From f2c9bf12cf4360893cacf01078bc2dbee966d69d Mon Sep 17 00:00:00 2001
From: Gayathri <142381512+gaya3-zipstack@users.noreply.github.com>
Date: Fri, 12 Apr 2024 11:00:07 +0530
Subject: [PATCH] [Feature] SDK llama index 0.10.x migration (#19)

* Llama index migration changes

* Service context deprecation

* Remove service_context file

* Fix for token usage

* Add comments

* Change signature

* Remove Optional/None type

* Avoid nesting

* Update llala-index version

---------

Signed-off-by: Gayathri <142381512+gaya3-zipstack@users.noreply.github.com>
---
 pdm.lock                                   | 2380 ++++++++++----------
 pyproject.toml                             |   18 +-
 src/unstract/sdk/__init__.py               |    2 +-
 src/unstract/sdk/audit.py                  |    3 +-
 src/unstract/sdk/embedding.py              |   60 +-
 src/unstract/sdk/index.py                  |   22 +-
 src/unstract/sdk/llm.py                    |   33 +-
 src/unstract/sdk/utils/callback_manager.py |  123 +
 src/unstract/sdk/utils/service_context.py  |  126 --
 src/unstract/sdk/utils/usage_handler.py    |    9 +-
 src/unstract/sdk/vector_db.py              |   19 +-
 tests/test_embedding.py                    |    2 +-
 tests/test_vector_db.py                    |    7 +-
 13 files changed, 1435 insertions(+), 1369 deletions(-)
 create mode 100644 src/unstract/sdk/utils/callback_manager.py
 delete mode 100644 src/unstract/sdk/utils/service_context.py

diff --git a/pdm.lock b/pdm.lock
index 3a36fd94..07d1c977 100644
--- a/pdm.lock
+++ b/pdm.lock
@@ -5,11 +5,11 @@
 groups = ["default", "docs", "lint", "test"]
 strategy = ["cross_platform"]
 lock_version = "4.4.1"
-content_hash = "sha256:9fef976c84eacdb66972cd8e1f4b96f58678b35e1343d2bdc1989e8db170b8bb"
+content_hash = "sha256:2857285563ce35cbcde5ade705f889a9f1bd2c55940bbac8061f402903751462"
 
 [[package]]
 name = "aiohttp"
-version = "3.9.3"
+version = "3.9.4"
 requires_python = ">=3.8"
 summary = "Async http client/server framework (asyncio)"
 dependencies = [
@@ -21,52 +21,52 @@ dependencies = [
     "yarl<2.0,>=1.0",
 ]
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+    {file = "aiohttp-3.9.4-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:74e4e48c8752d14ecfb36d2ebb3d76d614320570e14de0a3aa7a726ff150a03c"},
+    {file = "aiohttp-3.9.4-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:916b0417aeddf2c8c61291238ce25286f391a6acb6f28005dd9ce282bd6311b6"},
+    {file = "aiohttp-3.9.4-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:9b6787b6d0b3518b2ee4cbeadd24a507756ee703adbac1ab6dc7c4434b8c572a"},
+    {file = "aiohttp-3.9.4-cp39-cp39-musllinux_1_1_ppc64le.whl", hash = "sha256:221204dbda5ef350e8db6287937621cf75e85778b296c9c52260b522231940ed"},
+    {file = "aiohttp-3.9.4-cp39-cp39-musllinux_1_1_s390x.whl", hash = "sha256:10afd99b8251022ddf81eaed1d90f5a988e349ee7d779eb429fb07b670751e8c"},
+    {file = "aiohttp-3.9.4-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:2506d9f7a9b91033201be9ffe7d89c6a54150b0578803cce5cb84a943d075bc3"},
+    {file = "aiohttp-3.9.4-cp39-cp39-win32.whl", hash = "sha256:e571fdd9efd65e86c6af2f332e0e95dad259bfe6beb5d15b3c3eca3a6eb5d87b"},
+    {file = "aiohttp-3.9.4-cp39-cp39-win_amd64.whl", hash = "sha256:7d29dd5319d20aa3b7749719ac9685fbd926f71ac8c77b2477272725f882072d"},
+    {file = "aiohttp-3.9.4.tar.gz", hash = "sha256:6ff71ede6d9a5a58cfb7b6fffc83ab5d4a63138276c771ac91ceaaddf5459644"},
 ]
 
 [[package]]
@@ -94,7 +94,7 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.7.8"
+version = "0.17.0"
 requires_python = ">=3.7"
 summary = "The official Python library for the anthropic API"
 dependencies = [
@@ -104,11 +104,11 @@ dependencies = [
     "pydantic<3,>=1.9.0",
     "sniffio",
     "tokenizers>=0.13.0",
-    "typing-extensions<5,>=4.5",
+    "typing-extensions<5,>=4.7",
 ]
 files = [
-    {file = "anthropic-0.7.8-py3-none-any.whl", hash = "sha256:268db974578e34d1449cd0d22389394f0c61795ace9a101dcde4eab4b98439bf"},
-    {file = "anthropic-0.7.8.tar.gz", hash = "sha256:61bc698553b24bc7721cf71db8de50703f3025ea2d14fa4bcb5b1d2bf37f9e40"},
+    {file = "anthropic-0.17.0-py3-none-any.whl", hash = "sha256:e582635d65d940cd0d957631d548aa2d8add4f261556bf53f8c1f6e5fa6082fd"},
+    {file = "anthropic-0.17.0.tar.gz", hash = "sha256:6f1958e7ffd706a19741260d6dfef3fd9af07d31a57b837792331b4ba0aa067c"},
 ]
 
 [[package]]
@@ -127,44 +127,6 @@ files = [
     {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
 ]
 
-[[package]]
-name = "anyscale"
-version = "0.5.165"
-summary = "Command Line Interface for Anyscale"
-dependencies = [
-    "Click>=7.0",
-    "GitPython",
-    "aiohttp>=3.7.4.post0",
-    "argon2-cffi",
-    "boto3>=1.26.76",
-    "botocore>=1.19.52",
-    "certifi>=2023.7.22",
-    "colorama",
-    "google-auth",
-    "halo",
-    "humanize",
-    "jsonpatch",
-    "jsonschema",
-    "oauth2client",
-    "packaging",
-    "pathspec>=0.8.1",
-    "python-dateutil",
-    "pyyaml",
-    "requests",
-    "rich",
-    "six>=1.10",
-    "smart-open",
-    "tabulate",
-    "tqdm",
-    "typing-extensions",
-    "tzlocal",
-    "urllib3>=1.26.17",
-    "wrapt",
-]
-files = [
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-]
-
 [[package]]
 name = "argon2-cffi"
 version = "23.1.0"
@@ -294,13 +256,50 @@ files = [
 ]
 
