From 8eee3800a5c2d32ca861105d549f3d969bca14c5 Mon Sep 17 00:00:00 2001
From: Pierre Andrews <628467+Mortimerp9@users.noreply.github.com>
Date: Wed, 11 Dec 2024 09:55:11 +0000
Subject: [PATCH] move to uv for deps on fairseq2 + lint/format

---
 .github/actions/setup/action.yaml             |   11 +
 .github/workflows/lint_and_test.yml           |  159 +-
 .pre-commit-config.yaml                       |   16 +
 examples/bilingual_document.ipynb             |  150 +-
 examples/inference_pipelines.ipynb            |   58 +-
 examples/mutox_example.ipynb                  |   71 +-
 examples/sonar_text_demo.ipynb                |  116 +-
 huggingface_pipelines/audio.py                |    3 -
 huggingface_pipelines/text.py                 |    1 -
 pyproject.toml                                |   74 +-
 requirements-dev.txt                          |   12 -
 requirements.txt                              |    9 -
 sonar/__init__.py                             |    3 +-
 sonar/inference_pipelines/mutox_speech.py     |    1 -
 sonar/inference_pipelines/speech.py           |    4 +-
 sonar/inference_pipelines/utils.py            |    3 +-
 sonar/models/mutox/builder.py                 |    1 -
 sonar/models/mutox/classifier.py              |    2 -
 sonar/models/mutox/loader.py                  |    2 +-
 sonar/models/sonar_speech/loader.py           |   58 +-
 sonar/models/sonar_text/loader.py             |    2 -
 .../unit_tests/huggingface_pipelines/audio.py |    2 +-
 .../test_low_dimension_text_models.py         |    1 -
 uv.lock                                       | 2612 +++++++++++++++++
 24 files changed, 2990 insertions(+), 381 deletions(-)
 create mode 100644 .github/actions/setup/action.yaml
 create mode 100644 .pre-commit-config.yaml
 delete mode 100644 requirements-dev.txt
 delete mode 100644 requirements.txt
 create mode 100644 uv.lock

diff --git a/.github/actions/setup/action.yaml b/.github/actions/setup/action.yaml
new file mode 100644
index 0000000..488a190
--- /dev/null
+++ b/.github/actions/setup/action.yaml
@@ -0,0 +1,11 @@
+runs:
+  using: composite
+  steps:
+    - name: "Install UV"
+      shell: bash
+      run: |
+        curl -LsSf https://astral.sh/uv/install.sh | sh
+    - name: "Install libsndfile"
+      shell: bash
+      run: |
+        sudo apt-get install libsndfile1 python3-distutils
\ No newline at end of file
diff --git a/.github/workflows/lint_and_test.yml b/.github/workflows/lint_and_test.yml
index c73d227..6cbaa44 100644
--- a/.github/workflows/lint_and_test.yml
+++ b/.github/workflows/lint_and_test.yml
@@ -1,135 +1,52 @@
-# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
-# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python
-
-name: Python package
+name: Lint Python Code
 
 on:
+  # Trigger the workflow on push to master or any pull request
   push:
-    branches: ["main"]
   pull_request:
-    branches: ["main"]
+    branches:
+      - main
 
