diff --git a/README.md b/README.md
index e10d7c78..d0321890 100644
--- a/README.md
+++ b/README.md
@@ -12,7 +12,7 @@
 
 ### ⚡ The PyTorch Library for Large Language Model Applications ⚡
 
-*LightRAG* helps developers with both building and optimizing *Retriever-Agent-Generator (RAG)* pipelines.
+*LightRAG* helps developers with both building and optimizing *Retriever-Agent-Generator* pipelines.
 It is *light*, *modular*, and *robust*, with a 100% readable codebase.
 
 
@@ -22,7 +22,7 @@ It is *light*, *modular*, and *robust*, with a 100% readable codebase.
 
 LLMs are like water; they can almost do anything, from GenAI applications such as chatbots, translation, summarization, code generation, and autonomous agents to classical NLP tasks like text classification and named entity recognition. They interact with the world beyond the model’s internal knowledge via retrievers, memory, and tools (function calls). Each use case is unique in its data, business logic, and user experience.
 
-Because of this, no library can provide out-of-the-box solutions. Users must build towards their own use case, which requires the library to be modular, robust, and have a clean and readable codebase. The only code you should put into production is code you either trust 100% or are 100% clear about how to customize and iterate.
+Because of this, no library can provide out-of-the-box solutions. Users must build toward their own use case. This requires the library to be modular, robust, and have a clean, readable codebase. The only code you should put into production is code you either 100% trust or are 100% clear about how to customize and iterate.
 
 LightRAG is born to be light, modular, and robust, with a 100% readable codebase.
 
diff --git a/docs/.gitignore b/docs/.gitignore
index 911161cb..870d4664 100644
--- a/docs/.gitignore
+++ b/docs/.gitignore
@@ -13,3 +13,4 @@ source/apis/tracing/tracing*
 source/apis/tracing/modules*
 source/apis/optim/optim*
 source/apis/optim/modules*
+tests.txt
diff --git a/docs/poetry.lock b/docs/poetry.lock
index 379bae05..0430c326 100644
--- a/docs/poetry.lock
+++ b/docs/poetry.lock
@@ -40,6 +40,51 @@ files = [
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.30.1"
+description = "The official Python library for the anthropic API"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "anthropic-0.30.1-py3-none-any.whl", hash = "sha256:a58a8c3865a3df21e3b10e5fbd1a54b84cb01386f3e9fea9c65334b3cb306c6f"},
+    {file = "anthropic-0.30.1.tar.gz", hash = "sha256:e082aa2601834a8a374f8bb45bca68493d892b2a03a1c44cfcc38465550c9b8b"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+jiter = ">=0.4.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+tokenizers = ">=0.13.0"
+typing-extensions = ">=4.7,<5"
+
+[package.extras]
+bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
+vertex = ["google-auth (>=2,<3)"]
+
+[[package]]
+name = "anyio"
+version = "4.4.0"
+description = "High level compatibility layer for multiple asynchronous event loop implementations"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
+    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+]
+
+[package.dependencies]
+idna = ">=2.8"
+sniffio = ">=1.1"
+
+[package.extras]
+doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
+test = ["anyio[trio]", "coverage[toml] (>=7)", "exceptiongroup (>=1.2.0)", "hypothesis (>=4.0)", "psutil (>=5.9)", "pytest (>=7.0)", "pytest-mock (>=3.6.1)", "trustme", "uvloop (>=0.17)"]
+trio = ["trio (>=0.23)"]
+
 [[package]]
 name = "attrs"
 version = "23.2.0"
@@ -123,6 +168,44 @@ webencodings = "*"
 [package.extras]
 css = ["tinycss2 (>=1.1.0,<1.3)"]
 
+[[package]]
+name = "boto3"
+version = "1.34.142"
+description = "The AWS SDK for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "boto3-1.34.142.tar.gz", hash = "sha256:72daee953cfa0631c584c9e3aef594079e1fe6a2f64c81ff791dab9a7b25c013"},
+]
+
+[package.dependencies]
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+jmespath = ">=0.7.1,<2.0.0"
+s3transfer = ">=0.10.0,<0.11.0"
+
+[package.extras]
+crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
+
+[[package]]
+name = "botocore"
+version = "1.34.142"
+description = "Low-level, data-driven core of boto 3."
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "botocore-1.34.142.tar.gz", hash = "sha256:2eeb8e6be729c1f8ded723970ed6c6ac29cc3014d86a99e73428fa8bdca81f63"},
+]
+
+[package.dependencies]
+jmespath = ">=0.7.1,<2.0.0"
+python-dateutil = ">=2.1,<3.0.0"
+urllib3 = {version = ">=1.25.4,<2.2.0 || >2.2.0,<3", markers = "python_version >= \"3.10\""}
+
+[package.extras]
+crt = ["awscrt (==0.20.11)"]
+
 [[package]]
 name = "cachetools"
 version = "5.3.3"
@@ -308,6 +391,29 @@ files = [
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 ]
 
+[[package]]
+name = "cohere"
+version = "5.5.8"
+description = ""
+optional = false
+python-versions = "<4.0,>=3.8"
+files = [
+    {file = "cohere-5.5.8-py3-none-any.whl", hash = "sha256:e1ed84b90eadd13c6a68ee28e378a0bb955f8945eadc6eb7ee126b3399cafd54"},
+    {file = "cohere-5.5.8.tar.gz", hash = "sha256:84ce7666ff8fbdf4f41fb5f6ca452ab2639a514bc88967a2854a9b1b820d6ea0"},
+]
+
+[package.dependencies]
+boto3 = ">=1.34.0,<2.0.0"
+fastavro = ">=1.9.4,<2.0.0"
+httpx = ">=0.21.2"
+httpx-sse = ">=0.4.0,<0.5.0"
+parameterized = ">=0.9.0,<0.10.0"
+pydantic = ">=1.9.2"
+requests = ">=2.0.0,<3.0.0"
+tokenizers = ">=0.15,<1"
+types-requests = ">=2.0.0,<3.0.0"
+typing_extensions = ">=4.0.0"
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -330,6 +436,17 @@ files = [
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 ]
 
