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cherokee

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amber

777015e about 2 years ago

9.23 kB

import gradio as gr
from dotenv import load_dotenv

from models import get_all_models, get_random_models

load_dotenv()


share_js = """
function () {
    const captureElement = document.querySelector('#share-region-annoy');
    // console.log(captureElement);
    html2canvas(captureElement)
        .then(canvas => {
            canvas.style.display = 'none'
            document.body.appendChild(canvas)
            return canvas
        })
        .then(canvas => {
            const image = canvas.toDataURL('image/png')
            const a = document.createElement('a')
            a.setAttribute('download', 'guardrails-arena.png')
            a.setAttribute('href', image)
            a.click()
            canvas.remove()
        });
    return [];
}
"""


def activate_chat_buttons():
    regenerate_btn = gr.Button(
        value="🔄  Regenerate", interactive=True, elem_id="regenerate_btn"
    )
    clear_btn = gr.ClearButton(
        elem_id="clear_btn",
        interactive=True,
    )
    return regenerate_btn, clear_btn


def deactivate_chat_buttons():
    regenerate_btn = gr.Button(
        value="🔄  Regenerate", interactive=False, elem_id="regenerate_btn"
    )
    clear_btn = gr.ClearButton(
        elem_id="clear_btn",
        interactive=False,
    )
    return regenerate_btn, clear_btn


def handle_message(
    llms, user_input, temperature, top_p, max_output_tokens, states1, states2
):
    history1 = states1.value if states1 else []
    history2 = states2.value if states2 else []
    states = [states1, states2]
    history = [history1, history2]
    for hist in history:
        hist.append((user_input, None))
    for (
        updated_history1,
        updated_history2,
        updated_states1,
        updated_states2,
    ) in process_responses(
        llms, temperature, top_p, max_output_tokens, history, states
    ):
        yield updated_history1, updated_history2, updated_states1, updated_states2


def regenerate_message(llms, temperature, top_p, max_output_tokens, states1, states2):
    history1 = states1.value if states1 else []
    history2 = states2.value if states2 else []
    user_input = (
        history1.pop()[0] if history1 else None
    )  # Assumes regeneration is needed so there is at least one input
    if history2:
        history2.pop()
    states = [states1, states2]
    history = [history1, history2]
    for hist in history:
        hist.append((user_input, None))
    for (
        updated_history1,
        updated_history2,
        updated_states1,
        updated_states2,
    ) in process_responses(
        llms, temperature, top_p, max_output_tokens, history, states
    ):
        yield updated_history1, updated_history2, updated_states1, updated_states2


def process_responses(llms, temperature, top_p, max_output_tokens, history, states):
    generators = [
        llms[i]["model"](history[i], temperature, top_p, max_output_tokens)
        for i in range(2)
    ]
    responses = [[], []]
    done = [False, False]

    while not all(done):
        for i in range(2):
            if not done[i]:
                try:
                    response = next(generators[i])
                    if response:
                        responses[i].append(response)
                        history[i][-1] = (history[i][-1][0], "".join(responses[i]))
                        states[i] = gr.State(history[i])
                    yield history[0], history[1], states[0], states[1]
                except StopIteration:
                    done[i] = True
    yield history[0], history[1], states[0], states[1]


with gr.Blocks(
    title="Chatbot Arena",
    # theme=gr.themes.Soft(secondary_hue=gr.themes.colors.sky),
    theme=gr.themes.Base(),
) as demo:
    num_sides = 2
    states = [gr.State() for _ in range(num_sides)]
    chatbots = [None] * num_sides
    models = gr.State(get_random_models)
    all_models = get_all_models()
    # gr.Markdown(
    #     "# Cherokee Language Preserve Model V0.4 \n\nChat with multiple models at the same time and compare their responses. "
    # )
    with gr.Group(elem_id="share-region-annoy"):
        # with gr.Accordion(f"🔍 Expand to see the {len(all_models)} models", open=False):
        #     model_description_md = """| | | |\n| ---- | ---- | ---- |\n"""
        #     count = 0
        #     for model in all_models:
        #         if count % 3 == 0:
        #             model_description_md += "|"
        #         model_description_md += f" {model['name']} |"
        #         if count % 3 == 2:
        #             model_description_md += "\n"
        #         count += 1
        #     gr.Markdown(model_description_md, elem_id="model_description_markdown")
        with gr.Row():
            for i in range(num_sides):
                label = models.value[i]["name"]
                with gr.Column():
                    chatbots[i] = gr.Chatbot(
                        label=label,
                        elem_id=f"chatbot",
                        height=550,
                        show_copy_button=True,
                    )

