diff --git a/poetry.lock b/poetry.lock
index 8cce782f..45bb5d40 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,35 +1,5 @@
 # This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
 
-[[package]]
-name = "accelerate"
-version = "0.25.0"
-description = "Accelerate"
-optional = false
-python-versions = ">=3.8.0"
-files = [
-    {file = "accelerate-0.25.0-py3-none-any.whl", hash = "sha256:c7bb817eb974bba0ff3ea1ba0f24d55afb86d50e3d4fe98d6922dc69cf2ccff1"},
-    {file = "accelerate-0.25.0.tar.gz", hash = "sha256:ecf55b0ab278a1dac8539dde0d276977aff04683f07ede73eaf02478538576a1"},
-]
-
-[package.dependencies]
-huggingface-hub = "*"
-numpy = ">=1.17"
-packaging = ">=20.0"
-psutil = "*"
-pyyaml = "*"
-safetensors = ">=0.3.1"
-torch = ">=1.10.0"
-
-[package.extras]
-dev = ["bitsandbytes", "black (>=23.1,<24.0)", "datasets", "deepspeed", "evaluate", "hf-doc-builder (>=0.3.0)", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "rich", "ruff (>=0.0.241)", "scikit-learn", "scipy", "timm", "tqdm", "transformers", "urllib3 (<2.0.0)"]
-quality = ["black (>=23.1,<24.0)", "hf-doc-builder (>=0.3.0)", "ruff (>=0.0.241)", "urllib3 (<2.0.0)"]
-rich = ["rich"]
-sagemaker = ["sagemaker"]
-test-dev = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "scikit-learn", "scipy", "timm", "tqdm", "transformers"]
-test-prod = ["parameterized", "pytest", "pytest-subtests", "pytest-xdist"]
-test-trackers = ["comet-ml", "dvclive", "tensorboard", "wandb"]
-testing = ["bitsandbytes", "datasets", "deepspeed", "evaluate", "parameterized", "pytest", "pytest-subtests", "pytest-xdist", "scikit-learn", "scipy", "timm", "tqdm", "transformers"]
-
 [[package]]
 name = "aiofiles"
 version = "23.2.1"
@@ -150,20 +120,6 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
-[[package]]
-name = "aiostream"
-version = "0.5.2"
-description = "Generator-based operators for asynchronous iteration"
-optional = false
-python-versions = ">=3.8"
-files = [
-    {file = "aiostream-0.5.2-py3-none-any.whl", hash = "sha256:054660370be9d37f6fe3ece3851009240416bd082e469fd90cc8673d3818cf71"},
-    {file = "aiostream-0.5.2.tar.gz", hash = "sha256:b71b519a2d66c38f0872403ab86417955b77352f08d9ad02ad46fc3926b389f4"},
-]
-
-[package.dependencies]
-typing-extensions = "*"
-
 [[package]]
 name = "altair"
 version = "5.2.0"
@@ -222,7 +178,7 @@ trio = ["trio (<0.22)"]
 name = "asgiref"
 version = "3.7.2"
 description = "ASGI specs, helper code, and adapters"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "asgiref-3.7.2-py3-none-any.whl", hash = "sha256:89b2ef2247e3b562a16eef663bc0e2e703ec6468e2fa8a5cd61cd449786d4f6e"},
@@ -236,7 +192,7 @@ tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"]
 name = "async-timeout"
 version = "4.0.3"
 description = "Timeout context manager for asyncio programs"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"},
@@ -247,7 +203,7 @@ files = [
 name = "asyncpg"
 version = "0.29.0"
 description = "An asyncio PostgreSQL driver"
-optional = true
+optional = false
 python-versions = ">=3.8.0"
 files = [
     {file = "asyncpg-0.29.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:72fd0ef9f00aeed37179c62282a3d14262dbbafb74ec0ba16e1b1864d8a12169"},
@@ -322,7 +278,7 @@ tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pyte
 name = "backoff"
 version = "2.2.1"
 description = "Function decoration for backoff and retry"
-optional = true
+optional = false
 python-versions = ">=3.7,<4.0"
 files = [
     {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
@@ -333,7 +289,7 @@ files = [
 name = "bcrypt"
 version = "4.1.2"
 description = "Modern password hashing for your software and your servers"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "bcrypt-4.1.2-cp37-abi3-macosx_10_12_universal2.whl", hash = "sha256:ac621c093edb28200728a9cca214d7e838529e557027ef0581685909acd28b5e"},
@@ -371,19 +327,22 @@ typecheck = ["mypy"]
 
 [[package]]
 name = "beautifulsoup4"
-version = "4.12.2"
+version = "4.12.3"
 description = "Screen-scraping library"
 optional = false
 python-versions = ">=3.6.0"
 files = [
-    {file = "beautifulsoup4-4.12.2-py3-none-any.whl", hash = "sha256:bd2520ca0d9d7d12694a53d44ac482d181b4ec1888909b035a3dbf40d0f57d4a"},
-    {file = "beautifulsoup4-4.12.2.tar.gz", hash = "sha256:492bbc69dca35d12daac71c4db1bfff0c876c00ef4a2ffacce226d4638eb72da"},
+    {file = "beautifulsoup4-4.12.3-py3-none-any.whl", hash = "sha256:b80878c9f40111313e55da8ba20bdba06d8fa3969fc68304167741bbf9e082ed"},
+    {file = "beautifulsoup4-4.12.3.tar.gz", hash = "sha256:74e3d1928edc070d21748185c46e3fb33490f22f52a3addee9aee0f4f7781051"},
 ]
 
 [package.dependencies]
 soupsieve = ">1.2"
 
 [package.extras]
+cchardet = ["cchardet"]
+chardet = ["chardet"]
+charset-normalizer = ["charset-normalizer"]
 html5lib = ["html5lib"]
 lxml = ["lxml"]
 
@@ -422,32 +381,32 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "boto3"
-version = "1.34.2"
+version = "1.34.51"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">= 3.8"
 files = [
-    {file = "boto3-1.34.2-py3-none-any.whl", hash = "sha256:aad3f305fe3cd4f2bba545c9580cd460c366af56a8aabb6094528dd32317f8d2"},
-    {file = "boto3-1.34.2.tar.gz", hash = "sha256:970fd9f9f522eb48f3cd5574e927b369279ebf5bcf0f2fae5ed9cc6306e58558"},
+    {file = "boto3-1.34.51-py3-none-any.whl", hash = "sha256:67732634dc7d0afda879bd9a5e2d0818a2c14a98bef766b95a3e253ea5104cb9"},
+    {file = "boto3-1.34.51.tar.gz", hash = "sha256:2cd9463e738a184cbce8a6824027c22163c5f73e277a35ff5aa0fb0e845b4301"},
 ]
 
 [package.dependencies]
-botocore = ">=1.34.2,<1.35.0"
+botocore = ">=1.34.51,<1.35.0"
 jmespath = ">=0.7.1,<2.0.0"
-s3transfer = ">=0.9.0,<0.10.0"
+s3transfer = ">=0.10.0,<0.11.0"
 
 [package.extras]
 crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.34.2"
+version = "1.34.51"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">= 3.8"
 files = [
-    {file = "botocore-1.34.2-py3-none-any.whl", hash = "sha256:655b1ea2a5d7b989a0eb6006c16137f785bc7334f31378115668c4be5d4b00eb"},
-    {file = "botocore-1.34.2.tar.gz", hash = "sha256:8a9f4ad438ba814b9b7a22b24de3004f8aa232e7ae86e0087aea4d7792dc3a2a"},
+    {file = "botocore-1.34.51-py3-none-any.whl", hash = "sha256:01d5156247f991b3466a8404e3d7460a9ecbd9b214f9992d6ba797d9ddc6f120"},
+    {file = "botocore-1.34.51.tar.gz", hash = "sha256:5086217442e67dd9de36ec7e87a0c663f76b7790d5fb6a12de565af95e87e319"},
 ]
 
 [package.dependencies]
@@ -456,13 +415,49 @@ python-dateutil = ">=2.1,<3.0.0"
 urllib3 = {version = ">=1.25.4,<2.1", markers = "python_version >= \"3.10\""}
 
 [package.extras]
-crt = ["awscrt (==0.19.17)"]
+crt = ["awscrt (==0.19.19)"]
+
+[[package]]
+name = "bs4"
+version = "0.0.2"
+description = "Dummy package for Beautiful Soup (beautifulsoup4)"
+optional = false
+python-versions = "*"
+files = [
+    {file = "bs4-0.0.2-py2.py3-none-any.whl", hash = "sha256:abf8742c0805ef7f662dce4b51cca104cffe52b835238afc169142ab9b3fbccc"},
+    {file = "bs4-0.0.2.tar.gz", hash = "sha256:a48685c58f50fe127722417bae83fe6badf500d54b55f7e39ffe43b798653925"},
+]
+
+[package.dependencies]
+beautifulsoup4 = "*"
+
+[[package]]
+name = "build"
+version = "1.0.3"
+description = "A simple, correct Python build frontend"
+optional = false
+python-versions = ">= 3.7"
+files = [
+    {file = "build-1.0.3-py3-none-any.whl", hash = "sha256:589bf99a67df7c9cf07ec0ac0e5e2ea5d4b37ac63301c4986d1acb126aa83f8f"},
+    {file = "build-1.0.3.tar.gz", hash = "sha256:538aab1b64f9828977f84bc63ae570b060a8ed1be419e7870b8b4fc5e6ea553b"},
+]
+
+[package.dependencies]
+colorama = {version = "*", markers = "os_name == \"nt\""}
+packaging = ">=19.0"
+pyproject_hooks = "*"
+
+[package.extras]
+docs = ["furo (>=2023.08.17)", "sphinx (>=7.0,<8.0)", "sphinx-argparse-cli (>=1.5)", "sphinx-autodoc-typehints (>=1.10)", "sphinx-issues (>=3.0.0)"]
+test = ["filelock (>=3)", "pytest (>=6.2.4)", "pytest-cov (>=2.12)", "pytest-mock (>=2)", "pytest-rerunfailures (>=9.1)", "pytest-xdist (>=1.34)", "setuptools (>=42.0.0)", "setuptools (>=56.0.0)", "setuptools (>=56.0.0)", "setuptools (>=67.8.0)", "wheel (>=0.36.0)"]
+typing = ["importlib-metadata (>=5.1)", "mypy (>=1.5.0,<1.6.0)", "tomli", "typing-extensions (>=3.7.4.3)"]
+virtualenv = ["virtualenv (>=20.0.35)"]
 
 [[package]]
 name = "cachetools"
 version = "5.3.2"
 description = "Extensible memoizing collections and decorators"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "cachetools-5.3.2-py3-none-any.whl", hash = "sha256:861f35a13a451f94e301ce2bec7cac63e881232ccce7ed67fab9b5df4d3beaa1"},
@@ -594,7 +589,7 @@ files = [
 name = "chroma-hnswlib"
 version = "0.7.3"
 description = "Chromas fork of hnswlib"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "chroma-hnswlib-0.7.3.tar.gz", hash = "sha256:b6137bedde49fffda6af93b0297fe00429fc61e5a072b1ed9377f909ed95a932"},
@@ -629,17 +624,18 @@ numpy = "*"
 
