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6521775
1
Parent(s):
44fc64a
remove obsolete code
Browse files
.python-version
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synthetic-data-generator
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app.py
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from distilabel_dataset_generator.app import demo
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if __name__ == "__main__":
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demo.launch()
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import os
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from distilabel_dataset_generator.app import demo
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os.environ["API_KEY"] = "hf_..."
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os.environ["API_KEY"] = "hf_..."
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if __name__ == "__main__":
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demo.launch()
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src/distilabel_dataset_generator/apps/base.py
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@@ -1,6 +1,6 @@
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import io
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import uuid
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from typing import
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import argilla as rg
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import gradio as gr
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@@ -11,161 +11,14 @@ from gradio import OAuthToken
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from huggingface_hub import HfApi, upload_file
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from distilabel_dataset_generator.utils import (
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_LOGGED_OUT_CSS,
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get_argilla_client,
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get_login_button,
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list_orgs,
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swap_visibility,
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)
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TEXTCAT_TASK = "text_classification"
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SFT_TASK = "supervised_fine_tuning"
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def get_main_ui(
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default_dataset_descriptions: List[str],
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default_system_prompts: List[str],
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default_datasets: List[pd.DataFrame],
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fn_generate_system_prompt: Callable,
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fn_generate_dataset: Callable,
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task: str,
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):
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def fn_generate_sample_dataset(system_prompt, progress=gr.Progress()):
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if system_prompt in default_system_prompts:
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index = default_system_prompts.index(system_prompt)
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if index < len(default_datasets):
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return default_datasets[index]
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if task == TEXTCAT_TASK:
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result = fn_generate_dataset(
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system_prompt=system_prompt,
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difficulty="high school",
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clarity="clear",
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labels=[],
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num_labels=1,
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num_rows=1,
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progress=progress,
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is_sample=True,
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)
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else:
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result = fn_generate_dataset(
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system_prompt=system_prompt,
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num_turns=1,
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num_rows=1,
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progress=progress,
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is_sample=True,
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)
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return result
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with gr.Blocks(
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title="𧬠Synthetic Data Generator",
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head="𧬠Synthetic Data Generator",
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css=_LOGGED_OUT_CSS,
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) as app:
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with gr.Row():
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gr.HTML(
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"""<details style='display: inline-block;'><summary><h2 style='display: inline;'>How does it work?</h2></summary><img src='https://huggingface.co/spaces/argilla/synthetic-data-generator/resolve/main/assets/flow.png' width='100%' style='margin: 0 auto; display: block;'></details>"""
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)
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with gr.Row():
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gr.Markdown(
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"Want to run this locally or with other LLMs? Take a look at the FAQ tab. distilabel Synthetic Data Generator is free, we use the authentication token to push the dataset to the Hugging Face Hub and not for data generation."
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)
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with gr.Row():
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gr.Column()
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get_login_button()
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gr.Column()
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gr.Markdown("## Iterate on a sample dataset")
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with gr.Column() as main_ui:
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(
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dataset_description,
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examples,
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btn_generate_system_prompt,
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system_prompt,
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sample_dataset,
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btn_generate_sample_dataset,
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) = get_iterate_on_sample_dataset_ui(
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default_dataset_descriptions=default_dataset_descriptions,
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default_system_prompts=default_system_prompts,
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default_datasets=default_datasets,
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task=task,
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)
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gr.Markdown("## Generate full dataset")
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gr.Markdown(
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"Once you're satisfied with the sample, generate a larger dataset and push it to Argilla or the Hugging Face Hub."