 [[package]]
-name = "backoff"
-version = "2.2.1"
-requires_python = ">=3.7,<4.0"
-summary = "Function decoration for backoff and retry"
+name = "azure-core"
+version = "1.30.1"
+requires_python = ">=3.7"
+summary = "Microsoft Azure Core Library for Python"
+dependencies = [
+    "requests>=2.21.0",
+    "six>=1.11.0",
+    "typing-extensions>=4.6.0",
+]
+files = [
+    {file = "azure-core-1.30.1.tar.gz", hash = "sha256:26273a254131f84269e8ea4464f3560c731f29c0c1f69ac99010845f239c1a8f"},
+    {file = "azure_core-1.30.1-py3-none-any.whl", hash = "sha256:7c5ee397e48f281ec4dd773d67a0a47a0962ed6fa833036057f9ea067f688e74"},
+]
+
+[[package]]
+name = "azure-identity"
+version = "1.16.0"
+requires_python = ">=3.8"
+summary = "Microsoft Azure Identity Library for Python"
+dependencies = [
+    "azure-core>=1.23.0",
+    "cryptography>=2.5",
+    "msal-extensions>=0.3.0",
+    "msal>=1.24.0",
+]
+files = [
+    {file = "azure-identity-1.16.0.tar.gz", hash = "sha256:6ff1d667cdcd81da1ceab42f80a0be63ca846629f518a922f7317a7e3c844e1b"},
+    {file = "azure_identity-1.16.0-py3-none-any.whl", hash = "sha256:722fdb60b8fdd55fa44dc378b8072f4b419b56a5e54c0de391f644949f3a826f"},
+]
+
+[[package]]
+name = "azure-storage-blob"
+version = "12.19.1"
+requires_python = ">=3.7"
+summary = "Microsoft Azure Blob Storage Client Library for Python"
+dependencies = [
+    "azure-core<2.0.0,>=1.28.0",
+    "cryptography>=2.1.4",
+    "isodate>=0.6.1",
+    "typing-extensions>=4.3.0",
+]
 files = [
-    {file = "backoff-2.2.1-py3-none-any.whl", hash = "sha256:63579f9a0628e06278f7e47b7d7d5b6ce20dc65c5e96a6f3ca99a6adca0396e8"},
-    {file = "backoff-2.2.1.tar.gz", hash = "sha256:03f829f5bb1923180821643f8753b0502c3b682293992485b0eef2807afa5cba"},
+    {file = "azure-storage-blob-12.19.1.tar.gz", hash = "sha256:13e16ba42fc54ac2c7e8f976062173a5c82b9ec0594728e134aac372965a11b0"},
+    {file = "azure_storage_blob-12.19.1-py3-none-any.whl", hash = "sha256:c5530dc51c21c9564e4eb706cd499befca8819b10dd89716d3fc90d747556243"},
 ]
 
 [[package]]
@@ -350,37 +349,6 @@ files = [
     {file = "black-23.3.0.tar.gz", hash = "sha256:1c7b8d606e728a41ea1ccbd7264677e494e87cf630e399262ced92d4a8dac940"},
 ]
 
-[[package]]
-name = "boto3"
-version = "1.34.57"
-requires_python = ">= 3.8"
-summary = "The AWS SDK for Python"
-dependencies = [
-    "botocore<1.35.0,>=1.34.57",
-    "jmespath<2.0.0,>=0.7.1",
-    "s3transfer<0.11.0,>=0.10.0",
-]
-files = [
-    {file = "boto3-1.34.57-py3-none-any.whl", hash = "sha256:f8046e3e2d1186a49b49f7464c4811c265c86001f404dd1a96c4365c773a4245"},
-    {file = "boto3-1.34.57.tar.gz", hash = "sha256:c26c31ceeeb2bc5d2bb96ba0fdc9a04d7b10e6e0b081c55b9cea9069a0be04dd"},
-]
-
-[[package]]
-name = "botocore"
-version = "1.34.57"
-requires_python = ">= 3.8"
-summary = "Low-level, data-driven core of boto 3."
-dependencies = [
-    "jmespath<2.0.0,>=0.7.1",
-    "python-dateutil<3.0.0,>=2.1",
-    "urllib3<1.27,>=1.25.4; python_version < \"3.10\"",
-    "urllib3<2.1,>=1.25.4; python_version >= \"3.10\"",
-]
-files = [
-    {file = "botocore-1.34.57-py3-none-any.whl", hash = "sha256:c8dafe0ad378a88bcf4153e6972870b03fb5aab406b694202307500709940baf"},
-    {file = "botocore-1.34.57.tar.gz", hash = "sha256:9a5aa2034de9f0c367b4b61a92af0fa827f5c21affa19e0a284838a142e71083"},
-]
-
 [[package]]
 name = "cachetools"
 version = "5.3.3"
@@ -534,19 +502,6 @@ files = [
     {file = "colorama-0.4.6.tar.gz", hash = "sha256:08695f5cb7ed6e0531a20572697297273c47b8cae5a63ffc6d6ed5c201be6e44"},
 ]
 
-[[package]]
-name = "coloredlogs"
-version = "15.0.1"
-requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*"
-summary = "Colored terminal output for Python's logging module"
-dependencies = [
-    "humanfriendly>=9.1",
-]
-files = [
-    {file = "coloredlogs-15.0.1-py2.py3-none-any.whl", hash = "sha256:612ee75c546f53e92e70049c9dbfcc18c935a2b9a53b66085ce9ef6a6e5c0934"},
-    {file = "coloredlogs-15.0.1.tar.gz", hash = "sha256:7c991aa71a4577af2f82600d8f8f3a89f936baeaf9b50a9c197da014e5bf16b0"},
-]
-
 [[package]]
 name = "cryptography"
 version = "42.0.5"
@@ -618,15 +573,12 @@ files = [
 ]
 
 [[package]]
-name = "deprecation"
-version = "2.1.0"
-summary = "A library to handle automated deprecations"
-dependencies = [
-    "packaging",
-]
+name = "dirtyjson"
+version = "1.0.8"
+summary = "JSON decoder for Python that can extract data from the muck"
 files = [
-    {file = "deprecation-2.1.0-py2.py3-none-any.whl", hash = "sha256:a10811591210e1fb0e768a8c25517cabeabcba6f0bf96564f8ff45189f90b14a"},
-    {file = "deprecation-2.1.0.tar.gz", hash = "sha256:72b3bde64e5d778694b0cf68178aed03d15e15477116add3fb773e581f9518ff"},
+    {file = "dirtyjson-1.0.8-py3-none-any.whl", hash = "sha256:125e27248435a58acace26d5c2c4c11a1c0de0a9c5124c5a94ba78e517d74f53"},
+    {file = "dirtyjson-1.0.8.tar.gz", hash = "sha256:90ca4a18f3ff30ce849d100dcf4a003953c79d3a2348ef056f1d9c22231a25fd"},
 ]
 
