Initial project

.gitattributes

@@ -33,3 +33,5 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+# SCM syntax highlighting
+pixi.lock linguist-language=YAML linguist-generated=true

.gitignore

@@ -0,0 +1,172 @@
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Translations
+*.mo
+*.pot
+
+# Django stuff:
+*.log
+local_settings.py
+db.sqlite3
+db.sqlite3-journal
+
+# Flask stuff:
+instance/
+.webassets-cache
+
+# Scrapy stuff:
+.scrapy
+
+# Sphinx documentation
+docs/_build/
+
+# PyBuilder
+.pybuilder/
+target/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+# pyenv
+#   For a library or package, you might want to ignore these files since the code is
+#   intended to run in multiple environments; otherwise, check them in:
+# .python-version
+
+# pipenv
+#   According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
+#   However, in case of collaboration, if having platform-specific dependencies or dependencies
+#   having no cross-platform support, pipenv may install dependencies that don't work, or not
+#   install all needed dependencies.
+#Pipfile.lock
+
+# poetry
+#   Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
+#   This is especially recommended for binary packages to ensure reproducibility, and is more
+#   commonly ignored for libraries.
+#   https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
+#poetry.lock
+
+# pdm
+#   Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
+#pdm.lock
+#   pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
+#   in version control.
+#   https://pdm.fming.dev/latest/usage/project/#working-with-version-control
+.pdm.toml
+.pdm-python
+.pdm-build/
+
+# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
+__pypackages__/
+
+# Celery stuff
+celerybeat-schedule
+celerybeat.pid
+
+# SageMath parsed files
+*.sage.py
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/
+
+# Spyder project settings
+.spyderproject
+.spyproject
+
+# Rope project settings
+.ropeproject
+
+# mkdocs documentation
+/site
+
+# mypy
+.mypy_cache/
+.dmypy.json
+dmypy.json
+
+# Pyre type checker
+.pyre/
+
+# pytype static type analyzer
+.pytype/
+
+# Cython debug symbols
+cython_debug/
+
+# PyCharm
+#  JetBrains specific template is maintained in a separate JetBrains.gitignore that can
+#  be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
+#  and can be added to the global gitignore or merged into this file.  For a more nuclear
+#  option (not recommended) you can uncomment the following to ignore the entire idea folder.
+#.idea/
+
+# HuggingFace
+.cache/
+
+# CUSTOM
+*.db
+
+# pixi environments
+.pixi
+*.egg-info

.vscode/settings.json

@@ -0,0 +1,6 @@
+{
+  "editor.codeActionsOnSave": {
+    "source.organizeImports": "explicit",
+    "source.fixAll": "explicit"
+  }
+}