 [[package]]
 name = "chromadb"
-version = "0.4.20"
+version = "0.4.24"
 description = "Chroma."
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "chromadb-0.4.20-py3-none-any.whl", hash = "sha256:0b8ca7d22483273b12a282af7a4fbad0a804207d4431324a4673741fe3c92028"},
-    {file = "chromadb-0.4.20.tar.gz", hash = "sha256:69eb699ad6a5e46a2b558c8770ab91041dc32061ad66403aa8224fe5750229c5"},
+    {file = "chromadb-0.4.24-py3-none-any.whl", hash = "sha256:3a08e237a4ad28b5d176685bd22429a03717fe09d35022fb230d516108da01da"},
+    {file = "chromadb-0.4.24.tar.gz", hash = "sha256:a5c80b4e4ad9b236ed2d4899a5b9e8002b489293f2881cb2cadab5b199ee1c72"},
 ]
 
 [package.dependencies]
 bcrypt = ">=4.0.1"
+build = ">=1.0.3"
 chroma-hnswlib = "0.7.3"
 fastapi = ">=0.95.2"
 grpcio = ">=1.58.0"
@@ -652,6 +648,7 @@ opentelemetry-api = ">=1.2.0"
 opentelemetry-exporter-otlp-proto-grpc = ">=1.2.0"
 opentelemetry-instrumentation-fastapi = ">=0.41b0"
 opentelemetry-sdk = ">=1.2.0"
+orjson = ">=3.9.12"
 overrides = ">=7.3.1"
 posthog = ">=2.4.0"
 pulsar-client = ">=3.1.0"
@@ -865,48 +862,6 @@ files = [
 marshmallow = ">=3.18.0,<4.0.0"
 typing-inspect = ">=0.4.0,<1"
 
-[[package]]
-name = "datasets"
-version = "2.14.4"
-description = "HuggingFace community-driven open-source library of datasets"
-optional = false
-python-versions = ">=3.8.0"
-files = [
-    {file = "datasets-2.14.4-py3-none-any.whl", hash = "sha256:29336bd316a7d827ccd4da2236596279b20ca2ac78f64c04c9483da7cbc2459b"},
-    {file = "datasets-2.14.4.tar.gz", hash = "sha256:ef29c2b5841de488cd343cfc26ab979bff77efa4d2285af51f1ad7db5c46a83b"},
-]
-
-[package.dependencies]
-aiohttp = "*"
-dill = ">=0.3.0,<0.3.8"
-fsspec = {version = ">=2021.11.1", extras = ["http"]}
-huggingface-hub = ">=0.14.0,<1.0.0"
-multiprocess = "*"
-numpy = ">=1.17"
-packaging = "*"
-pandas = "*"
-pyarrow = ">=8.0.0"
-pyyaml = ">=5.1"
-requests = ">=2.19.0"
-tqdm = ">=4.62.1"
-xxhash = "*"
-
-[package.extras]
-apache-beam = ["apache-beam (>=2.26.0,<2.44.0)"]
-audio = ["librosa", "soundfile (>=0.12.1)"]
-benchmarks = ["tensorflow (==2.12.0)", "torch (==2.0.1)", "transformers (==4.30.1)"]
-dev = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "black (>=23.1,<24.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "pyyaml (>=5.3.1)", "rarfile (>=4.0)", "ruff (>=0.0.241)", "s3fs", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
-docs = ["s3fs", "tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos", "torch", "transformers"]
-jax = ["jax (>=0.2.8,!=0.3.2,<=0.3.25)", "jaxlib (>=0.1.65,<=0.3.25)"]
-metrics-tests = ["Werkzeug (>=1.0.1)", "accelerate", "bert-score (>=0.3.6)", "jiwer", "langdetect", "mauve-text", "nltk", "requests-file (>=1.5.1)", "rouge-score", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "spacy (>=3.0.0)", "texttable (>=1.6.3)", "tldextract", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "typer (<0.5.0)"]
-quality = ["black (>=23.1,<24.0)", "pyyaml (>=5.3.1)", "ruff (>=0.0.241)"]
-s3 = ["s3fs"]
-tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)", "tensorflow-macos"]
-tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
-tests = ["Pillow (>=6.2.1)", "absl-py", "apache-beam (>=2.26.0,<2.44.0)", "elasticsearch (<8.0.0)", "faiss-cpu (>=1.6.4)", "joblib (<1.3.0)", "joblibspark", "librosa", "lz4", "py7zr", "pyspark (>=3.4)", "pytest", "pytest-datadir", "pytest-xdist", "rarfile (>=4.0)", "s3fs (>=2021.11.1)", "soundfile (>=0.12.1)", "sqlalchemy (<2.0.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1)", "tensorflow-macos", "tiktoken", "torch", "transformers", "zstandard"]
-torch = ["torch"]
-vision = ["Pillow (>=6.2.1)"]
-
 [[package]]
 name = "deprecated"
 version = "1.2.14"
@@ -925,19 +880,16 @@ wrapt = ">=1.10,<2"
 dev = ["PyTest", "PyTest-Cov", "bump2version (<1)", "sphinx (<2)", "tox"]
 
 [[package]]
-name = "dill"
-version = "0.3.7"
-description = "serialize all of Python"
+name = "dirtyjson"
+version = "1.0.8"
+description = "JSON decoder for Python that can extract data from the muck"
 optional = false
-python-versions = ">=3.7"
+python-versions = "*"
 files = [
-    {file = "dill-0.3.7-py3-none-any.whl", hash = "sha256:76b122c08ef4ce2eedcd4d1abd8e641114bfc6c2867f49f3c41facf65bf19f5e"},
-    {file = "dill-0.3.7.tar.gz", hash = "sha256:cc1c8b182eb3013e24bd475ff2e9295af86c1a38eb1aff128dac8962a9ce3c03"},
+    {file = "dirtyjson-1.0.8-py3-none-any.whl", hash = "sha256:125e27248435a58acace26d5c2c4c11a1c0de0a9c5124c5a94ba78e517d74f53"},
+    {file = "dirtyjson-1.0.8.tar.gz", hash = "sha256:90ca4a18f3ff30ce849d100dcf4a003953c79d3a2348ef056f1d9c22231a25fd"},
 ]
 
-[package.extras]
-graph = ["objgraph (>=1.7.2)"]
-
 [[package]]
 name = "diskcache"
 version = "5.6.3"
@@ -1005,55 +957,18 @@ files = [
 dnspython = ">=2.0.0"
 idna = ">=2.0.0"
 
-[[package]]
-name = "evaluate"
-version = "0.4.1"
-description = "HuggingFace community-driven open-source library of evaluation"
-optional = false
-python-versions = ">=3.7.0"
-files = [
-    {file = "evaluate-0.4.1-py3-none-any.whl", hash = "sha256:3ff079ab09572c0a2c1e6d749887c19f6783ab993320412cd39f6fe501d28510"},
-    {file = "evaluate-0.4.1.tar.gz", hash = "sha256:d721d9f2059ced79770d8a0509e954fbd1bbac96a8f9160e29888d8073cda3d9"},
-]
-
-[package.dependencies]
-datasets = ">=2.0.0"
-dill = "*"
-fsspec = {version = ">=2021.05.0", extras = ["http"]}
-huggingface-hub = ">=0.7.0"
-multiprocess = "*"
-numpy = ">=1.17"
-packaging = "*"
-pandas = "*"
-requests = ">=2.19.0"
-responses = "<0.19"
-tqdm = ">=4.62.1"
-xxhash = "*"
-
-[package.extras]
-dev = ["Werkzeug (>=1.0.1)", "absl-py", "accelerate", "bert-score (>=0.3.6)", "black (>=22.0,<23.0)", "cer (>=1.2.0)", "charcut (>=1.1.1)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "jiwer", "mauve-text", "nltk", "pytest", "pytest-datadir", "pytest-xdist", "pyyaml (>=5.3.1)", "requests-file (>=1.5.1)", "rouge-score (>=0.1.2)", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1,<=2.10)", "texttable (>=1.6.3)", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "torch", "transformers", "trectools", "unidecode (>=1.3.4)"]
-docs = ["s3fs"]
-evaluator = ["scipy (>=1.7.1)", "transformers"]
-quality = ["black (>=22.0,<23.0)", "flake8 (>=3.8.3)", "isort (>=5.0.0)", "pyyaml (>=5.3.1)"]
-template = ["cookiecutter", "gradio (>=3.0.0)"]
-tensorflow = ["tensorflow (>=2.2.0,!=2.6.0,!=2.6.1)"]
-tensorflow-gpu = ["tensorflow-gpu (>=2.2.0,!=2.6.0,!=2.6.1)"]
-tests = ["Werkzeug (>=1.0.1)", "absl-py", "accelerate", "bert-score (>=0.3.6)", "cer (>=1.2.0)", "charcut (>=1.1.1)", "jiwer", "mauve-text", "nltk", "pytest", "pytest-datadir", "pytest-xdist", "requests-file (>=1.5.1)", "rouge-score (>=0.1.2)", "sacrebleu", "sacremoses", "scikit-learn", "scipy", "sentencepiece", "seqeval", "six (>=1.15.0,<1.16.0)", "tensorflow (>=2.3,!=2.6.0,!=2.6.1,<=2.10)", "texttable (>=1.6.3)", "tldextract (>=3.1.0)", "toml (>=0.10.1)", "torch", "transformers", "trectools", "unidecode (>=1.3.4)"]
-torch = ["torch"]
-
 [[package]]
 name = "fastapi"
-version = "0.103.2"
+version = "0.110.0"
 description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "fastapi-0.103.2-py3-none-any.whl", hash = "sha256:3270de872f0fe9ec809d4bd3d4d890c6d5cc7b9611d721d6438f9dacc8c4ef2e"},
-    {file = "fastapi-0.103.2.tar.gz", hash = "sha256:75a11f6bfb8fc4d2bec0bd710c2d5f2829659c0e8c0afd5560fdda6ce25ec653"},
+    {file = "fastapi-0.110.0-py3-none-any.whl", hash = "sha256:87a1f6fb632a218222c5984be540055346a8f5d8a68e8f6fb647b1dc9934de4b"},
+    {file = "fastapi-0.110.0.tar.gz", hash = "sha256:266775f0dcc95af9d3ef39bad55cff525329a931d5fd51930aadd4f428bf7ff3"},
 ]
 