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)
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with gr.Row(variant="panel") as custom_input_ui:
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pass
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(
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dataset_name,
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add_to_existing_dataset,
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btn_generate_full_dataset_argilla,
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btn_generate_and_push_to_argilla,
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btn_push_to_argilla,
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org_name,
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repo_name,
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private,
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btn_generate_full_dataset,
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btn_generate_and_push_to_hub,
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btn_push_to_hub,
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final_dataset,
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success_message,
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) = get_push_to_ui(default_datasets)
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sample_dataset.change(
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fn=lambda x: x,
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inputs=[sample_dataset],
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outputs=[final_dataset],
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)
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btn_generate_system_prompt.click(
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fn=fn_generate_system_prompt,
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inputs=[dataset_description],
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outputs=[system_prompt],
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show_progress=True,
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).then(
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fn=fn_generate_sample_dataset,
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inputs=[system_prompt],
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outputs=[sample_dataset],
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show_progress=True,
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)
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btn_generate_sample_dataset.click(
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fn=fn_generate_sample_dataset,
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inputs=[system_prompt],
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outputs=[sample_dataset],
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show_progress=True,
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)
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app.load(fn=swap_visibility, outputs=main_ui)
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app.load(get_org_dropdown, outputs=[org_name])
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return (
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app,
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main_ui,
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custom_input_ui,
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dataset_description,
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examples,
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btn_generate_system_prompt,
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system_prompt,
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sample_dataset,
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btn_generate_sample_dataset,
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dataset_name,
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add_to_existing_dataset,
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btn_generate_full_dataset_argilla,
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btn_generate_and_push_to_argilla,
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btn_push_to_argilla,
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org_name,
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repo_name,
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private,
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btn_generate_full_dataset,
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btn_generate_and_push_to_hub,
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btn_push_to_hub,
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final_dataset,
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success_message,
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)
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-
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-
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def validate_argilla_user_workspace_dataset(
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dataset_name: str,
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add_to_existing_dataset: bool = True,
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)
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def get_push_to_ui(default_datasets):
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with gr.Column() as push_to_ui:
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(
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dataset_name,
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add_to_existing_dataset,
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btn_generate_full_dataset_argilla,
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btn_generate_and_push_to_argilla,
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btn_push_to_argilla,
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) = get_argilla_tab()
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(
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org_name,
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repo_name,
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private,
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btn_generate_full_dataset,
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btn_generate_and_push_to_hub,
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btn_push_to_hub,
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) = get_hf_tab()
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final_dataset = get_final_dataset_row(default_datasets)
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success_message = get_success_message_row()
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return (
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dataset_name,
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add_to_existing_dataset,
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btn_generate_full_dataset_argilla,
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btn_generate_and_push_to_argilla,
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btn_push_to_argilla,
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org_name,
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repo_name,
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private,
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btn_generate_full_dataset,
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btn_generate_and_push_to_hub,
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btn_push_to_hub,
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final_dataset,
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success_message,
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)
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-
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-
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def get_iterate_on_sample_dataset_ui(
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default_dataset_descriptions: List[str],
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default_system_prompts: List[str],
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default_datasets: List[pd.DataFrame],
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task: str,
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):
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with gr.Column():
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dataset_description = gr.TextArea(
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label="Give a precise description of your desired application. Check the examples for inspiration.",
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value=default_dataset_descriptions[0],
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lines=2,
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)
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examples = gr.Examples(
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elem_id="system_prompt_examples",
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examples=[[example] for example in default_dataset_descriptions],
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inputs=[dataset_description],
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)
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with gr.Row():
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gr.Column(scale=1)
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btn_generate_system_prompt = gr.Button(
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value="Generate system prompt and sample dataset", variant="primary"
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)
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gr.Column(scale=1)
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system_prompt = gr.TextArea(
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label="System prompt for dataset generation. You can tune it and regenerate the sample.",
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value=default_system_prompts[0],
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lines=2 if task == TEXTCAT_TASK else 5,
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)
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with gr.Row():
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sample_dataset = gr.Dataframe(
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value=default_datasets[0],
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label=(
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"Sample dataset. Text truncated to 256 tokens."
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if task == TEXTCAT_TASK
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else "Sample dataset. Prompts and completions truncated to 256 tokens."