README.md

@@ -1,14 +1,23 @@
 ---
-title: Open Llm Leaderboard Results To Modelcard
-emoji: 🌖
-colorFrom: red
+title: Open LLM Leaderboard Results To Modelcard
+emoji: 🧐
+colorFrom: green
 colorTo: yellow
 sdk: gradio
 sdk_version: 5.7.1
+python_version: 3.12
 app_file: app.py
 pinned: false
 license: apache-2.0
 short_description: Adds Open LLM Leaderboard results to a target modelcard
+hf_oauth: true
+hf_oauth_scopes:
+- read-repos
+- write-discussions
+space_ci:
+  trusted_authors: []
+  secrets: []
+  hardware: cpu-basic
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,76 @@
+import os
+import time
+os.system("wget https://raw.githubusercontent.com/Weyaxi/scrape-open-llm-leaderboard/main/openllm.py")
+from huggingface_hub import HfApi, HfFileSystem
+import time
+import pandas as pd
+import threading
+import gradio as gr
+from gradio_space_ci import enable_space_ci
+from functions import commit
+
+enable_space_ci()
+
+HF_TOKEN = os.getenv('HF_TOKEN')
+BOT_HF_TOKEN = os.getenv('BOT_HF_TOKEN')
+
+
+api = HfApi()
+fs = HfFileSystem()
+
+def refresh(how_much=43200): # default to 12 hour
+  time.sleep(how_much)
+  try:
+      api.restart_space(repo_id="Weyaxi/leaderboard-results-to-modelcard")
+  except Exception as e:
+      print(f"Error while scraping leaderboard, trying again... {e}")
+      refresh(600) # 10 minutes if any error happens
+
+gradio_title="🧐 Open LLM Leaderboard Results PR Opener"
+gradio_desc= """🎯 This tool's aim is to provide [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) results in the model card.
+
+## 💭 What Does This Tool Do:
+
+- This tool adds the [Open LLM Leaderboard](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard) result of your model at the end of your model card.
+
+- This tool also adds evaluation results as your model's metadata to showcase the evaluation results as a widget.
+
+## 🛠️ Backend
+
+The leaderboard's backend mainly runs on the [Hugging Face Hub API](https://huggingface.co/docs/huggingface_hub/v0.5.1/en/package_reference/hf_api).
+
+## 🤝 Acknowledgements
+
+- Special thanks to [Clémentine Fourrier (clefourrier)](https://huggingface.co/clefourrier) for her help and contributions to the code.
+
+- Special thanks to [Lucain Pouget (Wauplin)](https://huggingface.co/Wauplin) for assisting with the [Hugging Face Hub API](https://huggingface.co/docs/huggingface_hub/v0.5.1/en/package_reference/hf_api).
+"""
+
+with gr.Blocks() as demo:
+    gr.HTML(f"""<h1 align="center" id="space-title">{gradio_title}</h1>""")
+    gr.HTML(f"""<h1 align="center" id="space-title" style="font-weight: bold; font-size: 40px; color: red;">DON'T SPAM MODELS!</h1>""")
+    gr.HTML(f"""<h1 align="center" id="space-title" style="font-weight: bold; font-size: 25px; color: red;">I understand why you are angry, but spamming won't change anything!</h1>""")
+    
+    gr.Markdown(gradio_desc)
+
+    with gr.Row(equal_height=False):
+        with gr.Column():
+            model_id = gr.Textbox(label="Model ID or URL", lines=1)
+            gr.LoginButton()
+
+        with gr.Column():
+            output = gr.Textbox(label="Output", lines=1)
+        
+    submit_btn = gr.Button("Submit", variant="primary")   
+    
+    def validate_model_id(input_id, oauth_token: gr.OAuthToken):
+        if "mattshumer/" in input_id:
+            gr.Error("DON'T, DON'T SPAM THAT MODELS")
+            return "DON'T, DON'T SPAM THAT MODELS"
+        else:
+            return commit(input_id, oauth_token=oauth_token.token)
+
+    submit_btn.click(validate_model_id, model_id, output)
+
+threading.Thread(target=refresh).start()
+demo.launch()

