app.py

import logging
import os

import gradio as gr
from dotenv import load_dotenv

from utils import add_result

logger = logging.getLogger(__name__)
logger.setLevel(logging.DEBUG)

load_dotenv()


def submit_result(user_answer):
    add_result({"user_answer": user_answer})
    return


def get_user_prompt():
    return {
        "images": [
            "images/1.jpeg",
            "images/1.jpeg",
            "images/1.jpeg",
        ],
        "labels": [
            "A pencil",
            "A camera",
            "A sheet of paper",
        ],
    }


hf_writer = gr.HuggingFaceDatasetSaver(
    hf_token=os.environ["HF_TOKEN"], dataset_name="acmc/maker-faire-bot", private=True
)
csv_writer = gr.CSVLogger(simplify_file_data=True)

theme = gr.themes.Default(primary_hue="cyan", secondary_hue="fuchsia")

with gr.Blocks(theme=theme) as demo:
    with gr.Row() as header:
        gr.Image(
            "maker-faire-logo.webp",
            show_download_button=False,
            show_label=False,
            show_share_button=False,
            container=False,
            # height=100,
            scale=0.2,
        )
        gr.Markdown(
            """
            # Maker Faire Bot
            """,
            visible=False,
        )

    user_prompt = gr.State(get_user_prompt())

    gr.Markdown("""# Think about these objects...""")
    gr.Markdown(
        """We want to teach the Maker Faire Bot some creativity. Help us get ideas on what you'd build!"""
    )
    with gr.Row(variant="panel") as row:
        for i in range(len(user_prompt.value["images"])):
            with gr.Column(variant="default") as col:
                gr.Image(
                    user_prompt.value["images"][i],
                    label=user_prompt.value["labels"][i],
                    interactive=False,
                    show_download_button=False,
                    show_share_button=False,
                )

    user_answer_object = gr.Textbox(
        autofocus=True,
        placeholder="(example): An electronic guitar",
        label="What would you build?",
    )
    user_answer_explanation = gr.TextArea(
        autofocus=True,
        label="How would you build it?",
        placeholder="""I'd use the camera to detect when the user touches the strings and make a sound using the loudspeakers when that happens.""",
    )

    csv_writer.setup(components=[user_prompt, user_answer_object, user_answer_explanation], flagging_dir="flagged_data_csv")
    hf_writer.setup(components=[user_prompt, user_answer_object, user_answer_explanation], flagging_dir="flagged_data_hf")

    submit_btn = gr.Button("Submit", variant="primary")
    def log_results(prompt, object, explanation):
        csv_writer.flag([prompt, object, explanation])
        hf_writer.flag([prompt, object, explanation])

    submit_btn.click(log_results, inputs=[user_prompt, user_answer_object, user_answer_explanation], preprocess=False)

    gr.Markdown(
        """
        This is an experimental project. Your data is anonymous and will be used to train an AI model. By using this tool, you agree to our [policy](https://makerfaire.com/privacy).
        """
    )

if __name__ == "__main__":
    demo.launch()