 [[package]]
@@ -649,13 +601,13 @@ files = [
 ]
 
 [[package]]
-name = "dnspython"
-version = "2.6.1"
-requires_python = ">=3.8"
-summary = "DNS toolkit"
+name = "docstring-parser"
+version = "0.16"
+requires_python = ">=3.6,<4.0"
+summary = "Parse Python docstrings in reST, Google and Numpydoc format"
 files = [
-    {file = "dnspython-2.6.1-py3-none-any.whl", hash = "sha256:5ef3b9680161f6fa89daf8ad451b5f1a33b18ae8a1c6778cdf4b43f08c0a6e50"},
-    {file = "dnspython-2.6.1.tar.gz", hash = "sha256:e8f0f9c23a7b7cb99ded64e6c3a6f3e701d78f50c55e002b839dea7225cff7cc"},
+    {file = "docstring_parser-0.16-py3-none-any.whl", hash = "sha256:bf0a1387354d3691d102edef7ec124f219ef639982d096e26e3b60aeffa90637"},
+    {file = "docstring_parser-0.16.tar.gz", hash = "sha256:538beabd0af1e2db0146b6bd3caa526c35a34d61af9fd2887f3a8a27a739aa6e"},
 ]
 
 [[package]]
@@ -692,32 +644,14 @@ files = [
     {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
 ]
 
-[[package]]
-name = "fastembed"
-version = "0.1.3"
-requires_python = ">=3.8.0,<3.12"
-summary = "Fast, light, accurate library built for retrieval embedding generation"
-dependencies = [
-    "huggingface-hub==0.19.4",
-    "onnx<2.0,>=1.11",
-    "onnxruntime<2.0,>=1.15",
-    "requests<3.0,>=2.31",
-    "tokenizers<0.16.0,>=0.15.0",
-    "tqdm<5.0,>=4.65",
-]
-files = [
-    {file = "fastembed-0.1.3-py3-none-any.whl", hash = "sha256:98b6c6d9effec8c96d97048e59cdd53627b16a70fcdbfa7c663772de66e11b3a"},
-    {file = "fastembed-0.1.3.tar.gz", hash = "sha256:c17dc83a02938f8baae6717f18d24ed0ff0c5397b5329cbb5c7264239411346f"},
-]
-
 [[package]]
 name = "filelock"
-version = "3.13.1"
+version = "3.13.4"
 requires_python = ">=3.8"
 summary = "A platform independent file lock."
 files = [
-    {file = "filelock-3.13.1-py3-none-any.whl", hash = "sha256:57dbda9b35157b05fb3e58ee91448612eb674172fab98ee235ccb0b5bee19a1c"},
-    {file = "filelock-3.13.1.tar.gz", hash = "sha256:521f5f56c50f8426f5e03ad3b281b490a87ef15bc6c526f168290f0c7148d44e"},
+    {file = "filelock-3.13.4-py3-none-any.whl", hash = "sha256:404e5e9253aa60ad457cae1be07c0f0ca90a63931200a47d9b6a6af84fd7b45f"},
+    {file = "filelock-3.13.4.tar.gz", hash = "sha256:d13f466618bfde72bd2c18255e269f72542c6e70e7bac83a0232d6b1cc5c8cf4"},
 ]
 
 [[package]]
@@ -757,26 +691,6 @@ files = [
     {file = "flake8_pyproject-1.2.3-py3-none-any.whl", hash = "sha256:6249fe53545205af5e76837644dc80b4c10037e73a0e5db87ff562d75fb5bd4a"},
 ]
 
-[[package]]
-name = "flatbuffers"
-version = "24.3.6"
-summary = "The FlatBuffers serialization format for Python"
-files = [
-    {file = "flatbuffers-24.3.6-py2.py3-none-any.whl", hash = "sha256:0bc1a9d968c0ba996f97b8c255214ec005cf21b962ef60157f7aa2fc647481f1"},
-    {file = "flatbuffers-24.3.6.tar.gz", hash = "sha256:8d90a756ad5754be1fcdaa77065065125c9832ed045b4078875b4d3bc1953352"},
-]
-
-[[package]]
-name = "flupy"
-version = "1.2.0"
-summary = "Method chaining built on generators"
-dependencies = [
-    "typing-extensions",
-]
-files = [
-    {file = "flupy-1.2.0.tar.gz", hash = "sha256:12487a008e9744cd35d0f6ea3cfa06f4b2b27cb138bf57d0788f5c26e57afe69"},
-]
-
 [[package]]
 name = "frozenlist"
 version = "1.4.1"
@@ -834,38 +748,12 @@ files = [
 
 [[package]]
 name = "fsspec"
-version = "2024.2.0"
+version = "2024.3.1"
 requires_python = ">=3.8"
 summary = "File-system specification"
 files = [
-    {file = "fsspec-2024.2.0-py3-none-any.whl", hash = "sha256:817f969556fa5916bc682e02ca2045f96ff7f586d45110fcb76022063ad2c7d8"},
-    {file = "fsspec-2024.2.0.tar.gz", hash = "sha256:b6ad1a679f760dda52b1168c859d01b7b80648ea6f7f7c7f5a8a91dc3f3ecb84"},
-]
-
-[[package]]
-name = "gitdb"
-version = "4.0.11"
-requires_python = ">=3.7"
-summary = "Git Object Database"
-dependencies = [
-    "smmap<6,>=3.0.1",
-]
-files = [
-    {file = "gitdb-4.0.11-py3-none-any.whl", hash = "sha256:81a3407ddd2ee8df444cbacea00e2d038e40150acfa3001696fe0dcf1d3adfa4"},
-    {file = "gitdb-4.0.11.tar.gz", hash = "sha256:bf5421126136d6d0af55bc1e7c1af1c397a34f5b7bd79e776cd3e89785c2b04b"},
-]
-
-[[package]]
-name = "gitpython"
-version = "3.1.42"
-requires_python = ">=3.7"
-summary = "GitPython is a Python library used to interact with Git repositories"
-dependencies = [
-    "gitdb<5,>=4.0.1",
-]
-files = [
-    {file = "GitPython-3.1.42-py3-none-any.whl", hash = "sha256:1bf9cd7c9e7255f77778ea54359e54ac22a72a5b51288c457c881057b7bb9ecd"},
-    {file = "GitPython-3.1.42.tar.gz", hash = "sha256:2d99869e0fef71a73cbd242528105af1d6c1b108c60dfabd994bf292f76c3ceb"},
+    {file = "fsspec-2024.3.1-py3-none-any.whl", hash = "sha256:918d18d41bf73f0e2b261824baeb1b124bcf771767e3a26425cd7dec3332f512"},
+    {file = "fsspec-2024.3.1.tar.gz", hash = "sha256:f39780e282d7d117ffb42bb96992f8a90795e4d0fb0f661a70ca39fe9c43ded9"},
 ]
 