functions.py

@@ -0,0 +1,223 @@
+import os
+
+import gradio as gr
+import pandas as pd
+from huggingface_hub import (
+    CommitOperationAdd,
+    EvalResult,
+    ModelCard,
+    RepoUrl,
+    create_commit,
+)
+from huggingface_hub.repocard_data import eval_results_to_model_index
+from pytablewriter import MarkdownTableWriter
+
+from openllm import get_datas, get_json_format_data
+
+BOT_HF_TOKEN = os.getenv("BOT_HF_TOKEN")
+
+
+def search(df, value):
+    result_df = df[df["Model"] == value]
+    return result_df.iloc[0].to_dict() if not result_df.empty else None
+
+
+def get_details_url(repo):
+    author, model = repo.split("/")
+    return f"https://huggingface.co/datasets/open-llm-leaderboard/{author}__{model}-details"
+
+
+def get_query_url(repo):
+    return f"https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query={repo}"
+
+
+def get_task_summary(results):
+    return {
+        "IFEval": {
+            "dataset_type": "HuggingFaceH4/ifeval",
+            "dataset_name": "IFEval (0-Shot)",
+            "metric_type": "inst_level_strict_acc and prompt_level_strict_acc",
+            "metric_value": results["IFEval"],
+            "dataset_config": None,  # don't know
+            "dataset_split": None,  # don't know
+            "dataset_revision": None,
+            "dataset_args": {"num_few_shot": 0},
+            "metric_name": "strict accuracy",
+        },
+        "BBH": {
+            "dataset_type": "BBH",
+            "dataset_name": "BBH (3-Shot)",
+            "metric_type": "acc_norm",
+            "metric_value": results["BBH"],
+            "dataset_config": None,  # don't know
+            "dataset_split": None,  # don't know
+            "dataset_revision": None,
+            "dataset_args": {"num_few_shot": 3},
+            "metric_name": "normalized accuracy",
+        },
+        "MATH Lvl 5": {
+            "dataset_type": "hendrycks/competition_math",
+            "dataset_name": "MATH Lvl 5 (4-Shot)",
+            "metric_type": "exact_match",
+            "metric_value": results["MATH Lvl 5"],
+            "dataset_config": None,  # don't know
+            "dataset_split": None,  # don't know
+            "dataset_revision": None,
+            "dataset_args": {"num_few_shot": 4},
+            "metric_name": "exact match",
+        },
+        "GPQA": {
+            "dataset_type": "Idavidrein/gpqa",
+            "dataset_name": "GPQA (0-shot)",
+            "metric_type": "acc_norm",
+            "metric_value": results["GPQA"],
+            "dataset_config": None,  # don't know
+            "dataset_split": None,  # don't know
+            "dataset_revision": None,
+            "dataset_args": {"num_few_shot": 0},
+            "metric_name": "acc_norm",
+        },
+        "MuSR": {
+            "dataset_type": "TAUR-Lab/MuSR",
+            "dataset_name": "MuSR (0-shot)",
+            "metric_type": "acc_norm",
+            "metric_value": results["MUSR"],
+            "dataset_config": None,  # don't know
+            "dataset_split": None,  # don't know
+            "dataset_args": {"num_few_shot": 0},
+            "metric_name": "acc_norm",
+        },
+        "MMLU-PRO": {
+            "dataset_type": "TIGER-Lab/MMLU-Pro",
+            "dataset_name": "MMLU-PRO (5-shot)",
+            "metric_type": "acc",
+            "metric_value": results["MMLU-PRO"],
+            "dataset_config": "main",
+            "dataset_split": "test",
+            "dataset_args": {"num_few_shot": 5},
+            "metric_name": "accuracy",
+        },
+    }
+
+
+def get_eval_results(df, repo):
+    results = search(df, repo)
+    task_summary = get_task_summary(results)
+    md_writer = MarkdownTableWriter()
+    md_writer.headers = ["Metric", "Value"]
+    md_writer.value_matrix = [["Avg.", results["Average ⬆️"]]] + [
+        [v["dataset_name"], v["metric_value"]] for v in task_summary.values()
+    ]
+
+    text = f"""
+# [Open LLM Leaderboard Evaluation Results](https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard)
+Detailed results can be found [here]({get_details_url(repo)})
+
+{md_writer.dumps()}
+"""
+    return text
+
+
+def get_edited_yaml_readme(df, repo, token: str | None):
+    card = ModelCard.load(repo, token=token)
+    results = search(df, repo)
+
+    common = {
+        "task_type": "text-generation",
+        "task_name": "Text Generation",
+        "source_name": "Open LLM Leaderboard",
+        "source_url": f"https://huggingface.co/spaces/open-llm-leaderboard/open_llm_leaderboard?query={repo}",
+    }
+
+    tasks_results = get_task_summary(results)
+
+    if not card.data[
+        "eval_results"
+    ]:  # No results reported yet, we initialize the metadata
+        card.data["model-index"] = eval_results_to_model_index(
+            repo.split("/")[1],
+            [EvalResult(**task, **common) for task in tasks_results.values()],
+        )
+    else:  # We add the new evaluations
+        for task in tasks_results.values():
+            cur_result = EvalResult(**task, **common)
+            if any(
+                result.is_equal_except_value(cur_result)
+                for result in card.data["eval_results"]
+            ):
+                continue
+            card.data["eval_results"].append(cur_result)
+
+    return str(card)
+
+
+def commit(
+    repo,
+    pr_number=None,
+    message="Adding Evaluation Results",
+    oauth_token: gr.OAuthToken | None = None,
+):  # specify pr number if you want to edit it, don't if you don't want
+    data = get_json_format_data()
+    finished_models = get_datas(data)
+    df = pd.DataFrame(finished_models)
+
+    desc = """
+  This is an automated PR created with https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr
+
+  The purpose of this PR is to add evaluation results from the Open LLM Leaderboard to your model card.
+
+  Please report any issues here: https://huggingface.co/spaces/Weyaxi/open-llm-leaderboard-results-pr/discussions
+  """
+
+    if not oauth_token:
+        raise gr.Warning(
+            "You are not logged in. Click on 'Sign in with Huggingface' to log in."
+        )
+    else:
+        token = oauth_token
+
+    if repo.startswith("https://huggingface.co/"):
+        try:
+            repo = RepoUrl(repo).repo_id
+        except Exception:
+            raise gr.Error(f"Not a valid repo id: {str(repo)}")
+
+    edited = {"revision": f"refs/pr/{pr_number}"} if pr_number else {"create_pr": True}
+
+    try:
+        try:  # check if there is a readme already
+            readme_text = get_edited_yaml_readme(
+                df, repo, token=token
+            ) + get_eval_results(df, repo)
+        except Exception as e:
+            if "Repo card metadata block was not found." in str(e):  # There is no readme
+                readme_text = get_edited_yaml_readme(df, repo, token=token)
+            else:
+                print(f"Something went wrong: {e}")
+
+        liste = [
+            CommitOperationAdd(
+                path_in_repo="README.md", path_or_fileobj=readme_text.encode()
+            )
+        ]
+        commit = create_commit(
+            repo_id=repo,
+            token=token,
+            operations=liste,
+            commit_message=message,
+            commit_description=desc,
+            repo_type="model",
+            **edited,
+        ).pr_url
+
+        return commit
+
+    except Exception as e:
+        if "Discussions are disabled for this repo" in str(e):
+            return "Discussions disabled"
+        elif "Cannot access gated repo" in str(e):
+            return "Gated repo"
+        elif "Repository Not Found" in str(e):
+            return "Repository Not Found"
+        else:
+            return e