 [package.dependencies]
-anyio = ">=3.7.1,<4.0.0"
 email-validator = {version = ">=2.0.0", optional = true, markers = "extra == \"all\""}
 httpx = {version = ">=0.23.0", optional = true, markers = "extra == \"all\""}
 itsdangerous = {version = ">=1.1.0", optional = true, markers = "extra == \"all\""}
@@ -1062,15 +977,15 @@ orjson = {version = ">=3.2.1", optional = true, markers = "extra == \"all\""}
 pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
 pydantic-extra-types = {version = ">=2.0.0", optional = true, markers = "extra == \"all\""}
 pydantic-settings = {version = ">=2.0.0", optional = true, markers = "extra == \"all\""}
-python-multipart = {version = ">=0.0.5", optional = true, markers = "extra == \"all\""}
+python-multipart = {version = ">=0.0.7", optional = true, markers = "extra == \"all\""}
 pyyaml = {version = ">=5.3.1", optional = true, markers = "extra == \"all\""}
-starlette = ">=0.27.0,<0.28.0"
-typing-extensions = ">=4.5.0"
+starlette = ">=0.36.3,<0.37.0"
+typing-extensions = ">=4.8.0"
 ujson = {version = ">=4.0.1,<4.0.2 || >4.0.2,<4.1.0 || >4.1.0,<4.2.0 || >4.2.0,<4.3.0 || >4.3.0,<5.0.0 || >5.0.0,<5.1.0 || >5.1.0", optional = true, markers = "extra == \"all\""}
 uvicorn = {version = ">=0.12.0", extras = ["standard"], optional = true, markers = "extra == \"all\""}
 
 [package.extras]
-all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
+all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.7)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
 
 [[package]]
 name = "ffmpy"
@@ -1271,10 +1186,6 @@ files = [
     {file = "fsspec-2023.12.2.tar.gz", hash = "sha256:8548d39e8810b59c38014934f6b31e57f40c1b20f911f4cc2b85389c7e9bf0cb"},
 ]
 
-[package.dependencies]
-aiohttp = {version = "<4.0.0a0 || >4.0.0a0,<4.0.0a1 || >4.0.0a1", optional = true, markers = "extra == \"http\""}
-requests = {version = "*", optional = true, markers = "extra == \"http\""}
-
 [package.extras]
 abfs = ["adlfs"]
 adl = ["adlfs"]
@@ -1303,7 +1214,7 @@ tqdm = ["tqdm"]
 name = "google-auth"
 version = "2.25.2"
 description = "Google Authentication Library"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "google-auth-2.25.2.tar.gz", hash = "sha256:42f707937feb4f5e5a39e6c4f343a17300a459aaf03141457ba505812841cc40"},
@@ -1326,7 +1237,7 @@ requests = ["requests (>=2.20.0,<3.0.0.dev0)"]
 name = "googleapis-common-protos"
 version = "1.62.0"
 description = "Common protobufs used in Google APIs"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "googleapis-common-protos-1.62.0.tar.gz", hash = "sha256:83f0ece9f94e5672cced82f592d2a5edf527a96ed1794f0bab36d5735c996277"},
@@ -1748,9 +1659,11 @@ files = [
 ]
 
 [package.dependencies]
+aiohttp = {version = "*", optional = true, markers = "extra == \"inference\""}
 filelock = "*"
 fsspec = ">=2023.5.0"
 packaging = ">=20.9"
+pydantic = {version = ">1.1,<3.0", optional = true, markers = "python_version > \"3.8\" and extra == \"inference\""}
 pyyaml = ">=5.1"
 requests = "*"
 tqdm = ">=4.42.1"
@@ -1823,7 +1736,7 @@ files = [
 name = "importlib-metadata"
 version = "6.11.0"
 description = "Read metadata from Python packages"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "importlib_metadata-6.11.0-py3-none-any.whl", hash = "sha256:f0afba6205ad8f8947c7d338b5342d5db2afbfd82f9cbef7879a9539cc12eb9b"},
@@ -2080,7 +1993,7 @@ files = [
 name = "kubernetes"
 version = "28.1.0"
 description = "Kubernetes python client"
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
     {file = "kubernetes-28.1.0-py2.py3-none-any.whl", hash = "sha256:10f56f8160dcb73647f15fafda268e7f60cf7dbc9f8e46d52fcd46d3beb0c18d"},
@@ -2104,16 +2017,17 @@ adal = ["adal (>=1.0.2)"]
 
 [[package]]
 name = "llama-cpp-python"
-version = "0.2.23"
+version = "0.2.53"
 description = "Python bindings for the llama.cpp library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "llama_cpp_python-0.2.23.tar.gz", hash = "sha256:364b61a13970932ea189b45a1c5dea89797b90e5da00f1fe6e72c47fbc512898"},
+    {file = "llama_cpp_python-0.2.53.tar.gz", hash = "sha256:f7ff8eda538ca6c80521a8bbf80d3ef4527ecb28f6d08fa9b3bb1f0cfc3b684e"},
 ]
 
 [package.dependencies]
 diskcache = ">=5.6.1"
+jinja2 = ">=2.11.3"
 numpy = ">=1.20.0"
 typing-extensions = ">=4.5.0"
 
@@ -2121,47 +2035,224 @@ typing-extensions = ">=4.5.0"
 all = ["llama_cpp_python[dev,server,test]"]
 dev = ["black (>=23.3.0)", "httpx (>=0.24.1)", "mkdocs (>=1.4.3)", "mkdocs-material (>=9.1.18)", "mkdocstrings[python] (>=0.22.0)", "pytest (>=7.4.0)", "twine (>=4.0.2)"]
 server = ["fastapi (>=0.100.0)", "pydantic-settings (>=2.0.1)", "sse-starlette (>=1.6.1)", "starlette-context (>=0.3.6,<0.4)", "uvicorn (>=0.22.0)"]
-test = ["httpx (>=0.24.1)", "pytest (>=7.4.0)"]
+test = ["httpx (>=0.24.1)", "pytest (>=7.4.0)", "scipy (>=1.10)"]
 
 [[package]]
-name = "llama-index"
-version = "0.9.3"
+name = "llama-index-core"
+version = "0.10.13"
 description = "Interface between LLMs and your data"
 optional = false
-python-versions = ">=3.8.1,<3.12"
+python-versions = ">=3.8.1,<4.0"
 files = [
-    {file = "llama_index-0.9.3-py3-none-any.whl", hash = "sha256:2b4b5be5f1a3b1158e8bcce49b728fee66370c776198c0b35ee22214a36a1e0b"},
-    {file = "llama_index-0.9.3.tar.gz", hash = "sha256:158c1feb68786e9134e3f70ab2c8a8e51b0e99f0f91f0a10162bd63c4d33f152"},
+    {file = "llama_index_core-0.10.13-py3-none-any.whl", hash = "sha256:40c76fc02be7cd948a333ca541f2ff38cf02774e1c960674e2b68c61943bac90"},
+    {file = "llama_index_core-0.10.13.tar.gz", hash = "sha256:826fded00767923fba8aca94f46c32b259e8879f517016ab7a3801b1b37187a1"},
 ]
 
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-aiostream = ">=0.5.2,<0.6.0"
-beautifulsoup4 = ">=4.12.2,<5.0.0"
-dataclasses-json = ">=0.5.7,<0.6.0"
+dataclasses-json = "*"
 deprecated = ">=1.2.9.3"
+dirtyjson = ">=1.0.8,<2.0.0"
 fsspec = ">=2023.5.0"
 httpx = "*"
+llamaindex-py-client = ">=0.1.13,<0.2.0"
 nest-asyncio = ">=1.5.8,<2.0.0"
+networkx = ">=3.0"
 nltk = ">=3.8.1,<4.0.0"
 numpy = "*"
 openai = ">=1.1.0"
-optimum = {version = ">=1.13.2,<2.0.0", extras = ["onnxruntime"], optional = true, markers = "extra == \"local-models\""}
-pandas = {version = "*", extras = ["jinja2"]}
-sentencepiece = {version = ">=0.1.99,<0.2.0", optional = true, markers = "extra == \"local-models\""}
+pandas = "*"
+pillow = ">=9.0.0"
+PyYAML = ">=6.0.1"
+requests = ">=2.31.0"
 SQLAlchemy = {version = ">=1.4.49", extras = ["asyncio"]}
 tenacity = ">=8.2.0,<9.0.0"
 tiktoken = ">=0.3.3"
-transformers = {version = ">=4.34.0,<5.0.0", extras = ["torch"], optional = true, markers = "extra == \"local-models\""}
+tqdm = ">=4.66.1,<5.0.0"
 typing-extensions = ">=4.5.0"
 typing-inspect = ">=0.8.0"
-urllib3 = "<2"
 
 [package.extras]
+gradientai = ["gradientai (>=1.4.0)"]
+html = ["beautifulsoup4 (>=4.12.2,<5.0.0)"]
 langchain = ["langchain (>=0.0.303)"]
-local-models = ["optimum[onnxruntime] (>=1.13.2,<2.0.0)", "sentencepiece (>=0.1.99,<0.2.0)", "transformers[torch] (>=4.34.0,<5.0.0)"]
-postgres = ["asyncpg (>=0.28.0,<0.29.0)", "pgvector (>=0.1.0,<0.2.0)", "psycopg-binary (>=3.1.12,<4.0.0)"]
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+postgres = ["asyncpg (>=0.28.0,<0.29.0)", "pgvector (>=0.1.0,<0.2.0)", "psycopg2-binary (>=2.9.9,<3.0.0)"]
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+
+[[package]]
+name = "llama-index-embeddings-huggingface"
+version = "0.1.4"
+description = "llama-index embeddings huggingface integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+[package.dependencies]
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+
+[[package]]
+name = "llama-index-embeddings-openai"
+version = "0.1.6"
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+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+[package.dependencies]
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+
+[[package]]
+name = "llama-index-llms-llama-cpp"
+version = "0.1.3"
+description = "llama-index llms llama cpp integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+[package.dependencies]
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+llama-index-core = ">=0.10.1,<0.11.0"
+
+[[package]]
+name = "llama-index-llms-ollama"
+version = "0.1.2"
+description = "llama-index llms ollama integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+[package.dependencies]
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+
+[[package]]
+name = "llama-index-llms-openai"
+version = "0.1.6"
+description = "llama-index llms openai integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+]
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+[package.dependencies]
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+
+[[package]]
+name = "llama-index-llms-openai-like"
+version = "0.1.3"
+description = "llama-index llms openai like integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+
+[[package]]
+name = "llama-index-readers-file"
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+description = "llama-index readers file integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+pypdf = ">=4.0.1,<5.0.0"
+
+[[package]]
+name = "llama-index-vector-stores-chroma"
+version = "0.1.4"
+description = "llama-index vector_stores chroma integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+    {file = "llama_index_vector_stores_chroma-0.1.4.tar.gz", hash = "sha256:7364f2a3f8a51b83d350da39da7e7046704cfa9c848ebe8fd1c6cb39ad4878f9"},
+]
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+[package.dependencies]
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+onnxruntime = ">=1.17.0,<2.0.0"
+tokenizers = ">=0.15.1,<0.16.0"
+
+[[package]]
+name = "llama-index-vector-stores-postgres"
+version = "0.1.2"
+description = "llama-index vector_stores postgres integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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+
+[[package]]
+name = "llama-index-vector-stores-qdrant"
+version = "0.1.3"
+description = "llama-index vector_stores qdrant integration"
+optional = false
+python-versions = ">=3.8.1,<4.0"
+files = [
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 description = "Python extension for MurmurHash (MurmurHash3), a set of fast and robust hash functions."
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 ]
 