 [[package]]
@@ -885,41 +773,42 @@ files = [
 
 [[package]]
 name = "google-api-core"
-version = "2.17.1"
+version = "2.18.0"
 requires_python = ">=3.7"
 summary = "Google API client core library"
 dependencies = [
     "google-auth<3.0.dev0,>=2.14.1",
     "googleapis-common-protos<2.0.dev0,>=1.56.2",
+    "proto-plus<2.0.0dev,>=1.22.3",
     "protobuf!=3.20.0,!=3.20.1,!=4.21.0,!=4.21.1,!=4.21.2,!=4.21.3,!=4.21.4,!=4.21.5,<5.0.0.dev0,>=3.19.5",
     "requests<3.0.0.dev0,>=2.18.0",
 ]
 files = [
-    {file = "google-api-core-2.17.1.tar.gz", hash = "sha256:9df18a1f87ee0df0bc4eea2770ebc4228392d8cc4066655b320e2cfccb15db95"},
-    {file = "google_api_core-2.17.1-py3-none-any.whl", hash = "sha256:610c5b90092c360736baccf17bd3efbcb30dd380e7a6dc28a71059edb8bd0d8e"},
+    {file = "google-api-core-2.18.0.tar.gz", hash = "sha256:62d97417bfc674d6cef251e5c4d639a9655e00c45528c4364fbfebb478ce72a9"},
+    {file = "google_api_core-2.18.0-py3-none-any.whl", hash = "sha256:5a63aa102e0049abe85b5b88cb9409234c1f70afcda21ce1e40b285b9629c1d6"},
 ]
 
 [[package]]
 name = "google-api-core"
-version = "2.17.1"
+version = "2.18.0"
 extras = ["grpc"]
 requires_python = ">=3.7"
 summary = "Google API client core library"
 dependencies = [
-    "google-api-core==2.17.1",
+    "google-api-core==2.18.0",
     "grpcio-status<2.0.dev0,>=1.33.2",
     "grpcio-status<2.0.dev0,>=1.49.1; python_version >= \"3.11\"",
     "grpcio<2.0dev,>=1.33.2",
     "grpcio<2.0dev,>=1.49.1; python_version >= \"3.11\"",
 ]
 files = [
-    {file = "google-api-core-2.17.1.tar.gz", hash = "sha256:9df18a1f87ee0df0bc4eea2770ebc4228392d8cc4066655b320e2cfccb15db95"},
-    {file = "google_api_core-2.17.1-py3-none-any.whl", hash = "sha256:610c5b90092c360736baccf17bd3efbcb30dd380e7a6dc28a71059edb8bd0d8e"},
+    {file = "google-api-core-2.18.0.tar.gz", hash = "sha256:62d97417bfc674d6cef251e5c4d639a9655e00c45528c4364fbfebb478ce72a9"},
+    {file = "google_api_core-2.18.0-py3-none-any.whl", hash = "sha256:5a63aa102e0049abe85b5b88cb9409234c1f70afcda21ce1e40b285b9629c1d6"},
 ]
 
 [[package]]
 name = "google-auth"
-version = "2.28.1"
+version = "2.29.0"
 requires_python = ">=3.7"
 summary = "Google Authentication Library"
 dependencies = [
@@ -928,37 +817,41 @@ dependencies = [
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-version = "3.4.1"
-summary = "A python implementation of GNU readline."
+name = "pypdf"
+version = "4.2.0"
+requires_python = ">=3.6"
+summary = "A pure-python PDF library capable of splitting, merging, cropping, and transforming PDF files"
+dependencies = [
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 [[package]]
@@ -2571,41 +2816,26 @@ files = [
 
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+version = "1.8.2"
 requires_python = ">=3.8"
 summary = "Client library for the Qdrant vector search engine"
 dependencies = [
     "grpcio-tools>=1.41.0",
     "grpcio>=1.41.0",
-    "httpx[http2]>=0.14.0",
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     "portalocker<3.0.0,>=2.7.0",
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 ]
 
 [[package]]
 name = "referencing"
-version = "0.33.0"
+version = "0.34.0"
 requires_python = ">=3.8"
 summary = "JSON Referencing + Python"
 dependencies = [
@@ -2613,8 +2843,8 @@ dependencies = [
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 [[package]]
@@ -2673,22 +2903,6 @@ files = [
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-summary = "Python client for Replicate"
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-    "packaging",
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-
 [[package]]
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 version = "2.31.0"
@@ -2813,19 +3027,6 @@ files = [
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-[[package]]
-name = "s3transfer"
-version = "0.10.0"
-requires_python = ">= 3.8"
-summary = "An Amazon S3 Transfer Manager"
-dependencies = [
-    "botocore<2.0a.0,>=1.33.2",
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-
 [[package]]
 name = "safetensors"
 version = "0.4.2"
@@ -2898,14 +3099,44 @@ files = [
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 ]
 
+[[package]]
+name = "scipy"
+version = "1.13.0"
+requires_python = ">=3.9"
+summary = "Fundamental algorithms for scientific computing in Python"
+dependencies = [
+    "numpy<2.3,>=1.22.4",
+]
+files = [
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+    "llama-index-embeddings-azure-openai==0.1.6",
+    "llama-index-embeddings-azure-openai==0.1.6",
+    "llama-index-embeddings-google==0.1.4",
+    "llama-index-llms-anthropic==0.1.5",
+    "llama-index-llms-anyscale==0.1.3",
+    "llama-index-llms-azure-openai==0.1.5",
+    "llama-index-llms-mistralai==0.1.10",
+    "llama-index-llms-palm==0.1.4",
+    "llama-index-llms-replicate==0.1.3",
+    "llama-index-llms-vertex==0.1.5",
+    "llama-index-vector-stores-milvus==0.1.6",
+    "llama-index-vector-stores-pinecone==0.1.4",
+    "llama-index-vector-stores-postgres==0.1.3",
+    "llama-index-vector-stores-qdrant==0.1.4",
+    "llama-index-vector-stores-weaviate==0.1.4",
+    "llama-index==0.10.28",
+    "singleton-decorator~=1.0.0",
+]
+files = [
+    {file = "unstract_adapters-0.9.0-py3-none-any.whl", hash = "sha256:4cdd4de1f0bb6fe09f3a13fadf6e229d7fcab8362d31707dd2be331f4ce79940"},
+    {file = "unstract_adapters-0.9.0.tar.gz", hash = "sha256:045bbe233a80fc7c08c8ba8f841bbfc3b57988762cd668fb90f2c09bddafab18"},
 ]
 