+[[package]]
+name = "distro"
+version = "1.9.0"
+description = "Distro - an OS platform information API"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2"},
+    {file = "distro-1.9.0.tar.gz", hash = "sha256:2fa77c6fd8940f116ee1d6b94a2f90b13b5ea8d019b98bc8bafdcabcdd9bdbed"},
+]
+
 [[package]]
 name = "docutils"
 version = "0.21.2"
@@ -341,6 +458,91 @@ files = [
     {file = "docutils-0.21.2.tar.gz", hash = "sha256:3a6b18732edf182daa3cd12775bbb338cf5691468f91eeeb109deff6ebfa986f"},
 ]
 
+[[package]]
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+version = "1.8.0.post1"
+description = "A library for efficient similarity search and clustering of dense vectors."
+optional = false
+python-versions = ">=3.8"
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+    {file = "fastavro-1.9.5-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:b5f7f2b1fe21231fd01f1a2a90e714ae267fe633cd7ce930c0aea33d1c9f4901"},
+    {file = "fastavro-1.9.5-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:88fbbe16c61d90a89d78baeb5a34dc1c63a27b115adccdbd6b1fb6f787deacf2"},
+    {file = "fastavro-1.9.5-cp39-cp39-win_amd64.whl", hash = "sha256:753f5eedeb5ca86004e23a9ce9b41c5f25eb64a876f95edcc33558090a7f3e4b"},
+    {file = "fastavro-1.9.5.tar.gz", hash = "sha256:6419ebf45f88132a9945c51fe555d4f10bb97c236288ed01894f957c6f914553"},
+]
+
+[package.extras]
+codecs = ["cramjam", "lz4", "zstandard"]
+lz4 = ["lz4"]
+snappy = ["cramjam"]
+zstandard = ["zstandard"]
+
 [[package]]
 name = "fastjsonschema"
 version = "2.20.0"
@@ -355,6 +557,61 @@ files = [
 [package.extras]
 devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benchmark", "pytest-cache", "validictory"]
 
+[[package]]
+name = "filelock"
+version = "3.15.4"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "filelock-3.15.4-py3-none-any.whl", hash = "sha256:6ca1fffae96225dab4c6eaf1c4f4f28cd2568d3ec2a44e15a08520504de468e7"},
+    {file = "filelock-3.15.4.tar.gz", hash = "sha256:2207938cbc1844345cb01a5a95524dae30f0ce089eba5b00378295a17e3e90cb"},
+]
+
+[package.extras]
+docs = ["furo (>=2023.9.10)", "sphinx (>=7.2.6)", "sphinx-autodoc-typehints (>=1.25.2)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3.2)", "diff-cover (>=8.0.1)", "pytest (>=7.4.3)", "pytest-asyncio (>=0.21)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)", "pytest-timeout (>=2.2)", "virtualenv (>=20.26.2)"]
+typing = ["typing-extensions (>=4.8)"]
+
+[[package]]
+name = "fsspec"
+version = "2024.6.1"
+description = "File-system specification"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fsspec-2024.6.1-py3-none-any.whl", hash = "sha256:3cb443f8bcd2efb31295a5b9fdb02aee81d8452c80d28f97a6d0959e6cee101e"},
+    {file = "fsspec-2024.6.1.tar.gz", hash = "sha256:fad7d7e209dd4c1208e3bbfda706620e0da5142bebbd9c384afb95b07e798e49"},
+]
+
+[package.extras]
+abfs = ["adlfs"]
+adl = ["adlfs"]
+arrow = ["pyarrow (>=1)"]
+dask = ["dask", "distributed"]
+dev = ["pre-commit", "ruff"]
+doc = ["numpydoc", "sphinx", "sphinx-design", "sphinx-rtd-theme", "yarl"]
+dropbox = ["dropbox", "dropboxdrivefs", "requests"]
+full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
+fuse = ["fusepy"]
+gcs = ["gcsfs"]
+git = ["pygit2"]
+github = ["requests"]
+gs = ["gcsfs"]
+gui = ["panel"]
+hdfs = ["pyarrow (>=1)"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)"]
+libarchive = ["libarchive-c"]
+oci = ["ocifs"]
+s3 = ["s3fs"]
+sftp = ["paramiko"]
+smb = ["smbprotocol"]
+ssh = ["paramiko"]
+test = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "numpy", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "requests"]
+test-downstream = ["aiobotocore (>=2.5.4,<3.0.0)", "dask-expr", "dask[dataframe,test]", "moto[server] (>4,<5)", "pytest-timeout", "xarray"]
+test-full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "cloudpickle", "dask", "distributed", "dropbox", "dropboxdrivefs", "fastparquet", "fusepy", "gcsfs", "jinja2", "kerchunk", "libarchive-c", "lz4", "notebook", "numpy", "ocifs", "pandas", "panel", "paramiko", "pyarrow", "pyarrow (>=1)", "pyftpdlib", "pygit2", "pytest", "pytest-asyncio (!=0.22.0)", "pytest-benchmark", "pytest-cov", "pytest-mock", "pytest-recording", "pytest-rerunfailures", "python-snappy", "requests", "smbprotocol", "tqdm", "urllib3", "zarr", "zstandard"]
+tqdm = ["tqdm"]
+
 [[package]]
 name = "google-ai-generativelanguage"
 version = "0.6.6"
@@ -399,13 +656,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.136.0"
+version = "2.137.0"
 description = "Google API Client Library for Python"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-api-python-client-2.136.0.tar.gz", hash = "sha256:161c722c8864e7ed39393e2b7eea76ef4e1c933a6a59f9d7c70409b6635f225d"},
-    {file = "google_api_python_client-2.136.0-py2.py3-none-any.whl", hash = "sha256:5a554c8b5edf0a609b905d89d7ced82e8f6ac31da1e4d8d5684ef63dbc0e49f5"},
+    {file = "google_api_python_client-2.137.0-py2.py3-none-any.whl", hash = "sha256:a8b5c5724885e5be9f5368739aa0ccf416627da4ebd914b410a090c18f84d692"},
+    {file = "google_api_python_client-2.137.0.tar.gz", hash = "sha256:e739cb74aac8258b1886cb853b0722d47c81fe07ad649d7f2206f06530513c04"},
 ]
 