 jobs:
-  linter:
+  lock_file:
     runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.8"]
-
     steps:
-      - uses: actions/checkout@v3
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v3
-        with:
-          python-version: ${{ matrix.python-version }}
-          cache: "pip"
-      - name: Install dependencies
-        run: |
-          sudo apt-get install libsndfile1
-          python -m pip install --upgrade pip
-          python -m pip install fairseq2n==0.3.0rc1+cpu --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install fairseq2==0.3.0rc1 --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install -r requirements.txt
-          python -m pip install -r requirements-dev.txt
-          python -m pip install -e .
-      - name: Lint with flake8
-        run: |
-          # stop the build if there are Python syntax errors or undefined names
-          flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
-          # exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
-          flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
-      - name: isort
-        run: isort --check --diff .
-      - name: black
-        run: black --check --diff .
-
-  mypy:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/setup
+      - run: uv lock --locked
+  linting:
     runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.10"]
+    needs: [lock_file]
     steps:
-      - uses: actions/checkout@v3
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v3
-        with:
-          python-version: ${{ matrix.python-version }}
-          cache: "pip"
-      - name: Install dependencies
-        run: |
-          sudo apt-get install libsndfile1
-          python -m pip install --upgrade pip          
-          python -m pip install fairseq2n==0.3.0rc1+cpu --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install fairseq2==0.3.0rc1 --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install -r requirements.txt
-          python -m pip install -r requirements-dev.txt
-          python -m pip install -e .
-      - name: mypy
-        run: mypy --install-types --non-interactive ./ --cache-dir=.mypy_cache/
-
-  unit_test:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/setup
+      - run: uvx ruff check .
+  formatting:
     runs-on: ubuntu-latest
-    timeout-minutes: 20
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.8"]
+    needs: [lock_file]
     steps:
-      - uses: actions/checkout@v3
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v3
-        with:
-          python-version: ${{ matrix.python-version }}
-          cache: "pip"
-      - name: Install dependencies
-        run: |
-          sudo apt-get install libsndfile1          
-          python -m pip install fairseq2n==0.3.0rc1+cpu --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install fairseq2==0.3.0rc1 --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install -r requirements.txt
-          python -m pip install -r requirements-dev.txt
-          python -m pip install -e .
-      - name: pytest_unit
-        run: pytest -s -v tests/unit_tests/
-
-  integration_test:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/setup
+      - run: uvx ruff check --select I .
+      - run: uvx ruff format --check .
+  type_consistency:
     runs-on: ubuntu-latest
-    strategy:
-      fail-fast: false
-      matrix:
-        python-version: ["3.8"]
-    timeout-minutes: 40
+    needs: [lock_file]
     steps:
-      - uses: actions/checkout@v3
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v3
-        with:
-          python-version: ${{ matrix.python-version }}
-          cache: "pip"
-      - name: Install dependencies
-        run: |
-          sudo apt-get install libsndfile1
-          python -m pip install --upgrade pip
-          python -m pip install fairseq2n==0.3.0rc1+cpu --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install fairseq2==0.3.0rc1 --pre --extra-index-url  https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/ 
-          python -m pip install -r requirements.txt
-          python -m pip install -r requirements-dev.txt
-          python -m pip install -e .
-      - name: Free Disk Space (Ubuntu)
-        uses: jlumbroso/free-disk-space@main
-        with:
-          # this might remove tools that are actually needed,
-          # if set to "true" but frees about 6 GB
-          tool-cache: false
-
-          # all of these default to true, but feel free to set to
-          # "false" if necessary for your workflow
-          android: true
-          dotnet: true
-          haskell: true
-          large-packages: true
-          docker-images: true
-      - name: pytest_integration
-        run: pytest -s -v tests/integration_tests/  --ignore-glob='*sonar*.py'
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/setup
+      - run: uvx --with=types-PyYAML mypy
+  tests:
+    runs-on: ubuntu-latest
+    needs: [lock_file]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/setup
+      - run: uv run --extra cpu pytest -s -v tests/unit_tests/
+  build:
+    runs-on: ubuntu-latest
+    needs: [lock_file, linting, formatting, type_consistency, tests]
+    steps:
+      - uses: actions/checkout@v4
+      - uses: ./.github/actions/setup
+      - run: uv build
\ No newline at end of file
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
new file mode 100644
index 0000000..f287b16
--- /dev/null
+++ b/.pre-commit-config.yaml
@@ -0,0 +1,16 @@
+repos:
+  - repo: https://github.com/astral-sh/uv-pre-commit
+    rev: 0.5.7
+    hooks:
+      - id: uv-lock
+  - repo: https://github.com/astral-sh/ruff-pre-commit
+    rev: v0.8.2
+    hooks:
+      # Lint
+      - id: ruff
+        args: [ --fix ]
+      # sort imports
+      - id: ruff
+        args: ["check", "--select", "I", "--fix"]
+      # format
+      - id: ruff-format
\ No newline at end of file
diff --git a/examples/bilingual_document.ipynb b/examples/bilingual_document.ipynb
index c47a429..e587e80 100644
--- a/examples/bilingual_document.ipynb
+++ b/examples/bilingual_document.ipynb
@@ -26,22 +26,22 @@
    "source": [
     "%pip install --quiet sonar-space scikit-learn fastdtw pandas matplotlib seaborn sentence-splitter\n",
     "\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "import torch\n",
+    "from fastdtw import fastdtw\n",
+    "from scipy.spatial.distance import cosine\n",
+    "from sentence_splitter import SentenceSplitter\n",
+    "from sklearn.metrics.pairwise import cosine_similarity\n",
+    "\n",
     "from sonar.inference_pipelines.text import TextToEmbeddingModelPipeline\n",
     "from sonar.models.sonar_text import (\n",
     "    load_sonar_text_encoder_model,\n",
     "    load_sonar_tokenizer,\n",
     ")\n",
     "\n",
-    "from sklearn.metrics.pairwise import cosine_similarity\n",
-    "import pandas as pd\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
-    "from pprint import pprint\n",
-    "from sentence_splitter import SentenceSplitter\n",
-    "from scipy.spatial.distance import cosine\n",
-    "from fastdtw import fastdtw\n",
-    "\n",
-    "import torch\n",
     "device = torch.device(\"cuda\") if torch.cuda.is_available() else torch.device(\"cpu\")"
    ]
   },
@@ -51,15 +51,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sklearn.metrics.pairwise import cosine_similarity\n",
-    "import pandas as pd\n",
-    "import seaborn as sns\n",
-    "import matplotlib.pyplot as plt\n",
-    "from pprint import pprint\n",
-    "from sentence_splitter import SentenceSplitter\n",
-    "from scipy.spatial.distance import cosine\n",
-    "\n",
     "import torch\n",
+    "\n",
     "device = torch.device(\"cuda\") if torch.cuda.is_available() else torch.device(\"cpu\")"
    ]
   },
@@ -69,24 +62,24 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "eng_splitter = SentenceSplitter(language='en')\n",
-    "spa_splitter = SentenceSplitter(language='es')\n",
-    "deu_splitter = SentenceSplitter(language='de')\n",
+    "eng_splitter = SentenceSplitter(language=\"en\")\n",
+    "spa_splitter = SentenceSplitter(language=\"es\")\n",
+    "deu_splitter = SentenceSplitter(language=\"de\")\n",
     "\n",
-    "eng_text = ''\n",
-    "spa_text = ''\n",
-    "deu_text = ''\n",
+    "eng_text = \"\"\n",
+    "spa_text = \"\"\n",
+    "deu_text = \"\"\n",
     "\n",
-    "with open('./data/metamor_eng.txt', 'r') as file:\n",
+    "with open(\"./data/metamor_eng.txt\", \"r\") as file:\n",
     "    eng_text = file.read()\n",
-    "with open('./data/metamor_spa.txt', 'r') as file:\n",
+    "with open(\"./data/metamor_spa.txt\", \"r\") as file:\n",