 [[package]]
 name = "urllib3"
-version = "1.26.18"
-requires_python = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*"
+version = "2.2.1"
+requires_python = ">=3.8"
 summary = "HTTP library with thread-safe connection pooling, file post, and more."
 files = [
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+    {file = "urllib3-2.2.1-py3-none-any.whl", hash = "sha256:450b20ec296a467077128bff42b73080516e71b56ff59a60a02bef2232c4fa9d"},
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 ]
 
 [[package]]
 name = "validators"
-version = "0.22.0"
+version = "0.28.0"
 requires_python = ">=3.8"
 summary = "Python Data Validation for Humans™"
 files = [
-    {file = "validators-0.22.0-py3-none-any.whl", hash = "sha256:61cf7d4a62bbae559f2e54aed3b000cea9ff3e2fdbe463f51179b92c58c9585a"},
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-]
-
-[[package]]
-name = "vecs"
-version = "0.4.3"
-summary = "pgvector client"
-dependencies = [
-    "deprecated==1.2.*",
-    "flupy==1.*",
-    "pgvector==0.1.*",
-    "psycopg2-binary==2.9.*",
-    "sqlalchemy==2.*",
-]
-files = [
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+    {file = "validators-0.28.0-py3-none-any.whl", hash = "sha256:e0184691dea3ba82b52c161ba81d3ec1d8be8da9609f0137d1430b395b366521"},
+    {file = "validators-0.28.0.tar.gz", hash = "sha256:85bc82511f6ccd0800f4c15d8c0dc546c15e369640c5ea1f24349ba0b3b17815"},
 ]
 
 [[package]]
@@ -3539,7 +3639,7 @@ files = [
 
 [[package]]
 name = "weaviate-client"
-version = "3.25.3"
+version = "3.26.2"
 requires_python = ">=3.8"
 summary = "A python native Weaviate client"
 dependencies = [
@@ -3548,76 +3648,8 @@ dependencies = [
     "validators<1.0.0,>=0.21.2",
 ]
 files = [
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-
-[[package]]
-name = "websockets"
-version = "11.0.3"
-requires_python = ">=3.7"
-summary = "An implementation of the WebSocket Protocol (RFC 6455 & 7692)"
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-    {file = "websockets-11.0.3.tar.gz", hash = "sha256:88fc51d9a26b10fc331be344f1781224a375b78488fc343620184e95a4b27016"},
-]
-
-[[package]]
-name = "win32-setctime"
-version = "1.1.0"
-requires_python = ">=3.5"
-summary = "A small Python utility to set file creation time on Windows"
-files = [
-    {file = "win32_setctime-1.1.0-py3-none-any.whl", hash = "sha256:231db239e959c2fe7eb1d7dc129f11172354f98361c4fa2d6d2d7e278baa8aad"},
-    {file = "win32_setctime-1.1.0.tar.gz", hash = "sha256:15cf5750465118d6929ae4de4eb46e8edae9a5634350c01ba582df868e932cb2"},
+    {file = "weaviate-client-3.26.2.tar.gz", hash = "sha256:63ec70839b64909810a64aa7b3e5b85088462e93c7e2ed3c32ebefb702f36723"},
+    {file = "weaviate_client-3.26.2-py3-none-any.whl", hash = "sha256:ca43bfb9c06b8ae3fd938dc9158acd93d4cbf4622192e173333e1ff63cf97164"},
 ]
 
 [[package]]
diff --git a/pyproject.toml b/pyproject.toml
index 2b662be6..c6cfc8aa 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -12,8 +12,8 @@ dependencies = [
     "python-magic~=0.4.27",
     "python-dotenv==1.0.0",
     # LLM Triad
-    "unstract-adapters~=0.8.0",
-    "llama-index==0.9.28",
+    "unstract-adapters~=0.9.0",
+    "llama-index==0.10.28",
     "tiktoken~=0.4.0",
     "transformers==4.37.0",
 ]
@@ -52,6 +52,15 @@ lint = [
     "yamllint>=1.35.1",
 ]
 
+[tool.isort]
+line_length = 80
+multi_line_output = 3
+include_trailing_comma = true
+force_grid_wrap = 0
+use_parentheses = true
+ensure_newline_before_comments = true
+profile = "black"
+
 [tool.pdm.build]
 includes = ["src"]
 package-dir = "src"
@@ -59,3 +68,8 @@ package-dir = "src"
 [tool.pdm.version]
 source = "file"
 path = "src/unstract/sdk/__init__.py"
+
+# Adding the following override to resolve dependency version
+# for environs. Otherwise, it stays stuck while resolving pins
+[tool.pdm.resolution.overrides]
+grpcio = ">=1.62.1"
diff --git a/src/unstract/sdk/__init__.py b/src/unstract/sdk/__init__.py
index e35b60ab..f2830af6 100644
--- a/src/unstract/sdk/__init__.py
+++ b/src/unstract/sdk/__init__.py
@@ -1,4 +1,4 @@
-__version__ = "0.18.2"
+__version__ = "0.19.0"
 
 
 def get_sdk_version():
diff --git a/src/unstract/sdk/audit.py b/src/unstract/sdk/audit.py
index e59081d6..ecc2a61e 100644
--- a/src/unstract/sdk/audit.py
+++ b/src/unstract/sdk/audit.py
@@ -1,6 +1,5 @@
 import requests
-from llama_index.callbacks import TokenCountingHandler
-from llama_index.callbacks.schema import CBEventType
+from llama_index.core.callbacks import CBEventType, TokenCountingHandler
 
 from unstract.sdk.constants import LogLevel, ToolEnv
 from unstract.sdk.helper import SdkHelper
diff --git a/src/unstract/sdk/embedding.py b/src/unstract/sdk/embedding.py
index 007367b2..05496838 100644
--- a/src/unstract/sdk/embedding.py
+++ b/src/unstract/sdk/embedding.py
@@ -1,11 +1,12 @@
 from typing import Optional
 
-from llama_index.embeddings.base import BaseEmbedding
+from llama_index.core.embeddings import BaseEmbedding
 from unstract.adapters.constants import Common
 from unstract.adapters.embedding import adapters
 
 from unstract.sdk.adapters import ToolAdapter
 from unstract.sdk.constants import LogLevel, ToolSettingsKey
+from unstract.sdk.exceptions import SdkError
 from unstract.sdk.tool.base import BaseTool
 