 [package.dependencies]
@@ -417,13 +674,13 @@ uritemplate = ">=3.0.1,<5"
 
 [[package]]
 name = "google-auth"
-version = "2.31.0"
+version = "2.32.0"
 description = "Google Authentication Library"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "google-auth-2.31.0.tar.gz", hash = "sha256:87805c36970047247c8afe614d4e3af8eceafc1ebba0c679fe75ddd1d575e871"},
-    {file = "google_auth-2.31.0-py2.py3-none-any.whl", hash = "sha256:042c4702efa9f7d3c48d3a69341c209381b125faa6dbf3ebe56bc7e40ae05c23"},
+    {file = "google_auth-2.32.0-py2.py3-none-any.whl", hash = "sha256:53326ea2ebec768070a94bee4e1b9194c9646ea0c2bd72422785bd0f9abfad7b"},
+    {file = "google_auth-2.32.0.tar.gz", hash = "sha256:49315be72c55a6a37d62819e3573f6b416aca00721f7e3e31a008d928bf64022"},
 ]
 
 [package.dependencies]
@@ -455,12 +712,12 @@ httplib2 = ">=0.19.0"
 
 [[package]]
 name = "google-generativeai"
-version = "0.7.1"
+version = "0.7.2"
 description = "Google Generative AI High level API client library and tools."
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "google_generativeai-0.7.1-py3-none-any.whl", hash = "sha256:25017b1278c873b6db65ba41c70566ee9fce8f265498e8b2f6aac036528ba1c7"},
+    {file = "google_generativeai-0.7.2-py3-none-any.whl", hash = "sha256:3117d1ebc92ee77710d4bc25ab4763492fddce9b6332eb25d124cf5d8b78b339"},
 ]
 
 [package.dependencies]
@@ -564,6 +821,25 @@ files = [
 docs = ["Sphinx", "furo"]
 test = ["objgraph", "psutil"]
 
+[[package]]
+name = "groq"
+version = "0.9.0"
+description = "The official Python library for the groq API"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "groq-0.9.0-py3-none-any.whl", hash = "sha256:d0e46f4ad645504672bb09c8100af3ced3a7db0d5119dc13e4aca535fc455874"},
+    {file = "groq-0.9.0.tar.gz", hash = "sha256:130ed5e35d3acfaab46b9e7a078eeaebf91052f4a9d71f86f87fb319b5fec332"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+typing-extensions = ">=4.7,<5"
+
 [[package]]
 name = "grpcio"
 version = "1.64.1"
@@ -638,6 +914,38 @@ googleapis-common-protos = ">=1.5.5"
 grpcio = ">=1.62.2"
 protobuf = ">=4.21.6"
 
+[[package]]
+name = "h11"
+version = "0.14.0"
+description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "h11-0.14.0-py3-none-any.whl", hash = "sha256:e3fe4ac4b851c468cc8363d500db52c2ead036020723024a109d37346efaa761"},
+    {file = "h11-0.14.0.tar.gz", hash = "sha256:8f19fbbe99e72420ff35c00b27a34cb9937e902a8b810e2c88300c6f0a3b699d"},
+]
+
+[[package]]
+name = "httpcore"
+version = "1.0.5"
+description = "A minimal low-level HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
+]
+
+[package.dependencies]
+certifi = "*"
+h11 = ">=0.13,<0.15"
+
+[package.extras]
+asyncio = ["anyio (>=4.0,<5.0)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
+
 [[package]]
 name = "httplib2"
 version = "0.22.0"
@@ -652,6 +960,75 @@ files = [
 [package.dependencies]
 pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0.2,<3.0.3 || >3.0.3,<4", markers = "python_version > \"3.0\""}
 
+[[package]]
+name = "httpx"
+version = "0.27.0"
+description = "The next generation HTTP client."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-0.27.0-py3-none-any.whl", hash = "sha256:71d5465162c13681bff01ad59b2cc68dd838ea1f10e51574bac27103f00c91a5"},
+    {file = "httpx-0.27.0.tar.gz", hash = "sha256:a0cb88a46f32dc874e04ee956e4c2764aba2aa228f650b06788ba6bda2962ab5"},
+]
+
+[package.dependencies]
+anyio = "*"
+certifi = "*"
+httpcore = "==1.*"
+idna = "*"
+sniffio = "*"
+
+[package.extras]
+brotli = ["brotli", "brotlicffi"]
+cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
+http2 = ["h2 (>=3,<5)"]
+socks = ["socksio (==1.*)"]
+
+[[package]]
+name = "httpx-sse"
+version = "0.4.0"
+description = "Consume Server-Sent Event (SSE) messages with HTTPX."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-sse-0.4.0.tar.gz", hash = "sha256:1e81a3a3070ce322add1d3529ed42eb5f70817f45ed6ec915ab753f961139721"},
+    {file = "httpx_sse-0.4.0-py3-none-any.whl", hash = "sha256:f329af6eae57eaa2bdfd962b42524764af68075ea87370a2de920af5341e318f"},
+]
+
+[[package]]
+name = "huggingface-hub"
+version = "0.23.4"
+description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
+optional = false
+python-versions = ">=3.8.0"
+files = [
+    {file = "huggingface_hub-0.23.4-py3-none-any.whl", hash = "sha256:3a0b957aa87150addf0cc7bd71b4d954b78e749850e1e7fb29ebbd2db64ca037"},
+    {file = "huggingface_hub-0.23.4.tar.gz", hash = "sha256:35d99016433900e44ae7efe1c209164a5a81dbbcd53a52f99c281dcd7ce22431"},
+]
+
+[package.dependencies]
+filelock = "*"
+fsspec = ">=2023.5.0"
+packaging = ">=20.9"
+pyyaml = ">=5.1"
+requests = "*"
+tqdm = ">=4.42.1"
+typing-extensions = ">=3.7.4.3"
+
+[package.extras]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+cli = ["InquirerPy (==0.3.4)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "mypy (==1.5.1)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.3.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
+hf-transfer = ["hf-transfer (>=0.1.4)"]
+inference = ["aiohttp", "minijinja (>=1.0)"]
+quality = ["mypy (==1.5.1)", "ruff (>=0.3.0)"]
+tensorflow = ["graphviz", "pydot", "tensorflow"]
+tensorflow-testing = ["keras (<3.0)", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio", "jedi", "minijinja (>=1.0)", "numpy", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+torch = ["safetensors", "torch"]
+typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
+
 [[package]]
 name = "idna"
 version = "3.7"
@@ -691,6 +1068,87 @@ MarkupSafe = ">=2.0"
 [package.extras]
 i18n = ["Babel (>=2.7)"]
 