     "    spa_text = file.read()\n",
-    "with open('./data/metamor_deu.txt', 'r') as file:\n",
+    "with open(\"./data/metamor_deu.txt\", \"r\") as file:\n",
     "    deu_text = file.read()\n",
     "\n",
     "eng_sentences = eng_splitter.split(text=eng_text)\n",
     "spa_sentences = spa_splitter.split(text=spa_text)\n",
-    "deu_sentences = deu_splitter.split(text=deu_text)\n"
+    "deu_sentences = deu_splitter.split(text=deu_text)"
    ]
   },
   {
@@ -104,10 +97,14 @@
     }
    ],
    "source": [
-    "text_encoder_model = load_sonar_text_encoder_model(\"text_sonar_basic_encoder\", device=device).eval()\n",
+    "text_encoder_model = load_sonar_text_encoder_model(\n",
+    "    \"text_sonar_basic_encoder\", device=device\n",
+    ").eval()\n",
     "text_tokenizer = load_sonar_tokenizer(\"text_sonar_basic_encoder\")\n",
     "\n",
-    "text_embedding_pipeline = TextToEmbeddingModelPipeline(text_encoder_model, text_tokenizer)"
+    "text_embedding_pipeline = TextToEmbeddingModelPipeline(\n",
+    "    text_encoder_model, text_tokenizer\n",
+    ")"
    ]
   },
   {
@@ -171,14 +168,24 @@
     }
    ],
    "source": [
-    "eng_spa_df = pd.DataFrame(eng_spa_cos_sim, index=[f\"Eng {i}\" for i in range(len(eng_sentences))],\n",
-    "                          columns=[f\"Spa {i}\" for i in range(len(spa_sentences))])\n",
+    "eng_spa_df = pd.DataFrame(\n",
+    "    eng_spa_cos_sim,\n",
+    "    index=[f\"Eng {i}\" for i in range(len(eng_sentences))],\n",
+    "    columns=[f\"Spa {i}\" for i in range(len(spa_sentences))],\n",
+    ")\n",
     "\n",
-    "eng_deu_df = pd.DataFrame(eng_deu_cos_sim, index=[f\"Eng {i}\" for i in range(len(eng_sentences))],\n",
-    "                          columns=[f\"Deu {i}\" for i in range(len(deu_sentences))])\n",
+    "eng_deu_df = pd.DataFrame(\n",
+    "    eng_deu_cos_sim,\n",
+    "    index=[f\"Eng {i}\" for i in range(len(eng_sentences))],\n",
+    "    columns=[f\"Deu {i}\" for i in range(len(deu_sentences))],\n",
+    ")\n",
+    "\n",
+    "spa_deu_df = pd.DataFrame(\n",
+    "    spa_deu_cos_sim,\n",
+    "    index=[f\"Spa {i}\" for i in range(len(spa_sentences))],\n",
+    "    columns=[f\"Deu {i}\" for i in range(len(deu_sentences))],\n",
+    ")\n",
     "\n",
-    "spa_deu_df = pd.DataFrame(spa_deu_cos_sim, index=[f\"Spa {i}\" for i in range(len(spa_sentences))],\n",
-    "                          columns=[f\"Deu {i}\" for i in range(len(deu_sentences))])\n",
     "\n",
     "def plot_heatmap(similarity_df, title):\n",
     "    plt.figure(figsize=(10, 8))\n",
@@ -186,6 +193,7 @@
     "    plt.title(title)\n",
     "    plt.show()\n",
     "\n",
+    "\n",
     "plot_heatmap(eng_spa_df, \"English-Spanish Cosine Similarity\")\n",
     "plot_heatmap(eng_deu_df, \"English-German Cosine Similarity\")\n",
     "plot_heatmap(spa_deu_df, \"Spanish-German Cosine Similarity\")"
@@ -309,9 +317,14 @@
     }
    ],
    "source": [
-    "def create_cosine_similarity_heatmap(cos_sim_matrix, sent1_list, sent2_list, lang1_name, lang2_name, threshold=0.6):\n",
-    "    df = pd.DataFrame(cos_sim_matrix, index=[f\"{lang1_name}_{i}\" for i in range(len(sent1_list))], \n",
-    "                      columns=[f\"{lang2_name}_{i}\" for i in range(len(sent2_list))])\n",
+    "def create_cosine_similarity_heatmap(\n",
+    "    cos_sim_matrix, sent1_list, sent2_list, lang1_name, lang2_name, threshold=0.6\n",
+    "):\n",
+    "    df = pd.DataFrame(\n",
+    "        cos_sim_matrix,\n",
+    "        index=[f\"{lang1_name}_{i}\" for i in range(len(sent1_list))],\n",
+    "        columns=[f\"{lang2_name}_{i}\" for i in range(len(sent2_list))],\n",
+    "    )\n",
     "\n",
     "    mask = df < threshold\n",
     "\n",
@@ -319,18 +332,38 @@
     "    for i in range(len(sent1_list)):\n",
     "        for j in range(len(sent2_list)):\n",
     "            if df.iat[i, j] >= threshold:\n",
-    "                print(f\"{lang1_name} Sentence {i}: {sent1_list[i]} <-> {lang2_name} Sentence {j}: {sent2_list[j]} (Cosine Similarity: {df.iat[i, j]:.2f})\")\n",
-    "    \n",
+    "                print(\n",
+    "                    f\"{lang1_name} Sentence {i}: {sent1_list[i]} <-> {lang2_name} Sentence {j}: {sent2_list[j]} (Cosine Similarity: {df.iat[i, j]:.2f})\"\n",
+    "                )\n",
+    "\n",
     "    plt.figure(figsize=(10, 8))\n",
-    "    sns.heatmap(df, mask=mask, annot=False, cmap=\"coolwarm\", cbar=True, linewidths=0.5, vmin=0, vmax=1)\n",
-    "    plt.title(f\"Cosine Similarity Heatmap: {lang1_name} -> {lang2_name} (Threshold > {threshold})\")\n",
+    "    sns.heatmap(\n",
+    "        df,\n",
+    "        mask=mask,\n",
+    "        annot=False,\n",
+    "        cmap=\"coolwarm\",\n",
+    "        cbar=True,\n",
+    "        linewidths=0.5,\n",
+    "        vmin=0,\n",
+    "        vmax=1,\n",
+    "    )\n",
+    "    plt.title(\n",
+    "        f\"Cosine Similarity Heatmap: {lang1_name} -> {lang2_name} (Threshold > {threshold})\"\n",
+    "    )\n",
     "    plt.xlabel(f\"{lang2_name} Sentences\")\n",
     "    plt.ylabel(f\"{lang1_name} Sentences\")\n",
     "    plt.show()\n",
     "\n",
-    "create_cosine_similarity_heatmap(eng_spa_cos_sim, eng_sentences, spa_sentences, \"English\", \"Spanish\", threshold=0.7)\n",
-    "create_cosine_similarity_heatmap(eng_deu_cos_sim, eng_sentences, deu_sentences, \"English\", \"German\", threshold=0.7)\n",
-    "create_cosine_similarity_heatmap(spa_deu_cos_sim, spa_sentences, deu_sentences, \"Spanish\", \"German\", threshold=0.7)\n"
+    "\n",
+    "create_cosine_similarity_heatmap(\n",
+    "    eng_spa_cos_sim, eng_sentences, spa_sentences, \"English\", \"Spanish\", threshold=0.7\n",
+    ")\n",
+    "create_cosine_similarity_heatmap(\n",
+    "    eng_deu_cos_sim, eng_sentences, deu_sentences, \"English\", \"German\", threshold=0.7\n",
+    ")\n",
+    "create_cosine_similarity_heatmap(\n",
+    "    spa_deu_cos_sim, spa_sentences, deu_sentences, \"Spanish\", \"German\", threshold=0.7\n",
+    ")"
    ]
   },
   {
@@ -642,12 +675,15 @@
    "source": [
     "def dtw_align(eng_embeddings, spa_embeddings):\n",
     "    alignments = []\n",
-    "    \n",
-    "    distance, path = fastdtw(eng_embeddings.numpy(), spa_embeddings.numpy(), dist=cosine)\n",
+    "\n",
+    "    distance, path = fastdtw(\n",
+    "        eng_embeddings.numpy(), spa_embeddings.numpy(), dist=cosine\n",
+    "    )\n",
     "    alignments.append(path)\n",
-    "    \n",
+    "\n",
     "    return alignments\n",
     "\n",
+    "\n",
     "eng_spa_alignments = dtw_align(eng_embeddings, spa_embeddings)\n",
     "\n",
     "\n",
@@ -655,22 +691,24 @@
     "\n",
     "alignment_table = []\n",
     "\n",
-    "for (eng_idx, spa_idx) in eng_spa_alignments[0]:\n",
+    "for eng_idx, spa_idx in eng_spa_alignments[0]:\n",
     "    eng_sentence = eng_sentences[eng_idx] if eng_idx < len(eng_sentences) else \"\"\n",
     "    spa_sentence = spa_sentences[spa_idx] if spa_idx < len(spa_sentences) else \"\"\n",
-    "    \n",
+    "\n",
     "    alignment_table.append((eng_sentence, spa_sentence))\n",
     "\n",
-    "bilingual_df = pd.DataFrame(alignment_table, columns=[\"English Sentence\", \"Spanish Sentence\"])\n",
-    "pd.set_option('display.max_colwidth', None)\n",
+    "bilingual_df = pd.DataFrame(\n",
+    "    alignment_table, columns=[\"English Sentence\", \"Spanish Sentence\"]\n",
+    ")\n",
+    "pd.set_option(\"display.max_colwidth\", None)\n",
     "\n",
     "html_table = bilingual_df.to_html(index=False)\n",
     "with open(\"bilingual_book.html\", \"w\") as f:\n",
     "    f.write(html_table)\n",
     "\n",
-    "from IPython.display import display, HTML\n",
-    "display(HTML(bilingual_df.to_html(index=False)))\n",
-    "\n"
+    "from IPython.display import HTML, display\n",
+    "\n",
+    "display(HTML(bilingual_df.to_html(index=False)))"
    ]
   },
   {
diff --git a/examples/inference_pipelines.ipynb b/examples/inference_pipelines.ipynb
index c981864..cc7acfb 100644
--- a/examples/inference_pipelines.ipynb
+++ b/examples/inference_pipelines.ipynb
@@ -44,6 +44,7 @@
    "outputs": [],
    "source": [
     "import torch\n",
+    "\n",
     "device = torch.device(\"cpu\")"
    ]
   },
@@ -74,7 +75,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "speech_encoder_model = load_sonar_speech_model(\"sonar_speech_encoder_eng\", device=device).eval()"
+    "speech_encoder_model = load_sonar_speech_model(\n",
+    "    \"sonar_speech_encoder_eng\", device=device\n",
+    ").eval()"
    ]
   },
   {
@@ -83,7 +86,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "text_encoder_model = load_sonar_text_encoder_model(\"text_sonar_basic_encoder\", device=device).eval()"
