diff --git a/poetry.lock b/poetry.lock
index 5734dcc..5473a38 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -170,7 +170,7 @@ unicode-backport = ["unicodedata2"]
 name = "click"
 version = "8.1.3"
 description = "Composable command line interface toolkit"
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -390,7 +390,7 @@ files = [
 name = "filelock"
 version = "3.9.0"
 description = "A platform independent file lock."
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.7"
 files = [
@@ -642,6 +642,37 @@ colorama = ">=0.4"
 [package.extras]
 async = ["aiofiles (>=0.7,<1.0)"]
 
+[[package]]
+name = "huggingface-hub"
+version = "0.11.1"
+description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
+category = "main"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "huggingface_hub-0.11.1-py3-none-any.whl", hash = "sha256:11eed7aab4fa4d1fb532f2aea3379ef4998d9f6bc24a330834dfedd3dac7f441"},
+    {file = "huggingface_hub-0.11.1.tar.gz", hash = "sha256:8b9ebf9bbb1782f6f0419ec490973a6487c6c4ed84293a8a325d34c4f898f53f"},
+]
+
+[package.dependencies]
+filelock = "*"
+packaging = ">=20.9"
+pyyaml = ">=5.1"
+requests = "*"
+tqdm = "*"
+typing-extensions = ">=3.7.4.3"
+
+[package.extras]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+cli = ["InquirerPy (==0.3.4)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "jedi", "mypy (==0.982)", "pytest", "pytest-cov", "pytest-env", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
+quality = ["black (==22.3)", "flake8 (>=3.8.3)", "flake8-bugbear", "isort (>=5.5.4)", "mypy (==0.982)"]
+tensorflow = ["graphviz", "pydot", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "isort (>=5.5.4)", "jedi", "pytest", "pytest-cov", "pytest-env", "soundfile"]
+torch = ["torch"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+
 [[package]]
 name = "identify"
 version = "2.5.12"
@@ -737,6 +768,18 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
+[[package]]
+name = "joblib"
+version = "1.2.0"
+description = "Lightweight pipelining with Python functions"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "joblib-1.2.0-py3-none-any.whl", hash = "sha256:091138ed78f800342968c523bdde947e7a305b8594b910a0fea2ab83c3c6d385"},
+    {file = "joblib-1.2.0.tar.gz", hash = "sha256:e1cee4a79e4af22881164f218d4311f60074197fb707e082e803b61f6d137018"},
+]
+
 [[package]]
 name = "langchain"
 version = "0.0.57"
@@ -1036,6 +1079,32 @@ files = [
     {file = "mypy_extensions-0.4.3.tar.gz", hash = "sha256:2d82818f5bb3e369420cb3c4060a7970edba416647068eb4c5343488a6c604a8"},
 ]
 
+[[package]]
+name = "nltk"
+version = "3.8.1"
+description = "Natural Language Toolkit"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "nltk-3.8.1-py3-none-any.whl", hash = "sha256:fd5c9109f976fa86bcadba8f91e47f5e9293bd034474752e92a520f81c93dda5"},
+    {file = "nltk-3.8.1.zip", hash = "sha256:1834da3d0682cba4f2cede2f9aad6b0fafb6461ba451db0efb6f9c39798d64d3"},
+]
+
+[package.dependencies]
+click = "*"
+joblib = "*"
+regex = ">=2021.8.3"
+tqdm = "*"
+
+[package.extras]
+all = ["matplotlib", "numpy", "pyparsing", "python-crfsuite", "requests", "scikit-learn", "scipy", "twython"]
+corenlp = ["requests"]
+machine-learning = ["numpy", "python-crfsuite", "scikit-learn", "scipy"]
+plot = ["matplotlib"]
+tgrep = ["pyparsing"]
+twitter = ["twython"]
+
 [[package]]
 name = "nodeenv"
 version = "1.7.0"
@@ -1089,6 +1158,71 @@ files = [
     {file = "numpy-1.24.1.tar.gz", hash = "sha256:2386da9a471cc00a1f47845e27d916d5ec5346ae9696e01a8a34760858fe9dd2"},
 ]
 