+[[package]]
+name = "jiter"
+version = "0.5.0"
+description = "Fast iterable JSON parser."
+optional = false
+python-versions = ">=3.8"
+files = [
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+[[package]]
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+version = "1.0.1"
+description = "JSON Matching Expressions"
+optional = false
+python-versions = ">=3.7"
+files = [
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+
 [[package]]
 name = "jsonlines"
 version = "4.0.0"
@@ -707,13 +1165,13 @@ attrs = ">=19.2.0"
 
 [[package]]
 name = "jsonschema"
-version = "4.22.0"
+version = "4.23.0"
 description = "An implementation of JSON Schema validation for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -724,7 +1182,7 @@ rpds-py = ">=0.7.1"
 
 [package.extras]
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 [[package]]
 name = "jsonschema-specifications"
@@ -795,24 +1253,26 @@ files = [
 
 [[package]]
 name = "lightrag"
-version = "0.0.0a13"
+version = "0.0.0-alpha.16"
 description = "The 'PyTorch' library for LLM applications. RAG=Retriever-Agent-Generator."
 optional = false
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+files = []
+develop = true
 
 [package.dependencies]
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+python-dotenv = "^1.0.1"
+pyyaml = "^6.0.1"
+tiktoken = "^0.7.0"
+tqdm = "^4.66.4"
+
+[package.source]
+type = "directory"
+url = "../lightrag"
 
 [[package]]
 name = "markupsafe"
@@ -1038,6 +1498,29 @@ files = [
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 ]
 
+[[package]]
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+version = "1.35.12"
+description = "The official Python library for the openai API"
+optional = false
+python-versions = ">=3.7.1"
+files = [
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+tqdm = ">4"
+typing-extensions = ">=4.7,<5"
+
+[package.extras]
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+
 [[package]]
 name = "packaging"
 version = "24.1"
@@ -1074,6 +1557,33 @@ files = [
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 ]
 
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+version = "0.9.0"
+description = "Parameterized testing with any Python test framework"
+optional = false
+python-versions = ">=3.7"
+files = [
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+
+[package.extras]
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+
+[[package]]
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+description = "pgvector support for Python"
+optional = false
+python-versions = ">=3.8"
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+
+[package.dependencies]
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+
 [[package]]
 name = "platformdirs"
 version = "4.2.2"
@@ -1720,110 +2230,110 @@ use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
 [[package]]
 name = "rpds-py"
-version = "0.18.1"
+version = "0.19.0"
 description = "Python bindings to Rust's persistent data structures (rpds)"
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 python-versions = ">=3.8"
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 doc = ["sphinx", "sphinx_rtd_theme"]
 test = ["pytest", "ruff"]
 
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+
+[package.dependencies]
+huggingface-hub = ">=0.16.4,<1.0"
+
+[package.extras]
+dev = ["tokenizers[testing]"]
+docs = ["setuptools-rust", "sphinx", "sphinx-rtd-theme"]
+testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
+
 [[package]]
 name = "tornado"
 version = "6.4.1"
@@ -2255,6 +3032,88 @@ files = [
 docs = ["myst-parser", "pydata-sphinx-theme", "sphinx"]
 test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,<8.2)", "pytest-mock", "pytest-mypy-testing"]
 