+    "text_encoder_model = load_sonar_text_encoder_model(\n",
+    "    \"text_sonar_basic_encoder\", device=device\n",
+    ").eval()"
    ]
   },
   {
@@ -92,7 +97,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "text_decoder_model = load_sonar_text_decoder_model(\"text_sonar_basic_decoder\", device=device).eval()"
+    "text_decoder_model = load_sonar_text_decoder_model(\n",
+    "    \"text_sonar_basic_decoder\", device=device\n",
+    ").eval()"
    ]
   },
   {
@@ -118,7 +125,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sonar.inference_pipelines.speech import SpeechToEmbeddingModelPipeline, SpeechToTextModelPipeline"
+    "from sonar.inference_pipelines.speech import (\n",
+    "    SpeechToEmbeddingModelPipeline,\n",
+    "    SpeechToTextModelPipeline,\n",
+    ")"
    ]
   },
   {
@@ -142,8 +152,12 @@
    ],
    "source": [
     "s2vec_model = SpeechToEmbeddingModelPipeline(encoder=speech_encoder_model)\n",
-    "s2vec_model.predict([\"../tests/integration_tests/data/audio_files/audio_1.wav\",\n",
-    "                     \"../tests/integration_tests/data/audio_files/audio_2.wav\"])"
+    "s2vec_model.predict(\n",
+    "    [\n",
+    "        \"../tests/integration_tests/data/audio_files/audio_1.wav\",\n",
+    "        \"../tests/integration_tests/data/audio_files/audio_2.wav\",\n",
+    "    ]\n",
+    ")"
    ]
   },
   {
@@ -164,12 +178,17 @@
     }
    ],
    "source": [
-    "s2t_model = SpeechToTextModelPipeline(encoder=speech_encoder_model,\n",
-    "                                      decoder=text_decoder_model,\n",
-    "                                      tokenizer=text_tokenizer)\n",
+    "s2t_model = SpeechToTextModelPipeline(\n",
+    "    encoder=speech_encoder_model, decoder=text_decoder_model, tokenizer=text_tokenizer\n",
+    ")\n",
     "\n",
-    "s2t_model.predict([\"../tests/integration_tests/data/audio_files/audio_1.wav\",\n",
-    "                   \"../tests/integration_tests/data/audio_files/audio_2.wav\"], target_lang=\"eng_Latn\")"
+    "s2t_model.predict(\n",
+    "    [\n",
+    "        \"../tests/integration_tests/data/audio_files/audio_1.wav\",\n",
+    "        \"../tests/integration_tests/data/audio_files/audio_2.wav\",\n",
+    "    ],\n",
+    "    target_lang=\"eng_Latn\",\n",
+    ")"
    ]
   },
   {
@@ -185,7 +204,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sonar.inference_pipelines.text import TextToTextModelPipeline, TextToEmbeddingModelPipeline"
+    "from sonar.inference_pipelines.text import (\n",
+    "    TextToEmbeddingModelPipeline,\n",
+    "    TextToTextModelPipeline,\n",
+    ")"
    ]
   },
   {
@@ -194,8 +216,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "text_embedding_pipeline = TextToEmbeddingModelPipeline(text_encoder_model, text_tokenizer)\n",
-    "text_to_text_pipeline = TextToTextModelPipeline(text_encoder_model, text_decoder_model, text_tokenizer)"
+    "text_embedding_pipeline = TextToEmbeddingModelPipeline(\n",
+    "    text_encoder_model, text_tokenizer\n",
+    ")\n",
+    "text_to_text_pipeline = TextToTextModelPipeline(\n",
+    "    text_encoder_model, text_decoder_model, text_tokenizer\n",
+    ")"
    ]
   },
   {
@@ -266,7 +292,9 @@
     }
    ],
    "source": [
-    "text_translation = text_to_text_pipeline.predict(data_source, source_lang=\"eng_Latn\", target_lang=\"fra_Latn\")\n",
+    "text_translation = text_to_text_pipeline.predict(\n",
+    "    data_source, source_lang=\"eng_Latn\", target_lang=\"fra_Latn\"\n",
+    ")\n",
     "text_translation"
    ]
   }
diff --git a/examples/mutox_example.ipynb b/examples/mutox_example.ipynb
index 4cbe982..1019482 100644
--- a/examples/mutox_example.ipynb
+++ b/examples/mutox_example.ipynb
@@ -28,9 +28,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "import torch\n",
     "from pathlib import Path\n",
     "\n",
+    "import torch\n",
+    "\n",
     "if torch.cuda.is_available():\n",
     "    device = torch.device(\"cuda:0\")\n",
     "    dtype = torch.float16\n",
@@ -63,22 +64,28 @@
    "outputs": [],
    "source": [
     "# get demo file\n",
-    "import urllib.request\n",
     "import tempfile\n",
+    "import urllib.request\n",
     "\n",
     "files = [\n",
-    "    (\"https://dl.fbaipublicfiles.com/seamless/tests/commonvoice_example_en_clocks.wav\", \"commonvoice_example_en_clocks.wav\"),\n",
-    "    (\"https://dl.fbaipublicfiles.com/seamlessM4T/LJ037-0171_sr16k.wav\", \"LJ037-0171_sr16k.wav\")\n",
+    "    (\n",
+    "        \"https://dl.fbaipublicfiles.com/seamless/tests/commonvoice_example_en_clocks.wav\",\n",
+    "        \"commonvoice_example_en_clocks.wav\",\n",
+    "    ),\n",
+    "    (\n",
+    "        \"https://dl.fbaipublicfiles.com/seamlessM4T/LJ037-0171_sr16k.wav\",\n",
+    "        \"LJ037-0171_sr16k.wav\",\n",
+    "    ),\n",
     "]\n",
     "\n",
     "tmpdir = Path(tempfile.mkdtemp())\n",
-    "tsv_file = (tmpdir / 'data.tsv')\n",
-    "with tsv_file.open('w') as tsv_file_p:\n",
-    "    print('path', file=tsv_file_p)\n",
-    "    for (uri, name) in files:\n",
+    "tsv_file = tmpdir / \"data.tsv\"\n",
+    "with tsv_file.open(\"w\") as tsv_file_p:\n",
+    "    print(\"path\", file=tsv_file_p)\n",
+    "    for uri, name in files:\n",
     "        dl = tmpdir / name\n",
     "        urllib.request.urlretrieve(uri, dl)\n",
-    "        print(dl, file=tsv_file_p)\n"
+    "        print(dl, file=tsv_file_p)"
    ]
   },
   {
@@ -87,12 +94,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from sonar.inference_pipelines.speech import SpeechInferenceParams\n",
     "from sonar.inference_pipelines.mutox_speech import MutoxSpeechClassifierPipeline\n",
+    "from sonar.inference_pipelines.speech import SpeechInferenceParams\n",
     "\n",
     "pipeline_builder = MutoxSpeechClassifierPipeline.load_model_from_name(\n",
-    "    mutox_classifier_name =\"sonar_mutox\",\n",
-    "    encoder_name=f\"sonar_speech_encoder_eng\",\n",
+    "    mutox_classifier_name=\"sonar_mutox\",\n",
+    "    encoder_name=\"sonar_speech_encoder_eng\",\n",
     "    device=device,\n",
     ")"
    ]
@@ -103,17 +110,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "pipeline = pipeline_builder.build_pipeline(SpeechInferenceParams(\n",
-    "    data_file=tsv_file,\n",
-    "    audio_root_dir=None,\n",
-    "    audio_path_index=0,\n",
-    "    target_lang=\"eng\",\n",
-    "    batch_size=4,\n",
-    "    pad_idx=0,\n",
-    "    device=device,\n",
-    "    fbank_dtype=torch.float32,\n",
-    "    n_parallel=4\n",
-    "))"
+    "pipeline = pipeline_builder.build_pipeline(\n",
+    "    SpeechInferenceParams(\n",
+    "        data_file=tsv_file,\n",
+    "        audio_root_dir=None,\n",
+    "        audio_path_index=0,\n",
+    "        target_lang=\"eng\",\n",
+    "        batch_size=4,\n",
+    "        pad_idx=0,\n",
+    "        device=device,\n",
+    "        fbank_dtype=torch.float32,\n",
+    "        n_parallel=4,\n",
+    "    )\n",
+    ")"
    ]
   },
   {
@@ -139,9 +148,9 @@
    ],
    "source": [
     "for batch in pipeline:\n",
-    "    ex = batch['audio']\n",
-    "    for idx, path in enumerate(ex['path']):\n",
-    "        print(str(path), ex[\"data\"][idx].item(), sep=\"\\t\")\n"
+    "    ex = batch[\"audio\"]\n",
+    "    for idx, path in enumerate(ex[\"path\"]):\n",
+    "        print(str(path), ex[\"data\"][idx].item(), sep=\"\\t\")"
    ]
   },
   {
@@ -152,6 +161,7 @@
    "source": [
     "# cleanup tmp dir\n",
     "import shutil\n",
+    "\n",
     "shutil.rmtree(tmpdir)"
    ]
   },
@@ -181,15 +191,15 @@
     }
    ],
    "source": [
-    "from sonar.models.mutox.loader import load_mutox_model\n",
     "from sonar.inference_pipelines.text import TextToEmbeddingModelPipeline\n",
+    "from sonar.models.mutox.loader import load_mutox_model\n",
     "\n",
     "t2vec_model = TextToEmbeddingModelPipeline(\n",
     "    encoder=\"text_sonar_basic_encoder\",\n",
     "    tokenizer=\"text_sonar_basic_encoder\",\n",
     "    device=device,\n",
     ")\n",
-    "text_column='lang_txt'\n",
+    "text_column = \"lang_txt\"\n",
     "classifier = load_mutox_model(\n",
     "    \"sonar_mutox\",\n",
     "    device=device,\n",
@@ -215,7 +225,10 @@
    ],
    "source": [
     "with torch.inference_mode():\n",
-    "    emb = t2vec_model.predict([\"De peur que le pays ne se prostitue et ne se remplisse de crimes.\"], source_lang='fra_Latn')\n",
+    "    emb = t2vec_model.predict(\n",
+    "        [\"De peur que le pays ne se prostitue et ne se remplisse de crimes.\"],\n",
+    "        source_lang=\"fra_Latn\",\n",
