patrickvonplaten
commited on
Commit
β’
a7e7106
1
Parent(s):
7a8dab7
Update app.py
Browse files
app.py
CHANGED
@@ -31,17 +31,6 @@ MODEL_KEYS = "-".join(SUBMISSIONS.keys())
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SUBMISSION_ORG = f"results-{MODEL_KEYS}"
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PROMPT_FORMAT = "Pick the picture that best matches the prompt: **{}**"
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all_datasets = list_datasets(author=SUBMISSION_ORG)
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relevant_ids = [d.id for d in all_datasets]
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submitted_ids = []
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for _id in relevant_ids:
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ds = load_dataset(_id)["train"]
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submitted_ids += ds["id"]
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submitted_ids = Counter(submitted_ids)
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submission_names = list(SUBMISSIONS.keys())
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num_images = len(SUBMISSIONS[submission_names[0]])
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@@ -65,10 +54,30 @@ def generate_random_hash(length=8):
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return random_hash
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-
def
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-
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ids = {**ids, **submitted_ids}
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# sort by count
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@@ -170,110 +179,113 @@ def change_view(row_number, dataframe):
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}
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## How it works π \n\n
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1. Click on 'Start'
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2. A prompt and 4 different images are displayed
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3. Select your favorite image
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4. Click on 'Select'
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5. After 10 rounds your favorite diffusion model is displayed
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"""
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with gr.Column(visible=True) as intro_view:
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gr.Markdown(EXPLANATION)
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start_button = gr.Button("Start").style(full_width=False)
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headers = ["prompt", "result", "id", "Challenge", "Category", "Note"] + [
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f"choice_{i}" for i in range(len(SUBMISSIONS))
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]
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datatype = ["str", "str", "number", "str", "str", "str"] + len(SUBMISSIONS) * [
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"number"
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]
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with gr.Column(visible=False):
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row_number = gr.Number(
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label="Current row selection index",
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value=0,
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precision=0,
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interactive=False,
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)
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# Create Data Frame
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with gr.Column(visible=False) as result_view:
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result = gr.Markdown("")
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dataframe = gr.Dataframe(
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headers=headers,
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datatype=datatype,
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row_count=NUM_QUESTIONS,
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col_count=(6 + len(SUBMISSIONS), "fixed"),
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interactive=False,
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)
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gr.Markdown("Click on start to play again!")
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with gr.Column(visible=False) as gallery_view:
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counter = gr.Markdown(f" ### 1/{NUM_QUESTIONS}")
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prompt = gr.Markdown(PROMPT_FORMAT.format(""))
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gallery = gr.Gallery(
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label="All images", show_label=False, elem_id="gallery"
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).style(columns=GALLERY_COLUMN_NUM, object_fit="contain")
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next_button = gr.Button("Select").style(full_width=False)
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with gr.Column(visible=False):
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selected_image = gr.Number(label="Selected index", value=-1, precision=0)
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start_button.click(
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fn=start,
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inputs=[],
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outputs=dataframe,
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show_progress=True
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).then(
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fn=lambda x: 0 if x == NUM_QUESTIONS else x,
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inputs=[row_number],
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outputs=[row_number],
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).then(
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fn=change_view,
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inputs=[row_number, dataframe],
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outputs=[intro_view, result_view, gallery_view, result]
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).then(
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fn=process, inputs=[dataframe], outputs=[gallery, prompt, counter]
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)
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)
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SUBMISSION_ORG = f"results-{MODEL_KEYS}"
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PROMPT_FORMAT = "Pick the picture that best matches the prompt: **{}**"
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submission_names = list(SUBMISSIONS.keys())
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num_images = len(SUBMISSIONS[submission_names[0]])
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return random_hash
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def load_submissions():
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all_datasets = list_datasets(author=SUBMISSION_ORG)
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relevant_ids = [d.id for d in all_datasets]
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submitted_ids = []
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for _id in relevant_ids:
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ds = load_dataset(_id)["train"]
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submitted_ids += ds["id"]
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submitted_ids = Counter(submitted_ids)
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return submitted_ids
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def refresh(row_number, dataframe):
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if row_number == NUM_QUESTIONS:
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submitted_ids = load_submissions()
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return start(submitted_ids)
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else:
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return dataframe
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def start(submitted_ids=None):
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if submitted_ids is None:
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submitted_ids = load_submissions()
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ids = {id: 0 for id in range(num_images)}
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ids = {**ids, **submitted_ids}
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# sort by count
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}
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TITLE = "# Community Parti Prompts - Who is your open-source genAI model?"
