Haofei Yu
commited on
pre-commit checking (#18)
Browse files* support pre-commit
* support running
* pre-commit running
* pre-commit running
- .gitignore +1 -1
- .pre-commit-config.yaml +1 -1
- app.py +40 -24
- ctm/ctms/ctm_base.py +3 -1
- requirements.txt +2 -1
.gitignore
CHANGED
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@@ -157,4 +157,4 @@ cython_debug/
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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-
#.idea/
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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+
#.idea/
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.pre-commit-config.yaml
CHANGED
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@@ -24,4 +24,4 @@ repos:
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- repo: https://github.com/kynan/nbstripout
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rev: 0.6.0
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hooks:
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-
- id: nbstripout
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- repo: https://github.com/kynan/nbstripout
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rev: 0.6.0
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hooks:
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+
- id: nbstripout
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app.py
CHANGED
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@@ -2,8 +2,8 @@ import os
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import sys
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import gradio as gr
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-
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-
sys.path.append(
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from ctm.ctms.ctm_base import BaseConsciousnessTuringMachine
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ctm = BaseConsciousnessTuringMachine()
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@@ -17,27 +17,27 @@ def convert_base64(image_array):
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buffer = io.BytesIO()
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image.save(buffer, format="PNG")
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byte_data = buffer.getvalue()
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-
base64_string = base64.b64encode(byte_data).decode(
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return base64_string
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def introduction():
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with gr.Column(scale=2):
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gr.Image(
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"images/CTM-AI.png", elem_id="banner-image", show_label=False
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-
)
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with gr.Column(scale=5):
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gr.Markdown(
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"""Consciousness Turing Machine Demo
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"""
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)
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def add_processor(processor_name, display_name, state):
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-
print(
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ctm.add_processor(processor_name)
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print(ctm.processor_group_map)
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print(len(ctm.processor_list))
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-
return display_name +
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def processor_tab():
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# Categorized model names
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@@ -45,14 +45,14 @@ def processor_tab():
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"gpt4_text_emotion_processor",
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"gpt4_text_summary_processor",
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"gpt4_speaker_intent_processor",
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-
"roberta_text_sentiment_processor"
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]
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vision_processors = [
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"gpt4v_cloth_fashion_processor",
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"gpt4v_face_emotion_processor",
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"gpt4v_ocr_processor",
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"gpt4v_posture",
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-
"gpt4v_scene_location_processor"
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]
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with gr.Blocks():
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@@ -60,37 +60,53 @@ def processor_tab():
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with gr.Column(scale=1):
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gr.Markdown("### Text Processors")
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for model_name in text_processors:
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-
display_name =
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button = gr.Button(display_name)
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processor_name = gr.Textbox(
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-
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button.click(
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fn=add_processor,
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inputs=[processor_name, display_name, gr.State()],
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-
outputs=[button]
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)
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with gr.Column(scale=1):
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gr.Markdown("### Vision Processors")
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for model_name in vision_processors:
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-
display_name =
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button = gr.Button(display_name)
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processor_name = gr.Textbox(
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-
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button.click(
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fn=add_processor,
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inputs=[processor_name, display_name, gr.State()],
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-
outputs=[button]
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)
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-
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-
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def forward(query, content, image, state):
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state[
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ask_processors_output_info, state = ask_processors(
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uptree_competition_output_info, state = uptree_competition(state)
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ask_supervisor_output_info, state = ask_supervisor(state)
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@@ -148,8 +164,8 @@ def interface_tab():
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text = gr.Textbox(label="Enter your text here")
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query = gr.Textbox(label="Enter your query here")
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image = gr.Image(label="Upload your image")
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-
#audio = gr.Audio(label="Upload or Record Audio")
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-
#video = gr.Video(label="Upload or Record Video")
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# Processing buttons
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forward_button = gr.Button("Start CTM forward process")
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import sys
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import gradio as gr
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+
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+
sys.path.append("./ctm")
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from ctm.ctms.ctm_base import BaseConsciousnessTuringMachine
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ctm = BaseConsciousnessTuringMachine()
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buffer = io.BytesIO()
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image.save(buffer, format="PNG")
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byte_data = buffer.getvalue()
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+
base64_string = base64.b64encode(byte_data).decode("utf-8")
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return base64_string