+[[package]]
+name = "nvidia-cublas-cu11"
+version = "11.10.3.66"
+description = "CUBLAS native runtime libraries"
+category = "main"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-manylinux1_x86_64.whl", hash = "sha256:d32e4d75f94ddfb93ea0a5dda08389bcc65d8916a25cb9f37ac89edaeed3bded"},
+    {file = "nvidia_cublas_cu11-11.10.3.66-py3-none-win_amd64.whl", hash = "sha256:8ac17ba6ade3ed56ab898a036f9ae0756f1e81052a317bf98f8c6d18dc3ae49e"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-nvrtc-cu11"
+version = "11.7.99"
+description = "NVRTC native runtime libraries"
+category = "main"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:9f1562822ea264b7e34ed5930567e89242d266448e936b85bc97a3370feabb03"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:f7d9610d9b7c331fa0da2d1b2858a4a8315e6d49765091d28711c8946e7425e7"},
+    {file = "nvidia_cuda_nvrtc_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:f2effeb1309bdd1b3854fc9b17eaf997808f8b25968ce0c7070945c4265d64a3"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cuda-runtime-cu11"
+version = "11.7.99"
+description = "CUDA Runtime native Libraries"
+category = "main"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-manylinux1_x86_64.whl", hash = "sha256:cc768314ae58d2641f07eac350f40f99dcb35719c4faff4bc458a7cd2b119e31"},
+    {file = "nvidia_cuda_runtime_cu11-11.7.99-py3-none-win_amd64.whl", hash = "sha256:bc77fa59a7679310df9d5c70ab13c4e34c64ae2124dd1efd7e5474b71be125c7"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
+[[package]]
+name = "nvidia-cudnn-cu11"
+version = "8.5.0.96"
+description = "cuDNN runtime libraries"
+category = "main"
+optional = false
+python-versions = ">=3"
+files = [
+    {file = "nvidia_cudnn_cu11-8.5.0.96-2-py3-none-manylinux1_x86_64.whl", hash = "sha256:402f40adfc6f418f9dae9ab402e773cfed9beae52333f6d86ae3107a1b9527e7"},
+    {file = "nvidia_cudnn_cu11-8.5.0.96-py3-none-manylinux1_x86_64.whl", hash = "sha256:71f8111eb830879ff2836db3cccf03bbd735df9b0d17cd93761732ac50a8a108"},
+]
+
+[package.dependencies]
+setuptools = "*"
+wheel = "*"
+
 [[package]]
 name = "openai"
 version = "0.25.0"
@@ -1867,7 +2001,7 @@ docs = ["Sphinx (>=3.3,<4.0)", "sphinx-autobuild (>=2020.9.1,<2021.0.0)", "sphin
 name = "regex"
 version = "2022.10.31"
 description = "Alternative regular expression module, to replace re."
-category = "dev"
+category = "main"
 optional = false
 python-versions = ">=3.6"
 files = [
@@ -2002,6 +2136,88 @@ pygments = ">=2.6.0,<3.0.0"
 [package.extras]
 jupyter = ["ipywidgets (>=7.5.1,<8.0.0)"]
 