 [package.dependencies]
@@ -2982,7 +3005,7 @@ datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 name = "opentelemetry-api"
 version = "1.21.0"
 description = "OpenTelemetry Python API"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_api-1.21.0-py3-none-any.whl", hash = "sha256:4bb86b28627b7e41098f0e93280fe4892a1abed1b79a19aec6f928f39b17dffb"},
@@ -2997,7 +3020,7 @@ importlib-metadata = ">=6.0,<7.0"
 name = "opentelemetry-exporter-otlp-proto-common"
 version = "1.21.0"
 description = "OpenTelemetry Protobuf encoding"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_exporter_otlp_proto_common-1.21.0-py3-none-any.whl", hash = "sha256:97b1022b38270ec65d11fbfa348e0cd49d12006485c2321ea3b1b7037d42b6ec"},
@@ -3012,7 +3035,7 @@ opentelemetry-proto = "1.21.0"
 name = "opentelemetry-exporter-otlp-proto-grpc"
 version = "1.21.0"
 description = "OpenTelemetry Collector Protobuf over gRPC Exporter"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_exporter_otlp_proto_grpc-1.21.0-py3-none-any.whl", hash = "sha256:ab37c63d6cb58d6506f76d71d07018eb1f561d83e642a8f5aa53dddf306087a4"},
@@ -3036,7 +3059,7 @@ test = ["pytest-grpc"]
 name = "opentelemetry-instrumentation"
 version = "0.42b0"
 description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_instrumentation-0.42b0-py3-none-any.whl", hash = "sha256:65ae54ddb90ca2d05d2d16bf6863173e7141eba1bbbf41fc9bbb02446adbe369"},
@@ -3052,7 +3075,7 @@ wrapt = ">=1.0.0,<2.0.0"
 name = "opentelemetry-instrumentation-asgi"
 version = "0.42b0"
 description = "ASGI instrumentation for OpenTelemetry"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_instrumentation_asgi-0.42b0-py3-none-any.whl", hash = "sha256:79b7278fb614aba1bf2211060960d3e8501c1d7d9314b857b30ad80ba34a2805"},
@@ -3074,7 +3097,7 @@ test = ["opentelemetry-instrumentation-asgi[instruments]", "opentelemetry-test-u
 name = "opentelemetry-instrumentation-fastapi"
 version = "0.42b0"
 description = "OpenTelemetry FastAPI Instrumentation"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_instrumentation_fastapi-0.42b0-py3-none-any.whl", hash = "sha256:d53a26c4859767d5ba67109038cabc7165d97a8a8b7654ccde4ce290036d1725"},
@@ -3096,7 +3119,7 @@ test = ["httpx (>=0.22,<1.0)", "opentelemetry-instrumentation-fastapi[instrument
 name = "opentelemetry-proto"
 version = "1.21.0"
 description = "OpenTelemetry Python Proto"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_proto-1.21.0-py3-none-any.whl", hash = "sha256:32fc4248e83eebd80994e13963e683f25f3b443226336bb12b5b6d53638f50ba"},
@@ -3110,7 +3133,7 @@ protobuf = ">=3.19,<5.0"
 name = "opentelemetry-sdk"
 version = "1.21.0"
 description = "OpenTelemetry Python SDK"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_sdk-1.21.0-py3-none-any.whl", hash = "sha256:9fe633243a8c655fedace3a0b89ccdfc654c0290ea2d8e839bd5db3131186f73"},
@@ -3126,7 +3149,7 @@ typing-extensions = ">=3.7.4"
 name = "opentelemetry-semantic-conventions"
 version = "0.42b0"
 description = "OpenTelemetry Semantic Conventions"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_semantic_conventions-0.42b0-py3-none-any.whl", hash = "sha256:5cd719cbfec448af658860796c5d0fcea2fdf0945a2bed2363f42cb1ee39f526"},
@@ -3137,128 +3160,77 @@ files = [
 name = "opentelemetry-util-http"
 version = "0.42b0"
 description = "Web util for OpenTelemetry"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "opentelemetry_util_http-0.42b0-py3-none-any.whl", hash = "sha256:764069ed2f7e9a98ed1a7a87111f838000484e388e81f467405933be4b0306c6"},
     {file = "opentelemetry_util_http-0.42b0.tar.gz", hash = "sha256:665e7d372837811aa08cbb9102d4da862441d1c9b1795d649ef08386c8a3cbbd"},
 ]
 
-[[package]]
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-version = "1.16.1"
-description = "Optimum Library is an extension of the Hugging Face Transformers library, providing a framework to integrate third-party libraries from Hardware Partners and interface with their specific functionality."
-optional = false
-python-versions = ">=3.7.0"
-files = [
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-]
-
-[package.dependencies]
-coloredlogs = "*"
-datasets = [
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-    {version = ">=1.2.1", optional = true, markers = "extra == \"onnxruntime\""},
-]
-evaluate = {version = "*", optional = true, markers = "extra == \"onnxruntime\""}
-huggingface-hub = ">=0.8.0"
-numpy = "*"
-onnx = {version = "*", optional = true, markers = "extra == \"onnxruntime\""}
-onnxruntime = {version = ">=1.11.0", optional = true, markers = "extra == \"onnxruntime\""}
-packaging = "*"
-protobuf = {version = ">=3.20.1", optional = true, markers = "extra == \"onnxruntime\""}
-sympy = "*"
-torch = ">=1.9"
-transformers = {version = ">=4.26.0", extras = ["sentencepiece"]}
-
-[package.extras]
-amd = ["optimum-amd"]
-benchmark = ["evaluate (>=0.2.0)", "optuna", "scikit-learn", "seqeval", "torchvision", "tqdm"]
-dev = ["Pillow", "accelerate", "black (>=23.1,<24.0)", "diffusers (>=0.17.0)", "einops", "invisible-watermark", "parameterized", "pytest", "pytest-xdist", "requests", "ruff (==0.1.5)", "sacremoses", "torchaudio", "torchvision"]
-diffusers = ["diffusers"]
-doc-build = ["accelerate"]
-exporters = ["onnx", "onnxruntime", "timm"]
-exporters-gpu = ["onnx", "onnxruntime-gpu", "timm"]
-exporters-tf = ["h5py", "numpy (<1.24.0)", "onnx", "onnxruntime", "tensorflow (>=2.4,<=2.12.1)", "tf2onnx", "timm"]
-furiosa = ["optimum-furiosa"]
-graphcore = ["optimum-graphcore"]
-habana = ["optimum-habana", "transformers (>=4.33.0,<4.35.0)"]
-intel = ["optimum-intel (>=1.12.0)"]
-neural-compressor = ["optimum-intel[neural-compressor] (>=1.12.0)"]
-neuron = ["optimum-neuron[neuron]"]
-neuronx = ["optimum-neuron[neuronx]"]
-nncf = ["optimum-intel[nncf] (>=1.12.0)"]
-onnxruntime = ["datasets (>=1.2.1)", "evaluate", "onnx", "onnxruntime (>=1.11.0)", "protobuf (>=3.20.1)"]
-onnxruntime-gpu = ["accelerate", "datasets (>=1.2.1)", "evaluate", "onnx", "onnxruntime-gpu (>=1.11.0)", "protobuf (>=3.20.1)"]
-openvino = ["optimum-intel[openvino] (>=1.12.0)"]
-quality = ["black (>=23.1,<24.0)", "ruff (==0.1.5)"]
-tests = ["Pillow", "accelerate", "diffusers (>=0.17.0)", "einops", "invisible-watermark", "parameterized", "pytest", "pytest-xdist", "requests", "sacremoses", "torchaudio", "torchvision"]
-
 [[package]]
 name = "orjson"
-version = "3.9.10"
+version = "3.9.15"
 description = "Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy"
 optional = false
 python-versions = ">=3.8"
 files = [
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 [[package]]
 name = "overrides"
 version = "7.4.0"
 description = "A decorator to automatically detect mismatch when overriding a method."
-optional = true
+optional = false
 python-versions = ">=3.6"
 files = [
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@@ -3355,7 +3327,7 @@ files = [
 name = "pgvector"
 version = "0.2.5"
 description = "pgvector support for Python"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
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@@ -3484,7 +3456,7 @@ tests = ["pytest (>=5.4.1)", "pytest-cov (>=2.8.1)", "pytest-mypy (>=0.8.0)", "p
 name = "posthog"
 version = "3.1.0"
 description = "Integrate PostHog into any python application."
-optional = true
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 python-versions = "*"
 files = [
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 ]
 
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-]
-
-[package.extras]
-test = ["enum34", "ipaddress", "mock", "pywin32", "wmi"]
-
 [[package]]
 name = "psycopg2-binary"
 version = "2.9.9"
 description = "psycopg2 - Python-PostgreSQL Database Adapter"
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
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@@ -3654,7 +3598,7 @@ files = [
 name = "pulsar-client"
 version = "3.3.0"
 description = "Apache Pulsar Python client library"
-optional = true
+optional = false
 python-versions = "*"
 files = [
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@@ -3697,59 +3641,11 @@ all = ["apache-bookkeeper-client (>=4.16.1)", "fastavro (==1.7.3)", "grpcio (>=1
 avro = ["fastavro (==1.7.3)"]
 functions = ["apache-bookkeeper-client (>=4.16.1)", "grpcio (>=1.8.2)", "prometheus-client", "protobuf (>=3.6.1,<=3.20.3)", "ratelimit"]
 
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-description = "Python library for Apache Arrow"
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-
-[package.dependencies]
-numpy = ">=1.16.6"
-
 [[package]]
 name = "pyasn1"
 version = "0.5.1"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
-optional = true
+optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
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@@ -3760,7 +3656,7 @@ files = [
 name = "pyasn1-modules"
 version = "0.3.0"
 description = "A collection of ASN.1-based protocols modules"
-optional = true
+optional = false
 python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,>=2.7"
 files = [
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@@ -3964,6 +3860,64 @@ files = [
 plugins = ["importlib-metadata"]
 windows-terminal = ["colorama (>=0.4.6)"]
 