 
@@ -23,41 +24,42 @@ def __init__(self, tool: BaseTool, tool_settings: dict[str, str] = {}):
 
     def get_embedding(
         self, adapter_instance_id: Optional[str] = None
-    ) -> Optional[BaseEmbedding]:
+    ) -> BaseEmbedding:
         adapter_instance_id = (
             adapter_instance_id
             if adapter_instance_id
             else self.embedding_adapter_instance_id
         )
-        if adapter_instance_id is not None:
-            try:
-                embedding_config_data = ToolAdapter.get_adapter_config(
-                    self.tool, adapter_instance_id
+        if not adapter_instance_id:
+            raise SdkError(
+                f"Adapter_instance_id does not have "
+                f"a valid value: {adapter_instance_id}"
+            )
+        try:
+            embedding_config_data = ToolAdapter.get_adapter_config(
+                self.tool, adapter_instance_id
+            )
+            embedding_adapter_id = embedding_config_data.get(Common.ADAPTER_ID)
+            self.embedding_adapter_id = embedding_adapter_id
+            if embedding_adapter_id in self.embedding_adapters:
+                embedding_adapter = self.embedding_adapters[
+                    embedding_adapter_id
+                ][Common.METADATA][Common.ADAPTER]
+                embedding_metadata = embedding_config_data.get(
+                    Common.ADAPTER_METADATA
                 )
-                embedding_adapter_id = embedding_config_data.get(
-                    Common.ADAPTER_ID
+                embedding_adapter_class = embedding_adapter(embedding_metadata)
+                return embedding_adapter_class.get_embedding_instance()
+            else:
+                raise SdkError(
+                    f"Embedding adapter not supported : "
+                    f"{embedding_adapter_id}"
                 )
-                self.embedding_adapter_id = embedding_adapter_id
-                if embedding_adapter_id in self.embedding_adapters:
-                    embedding_adapter = self.embedding_adapters[
-                        embedding_adapter_id
-                    ][Common.METADATA][Common.ADAPTER]
-                    embedding_metadata = embedding_config_data.get(
-                        Common.ADAPTER_METADATA
-                    )
-                    embedding_adapter_class = embedding_adapter(
-                        embedding_metadata
-                    )
-                    return embedding_adapter_class.get_embedding_instance()
-                else:
-                    return None
-            except Exception as e:
-                self.tool.stream_log(
-                    log=f"Error getting embedding: {e}", level=LogLevel.ERROR
-                )
-                return None
-        else:
-            return None
+        except Exception as e:
+            self.tool.stream_log(
+                log=f"Error getting embedding: {e}", level=LogLevel.ERROR
+            )
+            raise SdkError(f"Error getting embedding instance: {e}")
 
     def get_embedding_length(self, embedding: BaseEmbedding) -> int:
         embedding_list = embedding._get_text_embedding(self.__TEST_SNIPPET)
diff --git a/src/unstract/sdk/index.py b/src/unstract/sdk/index.py
index f07a7c2a..20e8600b 100644
--- a/src/unstract/sdk/index.py
+++ b/src/unstract/sdk/index.py
@@ -1,8 +1,10 @@
 from typing import Optional
 
-from llama_index import Document, StorageContext, VectorStoreIndex
-from llama_index.node_parser import SimpleNodeParser
-from llama_index.vector_stores import (
+from llama_index.core import Document
+from llama_index.core.indices.vector_store import VectorStoreIndex
+from llama_index.core.node_parser import SimpleNodeParser
+from llama_index.core.storage import StorageContext
+from llama_index.core.vector_stores import (
     FilterOperator,
     MetadataFilter,
     MetadataFilters,
@@ -17,7 +19,9 @@
 from unstract.sdk.exceptions import IndexingError, SdkError
 from unstract.sdk.tool.base import BaseTool
 from unstract.sdk.utils import ToolUtils
-from unstract.sdk.utils.service_context import ServiceContext
+from unstract.sdk.utils.callback_manager import (
+    CallbackManager as UNCallbackManager,
+)
 from unstract.sdk.vector_db import ToolVectorDB
 from unstract.sdk.x2txt import X2Text
 
@@ -281,12 +285,12 @@ def index_file(
                 chunk_size=chunk_size, chunk_overlap=chunk_overlap
             )
 
-            service_context = ServiceContext.get_service_context(
+            # Set callback_manager to collect Usage stats
+            callback_manager = UNCallbackManager.set_callback_manager(
                 platform_api_key=self.tool.get_env_or_die(
                     ToolEnv.PLATFORM_API_KEY
                 ),
-                embed_model=embedding_li,
-                node_parser=parser,
+                embedding=embedding_li,
             )
 
             self.tool.stream_log("Adding nodes to vector db...")
@@ -295,7 +299,9 @@ def index_file(
                     documents,
                     storage_context=storage_context,
                     show_progress=True,
-                    service_context=service_context,
+                    embed_model=embedding_li,
+                    node_parser=parser,
+                    callback_manager=callback_manager,
                 )
             except Exception as e:
                 self.tool.stream_log(
diff --git a/src/unstract/sdk/llm.py b/src/unstract/sdk/llm.py
index d8a2009d..9d4cb153 100644
--- a/src/unstract/sdk/llm.py
+++ b/src/unstract/sdk/llm.py
@@ -3,16 +3,18 @@
 import time
 from typing import Any, Optional
 
-from llama_index.llms import LLM
-from llama_index.llms.base import CompletionResponse
+from llama_index.core.llms import LLM, CompletionResponse
 from unstract.adapters.constants import Common
 from unstract.adapters.llm import adapters
 from unstract.adapters.llm.llm_adapter import LLMAdapter
 
 from unstract.sdk.adapters import ToolAdapter
 from unstract.sdk.constants import LogLevel, ToolSettingsKey
+from unstract.sdk.exceptions import SdkError
 from unstract.sdk.tool.base import BaseTool
-from unstract.sdk.utils.service_context import ServiceContext
+from unstract.sdk.utils.callback_manager import (
+    CallbackManager as UNCallbackManager,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -53,7 +55,8 @@ def run_completion(
         retries: int = 3,
         **kwargs: Any,
     ) -> Optional[dict[str, Any]]:
-        ServiceContext.get_service_context(
+        # Setup callback manager to collect Usage stats
+        UNCallbackManager.set_callback_manager(
             platform_api_key=platform_api_key, llm=llm
         )
         for i in range(retries):
@@ -87,13 +90,11 @@ def run_completion(
                 time.sleep(5)
         return None
 
-    def get_llm(
-        self, adapter_instance_id: Optional[str] = None
-    ) -> Optional[LLM]:
+    def get_llm(self, adapter_instance_id: Optional[str] = None) -> LLM:
         """Returns the LLM object for the tool.
 