+    "    )\n",
     "    x = classifier(emb.to(device).half())\n",
     "\n",
     "x"
diff --git a/examples/sonar_text_demo.ipynb b/examples/sonar_text_demo.ipynb
index 62866bf..c793d74 100644
--- a/examples/sonar_text_demo.ipynb
+++ b/examples/sonar_text_demo.ipynb
@@ -30,7 +30,11 @@
    "outputs": [],
    "source": [
     "import torch\n",
-    "from sonar.inference_pipelines.text import TextToTextModelPipeline, TextToEmbeddingModelPipeline"
+    "\n",
+    "from sonar.inference_pipelines.text import (\n",
+    "    TextToEmbeddingModelPipeline,\n",
+    "    TextToTextModelPipeline,\n",
+    ")"
    ]
   },
   {
@@ -39,11 +43,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "text2vec = TextToEmbeddingModelPipeline(encoder=\"text_sonar_basic_encoder\",\n",
-    "                                        tokenizer=\"text_sonar_basic_encoder\")\n",
-    "text2text = TextToTextModelPipeline(encoder=\"text_sonar_basic_encoder\",\n",
-    "                                    decoder=\"text_sonar_basic_decoder\",\n",
-    "                                    tokenizer=\"text_sonar_basic_encoder\")  # tokenizer is attached to both encoder and decoder cards"
+    "text2vec = TextToEmbeddingModelPipeline(\n",
+    "    encoder=\"text_sonar_basic_encoder\", tokenizer=\"text_sonar_basic_encoder\"\n",
+    ")\n",
+    "text2text = TextToTextModelPipeline(\n",
+    "    encoder=\"text_sonar_basic_encoder\",\n",
+    "    decoder=\"text_sonar_basic_decoder\",\n",
+    "    tokenizer=\"text_sonar_basic_encoder\",\n",
+    ")  # tokenizer is attached to both encoder and decoder cards"
    ]
   },
   {
@@ -62,37 +69,41 @@
    "outputs": [],
    "source": [
     "# shorted examples from FLORES dataset\n",
-    "english_sentences = ['He died in Osaka on Tuesday.',\n",
-    " 'No one was inside the apartment.',\n",
-    " 'Zayat was unhurt in the accident.',\n",
-    " '\"Some may not agree but I don\\'t care.',\n",
-    " 'He documented himself in a 1998 book.',\n",
-    " 'An inquiry was established to investigate.',\n",
-    " 'Then Whirling Dervishes took to the stage.',\n",
-    " 'In Berlin, police estimated 6,500 protestors.',\n",
-    " 'He joined them in 1945 and stayed until 1958.',\n",
-    " \"It is the biggest acquisition in eBay's history.\",\n",
-    " '\"We were all simply in shock,\" the mother stated.',\n",
-    " 'Unwanted murals or scribble is known as graffiti.',\n",
-    " 'Seven points behind, Johnson is second with 2,243.',\n",
-    " 'When the official arrived, the apartment exploded.',\n",
-    " 'A Hangi Meal is cooked in a hot pit in the ground.']\n",
+    "english_sentences = [\n",
+    "    \"He died in Osaka on Tuesday.\",\n",
+    "    \"No one was inside the apartment.\",\n",
+    "    \"Zayat was unhurt in the accident.\",\n",
+    "    \"\\\"Some may not agree but I don't care.\",\n",
+    "    \"He documented himself in a 1998 book.\",\n",
+    "    \"An inquiry was established to investigate.\",\n",
+    "    \"Then Whirling Dervishes took to the stage.\",\n",
+    "    \"In Berlin, police estimated 6,500 protestors.\",\n",
+    "    \"He joined them in 1945 and stayed until 1958.\",\n",
+    "    \"It is the biggest acquisition in eBay's history.\",\n",
+    "    '\"We were all simply in shock,\" the mother stated.',\n",
+    "    \"Unwanted murals or scribble is known as graffiti.\",\n",
+    "    \"Seven points behind, Johnson is second with 2,243.\",\n",
+    "    \"When the official arrived, the apartment exploded.\",\n",
+    "    \"A Hangi Meal is cooked in a hot pit in the ground.\",\n",
+    "]\n",
     "\n",
-    "french_sentences = ['Il est mort à Osaka mardi.',\n",
-    " \"Personne n'était à l'intérieur de l'appartement.\",\n",
-    " \"Zayat est sorti indemne de l'accident.\",\n",
-    " \"«\\xa0Certains ne seront peut-être pas d'accord, mais cela m'est égal.\",\n",
-    " 'Il a fait des recherches dans un livre paru en 1998.',\n",
-    " 'Une enquête a été ouverte.',\n",
-    " 'Puis les derviches tourneurs sont montés sur scène.',\n",
-    " \"À Berlin, la police estime qu'il y avait environ 6 500 manifestants.\",\n",
-    " \"Il le rejoint en 1945 et y reste jusqu'en 1958.\",\n",
-    " 'C’est la plus grande acquisition de l’histoire d’eBay.',\n",
-    " '« Nous étions tous simplement sous le choc », a déclaré la mère.',\n",
-    " 'Les peintures murales ou les gribouillages indésirables sont connus sous le nom de graffitis.',\n",
-    " 'Sept points de retard, Johnson est deuxième avec 2243 points.',\n",
-    " \"Une fois l'agent arrivé sur place, l'appartement a explosé.\",\n",
-    " 'On cuit un repas hangi dans une fosse chaude creusée dans le sol.']"
+    "french_sentences = [\n",
+    "    \"Il est mort à Osaka mardi.\",\n",
+    "    \"Personne n'était à l'intérieur de l'appartement.\",\n",
+    "    \"Zayat est sorti indemne de l'accident.\",\n",
+    "    \"«\\xa0Certains ne seront peut-être pas d'accord, mais cela m'est égal.\",\n",
+    "    \"Il a fait des recherches dans un livre paru en 1998.\",\n",
+    "    \"Une enquête a été ouverte.\",\n",
+    "    \"Puis les derviches tourneurs sont montés sur scène.\",\n",
+    "    \"À Berlin, la police estime qu'il y avait environ 6 500 manifestants.\",\n",
+    "    \"Il le rejoint en 1945 et y reste jusqu'en 1958.\",\n",
+    "    \"C’est la plus grande acquisition de l’histoire d’eBay.\",\n",
+    "    \"« Nous étions tous simplement sous le choc », a déclaré la mère.\",\n",
+    "    \"Les peintures murales ou les gribouillages indésirables sont connus sous le nom de graffitis.\",\n",
+    "    \"Sept points de retard, Johnson est deuxième avec 2243 points.\",\n",
+    "    \"Une fois l'agent arrivé sur place, l'appartement a explosé.\",\n",
+    "    \"On cuit un repas hangi dans une fosse chaude creusée dans le sol.\",\n",
+    "]"
    ]
   },
   {
@@ -143,13 +154,14 @@
    ],
    "source": [
     "#!pip install seaborn pandas\n",
-    "import seaborn as sns\n",
     "import pandas as pd\n",
+    "import seaborn as sns\n",
+    "\n",
     "cos_sim = embed_english_sentence.dot(embed_french_sentence.T)\n",
     "sim_df = pd.DataFrame(cos_sim, columns=french_sentences, index=english_sentences)\n",
-    "sns.set(font_scale=.8)\n",
-    "sns.set (rc = {'figure.figsize':(10, 10)})\n",
-    "sns.heatmap(sim_df, cmap=\"vlag\", linewidths=.5)"
+    "sns.set(font_scale=0.8)\n",
+    "sns.set(rc={\"figure.figsize\": (10, 10)})\n",
+    "sns.heatmap(sim_df, cmap=\"vlag\", linewidths=0.5)"
    ]
   },
   {
@@ -165,13 +177,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "french_translated_sentences = text2text.predict(english_sentences,\n",
-    "                                                source_lang=\"eng_Latn\", \n",
-    "                                                target_lang=\"fra_Latn\")\n",
+    "french_translated_sentences = text2text.predict(\n",
+    "    english_sentences, source_lang=\"eng_Latn\", target_lang=\"fra_Latn\"\n",
+    ")\n",
     "\n",
-    "english_translated_sentences = text2text.predict(french_sentences,\n",
-    "                                                 source_lang=\"fra_Latn\", \n",
-    "                                                 target_lang=\"eng_Latn\")"
+    "english_translated_sentences = text2text.predict(\n",
+    "    french_sentences, source_lang=\"fra_Latn\", target_lang=\"eng_Latn\"\n",
+    ")"
    ]
   },
   {
@@ -201,17 +213,21 @@
     }
    ],
    "source": [
-    "\n",
     "import sacrebleu\n",
-    "bleu_obj = sacrebleu.corpus_bleu(french_translated_sentences, [french_sentences], tokenize='flores200')\n",
+    "\n",
+    "bleu_obj = sacrebleu.corpus_bleu(\n",
+    "    french_translated_sentences, [french_sentences], tokenize=\"flores200\"\n",
+    ")\n",
     "print(\"*\" * 120)\n",
     "print(\"english to french translation bleu score :\")\n",
     "print(bleu_obj)\n",
     "\n",
-    "bleu_obj = sacrebleu.corpus_bleu(english_translated_sentences, [english_sentences], tokenize='flores200')\n",
+    "bleu_obj = sacrebleu.corpus_bleu(\n",
+    "    english_translated_sentences, [english_sentences], tokenize=\"flores200\"\n",
+    ")\n",
     "print(\"*\" * 120)\n",
     "print(\"french to english translation bleu score :\")\n",
-    "print(bleu_obj)\n"
+    "print(bleu_obj)"
    ]
   },
   {
diff --git a/huggingface_pipelines/audio.py b/huggingface_pipelines/audio.py
index 3341653..561e4bd 100644
--- a/huggingface_pipelines/audio.py
+++ b/huggingface_pipelines/audio.py
@@ -246,15 +246,12 @@ def process_batch(self, batch: Dict[str, Any]) -> Dict[str, Any]:
                 audio_inputs = self.collect_valid_audio_inputs(batch[column])
 