+[[package]]
+name = "pymupdf"
+version = "1.23.25"
+description = "A high performance Python library for data extraction, analysis, conversion & manipulation of PDF (and other) documents."
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
+PyMuPDFb = "1.23.22"
+
+[[package]]
+name = "pymupdfb"
+version = "1.23.22"
+description = "MuPDF shared libraries for PyMuPDF."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "PyMuPDFb-1.23.22-py3-none-macosx_10_9_x86_64.whl", hash = "sha256:9085a1e2fbf16f2820f9f7ad3d25e85f81d9b9eb0409110c1670d4cf5a27a678"},
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+    {file = "PyMuPDFb-1.23.22-py3-none-manylinux2014_aarch64.manylinux_2_17_aarch64.whl", hash = "sha256:cf50e814db91f2a2325219302fbac229a23682c372cf8232aabd51ea3f18210e"},
+    {file = "PyMuPDFb-1.23.22-py3-none-manylinux2014_x86_64.manylinux_2_17_x86_64.whl", hash = "sha256:3ffa713ad18e816e584c8a5f569995c32d22f8ac76ab6e4a61f2d2983c4b73d9"},
+    {file = "PyMuPDFb-1.23.22-py3-none-win32.whl", hash = "sha256:d00e372452845aea624659c302d25e935052269fd3aafe26948301576d6f2ee8"},
+    {file = "PyMuPDFb-1.23.22-py3-none-win_amd64.whl", hash = "sha256:7c9c157281fdee9f296e666a323307dbf74cb38f017921bb131fa7bfcd39c2bd"},
+]
+
 [[package]]
 name = "pyparsing"
 version = "3.1.1"
@@ -3980,13 +3934,13 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pypdf"
-version = "3.17.2"
+version = "4.0.2"
 description = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files"
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "pypdf-3.17.2-py3-none-any.whl", hash = "sha256:e149ed50aa41e04b176246714806cd8d6c6c6d68b528508f849642959041963a"},
-    {file = "pypdf-3.17.2.tar.gz", hash = "sha256:d6f077060912f8292d7db3da04f7bf2428ac974781e11eef219193a22120f649"},
+    {file = "pypdf-4.0.2-py3-none-any.whl", hash = "sha256:a62daa2a24d5a608ba1b6284dde185317ce3644f89b9ebe5314d0c5d1c9f257d"},
+    {file = "pypdf-4.0.2.tar.gz", hash = "sha256:3316d9ddfcff5df67ae3cdfe8b945c432aa43e7f970bae7c2a4ab4fe129cd937"},
 ]
 
 [package.extras]
@@ -4000,12 +3954,23 @@ image = ["Pillow (>=8.0.0)"]
 name = "pypika"
 version = "0.48.9"
 description = "A SQL query builder API for Python"
-optional = true
+optional = false
 python-versions = "*"
 files = [
     {file = "PyPika-0.48.9.tar.gz", hash = "sha256:838836a61747e7c8380cd1b7ff638694b7a7335345d0f559b04b2cd832ad5378"},
 ]
 
+[[package]]
+name = "pyproject-hooks"
+version = "1.0.0"
+description = "Wrappers to call pyproject.toml-based build backend hooks."
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "pyproject_hooks-1.0.0-py3-none-any.whl", hash = "sha256:283c11acd6b928d2f6a7c73fa0d01cb2bdc5f07c57a2eeb6e83d5e56b97976f8"},
+    {file = "pyproject_hooks-1.0.0.tar.gz", hash = "sha256:f271b298b97f5955d53fb12b72c1fb1948c22c1a6b70b315c54cedaca0264ef5"},
+]
+
 [[package]]
 name = "pyreadline3"
 version = "3.4.1"
@@ -4103,17 +4068,17 @@ cli = ["click (>=5.0)"]
 
 [[package]]
 name = "python-multipart"
-version = "0.0.6"
+version = "0.0.9"
 description = "A streaming multipart parser for Python"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "python_multipart-0.0.6-py3-none-any.whl", hash = "sha256:ee698bab5ef148b0a760751c261902cd096e57e10558e11aca17646b74ee1c18"},
-    {file = "python_multipart-0.0.6.tar.gz", hash = "sha256:e9925a80bb668529f1b67c7fdb0a5dacdd7cbfc6fb0bff3ea443fe22bdd62132"},
+    {file = "python_multipart-0.0.9-py3-none-any.whl", hash = "sha256:97ca7b8ea7b05f977dc3849c3ba99d51689822fab725c3703af7c866a0c2b215"},
+    {file = "python_multipart-0.0.9.tar.gz", hash = "sha256:03f54688c663f1b7977105f021043b0793151e4cb1c1a9d4a11fc13d622c4026"},
 ]
 
 [package.extras]
-dev = ["atomicwrites (==1.2.1)", "attrs (==19.2.0)", "coverage (==6.5.0)", "hatch", "invoke (==1.7.3)", "more-itertools (==4.3.0)", "pbr (==4.3.0)", "pluggy (==1.0.0)", "py (==1.11.0)", "pytest (==7.2.0)", "pytest-cov (==4.0.0)", "pytest-timeout (==2.1.0)", "pyyaml (==5.1)"]
+dev = ["atomicwrites (==1.4.1)", "attrs (==23.2.0)", "coverage (==7.4.1)", "hatch", "invoke (==2.2.0)", "more-itertools (==10.2.0)", "pbr (==6.0.0)", "pluggy (==1.4.0)", "py (==1.11.0)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-timeout (==2.2.0)", "pyyaml (==6.0.1)", "ruff (==0.2.1)"]
 
 [[package]]
 name = "pytz"
@@ -4210,13 +4175,13 @@ files = [
 
 [[package]]
 name = "qdrant-client"
-version = "1.7.0"
+version = "1.7.3"
 description = "Client library for the Qdrant vector search engine"
 optional = false
-python-versions = ">=3.8,<3.13"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -4226,7 +4191,7 @@ httpx = {version = ">=0.14.0", extras = ["http2"]}
 numpy = {version = ">=1.21", markers = "python_version >= \"3.8\" and python_version < \"3.12\""}
 portalocker = ">=2.7.0,<3.0.0"
 pydantic = ">=1.10.8"
-urllib3 = ">=1.26.14,<2.0.0"
+urllib3 = ">=1.26.14,<3"
 
 [package.extras]
 fastembed = ["fastembed (==0.1.1)"]
@@ -4368,7 +4333,7 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 name = "requests-oauthlib"
 version = "1.3.1"
 description = "OAuthlib authentication support for Requests."
-optional = true
+optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
 files = [
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@@ -4382,24 +4347,6 @@ requests = ">=2.0.0"
 [package.extras]
 rsa = ["oauthlib[signedtoken] (>=3.0.0)"]
 
-[[package]]
-name = "responses"
-version = "0.18.0"
-description = "A utility library for mocking out the `requests` Python library."
-optional = false
-python-versions = ">=3.7"
-files = [
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-
-[package.dependencies]
-requests = ">=2.0,<3.0"
-urllib3 = ">=1.25.10"
-
-[package.extras]
-tests = ["coverage (>=6.0.0)", "flake8", "mypy", "pytest (>=4.6)", "pytest-cov", "pytest-localserver", "types-mock", "types-requests"]
-
 [[package]]
 name = "rich"
 version = "13.7.0"
@@ -4530,7 +4477,7 @@ files = [
 name = "rsa"
 version = "4.9"
 description = "Pure-Python RSA implementation"
-optional = true
+optional = false
 python-versions = ">=3.6,<4"
 files = [
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@@ -4568,13 +4515,13 @@ files = [
 
 [[package]]
 name = "s3transfer"
-version = "0.9.0"
+version = "0.10.0"
 description = "An Amazon S3 Transfer Manager"
 optional = false
 python-versions = ">= 3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -5031,20 +4978,20 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "starlette"
-version = "0.27.0"
+version = "0.36.3"
 description = "The little ASGI library that shines."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 [package.dependencies]
 anyio = ">=3.4.0,<5"
 
 [package.extras]
-full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"]
+full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7)", "pyyaml"]
 
 [[package]]
 name = "sympy"
@@ -5139,109 +5086,121 @@ blobfile = ["blobfile (>=2)"]
 
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 python-versions = ">=3.7"
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 [package.dependencies]
@@ -5387,43 +5346,39 @@ telegram = ["requests"]
 
 [[package]]
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 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
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 tokenizers = ">=0.14,<0.19"
-torch = {version = ">=1.10,<1.12.0 || >1.12.0", optional = true, markers = "extra == \"torch\""}
 tqdm = ">=4.27"
 
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-]
-
 [[package]]
 name = "yarl"
 version = "1.9.4"
@@ -6257,7 +6097,7 @@ multidict = ">=4.0"
 name = "zipp"
 version = "3.17.0"
 description = "Backport of pathlib-compatible object wrapper for zip files"
-optional = true
+optional = false
 python-versions = ">=3.8"
 files = [
     {file = "zipp-3.17.0-py3-none-any.whl", hash = "sha256:0e923e726174922dce09c53c59ad483ff7bbb8e572e00c7f7c46b88556409f31"},
@@ -6275,4 +6115,4 @@ pgvector = ["asyncpg", "pgvector", "psycopg2-binary", "sqlalchemy"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.11,<3.12"
-content-hash = "ce0641f693c3fc99cfd560d9c2cbfc6fba83e12bbaecbbdea33eddcda9c286c3"
+content-hash = "61b133c46c9589c72010ebc29989fe6a01df7ce80f1b49e65dbfb5b1cf759a27"
diff --git a/private_gpt/components/embedding/embedding_component.py b/private_gpt/components/embedding/embedding_component.py
index e60c7af6..182b8184 100644
--- a/private_gpt/components/embedding/embedding_component.py
+++ b/private_gpt/components/embedding/embedding_component.py
@@ -1,8 +1,7 @@
 import logging
 
 from injector import inject, singleton
-from llama_index import MockEmbedding
-from llama_index.embeddings.base import BaseEmbedding
+from llama_index.core.embeddings import BaseEmbedding, MockEmbedding
 
 from private_gpt.paths import models_cache_path
 from private_gpt.settings.settings import Settings
@@ -20,7 +19,7 @@ class EmbeddingComponent:
         logger.info("Initializing the embedding model in mode=%s", embedding_mode)
         match embedding_mode:
             case "local":
-                from llama_index.embeddings import HuggingFaceEmbedding
+                from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 
                 self.embedding_model = HuggingFaceEmbedding(
                     model_name=settings.local.embedding_hf_model_name,
@@ -36,7 +35,7 @@ class EmbeddingComponent:
                     endpoint_name=settings.sagemaker.embedding_endpoint_name,
                 )
             case "openai":
-                from llama_index import OpenAIEmbedding
+                from llama_index.embeddings.openai import OpenAIEmbedding
 
                 openai_settings = settings.openai.api_key
                 self.embedding_model = OpenAIEmbedding(api_key=openai_settings)
diff --git a/private_gpt/components/ingest/ingest_component.py b/private_gpt/components/ingest/ingest_component.py
index e8ec1e8f..e21b6c23 100644
--- a/private_gpt/components/ingest/ingest_component.py
+++ b/private_gpt/components/ingest/ingest_component.py
@@ -8,16 +8,13 @@ import threading
 from pathlib import Path
 from typing import Any
 