    with gr.Row():
        textbox = gr.Textbox(
            show_label=False,
            placeholder="Enter your query and press ENTER",
            elem_id="input_box",
            scale=4,
        )
        send_btn = gr.Button(value="Send", variant="primary", scale=0)

    with gr.Row() as button_row:
        upload_button = gr.UploadButton("Upload File", file_types=["image", "video"], file_count="multiple")
        clear_btn = gr.ClearButton(
            value="🎲 New Round",
            elem_id="clear_btn",
            interactive=False,
            components=chatbots + states,
        )
        regenerate_btn = gr.Button(
            value="🔄 Regenerate", interactive=False, elem_id="regenerate_btn"
        )
        share_btn = gr.Button(value="📷 Share Image")

    with gr.Row():
        examples = gr.Examples(
            [
                "translate: ᎧᏃᎮᏍᎩ",
                "Could you assist in rendering this Cherokee word into English?\nᎤᏲᎢ",
                "translate the following Cherokee word into English. ᏧᎩᏨᏅᏓ",
            ],
            inputs=[textbox],
            label="Example task: Translate words",
        )
    with gr.Row():
        examples = gr.Examples(
            [
                "translate: ᏚᏁᏤᎴᏃ ᎬᏩᏍᏓᏩᏗᏙᎯ, ᎾᏍᎩ ᏥᏳ ᎤᎦᏘᏗᏍᏗᏱ, ᎤᏂᏣᏘ ᎨᏒ ᎢᏳᏍᏗ, ᎾᏍᎩ ᎬᏩᏁᏄᎳᏍᏙᏗᏱ ᏂᎨᏒᎾ",
                "translate following Cherokee sentences into English.\nᏥᏌᏃ ᎤᏓᏅᏎ ᏚᏘᏅᏎ ᎬᏩᏍᏓᏩᏗᏙᎯ ᎥᏓᎵ ᏭᏂᎶᏎᎢ; ᎤᏂᏣᏘᏃ ᎬᏩᏍᏓᏩᏛᏎᎢ, ᏅᏓᏳᏂᎶᏒᎯ ᎨᎵᎵ, ᎠᎴ ᏧᏗᏱ,",
                "translate following sentences.\nᎯᎠᏃ ᏄᏪᏎᎴ ᎠᏍᎦᏯ ᎤᏬᏰᏂ ᎤᏩᎢᏎᎸᎯ; ᎠᏰᎵ ᎭᎴᎲᎦ.",
            ],
            inputs=[textbox],
            label="Example task: Translate sentences",
        )

    with gr.Accordion("Parameters", open=False) as parameter_row:
        temperature = gr.Slider(
            minimum=0.0,
            maximum=2.0,
            value=0.5,
            step=0.1,
            interactive=True,
            label="Temperature",
        )
        top_p = gr.Slider(
            minimum=0.0,
            maximum=1.0,
            value=0.7,
            step=0.1,
            interactive=True,
            label="Top P",
        )
        max_output_tokens = gr.Slider(
            minimum=16,
            maximum=4096,
            value=1024,
            step=64,
            interactive=True,
            label="Max output tokens",
        )

    textbox.submit(
        handle_message,
        inputs=[
            models,
            textbox,
            temperature,
            top_p,
            max_output_tokens,
            states[0],
            states[1],
        ],
        outputs=[chatbots[0], chatbots[1], states[0], states[1]],
    ).then(
        activate_chat_buttons,
        inputs=[],
        outputs=[regenerate_btn, clear_btn],
    )

    send_btn.click(
        handle_message,
        inputs=[
            models,
            textbox,
            temperature,
            top_p,
            max_output_tokens,
            states[0],
            states[1],
        ],
        outputs=[chatbots[0], chatbots[1], states[0], states[1]],
    ).then(
        activate_chat_buttons,
        inputs=[],
        outputs=[regenerate_btn, clear_btn],
    )

    regenerate_btn.click(
        regenerate_message,
        inputs=[
            models,
            temperature,
            top_p,
            max_output_tokens,
            states[0],
            states[1],
        ],
        outputs=[chatbots[0], chatbots[1], states[0], states[1]],
    )

    clear_btn.click(
        deactivate_chat_buttons,
        inputs=[],
        outputs=[regenerate_btn, clear_btn],
    ).then(lambda: get_random_models(), inputs=None, outputs=[models])

    share_btn.click(None, inputs=[], outputs=[], js=share_js)

if __name__ == "__main__":
    demo.queue(default_concurrency_limit=10)
    demo.launch(server_name="127.0.01", server_port=5009, share=True)

