From ae923771a93d088e974589f0af3ac9142014612c Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Tue, 3 Dec 2024 12:23:49 +0100 Subject: [PATCH 1/4] update readme pypi downlaods --- README.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index eefe374..b1e48c3 100644 --- a/README.md +++ b/README.md @@ -32,7 +32,7 @@ hf_oauth_scopes: CI -CI +CI @@ -84,7 +84,7 @@ pip install synthetic-dataset-generator - `ARGILLA_API_KEY`: Your Argilla API key to push your datasets to Argilla. - `ARGILLA_API_URL`: Your Argilla API URL to push your datasets to Argilla. -## Quick Start +## Quickstart ```bash python app.py From 88a4065ec0da9299e84496b3f3b040e21860b705 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Tue, 3 Dec 2024 12:32:17 +0100 Subject: [PATCH 2/4] add support for running without argilla --- src/distilabel_dataset_generator/apps/eval.py | 25 +++++++++++-------- src/distilabel_dataset_generator/apps/sft.py | 4 ++- .../apps/textcat.py | 16 ++++++------ 3 files changed, 26 insertions(+), 19 deletions(-) diff --git a/src/distilabel_dataset_generator/apps/eval.py b/src/distilabel_dataset_generator/apps/eval.py index f415760..6e4a60a 100644 --- a/src/distilabel_dataset_generator/apps/eval.py +++ b/src/distilabel_dataset_generator/apps/eval.py @@ -39,9 +39,9 @@ extract_column_names, get_argilla_client, get_org_dropdown, + pad_or_truncate_list, process_columns, swap_visibility, - pad_or_truncate_list, ) @@ -334,8 +334,10 @@ def push_dataset( push_dataset_to_hub(dataframe, org_name, repo_name, oauth_token, private) try: progress(0.1, desc="Setting up user and workspace") - client = get_argilla_client() hf_user = HfApi().whoami(token=oauth_token.token)["name"] + client = get_argilla_client() + if client is None: + return "" if eval_type == "ultrafeedback": num_generations = len((dataframe["generations"][0])) fields = [ @@ -580,6 +582,7 @@ def push_dataset( def show_pipeline_code_visibility(): return {pipeline_code_ui: gr.Accordion(visible=True)} + def hide_pipeline_code_visibility(): return {pipeline_code_ui: gr.Accordion(visible=False)} @@ -708,15 +711,15 @@ def hide_pipeline_code_visibility(): visible=False, ) as pipeline_code_ui: code = generate_pipeline_code( - repo_id=search_in.value, - aspects=aspects_instruction_response.value, - instruction_column=instruction_instruction_response, - response_columns=response_instruction_response, - prompt_template=prompt_template.value, - structured_output=structured_output.value, - num_rows=num_rows.value, - eval_type=eval_type.value, - ) + repo_id=search_in.value, + aspects=aspects_instruction_response.value, + instruction_column=instruction_instruction_response, + response_columns=response_instruction_response, + prompt_template=prompt_template.value, + structured_output=structured_output.value, + num_rows=num_rows.value, + eval_type=eval_type.value, + ) pipeline_code = gr.Code( value=code, language="python", diff --git a/src/distilabel_dataset_generator/apps/sft.py b/src/distilabel_dataset_generator/apps/sft.py index 0e9986b..fad57d1 100644 --- a/src/distilabel_dataset_generator/apps/sft.py +++ b/src/distilabel_dataset_generator/apps/sft.py @@ -220,8 +220,10 @@ def push_dataset( push_dataset_to_hub(dataframe, org_name, repo_name, oauth_token, private) try: progress(0.1, desc="Setting up user and workspace") - client = get_argilla_client() hf_user = HfApi().whoami(token=oauth_token.token)["name"] + client = get_argilla_client() + if client is None: + return "" if "messages" in dataframe.columns: settings = rg.Settings( fields=[ diff --git a/src/distilabel_dataset_generator/apps/textcat.py b/src/distilabel_dataset_generator/apps/textcat.py index e40464e..2666d0a 100644 --- a/src/distilabel_dataset_generator/apps/textcat.py +++ b/src/distilabel_dataset_generator/apps/textcat.py @@ -58,7 +58,10 @@ def generate_system_prompt(dataset_description, temperature, progress=gr.Progres labels = data["labels"] return system_prompt, labels -def generate_sample_dataset(system_prompt, difficulty, clarity, labels, num_labels, progress=gr.Progress()): + +def generate_sample_dataset( + system_prompt, difficulty, clarity, labels, num_labels, progress=gr.Progress() +): dataframe = generate_dataset( system_prompt=system_prompt, difficulty=difficulty, @@ -138,11 +141,7 @@ def generate_dataset( # create final dataset distiset_results = [] for result in labeller_results: - record = { - key: result[key] - for key in ["labels", "text"] - if key in result - } + record = {key: result[key] for key in ["labels", "text"] if key in result} distiset_results.append(record) dataframe = pd.DataFrame(distiset_results) @@ -212,13 +211,16 @@ def push_dataset( push_dataset_to_hub( dataframe, org_name, repo_name, num_labels, labels, oauth_token, private ) + dataframe = dataframe[ (dataframe["text"].str.strip() != "") & (dataframe["text"].notna()) ] try: progress(0.1, desc="Setting up user and workspace") - client = get_argilla_client() hf_user = HfApi().whoami(token=oauth_token.token)["name"] + client = get_argilla_client() + if client is None: + return "" labels = get_preprocess_labels(labels) settings = rg.Settings( fields=[ From 5c6644f8947f0e7384f73ce34ff10b6fa6dca262 Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Tue, 3 Dec 2024 12:37:26 +0100 Subject: [PATCH 3/4] update success message based on argilla availability --- src/distilabel_dataset_generator/apps/base.py | 21 +++++++++++++++++++ 1 file changed, 21 insertions(+) diff --git a/src/distilabel_dataset_generator/apps/base.py b/src/distilabel_dataset_generator/apps/base.py index 4027954..0b6cc4f 100644 --- a/src/distilabel_dataset_generator/apps/base.py +++ b/src/distilabel_dataset_generator/apps/base.py @@ -475,6 +475,27 @@ def get_success_message_row() -> gr.Markdown: def show_success_message(org_name, repo_name) -> gr.Markdown: client = get_argilla_client() + if client is None: + return gr.Markdown( + value=""" +
+