-from llama_index import (
-    Document,
-    ServiceContext,
-    StorageContext,
-    VectorStoreIndex,
-    load_index_from_storage,
-)
-from llama_index.data_structs import IndexDict
-from llama_index.indices.base import BaseIndex
-from llama_index.ingestion import run_transformations
+from llama_index.core.data_structs import IndexDict
+from llama_index.core.embeddings.utils import EmbedType
+from llama_index.core.indices import VectorStoreIndex, load_index_from_storage
+from llama_index.core.indices.base import BaseIndex
+from llama_index.core.ingestion import run_transformations
+from llama_index.core.schema import Document, TransformComponent
+from llama_index.core.storage import StorageContext
 
 from private_gpt.components.ingest.ingest_helper import IngestionHelper
 from private_gpt.paths import local_data_path
@@ -30,13 +27,15 @@ class BaseIngestComponent(abc.ABC):
     def __init__(
         self,
         storage_context: StorageContext,
-        service_context: ServiceContext,
+        embed_model: EmbedType,
+        transformations: list[TransformComponent],
         *args: Any,
         **kwargs: Any,
     ) -> None:
         logger.debug("Initializing base ingest component type=%s", type(self).__name__)
         self.storage_context = storage_context
-        self.service_context = service_context
+        self.embed_model = embed_model
+        self.transformations = transformations
 
     @abc.abstractmethod
     def ingest(self, file_name: str, file_data: Path) -> list[Document]:
@@ -55,11 +54,12 @@ class BaseIngestComponentWithIndex(BaseIngestComponent, abc.ABC):
     def __init__(
         self,
         storage_context: StorageContext,
-        service_context: ServiceContext,
+        embed_model: EmbedType,
+        transformations: list[TransformComponent],
         *args: Any,
         **kwargs: Any,
     ) -> None:
-        super().__init__(storage_context, service_context, *args, **kwargs)
+        super().__init__(storage_context, embed_model, transformations, *args, **kwargs)
 
         self.show_progress = True
         self._index_thread_lock = (
@@ -73,9 +73,10 @@ class BaseIngestComponentWithIndex(BaseIngestComponent, abc.ABC):
             # Load the index with store_nodes_override=True to be able to delete them
             index = load_index_from_storage(
                 storage_context=self.storage_context,
-                service_context=self.service_context,
                 store_nodes_override=True,  # Force store nodes in index and document stores
                 show_progress=self.show_progress,
+                embed_model=self.embed_model,
+                transformations=self.transformations,
             )
         except ValueError:
             # There are no index in the storage context, creating a new one
@@ -83,9 +84,10 @@ class BaseIngestComponentWithIndex(BaseIngestComponent, abc.ABC):
             index = VectorStoreIndex.from_documents(
                 [],
                 storage_context=self.storage_context,
-                service_context=self.service_context,
                 store_nodes_override=True,  # Force store nodes in index and document stores
                 show_progress=self.show_progress,
+                embed_model=self.embed_model,
+                transformations=self.transformations,
             )
             index.storage_context.persist(persist_dir=local_data_path)
         return index
@@ -106,11 +108,12 @@ class SimpleIngestComponent(BaseIngestComponentWithIndex):
     def __init__(
         self,
         storage_context: StorageContext,
-        service_context: ServiceContext,
+        embed_model: EmbedType,
+        transformations: list[TransformComponent],
         *args: Any,
         **kwargs: Any,
     ) -> None:
-        super().__init__(storage_context, service_context, *args, **kwargs)
+        super().__init__(storage_context, embed_model, transformations, *args, **kwargs)
 
     def ingest(self, file_name: str, file_data: Path) -> list[Document]:
         logger.info("Ingesting file_name=%s", file_name)
@@ -151,16 +154,17 @@ class BatchIngestComponent(BaseIngestComponentWithIndex):
     def __init__(
         self,
         storage_context: StorageContext,
-        service_context: ServiceContext,
+        embed_model: EmbedType,
+        transformations: list[TransformComponent],
         count_workers: int,
         *args: Any,
         **kwargs: Any,
     ) -> None:
-        super().__init__(storage_context, service_context, *args, **kwargs)
+        super().__init__(storage_context, embed_model, transformations, *args, **kwargs)
         # Make an efficient use of the CPU and GPU, the embedding
         # must be in the transformations
         assert (
-            len(self.service_context.transformations) >= 2
+            len(self.transformations) >= 2
         ), "Embeddings must be in the transformations"
         assert count_workers > 0, "count_workers must be > 0"
         self.count_workers = count_workers
@@ -197,7 +201,7 @@ class BatchIngestComponent(BaseIngestComponentWithIndex):
         logger.debug("Transforming count=%s documents into nodes", len(documents))
         nodes = run_transformations(
             documents,  # type: ignore[arg-type]
-            self.service_context.transformations,
+            self.transformations,
             show_progress=self.show_progress,
         )
         # Locking the index to avoid concurrent writes
@@ -225,16 +229,17 @@ class ParallelizedIngestComponent(BaseIngestComponentWithIndex):
     def __init__(
         self,
         storage_context: StorageContext,
-        service_context: ServiceContext,
+        embed_model: EmbedType,
+        transformations: list[TransformComponent],
         count_workers: int,
         *args: Any,
         **kwargs: Any,
     ) -> None:
-        super().__init__(storage_context, service_context, *args, **kwargs)
+        super().__init__(storage_context, embed_model, transformations, *args, **kwargs)
         # To make an efficient use of the CPU and GPU, the embeddings
         # must be in the transformations (to be computed in batches)
         assert (
-            len(self.service_context.transformations) >= 2
+            len(self.transformations) >= 2
         ), "Embeddings must be in the transformations"
         assert count_workers > 0, "count_workers must be > 0"
         self.count_workers = count_workers
@@ -278,7 +283,7 @@ class ParallelizedIngestComponent(BaseIngestComponentWithIndex):
         logger.debug("Transforming count=%s documents into nodes", len(documents))
         nodes = run_transformations(
             documents,  # type: ignore[arg-type]
-            self.service_context.transformations,
+            self.transformations,
             show_progress=self.show_progress,
         )
         # Locking the index to avoid concurrent writes
@@ -311,18 +316,29 @@ class ParallelizedIngestComponent(BaseIngestComponentWithIndex):
 
 def get_ingestion_component(
     storage_context: StorageContext,
-    service_context: ServiceContext,
+    embed_model: EmbedType,
+    transformations: list[TransformComponent],
     settings: Settings,
 ) -> BaseIngestComponent:
     """Get the ingestion component for the given configuration."""
     ingest_mode = settings.embedding.ingest_mode
     if ingest_mode == "batch":
         return BatchIngestComponent(
-            storage_context, service_context, settings.embedding.count_workers
+            storage_context=storage_context,
+            embed_model=embed_model,
+            transformations=transformations,
+            count_workers=settings.embedding.count_workers,
         )
     elif ingest_mode == "parallel":
         return ParallelizedIngestComponent(
-            storage_context, service_context, settings.embedding.count_workers
+            storage_context=storage_context,
+            embed_model=embed_model,
+            transformations=transformations,
+            count_workers=settings.embedding.count_workers,
         )
     else:
-        return SimpleIngestComponent(storage_context, service_context)
+        return SimpleIngestComponent(
+            storage_context=storage_context,
+            embed_model=embed_model,
+            transformations=transformations,
+        )
diff --git a/private_gpt/components/ingest/ingest_helper.py b/private_gpt/components/ingest/ingest_helper.py
index 1de2f7fa..15920c3b 100644
--- a/private_gpt/components/ingest/ingest_helper.py
+++ b/private_gpt/components/ingest/ingest_helper.py
@@ -1,14 +1,53 @@
 import logging
 from pathlib import Path
+from typing import Dict, Type
 
-from llama_index import Document
-from llama_index.readers import JSONReader, StringIterableReader
-from llama_index.readers.file.base import DEFAULT_FILE_READER_CLS
+from llama_index.core.readers import StringIterableReader
+from llama_index.core.readers.base import BaseReader
+from llama_index.core.readers.json import JSONReader
+from llama_index.core.schema import Document
 
 logger = logging.getLogger(__name__)
 
+
+# Inspired by the `llama_index.core.readers.file.base` module
+def _try_loading_included_file_formats() -> Dict[str, Type[BaseReader]]:
+    try:
+        from llama_index.readers.file.docs import DocxReader, HWPReader, PDFReader
+        from llama_index.readers.file.epub import EpubReader
+        from llama_index.readers.file.image import ImageReader
+        from llama_index.readers.file.ipynb import IPYNBReader
+        from llama_index.readers.file.markdown import MarkdownReader
+        from llama_index.readers.file.mbox import MboxReader
+        from llama_index.readers.file.tabular import PandasCSVReader
+        from llama_index.readers.file.slides import PptxReader
+        from llama_index.readers.file.video_audio import VideoAudioReader
+    except ImportError:
+        raise ImportError("`llama-index-readers-file` package not found")
+
+    default_file_reader_cls: Dict[str, Type[BaseReader]] = {
+        ".hwp": HWPReader,
+        ".pdf": PDFReader,
+        ".docx": DocxReader,
+        ".pptx": PptxReader,
+        ".ppt": PptxReader,
+        ".pptm": PptxReader,
+        ".jpg": ImageReader,
+        ".png": ImageReader,
+        ".jpeg": ImageReader,
+        ".mp3": VideoAudioReader,
+        ".mp4": VideoAudioReader,
+        ".csv": PandasCSVReader,
+        ".epub": EpubReader,
+        ".md": MarkdownReader,
+        ".mbox": MboxReader,
+        ".ipynb": IPYNBReader,
+    }
+    return default_file_reader_cls
+
+
 # Patching the default file reader to support other file types
-FILE_READER_CLS = DEFAULT_FILE_READER_CLS.copy()
+FILE_READER_CLS = _try_loading_included_file_formats()
 FILE_READER_CLS.update(
     {
         ".json": JSONReader,
diff --git a/private_gpt/components/llm/llm_component.py b/private_gpt/components/llm/llm_component.py
index eebbdff0..b2ffd048 100644
--- a/private_gpt/components/llm/llm_component.py
+++ b/private_gpt/components/llm/llm_component.py
@@ -1,15 +1,16 @@
 import logging
 
 from injector import inject, singleton
-from llama_index import set_global_tokenizer
-from llama_index.llms import MockLLM
-from llama_index.llms.base import LLM
+from llama_index.core.llms import LLM, MockLLM
+from llama_index.core.utils import set_global_tokenizer
+from llama_index.core.settings import Settings as LlamaIndexSettings
 from transformers import AutoTokenizer  # type: ignore
 
 from private_gpt.components.llm.prompt_helper import get_prompt_style
 from private_gpt.paths import models_cache_path, models_path
 from private_gpt.settings.settings import Settings
 
+
 logger = logging.getLogger(__name__)
 
 
@@ -31,7 +32,7 @@ class LLMComponent:
         logger.info("Initializing the LLM in mode=%s", llm_mode)
         match settings.llm.mode:
             case "local":
-                from llama_index.llms import LlamaCPP
+                from llama_index.llms.llama_cpp import LlamaCPP
 
                 prompt_style = get_prompt_style(settings.local.prompt_style)
 