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),
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interactive=False,
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wrap=True,
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)
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with gr.Row():
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gr.Column(scale=1)
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btn_generate_sample_dataset = gr.Button(
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value="Generate sample dataset", variant="primary"
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)
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gr.Column(scale=1)
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return (
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dataset_description,
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examples,
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btn_generate_system_prompt,
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system_prompt,
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sample_dataset,
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btn_generate_sample_dataset,
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)
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-
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-
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def get_argilla_tab() -> Tuple[Any]:
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with gr.Tab(label="Argilla"):
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if get_argilla_client() is not None:
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with gr.Row(variant="panel"):
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dataset_name = gr.Textbox(
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label="Dataset name",
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placeholder="dataset_name",
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value="my-distiset",
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)
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add_to_existing_dataset = gr.Checkbox(
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label="Allow adding records to existing dataset",
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info="When selected, you do need to ensure the dataset options are the same as in the existing dataset.",
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value=False,
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interactive=True,
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scale=1,
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)
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-
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with gr.Row(variant="panel"):
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btn_generate_full_dataset_argilla = gr.Button(
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value="Generate", variant="primary", scale=2
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)
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btn_generate_and_push_to_argilla = gr.Button(
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value="Generate and Push to Argilla",
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variant="primary",
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scale=2,
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)
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btn_push_to_argilla = gr.Button(
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value="Push to Argilla", variant="primary", scale=2
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)
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else:
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gr.Markdown(
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"Please add `ARGILLA_API_URL` and `ARGILLA_API_KEY` to use Argilla or export the dataset to the Hugging Face Hub."
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)
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return (
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dataset_name,
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add_to_existing_dataset,
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btn_generate_full_dataset_argilla,
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btn_generate_and_push_to_argilla,
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btn_push_to_argilla,
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)
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| 343 |
-
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| 344 |
-
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def get_hf_tab() -> Tuple[Any]:
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| 346 |
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with gr.Tab("Hugging Face Hub"):
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| 347 |
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with gr.Row(variant="panel"):
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| 348 |
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org_name = get_org_dropdown()
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repo_name = gr.Textbox(
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label="Repo name",
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placeholder="dataset_name",
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value="my-distiset",
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)
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private = gr.Checkbox(
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label="Private dataset",