	import gradio as gr
	from dotenv import load_dotenv

	from models import get_all_models, get_random_models

	load_dotenv()


	share_js = """
	function () {
	const captureElement = document.querySelector('#share-region-annoy');
	// console.log(captureElement);
	html2canvas(captureElement)
	.then(canvas => {
	canvas.style.display = 'none'
	document.body.appendChild(canvas)
	return canvas
	})
	.then(canvas => {
	const image = canvas.toDataURL('image/png')
	const a = document.createElement('a')
	a.setAttribute('download', 'guardrails-arena.png')
	a.setAttribute('href', image)
	a.click()
	canvas.remove()
	});
	return [];
	}
	"""


	def activate_chat_buttons():
	regenerate_btn = gr.Button(
	value="🔄 Regenerate", interactive=True, elem_id="regenerate_btn"
	)
	clear_btn = gr.ClearButton(
	elem_id="clear_btn",
	interactive=True,
	)
	return regenerate_btn, clear_btn


	def deactivate_chat_buttons():
	regenerate_btn = gr.Button(
	value="🔄 Regenerate", interactive=False, elem_id="regenerate_btn"
	)
	clear_btn = gr.ClearButton(
	elem_id="clear_btn",
	interactive=False,
	)
	return regenerate_btn, clear_btn


	def handle_message(
	llms, user_input, temperature, top_p, max_output_tokens, states1, states2
	):
	history1 = states1.value if states1 else []
	history2 = states2.value if states2 else []
	states = [states1, states2]
	history = [history1, history2]
	for hist in history:
	hist.append((user_input, None))
	for (
	updated_history1,
	updated_history2,
	updated_states1,
	updated_states2,
	) in process_responses(
	llms, temperature, top_p, max_output_tokens, history, states
	):
	yield updated_history1, updated_history2, updated_states1, updated_states2


	def regenerate_message(llms, temperature, top_p, max_output_tokens, states1, states2):
	history1 = states1.value if states1 else []
	history2 = states2.value if states2 else []
	user_input = (
	history1.pop()[0] if history1 else None
	) # Assumes regeneration is needed so there is at least one input
	if history2:
	history2.pop()
	states = [states1, states2]
	history = [history1, history2]
	for hist in history:
	hist.append((user_input, None))
	for (
	updated_history1,
	updated_history2,
	updated_states1,
	updated_states2,
	) in process_responses(
	llms, temperature, top_p, max_output_tokens, history, states
	):
	yield updated_history1, updated_history2, updated_states1, updated_states2


	def process_responses(llms, temperature, top_p, max_output_tokens, history, states):
	generators = [
	llms[i]["model"](history[i], temperature, top_p, max_output_tokens)
	for i in range(2)
	]
	responses = [[], []]
	done = [False, False]

	while not all(done):
	for i in range(2):
	if not done[i]:
	try:
	response = next(generators[i])
	if response:
	responses[i].append(response)
	history[i][-1] = (history[i][-1][0], "".join(responses[i]))
	states[i] = gr.State(history[i])
	yield history[0], history[1], states[0], states[1]
	except StopIteration:
	done[i] = True
	yield history[0], history[1], states[0], states[1]


	with gr.Blocks(
	title="Chatbot Arena",
	# theme=gr.themes.Soft(secondary_hue=gr.themes.colors.sky),
	theme=gr.themes.Base(),
	) as demo:
	num_sides = 2
	states = [gr.State() for _ in range(num_sides)]
	chatbots = [None] * num_sides
	models = gr.State(get_random_models)
	all_models = get_all_models()
	# gr.Markdown(
	# "# Cherokee Language Preserve Model V0.4 \n\nChat with multiple models at the same time and compare their responses. "
	# )
	with gr.Group(elem_id="share-region-annoy"):
	# with gr.Accordion(f"🔍 Expand to see the {len(all_models)} models", open=False):
	# model_description_md = """\| \| \| \|\n\| ---- \| ---- \| ---- \|\n"""
	# count = 0
	# for model in all_models:
	# if count % 3 == 0:
	# model_description_md += "\|"
	# model_description_md += f" {model['name']} \|"
	# if count % 3 == 2:
	# model_description_md += "\n"
	# count += 1
	# gr.Markdown(model_description_md, elem_id="model_description_markdown")
	with gr.Row():
	for i in range(num_sides):
	label = models.value[i]["name"]
	with gr.Column():
	chatbots[i] = gr.Chatbot(
	label=label,
	elem_id=f"chatbot",
	height=550,
	show_copy_button=True,
	)