+[[package]]
+name = "scikit-learn"
+version = "1.2.0"
+description = "A set of python modules for machine learning and data mining"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "scikit-learn-1.2.0.tar.gz", hash = "sha256:680b65b3caee469541385d2ca5b03ff70408f6c618c583948312f0d2125df680"},
+    {file = "scikit_learn-1.2.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:1beaa631434d1f17a20b1eef5d842e58c195875d2bc11901a1a70b5fe544745b"},
+    {file = "scikit_learn-1.2.0-cp310-cp310-macosx_12_0_arm64.whl", hash = "sha256:d395730f26d8fc752321f1953ddf72647c892d8bed74fad4d7c816ec9b602dfa"},
+    {file = "scikit_learn-1.2.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:fd3480c982b9e616b9f76ad8587804d3f4e91b4e2a6752e7dafb8a2e1f541098"},
+    {file = "scikit_learn-1.2.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:184a42842a4e698ffa4d849b6019de50a77a0aa24d26afa28fa49c9190bb144b"},
+    {file = "scikit_learn-1.2.0-cp310-cp310-win_amd64.whl", hash = "sha256:867023a044fdfe59e5014a7fec7a3086a8928f10b5dce9382eedf4135f6709a2"},
+    {file = "scikit_learn-1.2.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:5546a8894a0616e92489ef995b39a0715829f3df96e801bb55cbf196be0d9649"},
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+[package.dependencies]
+joblib = ">=1.1.1"
+numpy = ">=1.17.3"
+scipy = ">=1.3.2"
+threadpoolctl = ">=2.0.0"
+
+[package.extras]
+benchmark = ["matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)", "pandas (>=1.0.5)"]
+docs = ["Pillow (>=7.1.2)", "matplotlib (>=3.1.3)", "memory-profiler (>=0.57.0)", "numpydoc (>=1.2.0)", "pandas (>=1.0.5)", "plotly (>=5.10.0)", "pooch (>=1.6.0)", "scikit-image (>=0.16.2)", "seaborn (>=0.9.0)", "sphinx (>=4.0.1)", "sphinx-gallery (>=0.7.0)", "sphinx-prompt (>=1.3.0)", "sphinxext-opengraph (>=0.4.2)"]
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+
+[[package]]
+name = "scipy"
+version = "1.9.3"
+description = "Fundamental algorithms for scientific computing in Python"
+category = "main"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "scipy-1.9.3-cp39-cp39-win_amd64.whl", hash = "sha256:5b88e6d91ad9d59478fafe92a7c757d00c59e3bdc3331be8ada76a4f8d683f58"},
+    {file = "scipy-1.9.3.tar.gz", hash = "sha256:fbc5c05c85c1a02be77b1ff591087c83bc44579c6d2bd9fb798bb64ea5e1a027"},
+]
+
+[package.dependencies]
+numpy = ">=1.18.5,<1.26.0"
+
+[package.extras]
+dev = ["flake8", "mypy", "pycodestyle", "typing_extensions"]
+doc = ["matplotlib (>2)", "numpydoc", "pydata-sphinx-theme (==0.9.0)", "sphinx (!=4.1.0)", "sphinx-panels (>=0.5.2)", "sphinx-tabs"]
+test = ["asv", "gmpy2", "mpmath", "pytest", "pytest-cov", "pytest-xdist", "scikit-umfpack", "threadpoolctl"]
+
 [[package]]
 name = "semver"
 version = "2.13.0"
@@ -2014,6 +2230,76 @@ files = [
     {file = "semver-2.13.0.tar.gz", hash = "sha256:fa0fe2722ee1c3f57eac478820c3a5ae2f624af8264cbdf9000c980ff7f75e3f"},
 ]
 
+[[package]]
+name = "sentence-transformers"
+version = "2.2.2"
+description = "Multilingual text embeddings"
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+testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests"]
+
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 version = "0.10.2"
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+]
+
+[package.dependencies]
+nvidia-cublas-cu11 = {version = "11.10.3.66", markers = "platform_system == \"Linux\""}
+nvidia-cuda-nvrtc-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""}
+nvidia-cuda-runtime-cu11 = {version = "11.7.99", markers = "platform_system == \"Linux\""}
+nvidia-cudnn-cu11 = {version = "8.5.0.96", markers = "platform_system == \"Linux\""}
+typing-extensions = "*"
+
+[package.extras]
+opt-einsum = ["opt-einsum (>=3.3)"]
+
+[[package]]
+name = "torchvision"
+version = "0.14.1"
+description = "image and video datasets and models for torch deep learning"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
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+    {file = "torchvision-0.14.1-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:68ed03359dcd3da9cd21b8ab94da21158df8a6a0c5bad0bf4a42f0e448d28cb3"},
+    {file = "torchvision-0.14.1-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:30fcf0e9fe57d4ac4ce6426659a57dce199637ccb6c70be1128670f177692624"},
+    {file = "torchvision-0.14.1-cp38-cp38-manylinux1_x86_64.whl", hash = "sha256:0ed02aefd09bf1114d35f1aa7dce55aa61c2c7e57f9aa02dce362860be654e85"},
+    {file = "torchvision-0.14.1-cp38-cp38-manylinux2014_aarch64.whl", hash = "sha256:a541e49fc3c4e90e49e6988428ab047415ed52ea97d0c0bfd147d8bacb8f4df8"},
+    {file = "torchvision-0.14.1-cp38-cp38-win_amd64.whl", hash = "sha256:6099b3191dc2516099a32ae38a5fb349b42e863872a13545ab1a524b6567be60"},
+    {file = "torchvision-0.14.1-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:c5e744f56e5f5b452deb5fc0f3f2ba4d2f00612d14d8da0dbefea8f09ac7690b"},
+    {file = "torchvision-0.14.1-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:758b20d079e810b4740bd60d1eb16e49da830e3360f9be379eb177ee221fa5d4"},
+    {file = "torchvision-0.14.1-cp39-cp39-manylinux1_x86_64.whl", hash = "sha256:83045507ef8d3c015d4df6be79491375b2f901352cfca6e72b4723e9c4f9a55d"},
+    {file = "torchvision-0.14.1-cp39-cp39-manylinux2014_aarch64.whl", hash = "sha256:eaed58cf454323ed9222d4e0dd5fb897064f454b400696e03a5200e65d3a1e76"},
+    {file = "torchvision-0.14.1-cp39-cp39-win_amd64.whl", hash = "sha256:b337e1245ca4353623dd563c03cd8f020c2496a7c5d12bba4d2e381999c766e0"},
+]
+
+[package.dependencies]
+numpy = "*"
+pillow = ">=5.3.0,<8.3.0 || >=8.4.0"
+requests = "*"
+torch = "1.13.1"
+typing-extensions = "*"
+
+[package.extras]
+scipy = ["scipy"]
+
 [[package]]
 name = "tornado"
 version = "6.2"
@@ -2246,6 +2675,72 @@ notebook = ["ipywidgets (>=6)"]
 slack = ["slack-sdk"]
 telegram = ["requests"]
 