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value=True,
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interactive=True,
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scale=1,
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)
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with gr.Row(variant="panel"):
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btn_generate_full_dataset = gr.Button(
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| 362 |
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value="Generate", variant="primary", scale=2
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)
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btn_generate_and_push_to_hub = gr.Button(
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value="Generate and Push to Hub", variant="primary", scale=2
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)
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btn_push_to_hub = gr.Button(value="Push to Hub", variant="primary", scale=2)
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return (
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org_name,
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repo_name,
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private,
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btn_generate_full_dataset,
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btn_generate_and_push_to_hub,
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btn_push_to_hub,
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)
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| 376 |
-
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| 377 |
-
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def push_pipeline_code_to_hub(
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pipeline_code: str,
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org_name: str,
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@@ -455,24 +138,6 @@ def validate_push_to_hub(org_name, repo_name):
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return repo_id
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| 457 |
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| 458 |
-
def get_final_dataset_row(default_datasets) -> gr.Dataframe:
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| 459 |
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with gr.Row():
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| 460 |
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final_dataset = gr.Dataframe(
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| 461 |
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value=default_datasets[0],
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label="Generated dataset",
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interactive=False,
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wrap=True,
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min_width=300,
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)
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return final_dataset
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-
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| 469 |
-
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def get_success_message_row() -> gr.Markdown:
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with gr.Row():
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success_message = gr.Markdown(visible=False)
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return success_message
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| 474 |
-
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| 475 |
-
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def show_success_message(org_name, repo_name) -> gr.Markdown:
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client = get_argilla_client()
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if client is None:
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import io
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import uuid
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+
from typing import List, Union
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import argilla as rg
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import gradio as gr
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from huggingface_hub import HfApi, upload_file
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from distilabel_dataset_generator.utils import (
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get_argilla_client,
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list_orgs,
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)
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TEXTCAT_TASK = "text_classification"
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SFT_TASK = "supervised_fine_tuning"
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| 22 |
def validate_argilla_user_workspace_dataset(
|
| 23 |
dataset_name: str,
|
| 24 |
add_to_existing_dataset: bool = True,
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| 58 |
)
|
| 59 |
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| 61 |
def push_pipeline_code_to_hub(
|
| 62 |
pipeline_code: str,
|
| 63 |
org_name: str,
|
|
|
|
| 138 |
return repo_id
|
| 139 |
|
| 140 |
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| 141 |
def show_success_message(org_name, repo_name) -> gr.Markdown:
|
| 142 |
client = get_argilla_client()
|
| 143 |
if client is None:
|
src/distilabel_dataset_generator/apps/sft.py
CHANGED
|
@@ -28,7 +28,6 @@ from distilabel_dataset_generator.pipelines.sft import (