	with gr.Row():
	textbox = gr.Textbox(
	show_label=False,
	placeholder="Enter your query and press ENTER",
	elem_id="input_box",
	scale=4,
	)
	send_btn = gr.Button(value="Send", variant="primary", scale=0)

	with gr.Row() as button_row:
	upload_button = gr.UploadButton("Upload File", file_types=["image", "video"], file_count="multiple")
	clear_btn = gr.ClearButton(
	value="🎲 New Round",
	elem_id="clear_btn",
	interactive=False,
	components=chatbots + states,
	)
	regenerate_btn = gr.Button(
	value="🔄 Regenerate", interactive=False, elem_id="regenerate_btn"
	)
	share_btn = gr.Button(value="📷 Share Image")

	with gr.Row():
	examples = gr.Examples(
	[
	"translate: ᎧᏃᎮᏍᎩ",
	"Could you assist in rendering this Cherokee word into English?\nᎤᏲᎢ",
	"translate the following Cherokee word into English. ᏧᎩᏨᏅᏓ",
	],
	inputs=[textbox],
	label="Example task: Translate words",
	)
	with gr.Row():
	examples = gr.Examples(
	[
	"translate: ᏚᏁᏤᎴᏃ ᎬᏩᏍᏓᏩᏗᏙᎯ, ᎾᏍᎩ ᏥᏳ ᎤᎦᏘᏗᏍᏗᏱ, ᎤᏂᏣᏘ ᎨᏒ ᎢᏳᏍᏗ, ᎾᏍᎩ ᎬᏩᏁᏄᎳᏍᏙᏗᏱ ᏂᎨᏒᎾ",
	"translate following Cherokee sentences into English.\nᏥᏌᏃ ᎤᏓᏅᏎ ᏚᏘᏅᏎ ᎬᏩᏍᏓᏩᏗᏙᎯ ᎥᏓᎵ ᏭᏂᎶᏎᎢ; ᎤᏂᏣᏘᏃ ᎬᏩᏍᏓᏩᏛᏎᎢ, ᏅᏓᏳᏂᎶᏒᎯ ᎨᎵᎵ, ᎠᎴ ᏧᏗᏱ,",
	"translate following sentences.\nᎯᎠᏃ ᏄᏪᏎᎴ ᎠᏍᎦᏯ ᎤᏬᏰᏂ ᎤᏩᎢᏎᎸᎯ; ᎠᏰᎵ ᎭᎴᎲᎦ.",
	],
	inputs=[textbox],
	label="Example task: Translate sentences",
	)

	with gr.Accordion("Parameters", open=False) as parameter_row:
	temperature = gr.Slider(
	minimum=0.0,
	maximum=2.0,
	value=0.5,
	step=0.1,
	interactive=True,
	label="Temperature",
	)
	top_p = gr.Slider(
	minimum=0.0,
	maximum=1.0,
	value=0.7,
	step=0.1,
	interactive=True,
	label="Top P",
	)
	max_output_tokens = gr.Slider(
	minimum=16,
	maximum=4096,
	value=1024,
	step=64,
	interactive=True,
	label="Max output tokens",
	)

	textbox.submit(
	handle_message,
	inputs=[
	models,
	textbox,
	temperature,
	top_p,
	max_output_tokens,
	states[0],
	states[1],
	],
	outputs=[chatbots[0], chatbots[1], states[0], states[1]],
	).then(
	activate_chat_buttons,
	inputs=[],
	outputs=[regenerate_btn, clear_btn],
	)

	send_btn.click(
	handle_message,
	inputs=[
	models,
	textbox,
	temperature,
	top_p,
	max_output_tokens,
	states[0],
	states[1],
	],
	outputs=[chatbots[0], chatbots[1], states[0], states[1]],
	).then(
	activate_chat_buttons,
	inputs=[],
	outputs=[regenerate_btn, clear_btn],
	)

	regenerate_btn.click(
	regenerate_message,
	inputs=[
	models,
	temperature,
	top_p,
	max_output_tokens,
	states[0],
	states[1],
	],
	outputs=[chatbots[0], chatbots[1], states[0], states[1]],
	)

	clear_btn.click(
	deactivate_chat_buttons,
	inputs=[],
	outputs=[regenerate_btn, clear_btn],
	).then(lambda: get_random_models(), inputs=None, outputs=[models])

	share_btn.click(None, inputs=[], outputs=[], js=share_js)

	if __name__ == "__main__":
	demo.queue(default_concurrency_limit=10)
	demo.launch(server_name="127.0.01", server_port=5009, share=True)