openllm.py

@@ -0,0 +1,59 @@
+import json
+
+import requests
+from bs4 import BeautifulSoup
+
+
+def get_json_format_data():
+    url = "https://open-llm-leaderboard-open-llm-leaderboard.hf.space/"
+    response = requests.get(url)
+    soup = BeautifulSoup(response.content, "html.parser")
+
+    script_elements = soup.find_all("script")
+    json_format_data = json.loads(str(script_elements[1])[31:-10])
+    return json_format_data
+
+
+def get_datas(data):
+    for component_index in range(
+        0, 50, 1
+    ):  # component_index sometimes changes when they update the space, we can use this "for" loop to avoid changing component index manually
+        try:
+            result_list = []
+            i = 0
+            columns = data["components"][component_index]["props"]["headers"]
+
+            while True:
+                try:
+                    results = data["components"][component_index]["props"]["value"]["data"][i]
+
+                    model_fullname_index = (
+                        columns.index("fullname")
+                        if "fullname" in [col.lower() for col in columns]
+                        else -3
+                    )  # Will be used when we extract the model name from the data
+
+                    try:
+                        results_json = {
+                            "T": results[0],
+                            "Model": results[model_fullname_index],
+                        }  # Set the first 2 manually because normally there is a link in the "Model" column
+
+                        if (
+                            len(columns) < 20
+                        ):  # If there are less than 20 columns (this number can definetly change), we know that we are trying wrong component index, so breaking loop to try next component index.
+                            break
+
+                        for col_index, col_name in enumerate(columns[2:], start=2):
+                            results_json[col_name] = results[col_index]
+
+                    except IndexError:  # Wrong component index, so breaking loop to try next component index. (NOTE: More than one component index can give you some results but we must find the right component index to get all results we want.)
+                        break
+                    result_list.append(results_json)
+                    i += 1
+                except IndexError:  # No rows to extract so return the list (We know it is the right component index because we didn't break out of loop on the other exception.)
+                    return result_list
+        except (KeyError, TypeError):
+            continue
+
+    return result_list