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def introduction():
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with gr.Column(scale=2):
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+
gr.Image("images/CTM-AI.png", elem_id="banner-image", show_label=False)
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with gr.Column(scale=5):
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gr.Markdown(
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"""Consciousness Turing Machine Demo
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"""
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)
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+
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def add_processor(processor_name, display_name, state):
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+
print("add processor ", processor_name)
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ctm.add_processor(processor_name)
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print(ctm.processor_group_map)
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print(len(ctm.processor_list))
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+
return display_name + " (added)"
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+
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def processor_tab():
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# Categorized model names
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"gpt4_text_emotion_processor",
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"gpt4_text_summary_processor",
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"gpt4_speaker_intent_processor",
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+
"roberta_text_sentiment_processor",
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]
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vision_processors = [
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"gpt4v_cloth_fashion_processor",
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"gpt4v_face_emotion_processor",
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"gpt4v_ocr_processor",
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"gpt4v_posture",
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+
"gpt4v_scene_location_processor",
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]
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with gr.Blocks():
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with gr.Column(scale=1):
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gr.Markdown("### Text Processors")
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for model_name in text_processors:
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+
display_name = (
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model_name.replace("processor", "")
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.replace("_", " ")
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.title()
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)
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button = gr.Button(display_name)
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processor_name = gr.Textbox(
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value=model_name, visible=False
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)
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display_name = gr.Textbox(
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value=display_name, visible=False
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)
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button.click(
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fn=add_processor,
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inputs=[processor_name, display_name, gr.State()],
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+
outputs=[button],
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)
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with gr.Column(scale=1):
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gr.Markdown("### Vision Processors")
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for model_name in vision_processors:
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+
display_name = (
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model_name.replace("processor", "")
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.replace("_", " ")
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.title()
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)
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button = gr.Button(display_name)
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processor_name = gr.Textbox(
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value=model_name, visible=False
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+
)
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display_name = gr.Textbox(
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value=display_name, visible=False
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+
)
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button.click(
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fn=add_processor,
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inputs=[processor_name, display_name, gr.State()],
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+
outputs=[button],
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)
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def forward(query, content, image, state):
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state["question"] = query
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+
ask_processors_output_info, state = ask_processors(
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query, content, image, state
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+
)
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uptree_competition_output_info, state = uptree_competition(state)
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ask_supervisor_output_info, state = ask_supervisor(state)
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text = gr.Textbox(label="Enter your text here")
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query = gr.Textbox(label="Enter your query here")
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image = gr.Image(label="Upload your image")
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+
# audio = gr.Audio(label="Upload or Record Audio")
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+
# video = gr.Video(label="Upload or Record Video")
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# Processing buttons
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forward_button = gr.Button("Start CTM forward process")
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ctm/ctms/ctm_base.py
CHANGED
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@@ -207,7 +207,9 @@ class BaseConsciousnessTuringMachine(object):
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audio_path=audio_path,
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video_path=video_path,
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)
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-
import pdb
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winning_output = self.uptree_competition(processor_output)
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answer, score = self.ask_supervisor(question, winning_output)
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if score > answer_threshold:
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audio_path=audio_path,
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video_path=video_path,
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)
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+
import pdb
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+
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pdb.set_trace()
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winning_output = self.uptree_competition(processor_output)
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answer, score = self.ask_supervisor(question, winning_output)
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if score > answer_threshold:
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requirements.txt
CHANGED
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@@ -2,4 +2,5 @@ scikit-learn==1.3.0
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huggingface-hub==0.21.4
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gradio==4.27.0
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gradio_client==0.15.1
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-
openai==1.23.3
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huggingface-hub==0.21.4
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gradio==4.27.0
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gradio_client==0.15.1
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+
openai==1.23.3
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+
pre-commit==3.7.0
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