                 if not audio_inputs:
-
                     raise ValueError(f"No valid audio inputs found in column {column}/")
 
                 try:
-
                     audio_embeddings: List[np.ndarray] = []
 
                     for i in range(0, len(audio_inputs), self.config.batch_size):
-
                         batch_inputs = [
                             tensor.to(self.config.device)
                             for tensor in audio_inputs[i : i + self.config.batch_size]
diff --git a/huggingface_pipelines/text.py b/huggingface_pipelines/text.py
index 1a72c34..7aea67b 100644
--- a/huggingface_pipelines/text.py
+++ b/huggingface_pipelines/text.py
@@ -477,7 +477,6 @@ def process_batch(self, batch: Dict[str, Any]) -> Dict[str, Any]:
         """
         for column in self.config.columns:
             if column in batch:
-
                 if not isinstance(batch[column], (list, np.ndarray)):
                     raise ValueError(
                         f"Expected list for column {column}, got {type(batch[column])}"
diff --git a/pyproject.toml b/pyproject.toml
index 7f20e08..fa899d4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -23,7 +23,6 @@ keywords = [
   "multi-language models",
 ]
 
-
 # zip_safe = false
 classifiers = [
   "Topic :: Scientific/Engineering",
@@ -31,10 +30,8 @@ classifiers = [
 ]
 
 dependencies = [
-#  "fairseq2>=0.3.0rc1", # install manually from https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/
+  "fairseq2>=0.3.0rc1",
   "numpy>=1.21",
-  "torch",
-  "torchaudio",
   "sox",
   "soundfile",
   "tqdm",
@@ -42,22 +39,17 @@ dependencies = [
   "typing_extensions",
 ]
 
-[project.optional-dependencies]
-dev = [
-  # Test
-  "pytest>=4.3.0",
-  "pytest-asyncio>=0.15.0",
-  "pytest-cov>=2.6.1",
-  "coverage[toml]>=5.1",
-  # Format
-  "black==24.3.0",
-  "isort>=5.10.1",
-  # Linters
-  "mypy>=0.782",
-  "pylint>=2.8.0",
-]
 
+[dependency-groups]
+dev = ["pytest-asyncio>=0.15.0", "pytest-cov>=2.6.1", "pytest>=4.3.0", "coverage[toml]>=5.1"]
 
+[project.optional-dependencies]
+cpu = [
+  "torch==2.5.1+cpu",
+  "torchaudio",
+  "fairseq2n==0.3.0rc1", 
+  "fairseq2[arrow]==0.3.0rc1", 
+]
 hg = [
   "transformers>=4.44.0",
   "datasets>=2.20.0",
@@ -67,7 +59,6 @@ hg = [
   "absl-py>=2.1.0",
 ]
 
-
 [project.urls]
 Source = "https://github.com/facebookresearch/SONAR"
 Tracker = "https://github.com/facebookresearch/SONAR/issues"
@@ -78,27 +69,13 @@ Tracker = "https://github.com/facebookresearch/SONAR/issues"
 [tool.flit.module]
 name = "sonar"
 
-[tool.black]
+[tool.ruff]
+target-version = "py38"
 line-length = 88
-include = '\.pyi?$'
-# 'extend-exclude' excludes files or directories in addition to the defaults
-extend-exclude = '''
-# A regex preceded with ^/ will apply only to files and directories
-# in the root of the project.
-(
-  ^/foo.py    # exclude a file named foo.py in the root of the project
-  | .*_pb2.py  # exclude autogenerated Protocol Buffer files anywhere in the project
-)
-'''
-
-[tool.flake8]
-extend_ignore = ["E", "Y"]              # Black
-per-file-ignores = ["__init__.py:F401"]
-
-[tool.isort]
-profile = "black"
-skip_gitignore = true
-skip_glob = []
+
+[tool.ruff.lint]
+ignore = ["E"]
+per-file-ignores = {"__init__.py"=["F401"]}
 
 [tool.mypy]
 python_version = "3.8"
@@ -111,3 +88,22 @@ files = ["sonar/"]
 minversion = "6.0"
 testpaths = ["tests/"]
 python_files = ["test_*.py"]
+
+[tool.uv.sources]
+fairseq2 = [
+  { index = "fairseq2-cpu", extra = 'cpu' }
+]
+fairseq2n = [
+  { index = "fairseq2-cpu", extra = 'cpu' }
+]
+torch={index="pytorch-cpu"}
+
+[[tool.uv.index]]
+name = "fairseq2-cpu"
+url = "https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/"
+explicit = true
+
+[[tool.uv.index]]
+name = "pytorch-cpu"
+url = "https://download.pytorch.org/whl/cpu"
+explicit = true
\ No newline at end of file
diff --git a/requirements-dev.txt b/requirements-dev.txt
deleted file mode 100644
index 22dfe8d..0000000
--- a/requirements-dev.txt
+++ /dev/null
@@ -1,12 +0,0 @@
-# Test
-pytest>=4.3.0
-pytest-asyncio>=0.15.0
-pytest-cov>=2.6.1
-coverage[toml]>=5.1
-# Format
-black==24.3.0
-isort>=5.10.1
-# Linter
-mypy>=0.782
-pylint>=2.8.0
-flake8
diff --git a/requirements.txt b/requirements.txt
deleted file mode 100644
index 281cc2f..0000000
--- a/requirements.txt
+++ /dev/null
@@ -1,9 +0,0 @@
-# fairseq2>=0.3.0rc1 # install manually from https://fair.pkg.atmeta.com/fairseq2/whl/rc/pt2.5.1/cpu/
-# See https://github.com/NVIDIA/TensorRT-LLM/issues/1145
-mpmath==1.3.0
-numpy>=1.21
-torch
-torchaudio
-sox
-soundfile
-tqdm
diff --git a/sonar/__init__.py b/sonar/__init__.py
index ecb3129..506cf70 100644
--- a/sonar/__init__.py
+++ b/sonar/__init__.py
@@ -4,9 +4,8 @@
 # This source code is licensed under the BSD-style license found in the
 # LICENSE file in the root directory of this source tree.
 
