Processors")
                 for model_name in vision_processors:
-                    display_name = model_name.replace("processor", "").replace("_", " ").title()
+                    display_name = (
+                        model_name.replace("processor", "")
+                        .replace("_", " ")
+                        .title()
+                    )
 
                     button = gr.Button(display_name)
-                    processor_name = gr.Textbox(value=model_name, visible=False)
-                    display_name = gr.Textbox(value=display_name, visible=False)
+                    processor_name = gr.Textbox(
+                        value=model_name, visible=False
+                    )
+                    display_name = gr.Textbox(
+                        value=display_name, visible=False
+                    )
                     button.click(
                         fn=add_processor,
                         inputs=[processor_name, display_name, gr.State()],
-                        outputs=[button]
+                        outputs=[button],
                     )
 
 
-
-
 def forward(query, content, image, state):
-    state['question'] = query
-    ask_processors_output_info, state = ask_processors(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
+    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, 
+        question=query,
+        context=content,
         image_path=None,
         audio_path=None,
-        video_path=None
+        video_path=None,
     )
-    output_info = ''
+    output_info = ""
     for name, info in processor_output.items():
         output_info += f"{name}: {info['gist']}\n"
-    state['processor_output'] = processor_output
+    state["processor_output"] = processor_output
     return output_info, state
 
 
 def uptree_competition(state):
-    winning_output = ctm.uptree_competition(
-        state['processor_output']
+    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"]
+        )
     )
-    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']
+    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
+    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
 
 
@@ -140,23 +166,25 @@ def interface_tab():
 
             # Outputs
             processors_output = gr.Textbox(
-                label="Processors Output", 
-                visible=True
+                label="Processors Output", visible=True
             )
             competition_output = gr.Textbox(
-                label="Up-tree Competition Output", 
-                visible=True
+                label="Up-tree Competition Output", visible=True
             )
             supervisor_output = gr.Textbox(
-                label="Supervisor Output", 
-                visible=True
+                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]
+            outputs=[
+                processors_output,
+                competition_output,
+                supervisor_output,
+                state,
+            ],
         )
 
     return interface_tab
@@ -190,4 +218,4 @@ def start_demo():
 
 
 if __name__ == "__main__":
-    start_demo()
+    start_demo()