@@ -41,6 +42,7 @@ class LLMComponent:
                     max_new_tokens=settings.llm.max_new_tokens,
                     context_window=settings.llm.context_window,
                     generate_kwargs={},
+                    callback_manager=LlamaIndexSettings.callback_manager,
                     # All to GPU
                     model_kwargs={"n_gpu_layers": -1, "offload_kqv": True},
                     # transform inputs into Llama2 format
@@ -58,7 +60,7 @@ class LLMComponent:
                     context_window=settings.llm.context_window,
                 )
             case "openai":
-                from llama_index.llms import OpenAI
+                from llama_index.llms.openai import OpenAI
 
                 openai_settings = settings.openai
                 self.llm = OpenAI(
@@ -67,7 +69,7 @@ class LLMComponent:
                     model=openai_settings.model,
                 )
             case "openailike":
-                from llama_index.llms import OpenAILike
+                from llama_index.llms.openai_like import OpenAILike
 
                 openai_settings = settings.openai
                 self.llm = OpenAILike(
@@ -81,7 +83,7 @@ class LLMComponent:
             case "mock":
                 self.llm = MockLLM()
             case "ollama":
-                from llama_index.llms import Ollama
+                from llama_index.llms.ollama import Ollama
 
                 ollama_settings = settings.ollama
                 self.llm = Ollama(
diff --git a/private_gpt/components/llm/prompt_helper.py b/private_gpt/components/llm/prompt_helper.py
index d1df9b81..985d217b 100644
--- a/private_gpt/components/llm/prompt_helper.py
+++ b/private_gpt/components/llm/prompt_helper.py
@@ -3,11 +3,7 @@ import logging
 from collections.abc import Sequence
 from typing import Any, Literal
 
-from llama_index.llms import ChatMessage, MessageRole
-from llama_index.llms.llama_utils import (
-    completion_to_prompt,
-    messages_to_prompt,
-)
+from llama_index.core.llms import ChatMessage, MessageRole
 
 logger = logging.getLogger(__name__)
 
@@ -73,7 +69,9 @@ class DefaultPromptStyle(AbstractPromptStyle):
 
 
 class Llama2PromptStyle(AbstractPromptStyle):
-    """Simple prompt style that just uses the default llama_utils functions.
+    """Simple prompt style that uses llama 2 prompt style.
+
+    Inspired by llama_index/legacy/llms/llama_utils.py
 
     It transforms the sequence of messages into a prompt that should look like:
     ```text
@@ -83,11 +81,61 @@ class Llama2PromptStyle(AbstractPromptStyle):
     ```
     """
 
+    BOS, EOS = "<s>", "</s>"
+    B_INST, E_INST = "[INST]", "[/INST]"
+    B_SYS, E_SYS = "<<SYS>>\n", "\n<</SYS>>\n\n"
+    DEFAULT_SYSTEM_PROMPT = """\
+    You are a helpful, respectful and honest assistant. \
+    Always answer as helpfully as possible and follow ALL given instructions. \
+    Do not speculate or make up information. \
+    Do not reference any given instructions or context. \
+    """
+
     def _messages_to_prompt(self, messages: Sequence[ChatMessage]) -> str:
-        return messages_to_prompt(messages)
+        string_messages: list[str] = []
+        if messages[0].role == MessageRole.SYSTEM:
+            # pull out the system message (if it exists in messages)
+            system_message_str = messages[0].content or ""
+            messages = messages[1:]
+        else:
+            system_message_str = self.DEFAULT_SYSTEM_PROMPT
+
+        system_message_str = f"{self.B_SYS} {system_message_str.strip()} {self.E_SYS}"
+
+        for i in range(0, len(messages), 2):
+            # first message should always be a user
+            user_message = messages[i]
+            assert user_message.role == MessageRole.USER
+
+            if i == 0:
+                # make sure system prompt is included at the start
+                str_message = f"{self.BOS} {self.B_INST} {system_message_str} "
+            else:
+                # end previous user-assistant interaction
+                string_messages[-1] += f" {self.EOS}"
+                # no need to include system prompt
+                str_message = f"{self.BOS} {self.B_INST} "
+
+            # include user message content
+            str_message += f"{user_message.content} {self.E_INST}"
+
+            if len(messages) > (i + 1):
+                # if assistant message exists, add to str_message
+                assistant_message = messages[i + 1]
+                assert assistant_message.role == MessageRole.ASSISTANT
+                str_message += f" {assistant_message.content}"
+
+            string_messages.append(str_message)
+
+        return "".join(string_messages)
 
     def _completion_to_prompt(self, completion: str) -> str:
-        return completion_to_prompt(completion)
+        system_prompt_str = self.DEFAULT_SYSTEM_PROMPT
+
+        return (
+            f"{self.BOS} {self.B_INST} {self.B_SYS} {system_prompt_str.strip()} {self.E_SYS} "
+            f"{completion.strip()} {self.E_INST}"
+        )
 
 
 class TagPromptStyle(AbstractPromptStyle):
diff --git a/private_gpt/components/node_store/node_store_component.py b/private_gpt/components/node_store/node_store_component.py
index c039bf50..4383cf93 100644
--- a/private_gpt/components/node_store/node_store_component.py
+++ b/private_gpt/components/node_store/node_store_component.py
@@ -1,9 +1,9 @@
 import logging
 
 from injector import inject, singleton
-from llama_index.storage.docstore import BaseDocumentStore, SimpleDocumentStore
-from llama_index.storage.index_store import SimpleIndexStore
-from llama_index.storage.index_store.types import BaseIndexStore
+from llama_index.core.storage.docstore import BaseDocumentStore, SimpleDocumentStore
+from llama_index.core.storage.index_store import SimpleIndexStore
+from llama_index.core.storage.index_store.types import BaseIndexStore
 
 from private_gpt.paths import local_data_path
 
diff --git a/private_gpt/components/vector_store/batched_chroma.py b/private_gpt/components/vector_store/batched_chroma.py
index f2cd9add..eac53650 100644
--- a/private_gpt/components/vector_store/batched_chroma.py
+++ b/private_gpt/components/vector_store/batched_chroma.py
@@ -1,9 +1,25 @@
+from collections.abc import Generator
 from typing import Any
 
-from llama_index.schema import BaseNode, MetadataMode
-from llama_index.vector_stores import ChromaVectorStore
-from llama_index.vector_stores.chroma import chunk_list
-from llama_index.vector_stores.utils import node_to_metadata_dict
+from llama_index.core.schema import BaseNode, MetadataMode
+from llama_index.core.vector_stores.utils import node_to_metadata_dict
+from llama_index.vector_stores.chroma import ChromaVectorStore
+
+
+def chunk_list(
+    lst: list[BaseNode], max_chunk_size: int
+) -> Generator[list[BaseNode], None, None]:
+    """Yield successive max_chunk_size-sized chunks from lst.
+
+    Args:
+        lst (List[BaseNode]): list of nodes with embeddings
+        max_chunk_size (int): max chunk size
+
+    Yields:
+        Generator[List[BaseNode], None, None]: list of nodes with embeddings
+    """
+    for i in range(0, len(lst), max_chunk_size):
+        yield lst[i : i + max_chunk_size]
 
 
 class BatchedChromaVectorStore(ChromaVectorStore):
diff --git a/private_gpt/components/vector_store/vector_store_component.py b/private_gpt/components/vector_store/vector_store_component.py
index 4e3ed114..0e965f8b 100644
--- a/private_gpt/components/vector_store/vector_store_component.py
+++ b/private_gpt/components/vector_store/vector_store_component.py
@@ -2,9 +2,8 @@ import logging
 import typing
 
 from injector import inject, singleton
-from llama_index import VectorStoreIndex
-from llama_index.indices.vector_store import VectorIndexRetriever
-from llama_index.vector_stores.types import VectorStore
+from llama_index.core.indices.vector_store import VectorIndexRetriever, VectorStoreIndex
+from llama_index.core.vector_stores.types import VectorStore
 
 from private_gpt.components.vector_store.batched_chroma import BatchedChromaVectorStore
 from private_gpt.open_ai.extensions.context_filter import ContextFilter
@@ -41,7 +40,7 @@ class VectorStoreComponent:
     def __init__(self, settings: Settings) -> None:
         match settings.vectorstore.database:
             case "pgvector":
-                from llama_index.vector_stores import PGVectorStore
+                from llama_index.vector_stores.postgres import PGVectorStore
 
                 if settings.pgvector is None:
                     raise ValueError(
diff --git a/private_gpt/launcher.py b/private_gpt/launcher.py
index 791e841a..3857a8cd 100644
--- a/private_gpt/launcher.py
+++ b/private_gpt/launcher.py
@@ -4,6 +4,8 @@ import logging
 from fastapi import Depends, FastAPI, Request
 from fastapi.middleware.cors import CORSMiddleware
 from injector import Injector
+from llama_index.core.callbacks import CallbackManager
+from llama_index.core.callbacks.global_handlers import create_global_handler
 
 from private_gpt.server.chat.chat_router import chat_router
 from private_gpt.server.chunks.chunks_router import chunks_router
@@ -12,6 +14,7 @@ from private_gpt.server.embeddings.embeddings_router import embeddings_router
 from private_gpt.server.health.health_router import health_router
 from private_gpt.server.ingest.ingest_router import ingest_router
 from private_gpt.settings.settings import Settings
+from llama_index.core.settings import Settings as LlamaIndexSettings
 
 logger = logging.getLogger(__name__)
 
@@ -31,6 +34,10 @@ def create_app(root_injector: Injector) -> FastAPI:
     app.include_router(embeddings_router)
     app.include_router(health_router)
 
+    # Add LlamaIndex simple observability
+    global_handler = create_global_handler("simple")
+    LlamaIndexSettings.callback_manager = CallbackManager([global_handler])
+
     settings = root_injector.get(Settings)
     if settings.server.cors.enabled:
         logger.debug("Setting up CORS middleware")
diff --git a/private_gpt/main.py b/private_gpt/main.py
index d249fa6c..58c4006c 100644
--- a/private_gpt/main.py
+++ b/private_gpt/main.py
@@ -1,11 +1,6 @@
 """FastAPI app creation, logger configuration and main API routes."""
 