         Returns:
-            Optional[LLM]: The LLM object for the tool.
+            LLM: The LLM object for the tool.
             (llama_index.llms.base.LLM)
         """
         adapter_instance_id = (
@@ -114,20 +115,22 @@ def get_llm(
                     ][Common.ADAPTER]
                     llm_metadata = llm_config_data.get(Common.ADAPTER_METADATA)
                     llm_adapter_class: LLMAdapter = llm_adapter(llm_metadata)
-                    llm_instance: Optional[
-                        LLM
-                    ] = llm_adapter_class.get_llm_instance()
+                    llm_instance: LLM = llm_adapter_class.get_llm_instance()
                     return llm_instance
                 else:
-                    return None
+                    raise SdkError(
+                        f"LLM adapter not supported : " f"{llm_adapter_id}"
+                    )
             except Exception as e:
                 self.tool.stream_log(
                     log=f"Unable to get llm instance: {e}", level=LogLevel.ERROR
                 )
-                return None
+                raise SdkError(f"Error getting llm instance: {e}")
         else:
-            logger.error("The adapter_instance_id parameter is None")
-            return None
+            raise SdkError(
+                f"Adapter_instance_id does not have "
+                f"a valid value: {adapter_instance_id}"
+            )
 
     def get_max_tokens(self, reserved_for_output: int = 0) -> int:
         """Returns the maximum number of tokens that can be used for the LLM.
diff --git a/src/unstract/sdk/utils/callback_manager.py b/src/unstract/sdk/utils/callback_manager.py
new file mode 100644
index 00000000..c50ca914
--- /dev/null
+++ b/src/unstract/sdk/utils/callback_manager.py
@@ -0,0 +1,123 @@
+import logging
+from typing import Callable, Optional, Union
+
+import tiktoken
+from llama_index.core.callbacks import (
+    CallbackManager as LlamaIndexCallbackManager,
+)
+from llama_index.core.callbacks import TokenCountingHandler
+from llama_index.core.embeddings import BaseEmbedding
+from llama_index.core.llms import LLM
+from transformers import AutoTokenizer
+
+from unstract.sdk.utils.usage_handler import UsageHandler
+
+logger = logging.getLogger(__name__)
+
+
+class CallbackManager:
+    """Class representing the CallbackManager to manage callbacks.
+
+    Use this over the default service context of llama index
+
+    This class supports a tokenizer, token counter,
+    usage handler, and  callback manager.
+
+    Attributes:
+        None
+
+    Methods:
+        set_callback_manager: Returns a standard callback manager
+
+    Example:
+        callback_manager = CallbackManager.
+                            set_callback_manager(
+                                llm="default",
+                                embedding="default")
+    """
+
+    @staticmethod
+    def set_callback_manager(
+        platform_api_key: str,
+        llm: Optional[LLM] = None,
+        embedding: Optional[BaseEmbedding] = None,
+        workflow_id: str = "",
+        execution_id: str = "",
+    ) -> LlamaIndexCallbackManager:
+        """Sets the standard callback manager for the llm. This is to be called
+        explicitly whenever there is a need for the callback handling defined
+        here as handlers is to be invoked.
+
+        Parameters:
+            llm (LLM): The LLM type
+
+        Returns:
+            CallbackManager tyoe of llama index
+
+        Example:
+            UNCallbackManager.set_callback_manager(
+                platform_api_key: "abc",
+                llm=llm,
+                embedding=embedding
+            )
+        """
+
+        if llm:
+            tokenizer = CallbackManager.get_tokenizer(llm)
+        elif embedding:
+            tokenizer = CallbackManager.get_tokenizer(embedding)
+
+        token_counter = TokenCountingHandler(tokenizer=tokenizer, verbose=True)
+        usage_handler = UsageHandler(
+            token_counter=token_counter,
+            platform_api_key=platform_api_key,
+            llm_model=llm,
+            embed_model=embedding,
+            workflow_id=workflow_id,
+            execution_id=execution_id,
+        )
+
+        callback_manager: LlamaIndexCallbackManager = LlamaIndexCallbackManager(
+            handlers=[token_counter, usage_handler]
+        )
+
+        if llm is not None:
+            llm.callback_manager = callback_manager
+        if embedding is not None:
+            embedding.callback_manager = callback_manager
+
+        return callback_manager
+
+    @staticmethod
+    def get_tokenizer(
+        model: Optional[Union[LLM, BaseEmbedding, None]],
+        fallback_tokenizer: Callable[[str], list] = tiktoken.encoding_for_model(
+            "gpt-3.5-turbo"
+        ).encode,
+    ) -> Callable[[str], list]:
+        """Returns a tokenizer function based on the provided model.
+
+        Args:
+            model (Optional[Union[LLM, BaseEmbedding]]): The model to use for
+            tokenization.
+
+        Returns:
+            Callable[[str], List]: The tokenizer function.
+
+        Raises:
+            OSError: If an error occurs while loading the tokenizer.
+        """
+
+        try:
+            if isinstance(model, LLM):
+                model_name: str = model.metadata.model_name
+            elif isinstance(model, BaseEmbedding):
+                model_name = model.model_name
+
+            tokenizer: Callable[[str], list] = AutoTokenizer.from_pretrained(
+                model_name
+            ).encode
+            return tokenizer
+        except OSError as e:
+            logger.warning(str(e))
+            return fallback_tokenizer
diff --git a/src/unstract/sdk/utils/service_context.py b/src/unstract/sdk/utils/service_context.py
deleted file mode 100644
index 17744566..00000000
--- a/src/unstract/sdk/utils/service_context.py
+++ /dev/null
@@ -1,126 +0,0 @@
-import logging
-from typing import Any, Callable, Optional, Union
-
-import tiktoken
-from llama_index import ServiceContext as LlamaIndexServiceContext
-from llama_index.callbacks import CallbackManager, TokenCountingHandler
-from llama_index.core.embeddings.base import BaseEmbedding
-from llama_index.llms import LLM
-from llama_index.llms.utils import LLMType
-from transformers import AutoTokenizer
-
-from unstract.sdk.utils.usage_handler import UsageHandler
-
-logger = logging.getLogger(__name__)
-
-
-class ServiceContext:
-    """Class representing the UNServiceContext.
-
-    Use this over the default service context of llama index
-
-    This class provides a static method to get the service context for
-    UNstract Tools. The service context includes a tokenizer, token counter,
-    usage handler, and  callback manager.
-
-    Attributes:
-        None
-
-    Methods:
-        get_service_context: Returns the service context for UNstract Tools.
-
-    Example:
-        service_context = UNServiceContext.
-                            get_service_context(
-                                workflow_id="123",
-                                execution_id="456",
-                                llm="default",
-                                embed_model="default")
-    """
-
-    @staticmethod
-    def get_service_context(
-        platform_api_key: str,
-        workflow_id: str = "",
-        execution_id: str = "",
-        llm: Optional[LLMType] = None,
-        embed_model: Optional[Any] = None,
-        **kwargs: Any,
-    ) -> LlamaIndexServiceContext:
-        """Returns the service context for UNstract Tools.
-
-        Parameters:
-            workflow_id (str): The workflow ID. Default is an empty string.
-            execution_id (str): The execution ID. Default is an empty string.
-            llm (Optional[LLMType]): The LLM type. Default is None.
-            embed_model (Optional[Any]): The embedding model. Default is None.
-
-        Returns:
-            ServiceContext: The service context for UNstract Tools.
-
-        Example:
-            service_context = UNServiceContext.get_service_context(
-                workflow_id="123",
-                execution_id="456",
-                llm="default",
-                embed_model="default"
-            )
-        """
-        if llm:
-            tokenizer = ServiceContext.get_tokenizer(llm)
-        elif embed_model:
-            tokenizer = ServiceContext.get_tokenizer(embed_model)
-
-        token_counter = TokenCountingHandler(tokenizer=tokenizer, verbose=True)
-        usage_handler = UsageHandler(
-            token_counter=token_counter,
-            platform_api_key=platform_api_key,
-            llm_model=llm,
-            embed_model=embed_model,
-            workflow_id=workflow_id,
-            execution_id=execution_id,
-        )
-
-        callback_manager = CallbackManager(
-            handlers=[token_counter, usage_handler]
-        )
-        return LlamaIndexServiceContext.from_defaults(
-            llm=llm,
-            embed_model=embed_model,
-            callback_manager=callback_manager,
-            **kwargs,
-        )
-
-    @staticmethod
-    def get_tokenizer(
-        model: Optional[Union[LLM, BaseEmbedding, None]],
-        fallback_tokenizer: Callable[[str], list] = tiktoken.encoding_for_model(
-            "gpt-3.5-turbo"
-        ).encode,
-    ) -> Callable[[str], list]:
-        """Returns a tokenizer function based on the provided model.
-
-        Args:
-            model (Optional[Union[LLM, BaseEmbedding]]): The model to use for
-            tokenization.
-
-        Returns:
-            Callable[[str], List]: The tokenizer function.
-
-        Raises:
-            OSError: If an error occurs while loading the tokenizer.
-        """
-
-        try:
-            if isinstance(model, LLM):
-                model_name: str = model.metadata.model_name
-            elif isinstance(model, BaseEmbedding):
-                model_name = model.model_name
-
-            tokenizer: Callable[[str], list] = AutoTokenizer.from_pretrained(
-                model_name
-            ).encode
-            return tokenizer
-        except OSError as e:
-            logger.warning(str(e))
-            return fallback_tokenizer
diff --git a/src/unstract/sdk/utils/usage_handler.py b/src/unstract/sdk/utils/usage_handler.py
index 196eafc2..129b5500 100644
--- a/src/unstract/sdk/utils/usage_handler.py
+++ b/src/unstract/sdk/utils/usage_handler.py
@@ -1,10 +1,9 @@
 from typing import Any, Optional
 