+[[package]]
+name = "transformers"
+version = "4.42.3"
+description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
+optional = false
+python-versions = ">=3.8.0"
+files = [
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+]
+
+[package.dependencies]
+filelock = "*"
+huggingface-hub = ">=0.23.2,<1.0"
+numpy = ">=1.17,<2.0"
+packaging = ">=20.0"
+pyyaml = ">=5.1"
+regex = "!=2019.12.17"
+requests = "*"
+safetensors = ">=0.4.1"
+tokenizers = ">=0.19,<0.20"
+tqdm = ">=4.27"
+
+[package.extras]
+accelerate = ["accelerate (>=0.21.0)"]
+agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
+all = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "codecarbon (==1.2.0)", "decord (==0.6.0)", "flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "phonemizer", "protobuf", "pyctcdecode (>=0.4.0)", "ray[tune] (>=2.7.0)", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision"]
+audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+benchmark = ["optimum-benchmark (>=0.2.0)"]
+codecarbon = ["codecarbon (==1.2.0)"]
+deepspeed = ["accelerate (>=0.21.0)", "deepspeed (>=0.9.3)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.21.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "optuna", "parameterized", "protobuf", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+dev = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "av (==9.2.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "decord (==0.6.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "flax (>=0.4.1,<=0.7.0)", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "optax (>=0.0.8,<=0.1.4)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "scipy (<1.13.0)", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+dev-tensorflow = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "isort (>=5.5.4)", "kenlm", "keras-nlp (>=0.3.1)", "librosa", "nltk", "onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx", "timeout-decorator", "tokenizers (>=0.19,<0.20)", "urllib3 (<2.0.0)"]
+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.21.0)", "beautifulsoup4", "codecarbon (==1.2.0)", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "isort (>=5.5.4)", "kenlm", "librosa", "nltk", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "optuna", "parameterized", "phonemizer", "protobuf", "psutil", "pyctcdecode (>=0.4.0)", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "ray[tune] (>=2.7.0)", "rhoknp (>=1.1.0,<1.3.1)", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "scikit-learn", "sentencepiece (>=0.1.91,!=0.1.92)", "sigopt", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "tensorboard", "timeout-decorator", "timm (<=0.9.16)", "tokenizers (>=0.19,<0.20)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
+flax = ["flax (>=0.4.1,<=0.7.0)", "jax (>=0.4.1,<=0.4.13)", "jaxlib (>=0.4.1,<=0.4.13)", "optax (>=0.0.8,<=0.1.4)", "scipy (<1.13.0)"]
+flax-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+ftfy = ["ftfy"]
+integrations = ["optuna", "ray[tune] (>=2.7.0)", "sigopt"]
+ja = ["fugashi (>=1.0)", "ipadic (>=1.0.0,<2.0)", "rhoknp (>=1.1.0,<1.3.1)", "sudachidict-core (>=20220729)", "sudachipy (>=0.6.6)", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)"]
+modelcreation = ["cookiecutter (==1.7.3)"]
+natten = ["natten (>=0.14.6,<0.15.0)"]
+onnx = ["onnxconverter-common", "onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)", "tf2onnx"]
+onnxruntime = ["onnxruntime (>=1.4.0)", "onnxruntime-tools (>=1.4.2)"]
+optuna = ["optuna"]
+quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "ruff (==0.4.4)", "urllib3 (<2.0.0)"]
+ray = ["ray[tune] (>=2.7.0)"]
+retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
+ruff = ["ruff (==0.4.4)"]
+sagemaker = ["sagemaker (>=2.31.0)"]
+sentencepiece = ["protobuf", "sentencepiece (>=0.1.91,!=0.1.92)"]
+serving = ["fastapi", "pydantic", "starlette", "uvicorn"]
+sigopt = ["sigopt"]
+sklearn = ["scikit-learn"]
+speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
+testing = ["GitPython (<3.1.19)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk", "parameterized", "psutil", "pydantic", "pytest (>=7.2.0,<8.0.0)", "pytest-rich", "pytest-timeout", "pytest-xdist", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.4.4)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+tf = ["keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
+tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1)", "onnxconverter-common", "tensorflow-cpu (>2.9,<2.16)", "tensorflow-probability (<0.24)", "tensorflow-text (<2.16)", "tf2onnx"]
+tf-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
+timm = ["timm (<=0.9.16)"]
+tokenizers = ["tokenizers (>=0.19,<0.20)"]
+torch = ["accelerate (>=0.21.0)", "torch"]
+torch-speech = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)", "torchaudio"]
+torch-vision = ["Pillow (>=10.0.1,<=15.0)", "torchvision"]
+torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17,<2.0)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.19,<0.20)", "torch", "tqdm (>=4.27)"]
+video = ["av (==9.2.0)", "decord (==0.6.0)"]
+vision = ["Pillow (>=10.0.1,<=15.0)"]
+
+[[package]]
+name = "types-requests"
+version = "2.32.0.20240622"
+description = "Typing stubs for requests"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "types-requests-2.32.0.20240622.tar.gz", hash = "sha256:ed5e8a412fcc39159d6319385c009d642845f250c63902718f605cd90faade31"},
+    {file = "types_requests-2.32.0.20240622-py3-none-any.whl", hash = "sha256:97bac6b54b5bd4cf91d407e62f0932a74821bc2211f22116d9ee1dd643826caf"},
+]
+
+[package.dependencies]
+urllib3 = ">=2"
+
 [[package]]
 name = "typing-extensions"
 version = "4.12.2"
@@ -2308,4 +3167,4 @@ files = [
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.11, <4.0"
-content-hash = "ff3d3c46a7b28f8bcecf06db3a9fafc21eccc121793645b340a8e0f3b6fbcbeb"
+content-hash = "80950ed5eff2c0caf8bf347256c4301dbee61fa505d0114d54aaacd8ff818ebd"
diff --git a/docs/pyproject.toml b/docs/pyproject.toml
index be4d3c83..b182d7d8 100644
--- a/docs/pyproject.toml
+++ b/docs/pyproject.toml
@@ -8,8 +8,7 @@ packages = [{ from = "_dummy", include = "dummy" }]    # empty packages
 
 [tool.poetry.dependencies]
 python = ">=3.11, <4.0"
-lightrag = "^0.0.0a13"  # Assuming this is the main library you are developing
-
+lightrag = { path = "../lightrag", develop = true } # document always follow the latest version of the library
 
 [tool.poetry.group.doc.dependencies]
 pydata-sphinx-theme = "^0.15.3"
@@ -20,8 +19,16 @@ nbsphinx = "^0.9.4"
 nbconvert = "^7.16.4"
 pandoc = "^2.3"
 readthedocs-sphinx-search = "^0.3.2"
+# add optional packages to compile the documents correctly
 sqlalchemy = "^2.0.31"
 google-generativeai = "^0.7.1"
+anthropic = "^0.30.1"
+cohere = "^5.5.8"
+transformers = "^4.42.3"
+openai = "^1.35.12"
+groq = "^0.9.0"
+pgvector = "^0.3.0"
+faiss-cpu = "^1.8.0.post1"
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]
diff --git a/docs/source/developer_notes/lightrag_design_philosophy.rst b/docs/source/developer_notes/lightrag_design_philosophy.rst
index f2fb932c..e7242a0d 100644
--- a/docs/source/developer_notes/lightrag_design_philosophy.rst
+++ b/docs/source/developer_notes/lightrag_design_philosophy.rst
@@ -6,11 +6,11 @@ Right from the begining, `LightRAG` follows three fundamental principles.
 