Dataset Published Successfully!

+

+ The generated dataset is in the right format for fine-tuning with TRL, AutoTrain, or other frameworks. Your dataset is now available at: + + https://huggingface.co/datasets/{org_name}/{repo_name} + +

+

+ By configuring an `ARGILLA_API_URL` and `ARGILLA_API_KEY` you can curate the dataset in Argilla. + Unfamiliar with Argilla? Here are some docs to help you get started: +
How to get started with Argilla +
How to curate data in Argilla +
How to export data once you have reviewed the dataset +

+
+ """ + ) argilla_api_url = client.api_url return gr.Markdown( value=f""" From 2cf2cd7dd7bd40795b68622b3d5bc762cdbd709e Mon Sep 17 00:00:00 2001 From: davidberenstein1957 Date: Tue, 3 Dec 2024 12:49:19 +0100 Subject: [PATCH 4/4] add section on Argilla integration --- README.md | 11 ++++++++++- assets/argilla.png | Bin 0 -> 474983 bytes 2 files changed, 10 insertions(+), 1 deletion(-) create mode 100644 assets/argilla.png diff --git a/README.md b/README.md index b1e48c3..16c61ad 100644 --- a/README.md +++ b/README.md @@ -80,7 +80,10 @@ pip install synthetic-dataset-generator ### Environment Variables -- `HF_TOKEN`: Your Hugging Face token to push your datasets to the Hugging Face Hub and run Inference Endpoints Requests. You can get one [here](https://huggingface.co/settings/tokens/new?ownUserPermissions=repo.content.read&ownUserPermissions=repo.write&globalPermissions=inference.serverless.write&tokenType=fineGrained). +- `HF_TOKEN`: Your Hugging Face token to push your datasets to the Hugging Face Hub and run *Free* Inference Endpoints Requests. You can get one [here](https://huggingface.co/settings/tokens/new?ownUserPermissions=repo.content.read&ownUserPermissions=repo.write&globalPermissions=inference.serverless.write&tokenType=fineGrained). + +Optionally, you can also push your datasets to Argilla for further curation by setting the following environment variables: + - `ARGILLA_API_KEY`: Your Argilla API key to push your datasets to Argilla. - `ARGILLA_API_URL`: Your Argilla API URL to push your datasets to Argilla. @@ -90,6 +93,12 @@ pip install synthetic-dataset-generator python app.py ``` +### Argilla integration + +Argilla is a open source tool for data curation. It allows you to annotate and review datasets, and push curated datasets to the Hugging Face Hub. You can easily get started with Argilla by following the [quickstart guide](https://docs.argilla.io/latest/getting_started/quickstart/). + +![Argilla integration](https://huggingface.co/spaces/argilla/synthetic-data-generator/resolve/main/assets/argilla.png) + ## Custom synthetic data generation? 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