-"""SONAR provides a set of speech and text encoders for multilingual, multimodal semantic embedding.
+"""SONAR provides a set of speech and text encoders for multilingual, multimodal semantic embedding."""
 
-"""
 from fairseq2.assets import default_asset_store
 
 __version__ = "0.3.1"
diff --git a/sonar/inference_pipelines/mutox_speech.py b/sonar/inference_pipelines/mutox_speech.py
index 8e7ff71..9d990c4 100644
--- a/sonar/inference_pipelines/mutox_speech.py
+++ b/sonar/inference_pipelines/mutox_speech.py
@@ -14,7 +14,6 @@
     AudioToFbankDataPipelineBuilder,
     SpeechInferenceParams,
     SpeechInferencePipeline,
-    SpeechToEmbeddingPipeline,
 )
 from sonar.inference_pipelines.utils import extract_sequence_batch
 from sonar.models.encoder_model import SonarEncoderModel
diff --git a/sonar/inference_pipelines/speech.py b/sonar/inference_pipelines/speech.py
index 102a0a0..6053207 100644
--- a/sonar/inference_pipelines/speech.py
+++ b/sonar/inference_pipelines/speech.py
@@ -94,9 +94,7 @@ def prebuild_pipeline(self, context: SpeechInferenceParams) -> DataPipelineBuild
         # Start building the pipeline
         pipeline_builder = (
             # Open TSV, skip the header line, split into fields, and return audio field
-            read_text(context.data_file, rtrim=True)
-            .skip(1)
-            .map(split_tsv)
+            read_text(context.data_file, rtrim=True).skip(1).map(split_tsv)
         )
 
         # Memory map audio files and cache up to 10 files.
diff --git a/sonar/inference_pipelines/utils.py b/sonar/inference_pipelines/utils.py
index 6d26112..16fde62 100644
--- a/sonar/inference_pipelines/utils.py
+++ b/sonar/inference_pipelines/utils.py
@@ -11,12 +11,11 @@
 from fairseq2.data import SequenceData
 from fairseq2.models.sequence import SequenceBatch
 from fairseq2.nn.padding import get_seqs_and_padding_mask
-from fairseq2.typing import DataType, Device
+from fairseq2.typing import Device
 from tqdm.auto import tqdm
 
 
 def extract_sequence_batch(x: SequenceData, device: Device) -> SequenceBatch:
-
     seqs, padding_mask = get_seqs_and_padding_mask(x, device=device)
 
     return SequenceBatch(seqs, padding_mask)
diff --git a/sonar/models/mutox/builder.py b/sonar/models/mutox/builder.py
index b308cb9..0790bae 100644
--- a/sonar/models/mutox/builder.py
+++ b/sonar/models/mutox/builder.py
@@ -6,7 +6,6 @@
 
 import typing as tp
 
-import torch
 from fairseq2.typing import DataType, Device
 from torch import nn
 
diff --git a/sonar/models/mutox/classifier.py b/sonar/models/mutox/classifier.py
index 9fcdb3a..7f2565c 100644
--- a/sonar/models/mutox/classifier.py
+++ b/sonar/models/mutox/classifier.py
@@ -5,11 +5,9 @@
 # MIT_LICENSE file in the root directory of this source tree.
 
 from dataclasses import dataclass
-from typing import Optional
 
 import torch
 from fairseq2.config_registry import ConfigRegistry
-from fairseq2.typing import DataType, Device
 from torch import nn
 
 
diff --git a/sonar/models/mutox/loader.py b/sonar/models/mutox/loader.py
index a1137d1..55776f9 100644
--- a/sonar/models/mutox/loader.py
+++ b/sonar/models/mutox/loader.py
@@ -10,7 +10,7 @@
 from fairseq2.models.loader import StandardModelLoader, load_model
 
 from .builder import create_mutox_model
-from .classifier import MutoxClassifier, MutoxConfig, mutox_archs
+from .classifier import MutoxConfig, mutox_archs
 