+[[package]]
+name = "transformers"
+version = "4.25.1"
+description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
+category = "main"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "transformers-4.25.1-py3-none-any.whl", hash = "sha256:60f1be15e17e4a54373c787c713ec149dabcc63464131ac45611618fe7c2016e"},
+    {file = "transformers-4.25.1.tar.gz", hash = "sha256:6dad398b792d45dc04e9ee7e9e06bf758ab19dca2efc119065e661bb0f8f843b"},
+]
+
+[package.dependencies]
+filelock = "*"
+huggingface-hub = ">=0.10.0,<1.0"
+numpy = ">=1.17"
+packaging = ">=20.0"
+pyyaml = ">=5.1"
+regex = "!=2019.12.17"
+requests = "*"
+tokenizers = ">=0.11.1,<0.11.3 || >0.11.3,<0.14"
+tqdm = ">=4.27"
+
+[package.extras]
+accelerate = ["accelerate (>=0.10.0)"]
+all = ["Pillow", "accelerate (>=0.10.0)", "codecarbon (==1.2.0)", "flax (>=0.4.1)", "jax (>=0.2.8,!=0.3.2,<=0.3.6)", "jaxlib (>=0.1.65,<=0.3.6)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8)", "optuna", "phonemizer", "protobuf (<=3.20.2)", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.4,<2.11)", "tensorflow-text", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.7,!=1.12.0)", "torchaudio"]
+audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+codecarbon = ["codecarbon (==1.2.0)"]
+deepspeed = ["accelerate (>=0.10.0)", "deepspeed (>=0.6.5)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.10.0)", "beautifulsoup4", "black (==22.3)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.6.5)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "optuna", "parameterized", "protobuf (<=3.20.2)", "psutil", "pytest", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "safetensors (>=0.2.1)", "timeout-decorator"]
+dev = ["GitPython (<3.1.19)", "Pillow", "accelerate (>=0.10.0)", "beautifulsoup4", "black (==22.3)", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flake8 (>=3.8.3)", "flax (>=0.4.1)", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.2.8,!=0.3.2,<=0.3.6)", "jaxlib (>=0.1.65,<=0.3.6)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8)", "optuna", "parameterized", "phonemizer", "protobuf (<=3.20.2)", "psutil", "pyctcdecode (>=0.4.0)", "pyknp (>=0.6.1)", "pytest", "pytest-timeout", "pytest-xdist", "ray[tune]", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "safetensors (>=0.2.1)", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorflow (>=2.4,<2.11)", "tensorflow-text", "tf2onnx", "timeout-decorator", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.7,!=1.12.0)", "torchaudio", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
+dev-tensorflow = ["GitPython (<3.1.19)", "Pillow", "beautifulsoup4", "black (==22.3)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flake8 (>=3.8.3)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf (<=3.20.2)", "psutil", "pyctcdecode (>=0.4.0)", "pytest", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "safetensors (>=0.2.1)", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorflow (>=2.4,<2.11)", "tensorflow-text", "tf2onnx", "timeout-decorator", "tokenizers (>=0.11.1,!=0.11.3,<0.14)"]
+dev-torch = ["GitPython (<3.1.19)", "Pillow", "beautifulsoup4", "black (==22.3)", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flake8 (>=3.8.3)", "fugashi (>=1.0)", "hf-doc-builder", "hf-doc-builder (>=0.3.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf (<=3.20.2)", "psutil", "pyctcdecode (>=0.4.0)", "pyknp (>=0.6.1)", "pytest", "pytest-timeout", "pytest-xdist", "ray[tune]", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "safetensors (>=0.2.1)", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "timeout-decorator", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.7,!=1.12.0)", "torchaudio", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
+docs = ["Pillow", "accelerate (>=0.10.0)", "codecarbon (==1.2.0)", "flax (>=0.4.1)", "hf-doc-builder", "jax (>=0.2.8,!=0.3.2,<=0.3.6)", "jaxlib (>=0.1.65,<=0.3.6)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8)", "optuna", "phonemizer", "protobuf (<=3.20.2)", "pyctcdecode (>=0.4.0)", "ray[tune]", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>=2.4,<2.11)", "tensorflow-text", "tf2onnx", "timm", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.7,!=1.12.0)", "torchaudio"]
+docs-specific = ["hf-doc-builder"]
+fairscale = ["fairscale (>0.3)"]
+flax = ["flax (>=0.4.1)", "jax (>=0.2.8,!=0.3.2,<=0.3.6)", "jaxlib (>=0.1.65,<=0.3.6)", "optax (>=0.0.8)"]
+flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+ftfy = ["ftfy"]
+integrations = ["optuna", "ray[tune]", "sigopt"]
+ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "pyknp (>=0.6.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
+modelcreation = ["cookiecutter (==1.7.3)"]
+natten = ["natten (>=0.14.4)"]
+onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
+onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
+optuna = ["optuna"]
+quality = ["GitPython (<3.1.19)", "black (==22.3)", "datasets (!=2.5.0)", "flake8 (>=3.8.3)", "hf-doc-builder (>=0.3.0)", "isort (>=5.5.4)"]
+ray = ["ray[tune]"]
+retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
+sagemaker = ["sagemaker (>=2.31.0)"]
+sentencepiece = ["protobuf (<=3.20.2)", "sentencepiece (>=0.1.91,!=0.1.92)"]
+serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
+sigopt = ["sigopt"]
+sklearn = ["scikit-learn"]
+speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
+testing = ["GitPython (<3.1.19)", "beautifulsoup4", "black (==22.3)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "hf-doc-builder (>=0.3.0)", "nltk", "parameterized", "protobuf (<=3.20.2)", "psutil", "pytest", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "safetensors (>=0.2.1)", "timeout-decorator"]
+tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>=2.4,<2.11)", "tensorflow-text", "tf2onnx"]
+tf-cpu = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>=2.4,<2.11)", "tensorflow-text", "tf2onnx"]
+tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+timm = ["timm"]
+tokenizers = ["tokenizers (>=0.11.1,!=0.11.3,<0.14)"]
+torch = ["torch (>=1.7,!=1.12.0)"]
+torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
+torchhub = ["filelock", "huggingface-hub (>=0.10.0,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf (<=3.20.2)", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.11.1,!=0.11.3,<0.14)", "torch (>=1.7,!=1.12.0)", "tqdm (>=4.27)"]
+vision = ["Pillow"]
+
 [[package]]
 name = "tryceratops"
 version = "1.1.0"
@@ -2378,6 +2873,21 @@ files = [
     {file = "webencodings-0.5.1.tar.gz", hash = "sha256:b36a1c245f2d304965eb4e0a82848379241dc04b865afcc4aab16748587e1923"},
 ]
 