-from llama_index.callbacks import TokenCountingHandler
-from llama_index.callbacks.base_handler import BaseCallbackHandler
-from llama_index.callbacks.schema import CBEventType
-from llama_index.core.embeddings.base import BaseEmbedding
-from llama_index.llms.llm import LLM
+from llama_index.core.callbacks import CBEventType, TokenCountingHandler
+from llama_index.core.callbacks.base_handler import BaseCallbackHandler
+from llama_index.core.embeddings import BaseEmbedding
+from llama_index.core.llms import LLM
 
 from unstract.sdk.audit import Audit
 from unstract.sdk.constants import LogLevel
diff --git a/src/unstract/sdk/vector_db.py b/src/unstract/sdk/vector_db.py
index fdf0b1c6..08c2ce4b 100644
--- a/src/unstract/sdk/vector_db.py
+++ b/src/unstract/sdk/vector_db.py
@@ -1,7 +1,10 @@
 import logging
 from typing import Union
 
-from llama_index.vector_stores.types import BasePydanticVectorStore, VectorStore
+from llama_index.core.vector_stores.types import (
+    BasePydanticVectorStore,
+    VectorStore,
+)
 from unstract.adapters.constants import Common
 from unstract.adapters.vectordb import adapters
 from unstract.adapters.vectordb.constants import VectorDbConstants
@@ -41,7 +44,7 @@ def __get_org_id(self) -> str:
 
     def get_vector_db(
         self, adapter_instance_id: str, embedding_dimension: int
-    ) -> Union[BasePydanticVectorStore, VectorStore, None]:
+    ) -> Union[BasePydanticVectorStore, VectorStore]:
         adapter_instance_id = (
             adapter_instance_id
             if adapter_instance_id
@@ -73,10 +76,18 @@ def get_vector_db(
                     )
                     return vector_db_adapter_class.get_vector_db_instance()
                 else:
-                    return None
+                    raise SdkError(
+                        f"VectorDB adapter not supported : "
+                        f"{vector_db_adapter_id}"
+                    )
             except Exception as e:
                 self.tool.stream_log(
                     log=f"Unable to get vector_db {adapter_instance_id}: {e}",
                     level=LogLevel.ERROR,
                 )
-                return None
+                raise SdkError(f"Error getting vectorDB instance: {e}")
+        else:
+            raise SdkError(
+                f"Adapter_instance_id does not have "
+                f"a valid value: {adapter_instance_id}"
+            )
diff --git a/tests/test_embedding.py b/tests/test_embedding.py
index 7a5e2b0c..890f8474 100644
--- a/tests/test_embedding.py
+++ b/tests/test_embedding.py
@@ -3,7 +3,7 @@
 import unittest
 
 from dotenv import load_dotenv
-from llama_index.core.embeddings.base import BaseEmbedding
+from llama_index.core.embeddings import BaseEmbedding
 from parameterized import parameterized
 
 from unstract.sdk.embedding import ToolEmbedding
diff --git a/tests/test_vector_db.py b/tests/test_vector_db.py
index 269d5307..345a7164 100644
--- a/tests/test_vector_db.py
+++ b/tests/test_vector_db.py
@@ -4,8 +4,11 @@
 import unittest
 
 from dotenv import load_dotenv
-from llama_index import MockEmbedding
-from llama_index.vector_stores.types import BasePydanticVectorStore, VectorStore
+from llama_index.core import MockEmbedding
+from llama_index.core.vector_stores.types import (
+    BasePydanticVectorStore,
+    VectorStore,
+)
 from parameterized import parameterized
 from unstract.adapters.vectordb.helper import VectorDBHelper