 __import__("sonar")  # Import only to update asset_store
 
diff --git a/sonar/models/sonar_speech/loader.py b/sonar/models/sonar_speech/loader.py
index 996311d..14fa27f 100644
--- a/sonar/models/sonar_speech/loader.py
+++ b/sonar/models/sonar_speech/loader.py
@@ -37,39 +37,37 @@ def convert_sonar_speech_checkpoint(
     key_map = {
         # fmt: off
         # encoder
-        r"^encoder.w2v_model.layer_norm\.":                                              r"encoder_frontend.post_extract_layer_norm.",
-        r"^encoder.w2v_model.post_extract_proj\.":                                       r"encoder_frontend.model_dim_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.batch_norm\.":      r"encoder.layers.\1.conv.batch_norm.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.depthwise_conv\.":  r"encoder.layers.\1.conv.depthwise_conv.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.layer_norm\.":      r"encoder.layers.\1.conv_layer_norm.",
+        r"^encoder.w2v_model.layer_norm\.": r"encoder_frontend.post_extract_layer_norm.",
+        r"^encoder.w2v_model.post_extract_proj\.": r"encoder_frontend.model_dim_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.batch_norm\.": r"encoder.layers.\1.conv.batch_norm.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.depthwise_conv\.": r"encoder.layers.\1.conv.depthwise_conv.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.layer_norm\.": r"encoder.layers.\1.conv_layer_norm.",
         r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.pointwise_conv1\.": r"encoder.layers.\1.conv.pointwise_conv1.",
         r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.conv_module\.pointwise_conv2\.": r"encoder.layers.\1.conv.pointwise_conv2.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.ffn(1|2)\.layer_norm\.":         r"encoder.layers.\1.ffn\2_layer_norm.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.ffn(1|2)\.w_1\.":                r"encoder.layers.\1.ffn\2.inner_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.ffn(1|2)\.w_2\.":                r"encoder.layers.\1.ffn\2.output_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn_layer_norm\.":         r"encoder.layers.\1.self_attn_layer_norm.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_q\.":          r"encoder.layers.\1.self_attn.q_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_k\.":          r"encoder.layers.\1.self_attn.k_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_v\.":          r"encoder.layers.\1.self_attn.v_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_out\.":        r"encoder.layers.\1.self_attn.output_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_pos\.":        r"encoder.layers.\1.self_attn.sdpa.r_proj.",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.pos_bias_u":          r"encoder.layers.\1.self_attn.sdpa.u_bias",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.pos_bias_v":          r"encoder.layers.\1.self_attn.sdpa.v_bias",
-        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.final_layer_norm\.":             r"encoder.layers.\1.layer_norm.",
-        r"^encoder.w2v_model.encoder\.layer_norm\.":                                     r"encoder.layer_norm.",
-
-        r"^decoder\.embed_tokens\.":                              r"encoder_pooler.decoder_frontend.embed.",
-        r"^decoder\.layers\.([0-9]+)\.self_attn_layer_norm\.":    r"encoder_pooler.decoder.layers.\1.self_attn_layer_norm.",
-        r"^decoder\.layers\.([0-9]+)\.self_attn\.out_proj\.":     r"encoder_pooler.decoder.layers.\1.self_attn.output_proj.",
-        r"^decoder\.layers\.([0-9]+)\.self_attn\.":               r"encoder_pooler.decoder.layers.\1.self_attn.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.ffn(1|2)\.layer_norm\.": r"encoder.layers.\1.ffn\2_layer_norm.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.ffn(1|2)\.w_1\.": r"encoder.layers.\1.ffn\2.inner_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.ffn(1|2)\.w_2\.": r"encoder.layers.\1.ffn\2.output_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn_layer_norm\.": r"encoder.layers.\1.self_attn_layer_norm.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_q\.": r"encoder.layers.\1.self_attn.q_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_k\.": r"encoder.layers.\1.self_attn.k_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_v\.": r"encoder.layers.\1.self_attn.v_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_out\.": r"encoder.layers.\1.self_attn.output_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.linear_pos\.": r"encoder.layers.\1.self_attn.sdpa.r_proj.",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.pos_bias_u": r"encoder.layers.\1.self_attn.sdpa.u_bias",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.self_attn\.pos_bias_v": r"encoder.layers.\1.self_attn.sdpa.v_bias",
+        r"^encoder.w2v_model.encoder\.layers\.([0-9]+)\.final_layer_norm\.": r"encoder.layers.\1.layer_norm.",
+        r"^encoder.w2v_model.encoder\.layer_norm\.": r"encoder.layer_norm.",
+        r"^decoder\.embed_tokens\.": r"encoder_pooler.decoder_frontend.embed.",
+        r"^decoder\.layers\.([0-9]+)\.self_attn_layer_norm\.": r"encoder_pooler.decoder.layers.\1.self_attn_layer_norm.",
+        r"^decoder\.layers\.([0-9]+)\.self_attn\.out_proj\.": r"encoder_pooler.decoder.layers.\1.self_attn.output_proj.",
+        r"^decoder\.layers\.([0-9]+)\.self_attn\.": r"encoder_pooler.decoder.layers.\1.self_attn.",
         r"^decoder\.layers\.([0-9]+)\.encoder_attn_layer_norm\.": r"encoder_pooler.decoder.layers.\1.encoder_decoder_attn_layer_norm.",
-        r"^decoder\.layers\.([0-9]+)\.encoder_attn\.out_proj\.":  r"encoder_pooler.decoder.layers.\1.encoder_decoder_attn.output_proj.",
-        r"^decoder\.layers\.([0-9]+)\.encoder_attn\.":            r"encoder_pooler.decoder.layers.\1.encoder_decoder_attn.",
-        r"^decoder\.layers\.([0-9]+)\.fc1\.":                     r"encoder_pooler.decoder.layers.\1.ffn.inner_proj.",
-        r"^decoder\.layers\.([0-9]+)\.fc2\.":                     r"encoder_pooler.decoder.layers.\1.ffn.output_proj.",
-        r"^decoder\.layers\.([0-9]+)\.final_layer_norm\.":        r"encoder_pooler.decoder.layers.\1.ffn_layer_norm.",
-
-        r"^decoder\.embed_out":                                   r"encoder_pooler.projection_out.weight",
+        r"^decoder\.layers\.([0-9]+)\.encoder_attn\.out_proj\.": r"encoder_pooler.decoder.layers.\1.encoder_decoder_attn.output_proj.",
+        r"^decoder\.layers\.([0-9]+)\.encoder_attn\.": r"encoder_pooler.decoder.layers.\1.encoder_decoder_attn.",
+        r"^decoder\.layers\.([0-9]+)\.fc1\.": r"encoder_pooler.decoder.layers.\1.ffn.inner_proj.",
+        r"^decoder\.layers\.([0-9]+)\.fc2\.": r"encoder_pooler.decoder.layers.\1.ffn.output_proj.",
+        r"^decoder\.layers\.([0-9]+)\.final_layer_norm\.": r"encoder_pooler.decoder.layers.\1.ffn_layer_norm.",
+        r"^decoder\.embed_out": r"encoder_pooler.projection_out.weight",
         # fmt: on
     }
 
diff --git a/sonar/models/sonar_text/loader.py b/sonar/models/sonar_text/loader.py
index 295460c..c87f94b 100644
--- a/sonar/models/sonar_text/loader.py
+++ b/sonar/models/sonar_text/loader.py
@@ -20,8 +20,6 @@
     sonar_text_decoder_archs,
     sonar_text_encoder_archs,
 )
-from sonar.models.sonar_text.model import SonarTextTransformerEncoderModel
-from sonar.nn.conditional_decoder_model import ConditionalTransformerDecoderModel
 
 
 def convert_sonar_text_encoder_checkpoint(
diff --git a/tests/unit_tests/huggingface_pipelines/audio.py b/tests/unit_tests/huggingface_pipelines/audio.py
index e90cca6..674cb1f 100644
--- a/tests/unit_tests/huggingface_pipelines/audio.py
+++ b/tests/unit_tests/huggingface_pipelines/audio.py
@@ -1,5 +1,5 @@
 from typing import Any, Dict
-from unittest.mock import MagicMock, patch
+from unittest.mock import patch
 
 import numpy as np
 import pytest
diff --git a/tests/unit_tests/test_low_dimension_text_models.py b/tests/unit_tests/test_low_dimension_text_models.py
index 9a4a047..06d7638 100644
--- a/tests/unit_tests/test_low_dimension_text_models.py
+++ b/tests/unit_tests/test_low_dimension_text_models.py
@@ -14,7 +14,6 @@
     decoder_toy,
     encoder_basic,
 )
-from sonar.models.sonar_text.model import Pooling
 
 
 def test_low_dim_encoder():
diff --git a/uv.lock b/uv.lock
new file mode 100644
index 0000000..1c63cb9
--- /dev/null
+++ b/uv.lock
@@ -0,0 +1,2612 @@
+version = 1
+requires-python = ">=3.8"
+resolution-markers = [
+    "python_full_version < '3.9'",
+    "python_full_version == '3.9.*'",
+    "python_full_version == '3.10.*'",
+    "python_full_version == '3.11.*'",
+    "python_full_version >= '3.12'",
+]
+
+[[package]]
+name = "absl-py"
+version = "2.1.0"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/7a/8f/fc001b92ecc467cc32ab38398bd0bfb45df46e7523bf33c2ad22a505f06e/absl-py-2.1.0.tar.gz", hash = "sha256:7820790efbb316739cde8b4e19357243fc3608a152024288513dd968d7d959ff", size = 118055 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/a2/ad/e0d3c824784ff121c03cc031f944bc7e139a8f1870ffd2845cc2dd76f6c4/absl_py-2.1.0-py3-none-any.whl", hash = "sha256:526a04eadab8b4ee719ce68f204172ead1027549089702d99b9059f129ff1308", size = 133706 },
+]
+
+[[package]]
+name = "aiohappyeyeballs"
+version = "2.4.4"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/7f/55/e4373e888fdacb15563ef6fa9fa8c8252476ea071e96fb46defac9f18bf2/aiohappyeyeballs-2.4.4.tar.gz", hash = "sha256:5fdd7d87889c63183afc18ce9271f9b0a7d32c2303e394468dd45d514a757745", size = 21977 }
+wheels = [
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+]
+
+[[package]]
+name = "aiohttp"
+version = "3.10.11"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "aiohappyeyeballs" },
+    { name = "aiosignal" },
+    { name = "async-timeout", marker = "python_full_version < '3.11'" },
+    { name = "attrs" },
+    { name = "frozenlist" },
+    { name = "multidict" },
+    { name = "yarl" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/25/a8/8e2ba36c6e3278d62e0c88aa42bb92ddbef092ac363b390dab4421da5cf5/aiohttp-3.10.11.tar.gz", hash = "sha256:9dc2b8f3dcab2e39e0fa309c8da50c3b55e6f34ab25f1a71d3288f24924d33a7", size = 7551886 }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/11/c7/575f9e82d7ef13cb1b45b9db8a5b8fadb35107fb12e33809356ae0155223/aiohttp-3.10.11-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:5077b1a5f40ffa3ba1f40d537d3bec4383988ee51fbba6b74aa8fb1bc466599e", size = 588218 },
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