+[[package]]
+name = "wheel"
+version = "0.38.4"
+description = "A built-package format for Python"
+category = "main"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "wheel-0.38.4-py3-none-any.whl", hash = "sha256:b60533f3f5d530e971d6737ca6d58681ee434818fab630c83a734bb10c083ce8"},
+    {file = "wheel-0.38.4.tar.gz", hash = "sha256:965f5259b566725405b05e7cf774052044b1ed30119b5d586b2703aafe8719ac"},
+]
+
+[package.extras]
+test = ["pytest (>=3.0.0)"]
+
 [[package]]
 name = "zipp"
 version = "3.11.0"
@@ -2397,4 +2907,4 @@ testing = ["flake8 (<5)", "func-timeout", "jaraco.functools", "jaraco.itertools"
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.9.0, <4.0"
-content-hash = "98276af914546a90b1ddf76a62d2bb170c9d31135b9d9ef6f855e7029bae1fd7"
+content-hash = "34a3fad8c1a4f517b1a0b69126ef05892054d27a1ee8600d0c57da19f61130fa"
diff --git a/pyproject.toml b/pyproject.toml
index e445ced..2e94486 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -41,6 +41,7 @@ faiss-cpu = "^1.7.3"
 python-dotenv = "^0.21.0"
 panel = "^0.14.2"
 slug = "^2.0"
+sentence-transformers = "^2.2.2"
 