|
|
| 28 |
get_response_generator,
|
| 29 |
)
|
| 30 |
from distilabel_dataset_generator.utils import (
|
| 31 |
-
_LOGGED_OUT_CSS,
|
| 32 |
get_argilla_client,
|
| 33 |
get_org_dropdown,
|
| 34 |
swap_visibility,
|
|
@@ -350,7 +349,7 @@ def hide_pipeline_code_visibility():
|
|
| 350 |
######################
|
| 351 |
|
| 352 |
|
| 353 |
-
with gr.Blocks(
|
| 354 |
with gr.Column() as main_ui:
|
| 355 |
if not SFT_AVAILABLE:
|
| 356 |
gr.Markdown(
|
|
|
|
| 28 |
get_response_generator,
|
| 29 |
)
|
| 30 |
from distilabel_dataset_generator.utils import (
|
|
|
|
| 31 |
get_argilla_client,
|
| 32 |
get_org_dropdown,
|
| 33 |
swap_visibility,
|
|
|
|
| 349 |
######################
|
| 350 |
|
| 351 |
|
| 352 |
+
with gr.Blocks() as app:
|
| 353 |
with gr.Column() as main_ui:
|
| 354 |
if not SFT_AVAILABLE:
|
| 355 |
gr.Markdown(
|
src/distilabel_dataset_generator/apps/textcat.py
CHANGED
|
@@ -28,7 +28,6 @@ from src.distilabel_dataset_generator.pipelines.textcat import (
|
|
| 28 |
get_textcat_generator,
|
| 29 |
)
|
| 30 |
from src.distilabel_dataset_generator.utils import (
|
| 31 |
-
_LOGGED_OUT_CSS,
|
| 32 |
get_argilla_client,
|
| 33 |
get_org_dropdown,
|
| 34 |
get_preprocess_labels,
|
|
@@ -332,7 +331,7 @@ def hide_pipeline_code_visibility():
|
|
| 332 |
######################
|
| 333 |
|
| 334 |
|
| 335 |
-
with gr.Blocks(
|
| 336 |
with gr.Column() as main_ui:
|
| 337 |
gr.Markdown("## 1. Describe the dataset you want")
|
| 338 |
with gr.Row():
|
|
|
|
| 28 |
get_textcat_generator,
|
| 29 |
)
|
| 30 |
from src.distilabel_dataset_generator.utils import (
|
|
|
|
| 31 |
get_argilla_client,
|
| 32 |
get_org_dropdown,
|
| 33 |
get_preprocess_labels,
|
|
|
|
| 331 |
######################
|
| 332 |
|
| 333 |
|
| 334 |
+
with gr.Blocks() as app:
|
| 335 |
with gr.Column() as main_ui:
|
| 336 |
gr.Markdown("## 1. Describe the dataset you want")
|
| 337 |
with gr.Row():
|
src/distilabel_dataset_generator/utils.py
CHANGED
|
@@ -6,10 +6,7 @@ import gradio as gr
|
|
| 6 |
import numpy as np
|
| 7 |
import pandas as pd
|
| 8 |
from gradio.oauth import (
|
| 9 |
-
|
| 10 |
-
OAUTH_CLIENT_SECRET,
|
| 11 |
-
OAUTH_SCOPES,
|
| 12 |
-
OPENID_PROVIDER_URL,
|
| 13 |
get_space,
|
| 14 |
)
|
| 15 |
from huggingface_hub import whoami
|
|
@@ -17,30 +14,6 @@ from jinja2 import Environment, meta
|
|
| 17 |
|
| 18 |
from distilabel_dataset_generator.constants import argilla_client
|
| 19 |
|
| 20 |
-
_LOGGED_OUT_CSS = ".main_ui_logged_out{opacity: 0.3; pointer-events: none}"
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
_CHECK_IF_SPACE_IS_SET = (
|
| 24 |
-
all(
|
| 25 |
-
[
|
| 26 |
-
OAUTH_CLIENT_ID,
|
| 27 |
-
OAUTH_CLIENT_SECRET,
|
| 28 |
-
OAUTH_SCOPES,
|
| 29 |
-
OPENID_PROVIDER_URL,
|
| 30 |
-
]
|
| 31 |
-
)
|
| 32 |
-
or get_space() is None
|
| 33 |
-
)
|
| 34 |
-
|
| 35 |
-
if _CHECK_IF_SPACE_IS_SET:
|
| 36 |
-
from gradio.oauth import OAuthToken
|
| 37 |
-
else:
|
| 38 |
-
OAuthToken = str
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
def get_login_button():
|
| 42 |
-
return gr.LoginButton(value="Sign in!", size="sm", scale=2).activate()
|
| 43 |
-
|
| 44 |
|
| 45 |
def get_duplicate_button():
|
| 46 |
if get_space() is not None:
|
|
@@ -85,13 +58,6 @@ def get_org_dropdown(oauth_token: Union[OAuthToken, None] = None):
|
|
| 85 |
)
|
| 86 |
|
| 87 |
|
| 88 |
-
def get_token(oauth_token: Union[OAuthToken, None]):
|
| 89 |
-
if oauth_token:
|
| 90 |
-
return oauth_token.token
|
| 91 |
-
else:
|
| 92 |
-
return ""
|
| 93 |
-
|
| 94 |
-
|
| 95 |
def swap_visibility(oauth_token: Union[OAuthToken, None]):
|
| 96 |
if oauth_token:
|
| 97 |
return gr.update(elem_classes=["main_ui_logged_in"])
|
|
@@ -99,28 +65,6 @@ def swap_visibility(oauth_token: Union[OAuthToken, None]):
|
|
| 99 |
return gr.update(elem_classes=["main_ui_logged_out"])
|
| 100 |
|
| 101 |
|
| 102 |
-
def get_base_app():
|
| 103 |
-
with gr.Blocks(
|
| 104 |
-
title="𧬠Synthetic Data Generator",
|
| 105 |
-
head="𧬠Synthetic Data Generator",
|
| 106 |
-
css=_LOGGED_OUT_CSS,
|
| 107 |
-
) as app:
|
| 108 |
-
with gr.Row():
|
| 109 |
-
gr.Markdown(
|
| 110 |
-
"Want to run this locally or with other LLMs? Take a look at the FAQ tab. distilabel Synthetic Data Generator is free, we use the authentication token to push the dataset to the Hugging Face Hub and not for data generation."
|
| 111 |
-
)
|
| 112 |
-
with gr.Row():
|
| 113 |
-
gr.Column()
|
| 114 |
-
get_login_button()
|
| 115 |
-
gr.Column()
|
| 116 |
-
|
| 117 |
-
gr.Markdown("## Iterate on a sample dataset")
|
| 118 |
-
with gr.Column() as main_ui:
|
| 119 |
-
pass
|
| 120 |
-
|
| 121 |
-
return app
|
| 122 |
-
|
| 123 |
-
|
| 124 |
def get_argilla_client() -> Union[rg.Argilla, None]:
|
| 125 |
return argilla_client
|
| 126 |
|
|
|
|
| 6 |
import numpy as np
|
| 7 |
import pandas as pd
|
| 8 |
from gradio.oauth import (
|
| 9 |
+
OAuthToken,
|
|
|
|
|
|
|
|
|
|
| 10 |
get_space,
|
| 11 |
)
|
| 12 |
from huggingface_hub import whoami
|
|
|
|
| 14 |
|
| 15 |
from distilabel_dataset_generator.constants import argilla_client
|
| 16 |
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
|
| 17 |
|
| 18 |
def get_duplicate_button():
|
| 19 |
if get_space() is not None:
|
|
|
|
| 58 |
)
|
| 59 |
|
| 60 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 61 |
def swap_visibility(oauth_token: Union[OAuthToken, None]):
|
| 62 |
if oauth_token:
|
| 63 |
return gr.update(elem_classes=["main_ui_logged_in"])
|
|
|
|
| 65 |
return gr.update(elem_classes=["main_ui_logged_out"])
|
| 66 |
|
| 67 |
|
|
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|
| 68 |
def get_argilla_client() -> Union[rg.Argilla, None]:
|
| 69 |
return argilla_client
|
| 70 |
|