 Principle 1:  Simplicity over Complexity
 -----------------------------------------------------------------------
-We put these three hard rules while designing LightRAG:
+ We put these three hard rules while designing LightRAG:
 
 - Every layer of abstraction needs to be adjusted and overall we do not allow more than 3 layers of abstraction.
 - We minimize the lines of code instead of maximizing the lines of code.
-- Go *deep* and *wide* in order to *simplify*.  The clarity we achieve is not the result of being easy, but the result of being deep.
+- Go *deep* and *wide* in order to *simplify*.  The clarity we achieve is not the result of being easy.
 
 
 
diff --git a/docs/source/get_started/lightrag_in_10_mins.rst b/docs/source/get_started/lightrag_in_10_mins.rst
index 1bdec107..d046c77f 100644
--- a/docs/source/get_started/lightrag_in_10_mins.rst
+++ b/docs/source/get_started/lightrag_in_10_mins.rst
@@ -1,13 +1,15 @@
 LightRAG in 10 minutes
 =============================
-[Li]
 
+Coming soon...
 
-Will use end to end trec classifier as an example to demonstrate:
+We will showcase a use case end-to-end, including task pipeline, configuration, logging and tracing, evaluation, and optimization.
 
-1. Look at the data and task, create `data class`, `prompt`, and `task`, and set up `log` and tracing.
-2. Create datasets with `train`, `eval`, and `test` splits.
-3. Eval zero-shot with manual prompts.
+.. Will use end to end trec classifier as an example to demonstrate:
 
+.. 1. Look at the data and task, create `data class`, `prompt`, and `task`, and set up `log` and tracing.
+.. 2. Create datasets with `train`, `eval`, and `test` splits.
+.. 3. Eval zero-shot with manual prompts.
 
-The content will be from `/use_cases/classification/readme.md`.
\ No newline at end of file
+
+.. The content will be from `/use_cases/classification/readme.md`.
diff --git a/docs/source/index.rst b/docs/source/index.rst
index 519db7a7..007139d6 100644
--- a/docs/source/index.rst
+++ b/docs/source/index.rst
@@ -26,7 +26,7 @@
 
     <div style="text-align: center;">
         <p>
-            <em>LightRAG</em> helps developers with both building and optimizing <em>Retriever-Agent-Generator (RAG)</em> pipelines.<br>
+            <em>LightRAG</em> helps developers with both building and optimizing <em>Retriever-Agent-Generator</em> pipelines.<br>
             It is <em>light</em>, <em>modular</em>, and <em>robust</em>,  with a 100% readable codebase.
         </p>
     </div>
diff --git a/docs/tests.txt b/docs/tests.txt
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diff --git a/lightrag/lightrag/components/model_client/anthropic_client.py b/lightrag/lightrag/components/model_client/anthropic_client.py
index c53049ef..869d6a2b 100644
--- a/lightrag/lightrag/components/model_client/anthropic_client.py
+++ b/lightrag/lightrag/components/model_client/anthropic_client.py
@@ -34,6 +34,9 @@ def get_first_message_content(completion: Message) -> str:
     return completion.content[0].text
 
 
+__all__ = ["AnthropicAPIClient", "get_first_message_content"]
+
+
 # NOTE: using customize parser might make the new_component more complex when we have to handle a callable
 class AnthropicAPIClient(ModelClient):
     __doc__ = r"""A component wrapper for the Anthropic API client.
diff --git a/lightrag/lightrag/components/model_client/cohere_client.py b/lightrag/lightrag/components/model_client/cohere_client.py
index 2ec3048d..93132234 100644
--- a/lightrag/lightrag/components/model_client/cohere_client.py
+++ b/lightrag/lightrag/components/model_client/cohere_client.py
@@ -77,9 +77,12 @@ def convert_inputs_to_api_kwargs(
         final_model_kwargs = model_kwargs.copy()
         if model_type == ModelType.RERANKER:
             final_model_kwargs["query"] = input
-            assert "model" in final_model_kwargs, "model must be specified"
-            assert "documents" in final_model_kwargs, "documents must be specified"
-            assert "top_k" in final_model_kwargs, "top_k must be specified"
+            if "model" not in final_model_kwargs:
+                raise ValueError("model must be specified")
+            if "documents" not in final_model_kwargs:
+                raise ValueError("documents must be specified")
+            if "top_k" not in final_model_kwargs:
+                raise ValueError("top_k must be specified")
 
             # convert top_k to the api specific, which is top_n
             final_model_kwargs["top_n"] = final_model_kwargs.pop("top_k")
@@ -123,7 +126,8 @@ async def acall(
     ):
         if self.async_client is None:
             self.init_async_client()
-        assert "model" in api_kwargs, "model must be specified"
+        if "model" not in api_kwargs:
+            raise ValueError("model must be specified")
         if model_type == ModelType.RERANKER:
             response = await self.async_client.rerank(**api_kwargs)
             top_k_scores = [result.relevance_score for result in response.results]
diff --git a/lightrag/lightrag/components/model_client/google_client.py b/lightrag/lightrag/components/model_client/google_client.py
index c097a9e6..9c4d57a0 100644
--- a/lightrag/lightrag/components/model_client/google_client.py
+++ b/lightrag/lightrag/components/model_client/google_client.py
@@ -66,7 +66,8 @@ def convert_inputs_to_api_kwargs(
             if isinstance(input, str):
                 input = [input]
             # convert input to input
-            assert isinstance(input, Sequence), "input must be a sequence of text"
+            if not isinstance(input, Sequence):
+                raise TypeError("input must be a sequence of text")
             final_model_kwargs["input"] = input
         elif model_type == ModelType.LLM:
 
diff --git a/lightrag/lightrag/components/model_client/openai_client.py b/lightrag/lightrag/components/model_client/openai_client.py
index 8dc4874b..d374d123 100644
--- a/lightrag/lightrag/components/model_client/openai_client.py
+++ b/lightrag/lightrag/components/model_client/openai_client.py
@@ -118,7 +118,6 @@ def parse_chat_completion(self, completion: Completion) -> Any:
         """Parse the completion to a str."""
         log.debug(f"completion: {completion}")
         return self.chat_completion_parser(completion)
-        # return completion.choices[0].message.content
 