-import llama_index
-
 from private_gpt.di import global_injector
 from private_gpt.launcher import create_app
 
-# Add LlamaIndex simple observability
-llama_index.set_global_handler("simple")
-
 app = create_app(global_injector)
diff --git a/private_gpt/open_ai/openai_models.py b/private_gpt/open_ai/openai_models.py
index dd78daf3..67b67dd4 100644
--- a/private_gpt/open_ai/openai_models.py
+++ b/private_gpt/open_ai/openai_models.py
@@ -3,7 +3,7 @@ import uuid
 from collections.abc import Iterator
 from typing import Literal
 
-from llama_index.llms import ChatResponse, CompletionResponse
+from llama_index.core.llms import ChatResponse, CompletionResponse
 from pydantic import BaseModel, Field
 
 from private_gpt.server.chunks.chunks_service import Chunk
diff --git a/private_gpt/server/chat/chat_router.py b/private_gpt/server/chat/chat_router.py
index 385ba173..ed86cdbb 100644
--- a/private_gpt/server/chat/chat_router.py
+++ b/private_gpt/server/chat/chat_router.py
@@ -1,5 +1,5 @@
 from fastapi import APIRouter, Depends, Request
-from llama_index.llms import ChatMessage, MessageRole
+from llama_index.core.llms import ChatMessage, MessageRole
 from pydantic import BaseModel
 from starlette.responses import StreamingResponse
 
diff --git a/private_gpt/server/chat/chat_service.py b/private_gpt/server/chat/chat_service.py
index ffdb3f90..6b94f352 100644
--- a/private_gpt/server/chat/chat_service.py
+++ b/private_gpt/server/chat/chat_service.py
@@ -1,14 +1,15 @@
 from dataclasses import dataclass
 
 from injector import inject, singleton
-from llama_index import ServiceContext, StorageContext, VectorStoreIndex
-from llama_index.chat_engine import ContextChatEngine, SimpleChatEngine
-from llama_index.chat_engine.types import (
+from llama_index.core.chat_engine import ContextChatEngine, SimpleChatEngine
+from llama_index.core.chat_engine.types import (
     BaseChatEngine,
 )
-from llama_index.indices.postprocessor import MetadataReplacementPostProcessor
-from llama_index.llms import ChatMessage, MessageRole
-from llama_index.types import TokenGen
+from llama_index.core.indices import VectorStoreIndex
+from llama_index.core.indices.postprocessor import MetadataReplacementPostProcessor
+from llama_index.core.llms import ChatMessage, MessageRole
+from llama_index.core.storage import StorageContext
+from llama_index.core.types import TokenGen
 from pydantic import BaseModel
 
 from private_gpt.components.embedding.embedding_component import EmbeddingComponent
@@ -75,20 +76,19 @@ class ChatService:
         embedding_component: EmbeddingComponent,
         node_store_component: NodeStoreComponent,
     ) -> None:
-        self.llm_service = llm_component
+        self.llm_component = llm_component
+        self.embedding_component = embedding_component
         self.vector_store_component = vector_store_component
         self.storage_context = StorageContext.from_defaults(
             vector_store=vector_store_component.vector_store,
             docstore=node_store_component.doc_store,
             index_store=node_store_component.index_store,
         )
-        self.service_context = ServiceContext.from_defaults(
-            llm=llm_component.llm, embed_model=embedding_component.embedding_model
-        )
         self.index = VectorStoreIndex.from_vector_store(
             vector_store_component.vector_store,
             storage_context=self.storage_context,
-            service_context=self.service_context,
+            llm=llm_component.llm,
+            embed_model=embedding_component.embedding_model,
             show_progress=True,
         )
 
@@ -102,10 +102,17 @@ class ChatService:
             vector_index_retriever = self.vector_store_component.get_retriever(
                 index=self.index, context_filter=context_filter
             )
+            # TODO ContextChatEngine is still not migrated by LlamaIndex to accept
+            # llm directly, so we are passing legacy ServiceContext until it is fixed.
+            from llama_index.core import ServiceContext
             return ContextChatEngine.from_defaults(
                 system_prompt=system_prompt,
                 retriever=vector_index_retriever,
-                service_context=self.service_context,
+                llm=self.llm_component.llm,  # Takes no effect at the moment
+                service_context=ServiceContext.from_defaults(
+                    llm=self.llm_component.llm,
+                    embed_model=self.embedding_component.embedding_model,
+                ),
                 node_postprocessors=[
                     MetadataReplacementPostProcessor(target_metadata_key="window"),
                 ],
@@ -113,7 +120,7 @@ class ChatService:
         else:
             return SimpleChatEngine.from_defaults(
                 system_prompt=system_prompt,
-                service_context=self.service_context,
+                llm=self.llm_component.llm,
             )
 
     def stream_chat(
diff --git a/private_gpt/server/chunks/chunks_service.py b/private_gpt/server/chunks/chunks_service.py
index 7fbe8550..7bda5d90 100644
--- a/private_gpt/server/chunks/chunks_service.py
+++ b/private_gpt/server/chunks/chunks_service.py
@@ -1,8 +1,9 @@
 from typing import TYPE_CHECKING, Literal
 
 from injector import inject, singleton
-from llama_index import ServiceContext, StorageContext, VectorStoreIndex
-from llama_index.schema import NodeWithScore
+from llama_index.core.indices import VectorStoreIndex
+from llama_index.core.schema import NodeWithScore
+from llama_index.core.storage import StorageContext
 from pydantic import BaseModel, Field
 
 from private_gpt.components.embedding.embedding_component import EmbeddingComponent
@@ -15,7 +16,7 @@ from private_gpt.open_ai.extensions.context_filter import ContextFilter
 from private_gpt.server.ingest.model import IngestedDoc
 
 if TYPE_CHECKING:
-    from llama_index.schema import RelatedNodeInfo
+    from llama_index.core.schema import RelatedNodeInfo
 
 
 class Chunk(BaseModel):
@@ -63,14 +64,13 @@ class ChunksService:
         node_store_component: NodeStoreComponent,
     ) -> None:
         self.vector_store_component = vector_store_component
+        self.llm_component = llm_component
+        self.embedding_component = embedding_component
         self.storage_context = StorageContext.from_defaults(
             vector_store=vector_store_component.vector_store,
             docstore=node_store_component.doc_store,
             index_store=node_store_component.index_store,
         )
-        self.query_service_context = ServiceContext.from_defaults(
-            llm=llm_component.llm, embed_model=embedding_component.embedding_model
-        )
 
     def _get_sibling_nodes_text(
         self, node_with_score: NodeWithScore, related_number: int, forward: bool = True
@@ -103,7 +103,8 @@ class ChunksService:
         index = VectorStoreIndex.from_vector_store(
             self.vector_store_component.vector_store,
             storage_context=self.storage_context,
-            service_context=self.query_service_context,
+            llm=self.llm_component.llm,
+            embed_model=self.embedding_component.embedding_model,
             show_progress=True,
         )
         vector_index_retriever = self.vector_store_component.get_retriever(
diff --git a/private_gpt/server/ingest/ingest_service.py b/private_gpt/server/ingest/ingest_service.py
index aa2f73c3..1d6f5ba2 100644
--- a/private_gpt/server/ingest/ingest_service.py
+++ b/private_gpt/server/ingest/ingest_service.py
@@ -4,11 +4,8 @@ from pathlib import Path
 from typing import AnyStr, BinaryIO
 
 from injector import inject, singleton
-from llama_index import (
-    ServiceContext,
-    StorageContext,
-)
-from llama_index.node_parser import SentenceWindowNodeParser
+from llama_index.core.node_parser import SentenceWindowNodeParser
+from llama_index.core.storage import StorageContext
 
 from private_gpt.components.embedding.embedding_component import EmbeddingComponent
 from private_gpt.components.ingest.ingest_component import get_ingestion_component
@@ -40,17 +37,12 @@ class IngestService:
             index_store=node_store_component.index_store,
         )
         node_parser = SentenceWindowNodeParser.from_defaults()
-        self.ingest_service_context = ServiceContext.from_defaults(
-            llm=self.llm_service.llm,
-            embed_model=embedding_component.embedding_model,
-            node_parser=node_parser,
-            # Embeddings done early in the pipeline of node transformations, right
-            # after the node parsing
-            transformations=[node_parser, embedding_component.embedding_model],
-        )
 
         self.ingest_component = get_ingestion_component(
-            self.storage_context, self.ingest_service_context, settings=settings()
+            self.storage_context,
+            embed_model=embedding_component.embedding_model,
+            transformations=[node_parser, embedding_component.embedding_model],
+            settings=settings(),
         )
 
     def _ingest_data(self, file_name: str, file_data: AnyStr) -> list[IngestedDoc]:
diff --git a/private_gpt/server/ingest/model.py b/private_gpt/server/ingest/model.py
index eb957ee0..9f4139e6 100644
--- a/private_gpt/server/ingest/model.py
+++ b/private_gpt/server/ingest/model.py
@@ -1,6 +1,6 @@
 from typing import Any, Literal
 
-from llama_index import Document
+from llama_index.core.schema import Document
 from pydantic import BaseModel, Field
 
 
diff --git a/private_gpt/ui/ui.py b/private_gpt/ui/ui.py
index a4b131fe..bcc1f675 100644
--- a/private_gpt/ui/ui.py
+++ b/private_gpt/ui/ui.py
@@ -10,7 +10,7 @@ import gradio as gr  # type: ignore
 from fastapi import FastAPI
 from gradio.themes.utils.colors import slate  # type: ignore
 from injector import inject, singleton
-from llama_index.llms import ChatMessage, ChatResponse, MessageRole
+from llama_index.core.llms import ChatMessage, ChatResponse, MessageRole
 from pydantic import BaseModel
 
 from private_gpt.constants import PROJECT_ROOT_PATH
diff --git a/pyproject.toml b/pyproject.toml
index 1b380e20..59f8ff70 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -6,15 +6,24 @@ authors = ["Zylon <hi@zylon.ai>"]
 
 [tool.poetry.dependencies]
 python = ">=3.11,<3.12"
-fastapi = { extras = ["all"], version = "^0.103.1" }
-boto3 = "^1.28.56"
+fastapi = { extras = ["all"], version = "^0.110.0" }
+boto3 = "^1.34.51"
 injector = "^0.21.0"
 pyyaml = "^6.0.1"
-python-multipart = "^0.0.6"
-pypdf = "^3.16.2"
-llama-index = { extras = ["local_models"], version = "0.9.3" }
-watchdog = "^3.0.0"
-qdrant-client = "^1.6.9"
+python-multipart = "^0.0.9"
+llama-index-core = "^0.10.13"
+llama-index-readers-file = "^0.1.6"
+llama-index-embeddings-huggingface = "^0.1.4"
+llama-index-embeddings-openai = "^0.1.6"
+llama-index-vector-stores-qdrant = "^0.1.3"
+llama-index-vector-stores-chroma = "^0.1.4"
+llama-index-llms-llama-cpp = "^0.1.3"
+llama-index-llms-openai = "^0.1.6"
+llama-index-llms-openai-like = "^0.1.3"
+llama-index-llms-ollama = "^0.1.2"
+llama-index-vector-stores-postgres = "^0.1.2"
+watchdog = "^4.0.0"
+qdrant-client = "^1.7.3"
 chromadb = {version = "^0.4.13", optional = true}
 asyncpg = {version = "^0.29.0", optional = true}
 pgvector = {version = "^0.2.5", optional = true}
diff --git a/tests/test_prompt_helper.py b/tests/test_prompt_helper.py
index 48597698..3b5af914 100644
--- a/tests/test_prompt_helper.py
+++ b/tests/test_prompt_helper.py
@@ -1,5 +1,5 @@
 import pytest
-from llama_index.llms import ChatMessage, MessageRole
+from llama_index.core.llms import ChatMessage, MessageRole
 
 from private_gpt.components.llm.prompt_helper import (
     ChatMLPromptStyle,