pixi.lock

@@ -0,0 +1,1634 @@
+version: 5
+environments:
+  default:
+    channels:
+    - url: https://conda.anaconda.org/conda-forge/
+    - url: https://conda.anaconda.org/huggingface/
+    indexes:
+    - https://pypi.org/simple
+    packages:
+      win-64:
+      - conda: https://conda.anaconda.org/conda-forge/win-64/brotli-python-1.1.0-py310h9e98ed7_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/bzip2-1.0.8-h2466b09_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/ca-certificates-2024.8.30-h56e8100_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2024.8.30-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/cffi-1.17.1-py310ha8f682b_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.4.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/colorama-0.4.6-pyhd8ed1ab_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/filelock-3.16.1-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/fsspec-2024.10.0-pyhff2d567_0.conda
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+      - conda: https://conda.anaconda.org/conda-forge/noarch/hpack-4.0.0-pyh9f0ad1d_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/huggingface_hub-0.26.2-pyh0610db2_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/hyperframe-6.0.1-pyhd8ed1ab_0.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/noarch/idna-3.10-pyhd8ed1ab_0.conda
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+      - conda: https://conda.anaconda.org/conda-forge/win-64/libzlib-1.3.1-h2466b09_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/openssl-3.4.0-h2466b09_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/packaging-24.2-pyhff2d567_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pycparser-2.22-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyh0701188_6.tar.bz2
+      - conda: https://conda.anaconda.org/conda-forge/win-64/python-3.10.15-hfaddaf0_2_cpython.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/python_abi-3.10-5_cp310.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/pyyaml-6.0.2-py310ha8f682b_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/requests-2.32.3-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/ruff-0.8.1-py310he03e3bc_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/win-64/tk-8.6.13-h5226925_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/tqdm-4.67.1-pyhd8ed1ab_0.conda
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+  url: https://conda.anaconda.org/conda-forge/win-64/xz-5.2.6-h8d14728_0.tar.bz2
+  sha256: 54d9778f75a02723784dc63aff4126ff6e6749ba21d11a6d03c1f4775f269fe0
+  md5: 515d77642eaa3639413c6b1bc3f94219
+  depends:
+  - vc >=14.1,<15
+  - vs2015_runtime >=14.16.27033
+  license: LGPL-2.1 and GPL-2.0
+  purls: []
+  size: 217804
+  timestamp: 1660346976440
+- kind: conda
+  name: yaml
+  version: 0.2.5
+  build: h8ffe710_2
+  build_number: 2
+  subdir: win-64
+  url: https://conda.anaconda.org/conda-forge/win-64/yaml-0.2.5-h8ffe710_2.tar.bz2
+  sha256: 4e2246383003acbad9682c7c63178e2e715ad0eb84f03a8df1fbfba455dfedc5
+  md5: adbfb9f45d1004a26763652246a33764
+  depends:
+  - vc >=14.1,<15.0a0
+  - vs2015_runtime >=14.16.27012
+  license: MIT
+  license_family: MIT
+  purls: []
+  size: 63274
+  timestamp: 1641347623319
+- kind: conda
+  name: zstandard
+  version: 0.23.0
+  build: py310he5e10e1_1
+  build_number: 1
+  subdir: win-64
+  url: https://conda.anaconda.org/conda-forge/win-64/zstandard-0.23.0-py310he5e10e1_1.conda
+  sha256: 4e8aff4d0d42024e9f70783e51666186a681384d59fdd03fafda4b28f1fd540e
+  md5: 2a879227ccc1a10a2caddf12607ffaeb
+  depends:
+  - cffi >=1.11
+  - python >=3.10,<3.11.0a0
+  - python_abi 3.10.* *_cp310
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  - zstd >=1.5.6,<1.5.7.0a0
+  - zstd >=1.5.6,<1.6.0a0
+  license: BSD-3-Clause
+  license_family: BSD
+  purls:
+  - pkg:pypi/zstandard?source=hash-mapping
+  size: 311278
+  timestamp: 1725306039901
+- kind: conda
+  name: zstd
+  version: 1.5.6
+  build: h0ea2cb4_0
+  subdir: win-64
+  url: https://conda.anaconda.org/conda-forge/win-64/zstd-1.5.6-h0ea2cb4_0.conda
+  sha256: 768e30dc513568491818fb068ee867c57c514b553915536da09e5d10b4ebf3c3
+  md5: 9a17230f95733c04dc40a2b1e5491d74
+  depends:
+  - libzlib >=1.2.13,<2.0.0a0
+  - ucrt >=10.0.20348.0
+  - vc >=14.2,<15
+  - vc14_runtime >=14.29.30139
+  license: BSD-3-Clause
+  license_family: BSD
+  purls: []
+  size: 349143
+  timestamp: 1714723445995

pixi.toml

@@ -0,0 +1,44 @@
+[project]
+channels = ["conda-forge", "huggingface"]
+description = "Add a short description here"
+name = "open-llm-leaderboard-results-to-modelcard"
+platforms = ["win-64"]
+version = "0.1.0"
+
+[tasks]
+
+[dependencies]
+python = "3.10.*"
+huggingface_hub = ">=0.26.2,<0.27"
+ruff = ">=0.8.1,<0.9"
+
+[pypi-dependencies]
+gradio = "==5.7.1"
+pytablewriter = ">=1.2.0, <2"
+gradio-space-ci = { git = "https://huggingface.co/spaces/Wauplin/gradio-space-ci", rev = "0.2.3" }
+beautifulsoup4 = ">=4.12.3, <5"
+
+[tool.ruff]
+exclude = [".pixi", "__pycache__"]
+ignore = ["E501", "E402"]
+select = [
+    # pycodestyle
+    "E",
+    # Pyflakes
+    "F",
+    # Warnings
+    "W",
+    # isort
+    "I",
+    # pyupgrade
+    "UP",
+    # flake8-bugbear
+    "B",
+    # flake8-simplify
+    "SIM",
+    # flake8-quotes
+    "Q",
+    # flake8-async
+    "ASYNC"
+]
+line-length = 132