     def parse_embedding_response(
         self, response: CreateEmbeddingResponse
@@ -148,16 +147,14 @@ def convert_inputs_to_api_kwargs(
             if isinstance(input, str):
                 input = [input]
             # convert input to input
-            assert isinstance(input, Sequence), "input must be a sequence of text"
+            if not isinstance(input, Sequence):
+                raise TypeError("input must be a sequence of text")
             final_model_kwargs["input"] = input
         elif model_type == ModelType.LLM:
             # convert input to messages
             messages: List[Dict[str, str]] = []
             if input is not None and input != "":
                 messages.append({"role": "system", "content": input})
-            assert isinstance(
-                messages, Sequence
-            ), "input must be a sequence of messages"
             final_model_kwargs["messages"] = messages
         else:
             raise ValueError(f"model_type {model_type} is not supported")
diff --git a/lightrag/lightrag/components/model_client/transformers_client.py b/lightrag/lightrag/components/model_client/transformers_client.py
index 1517a8ad..16ab0ae5 100644
--- a/lightrag/lightrag/components/model_client/transformers_client.py
+++ b/lightrag/lightrag/components/model_client/transformers_client.py
@@ -374,10 +374,11 @@ def parse_embedding_response(self, response: Any) -> EmbedderOutput:
         return response
 
     def call(self, api_kwargs: Dict = {}, model_type: ModelType = ModelType.UNDEFINED):
-        assert "model" in api_kwargs, "model is required"
-        assert (
-            api_kwargs["model"] in self.support_models
-        ), f"model {api_kwargs['model']} is not supported"
+        if "model" not in api_kwargs:
+            raise ValueError("model must be specified in api_kwargs")
+        if api_kwargs["model"] not in self.support_models:
+            raise ValueError(f"model {api_kwargs['model']} is not supported")
+
         if (
             model_type == ModelType.EMBEDDER
             and "model" in api_kwargs
diff --git a/lightrag/lightrag/components/model_client/utils.py b/lightrag/lightrag/components/model_client/utils.py
index a7bec9aa..2b81d96e 100644
--- a/lightrag/lightrag/components/model_client/utils.py
+++ b/lightrag/lightrag/components/model_client/utils.py
@@ -1,5 +1,4 @@
 "Helpers for model client for integrating models and parsing the output."
-
 from lightrag.core.types import EmbedderOutput, Embedding, Usage
 
 
diff --git a/lightrag/lightrag/database/sqlalchemy/model.py b/lightrag/lightrag/database/sqlalchemy/model.py
index 2b56f47e..7ba1b728 100644
--- a/lightrag/lightrag/database/sqlalchemy/model.py
+++ b/lightrag/lightrag/database/sqlalchemy/model.py
@@ -30,7 +30,14 @@
 from typing import Optional, Dict, List
 from datetime import datetime
 import logging
+from lightrag.utils.lazy_import import safe_import, OptionalPackages
 
+sqlalchemy = safe_import(
+    OptionalPackages.SQLALCHEMY.value[0], OptionalPackages.SQLALCHEMY.value[1]
+)
+pgvector = safe_import(
+    OptionalPackages.PGVECTOR.value[0], OptionalPackages.PGVECTOR.value[1]
+)
 from sqlalchemy import (
     Column,
     Integer,
@@ -48,11 +55,8 @@
 
 from pgvector.sqlalchemy import Vector
 
-from lightrag.utils.lazy_import import safe_import, OptionalPackages
 from lightrag.database.sqlalchemy.base import Base
 
-safe_import(OptionalPackages.SQLALCHEMY.value[0], OptionalPackages.SQLALCHEMY.value[1])
-safe_import(OptionalPackages.PGVECTOR.value[0], OptionalPackages.PGVECTOR.value[1])
 
 log = logging.getLogger(__name__)
 
diff --git a/lightrag/lightrag/utils/lazy_import.py b/lightrag/lightrag/utils/lazy_import.py
index 18741b68..db0d1293 100644
--- a/lightrag/lightrag/utils/lazy_import.py
+++ b/lightrag/lightrag/utils/lazy_import.py
@@ -2,6 +2,7 @@
 
 import importlib
 import logging
+from types import ModuleType
 
 
 from enum import Enum
@@ -65,7 +66,16 @@ class LazyImport:
         optional_package (OptionalPackages): The optional package to import, it helps define the package name and error message.
     """
 
-    def __init__(self, import_path: str, optional_package: OptionalPackages):
+    def __init__(
+        self, import_path: str, optional_package: OptionalPackages, *args, **kwargs
+    ):
+        if args or kwargs:
+            raise TypeError(
+                "LazyImport does not support subclassing or additional arguments. "
+                "Import the class directly from its specific module instead. For example, "
+                "from lightrag.components.model_client.cohere_client import CohereAPIClient"
+                "instead of using the lazy import with: from lightrag.components.model_client import CohereAPIClient"
+            )
         self.import_path = import_path
         self.optional_package = optional_package
         self.module = None
@@ -100,10 +110,34 @@ def __call__(self, *args, **kwargs):
         return self.class_(*args, **kwargs)
 
 
-def safe_import(module_name, install_message):
+def safe_import(module_name: str, install_message: str) -> ModuleType:
     """Safely import a module and raise an ImportError with the install message if the module is not found.
 
     Mainly used internally to import optional packages only when needed.
+
+    Example:
+
+    1. Tests
+
+    .. code-block:: python
+
+        try:
+            numpy = safe_import("numpy", "Please install numpy with: pip install numpy")
+            print(numpy.__version__)
+        except ImportError as e:
+            print(e)
+
+    When numpy is not installed, it will raise an ImportError with the install message.
+    When numpy is installed, it will print the numpy version.
+
+    2. Use it to delay the import of optional packages in the library.
+
+    .. code-block:: python
+
+        from lightrag.utils.lazy_import import safe_import, OptionalPackages
+
+        numpy = safe_import(OptionalPackages.NUMPY.value[0], OptionalPackages.NUMPY.value[1])
+
     """
     try:
         return importlib.import_module(module_name)
diff --git a/lightrag/lightrag/utils/setup_env.py b/lightrag/lightrag/utils/setup_env.py
index a201d070..d2250e26 100644
--- a/lightrag/lightrag/utils/setup_env.py
+++ b/lightrag/lightrag/utils/setup_env.py
@@ -1,7 +1,18 @@
 import dotenv
+import os
+import logging
+
+log = logging.getLogger(__name__)
 
 
 def setup_env(dotenv_path: str = ".env"):
     """Load environment variables from .env file."""
 