 [tool.poetry.group.dev.dependencies]
 autoflake = "*"
diff --git a/src/doc_search/app.py b/src/doc_search/app.py
index 0cfbf2c..cae2338 100644
--- a/src/doc_search/app.py
+++ b/src/doc_search/app.py
@@ -32,6 +32,13 @@ def parse_args() -> Namespace:
     parser.add_argument("-t", "--train", action="store_true", help="Train and index the PDF file")
     parser.add_argument("-a", "--web-app", action="store_true", help="Start WebApp")
     parser.add_argument("-p", "--pre-process", action="store_true", help="Extract text from PDF file")
+    parser.add_argument(
+        "-b",
+        "--embedding",
+        choices=["openai", "huggingface", "huggingface-hub", "cohere"],
+        default="openai",
+        help="Embedding to use",
+    )
 
     parser.add_argument(
         "-v",
diff --git a/src/doc_search/workflow/__init__.py b/src/doc_search/workflow/__init__.py
index 2b76c72..f09eed0 100644
--- a/src/doc_search/workflow/__init__.py
+++ b/src/doc_search/workflow/__init__.py
@@ -7,6 +7,9 @@
 import faiss  # type: ignore
 import openai
 from langchain import OpenAI, VectorDBQA
+from langchain.embeddings import HuggingFaceEmbeddings, HuggingFaceHubEmbeddings
+from langchain.embeddings.base import Embeddings
+from langchain.embeddings.cohere import CohereEmbeddings
 from langchain.embeddings.openai import OpenAIEmbeddings
 from langchain.prompts import PromptTemplate
 from langchain.text_splitter import CharacterTextSplitter
@@ -158,11 +161,22 @@ class CreateIndex(WorkflowBase):
     app_dir: Path
     overwrite_index: bool
     chunked_text_list: list[str]
+    embedding: str
 
     @retry(exceptions=openai.error.RateLimitError, tries=2, delay=60, back_off=2)
-    def append_to_index(self, docsearch: FAISS, text: str, embeddings: OpenAIEmbeddings) -> None:
+    def append_to_index(self, docsearch: FAISS, text: str, embeddings: Embeddings) -> None:
         docsearch.from_texts([text], embeddings)
 
+    def embedding_from_selection(self) -> Embeddings:
+        if self.embedding == "huggingface":
+            return HuggingFaceEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
+        elif self.embedding == "huggingface-hub":
+            return HuggingFaceHubEmbeddings(model_name="sentence-transformers/all-mpnet-base-v2")
+        elif self.embedding == "cohere":
+            return CohereEmbeddings()
+        else:
+            return OpenAIEmbeddings()
+
     def execute(self) -> dict:
         faiss_db = pdf_to_faiss_db_path(self.app_dir, self.input_pdf_path)
         index_path = pdf_to_index_path(self.app_dir, self.input_pdf_path)
@@ -178,7 +192,7 @@ def execute(self) -> dict:
                 faiss_db.exists(),
             )
 
-        embeddings = OpenAIEmbeddings()
+        embeddings = self.embedding_from_selection()
         docsearch: FAISS = FAISS.from_texts(self.chunked_text_list[:2], embeddings)
         for text in self.chunked_text_list[2:]:
             self.append_to_index(docsearch, text, embeddings)