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DESCRIPTION = """
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*This is an interactive game in which you click through pre-generated images from SD-v1-5, SD-v2.1, Karlo, and IF
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using [Parti Prompts](https://huggingface.co/datasets/nateraw/parti-prompts) prompts.* \n
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*You choices will go into the public community [genAI leaderboard](TODO).*
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"""
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EXPLANATION = """\n\n
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## How it works π \n\n
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1. Click on 'Start'
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2. A prompt and 4 different images are displayed
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3. Select your favorite image
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4. Click on 'Select'
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5. After 10 rounds your favorite diffusion model is displayed
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"""
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GALLERY_COLUMN_NUM = len(SUBMISSIONS)
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with gr.Blocks() as demo:
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gr.Markdown(TITLE)
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gr.Markdown(DESCRIPTION)
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with gr.Column(visible=True) as intro_view:
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gr.Markdown(EXPLANATION)
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start_button = gr.Button("Start").style(full_width=False)
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headers = ["prompt", "result", "id", "Challenge", "Category", "Note"] + [
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f"choice_{i}" for i in range(len(SUBMISSIONS))
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]
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datatype = ["str", "str", "number", "str", "str", "str"] + len(SUBMISSIONS) * [
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"number"
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]
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with gr.Column(visible=False):
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row_number = gr.Number(
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label="Current row selection index",
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value=0,
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precision=0,
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interactive=False,
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)
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# Create Data Frame
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with gr.Column(visible=False) as result_view:
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result = gr.Markdown("")
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dataframe = gr.Dataframe(
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headers=headers,
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datatype=datatype,
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row_count=NUM_QUESTIONS,
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col_count=(6 + len(SUBMISSIONS), "fixed"),
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interactive=False,
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)
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gr.Markdown("Click on start to play again!")
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with gr.Column(visible=False) as gallery_view:
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counter = gr.Markdown(f" ### 1/{NUM_QUESTIONS}")
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prompt = gr.Markdown(PROMPT_FORMAT.format(""))
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gallery = gr.Gallery(
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label="All images", show_label=False, elem_id="gallery"
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).style(columns=GALLERY_COLUMN_NUM, object_fit="contain")
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next_button = gr.Button("Select").style(full_width=False)
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with gr.Column(visible=False):
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selected_image = gr.Number(label="Selected index", value=-1, precision=0)
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start_button.click(
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fn=start,
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inputs=[],
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outputs=dataframe,
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show_progress=True
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).then(
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fn=lambda x: 0 if x == NUM_QUESTIONS else x,
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inputs=[row_number],
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outputs=[row_number],
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).then(
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fn=change_view,
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inputs=[row_number, dataframe],
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outputs=[intro_view, result_view, gallery_view, result]
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).then(
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fn=process, inputs=[dataframe], outputs=[gallery, prompt, counter]
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)
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gallery.select(
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fn=get_index,
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outputs=selected_image,
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queue=False,
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)
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next_button.click(
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fn=write_result,
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inputs=[selected_image, row_number, dataframe],
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outputs=[row_number, dataframe],
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).then(
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fn=change_view,
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inputs=[row_number, dataframe],
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outputs=[intro_view, result_view, gallery_view, result]
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).then(
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fn=process,
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inputs=[dataframe, row_number],
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outputs=[gallery, prompt, counter]
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).then(
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fn=lambda x: 0 if x == NUM_QUESTIONS else x,
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inputs=[row_number],
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outputs=[row_number],
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).then(
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fn=refresh,
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inputs=[row_number, dataframe],
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outputs=[dataframe],
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)
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demo.launch()
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