-    dotenv.load_dotenv(dotenv_path=dotenv_path)
+    if not os.path.exists(dotenv_path):
+        raise FileNotFoundError(f"File not found: {dotenv_path}")
+
+    try:
+        dotenv.load_dotenv(dotenv_path=dotenv_path, verbose=True, override=False)
+    except Exception as e:
+        log.error(f"Error loading .env file: {e}")
+        raise e
diff --git a/lightrag/poetry.lock b/lightrag/poetry.lock
index 1fb66df7..02d8f4b7 100644
--- a/lightrag/poetry.lock
+++ b/lightrag/poetry.lock
@@ -507,13 +507,13 @@ typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "t
 
 [[package]]
 name = "identify"
-version = "2.5.36"
+version = "2.6.0"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "identify-2.5.36-py2.py3-none-any.whl", hash = "sha256:37d93f380f4de590500d9dba7db359d0d3da95ffe7f9de1753faa159e71e7dfa"},
-    {file = "identify-2.5.36.tar.gz", hash = "sha256:e5e00f54165f9047fbebeb4a560f9acfb8af4c88232be60a488e9b68d122745d"},
+    {file = "identify-2.6.0-py2.py3-none-any.whl", hash = "sha256:e79ae4406387a9d300332b5fd366d8994f1525e8414984e1a59e058b2eda2dd0"},
+    {file = "identify-2.6.0.tar.gz", hash = "sha256:cb171c685bdc31bcc4c1734698736a7d5b6c8bf2e0c15117f4d469c8640ae5cf"},
 ]
 
 [package.extras]
@@ -966,13 +966,13 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.35.10"
+version = "1.35.12"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
-    {file = "openai-1.35.10-py3-none-any.whl", hash = "sha256:962cb5c23224b5cbd16078308dabab97a08b0a5ad736a4fdb3dc2ffc44ac974f"},
-    {file = "openai-1.35.10.tar.gz", hash = "sha256:85966949f4f960f3e4b239a659f9fd64d3a97ecc43c44dc0a044b5c7f11cccc6"},
+    {file = "openai-1.35.12-py3-none-any.whl", hash = "sha256:c3a8c9be524480ae32a3212b78d90786b112844eb8f96235ebb8bc5f35cb1e72"},
+    {file = "openai-1.35.12.tar.gz", hash = "sha256:2dd0f1d9ff34bf6bc89d15246245369d281b2ba01ae07eae5555a00da4b51e0b"},
 ]
 
 [package.dependencies]
@@ -1614,17 +1614,20 @@ sqlcipher = ["sqlcipher3_binary"]
 
 [[package]]
 name = "sympy"
-version = "1.12.1"
+version = "1.13.0"
 description = "Computer algebra system (CAS) in Python"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "sympy-1.12.1-py3-none-any.whl", hash = "sha256:9b2cbc7f1a640289430e13d2a56f02f867a1da0190f2f99d8968c2f74da0e515"},
-    {file = "sympy-1.12.1.tar.gz", hash = "sha256:2877b03f998cd8c08f07cd0de5b767119cd3ef40d09f41c30d722f6686b0fb88"},
+    {file = "sympy-1.13.0-py3-none-any.whl", hash = "sha256:6b0b32a4673fb91bd3cac3b55406c8e01d53ae22780be467301cc452f6680c92"},
+    {file = "sympy-1.13.0.tar.gz", hash = "sha256:3b6af8f4d008b9a1a6a4268b335b984b23835f26d1d60b0526ebc71d48a25f57"},
 ]
 
 [package.dependencies]
-mpmath = ">=1.1.0,<1.4.0"
+mpmath = ">=1.1.0,<1.4"
+
+[package.extras]
+dev = ["hypothesis (>=6.70.0)", "pytest (>=7.1.0)"]
 
 [[package]]
 name = "tbb"
diff --git a/lightrag/pyproject.toml b/lightrag/pyproject.toml
index bc8c91d7..44d6a9de 100644
--- a/lightrag/pyproject.toml
+++ b/lightrag/pyproject.toml
@@ -2,7 +2,7 @@
 name = "lightrag"
 
 version = "0.0.0-alpha.16"
-description = "The 'PyTorch' library for LLM applications. RAG=Retriever-Agent-Generator."
+description = "The 'PyTorch' library for LLM applications."
 authors = ["Li Yin <li@sylphai.com>"]
 readme = "README.md"
 repository = "https://github.com/SylphAI-Inc/LightRAG"
diff --git a/pyproject.toml b/pyproject.toml
index 5278c225..9e739301 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -11,10 +11,7 @@ packages = [{ from = "_lightrag", include = "lightrag" }]          # empty packa
 python = ">=3.11, <4.0"
 # lightrag = { path = "lightrag", develop = true }
 torch = "^2.3.1"
-# flagembedding = "^1.2.10"
 openai = "^1.34.0"
-networkx = "^3.3"
-pyvis = "^0.3.2"
 # lightrag = {path = "lightrag/dist/lightrag-0.0.0a11-py3-none-any.whl"}
 lightrag = "^0.0.0a13"
 
@@ -22,7 +19,6 @@ lightrag = "^0.0.0a13"
 [tool.poetry.group.dev.dependencies]
 
 pre-commit = "^3.7.0"
-
 anthropic = "^0.26.0"
 torchmetrics = "^1.4.0.post0"
 jupyter = "^1.0.0"