diff --git a/poetry.lock b/poetry.lock
index 3ffc94c66..2bce047cc 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -13,113 +13,113 @@ files = [
 
 [[package]]
 name = "aiohappyeyeballs"
-version = "2.4.0"
+version = "2.4.3"
 description = "Happy Eyeballs for asyncio"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
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 optional = false
 python-versions = ">=3.8"
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+    {file = "aiohttp-3.10.8-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:d088ca05381fd409793571d8e34eca06daf41c8c50a05aeed358d2d340c7af81"},
+    {file = "aiohttp-3.10.8-cp39-cp39-win32.whl", hash = "sha256:ee97c4e54f457c366e1f76fbbf3e8effee9de57dae671084a161c00f481106ce"},
+    {file = "aiohttp-3.10.8-cp39-cp39-win_amd64.whl", hash = "sha256:d95ae4420669c871667aad92ba8cce6251d61d79c1a38504621094143f94a8b4"},
+    {file = "aiohttp-3.10.8.tar.gz", hash = "sha256:21f8225f7dc187018e8433c9326be01477fb2810721e048b33ac49091b19fb4a"},
 ]
 
 [package.dependencies]
@@ -129,7 +129,7 @@ async-timeout = {version = ">=4.0,<5.0", markers = "python_version < \"3.11\""}
 attrs = ">=17.3.0"
 frozenlist = ">=1.1.1"
 multidict = ">=4.5,<7.0"
-yarl = ">=1.0,<2.0"
+yarl = ">=1.12.0,<2.0"
 
 [package.extras]
 speedups = ["Brotli", "aiodns (>=3.2.0)", "brotlicffi"]
@@ -148,6 +148,17 @@ files = [
 [package.dependencies]
 frozenlist = ">=1.1.0"
 
+[[package]]
+name = "annotated-types"
+version = "0.7.0"
+description = "Reusable constraint types to use with typing.Annotated"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
+]
+
 [[package]]
 name = "anthropic"
 version = "0.31.2"
@@ -175,13 +186,13 @@ vertex = ["google-auth (>=2,<3)"]
 
 [[package]]
 name = "anyio"
-version = "4.4.0"
+version = "4.6.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
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-    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
+    {file = "anyio-4.6.0-py3-none-any.whl", hash = "sha256:c7d2e9d63e31599eeb636c8c5c03a7e108d73b345f064f1c19fdc87b79036a9a"},
+    {file = "anyio-4.6.0.tar.gz", hash = "sha256:137b4559cbb034c477165047febb6ff83f390fc3b20bf181c1fc0a728cb8beeb"},
 ]
 
 [package.dependencies]
@@ -191,9 +202,9 @@ sniffio = ">=1.1"
 typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
 
 [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)"]
+doc = ["Sphinx (>=7.4,<8.0)", "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 (>=0.21.0b1)"]
+trio = ["trio (>=0.26.1)"]
 
 [[package]]
 name = "appnope"
@@ -237,22 +248,22 @@ files = [
 
 [[package]]
 name = "attrs"
-version = "24.2.0"
+version = "23.2.0"
 description = "Classes Without Boilerplate"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"},
+    {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"},
 ]
 
 [package.extras]
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-docs = ["cogapp", "furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier (<24.7)"]
-tests = ["cloudpickle", "hypothesis", "mypy (>=1.11.1)", "pympler", "pytest (>=4.3.0)", "pytest-mypy-plugins", "pytest-xdist[psutil]"]
-tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
+cov = ["attrs[tests]", "coverage[toml] (>=5.3)"]
+dev = ["attrs[tests]", "pre-commit"]
+docs = ["furo", "myst-parser", "sphinx", "sphinx-notfound-page", "sphinxcontrib-towncrier", "towncrier", "zope-interface"]
+tests = ["attrs[tests-no-zope]", "zope-interface"]
+tests-mypy = ["mypy (>=1.6)", "pytest-mypy-plugins"]
+tests-no-zope = ["attrs[tests-mypy]", "cloudpickle", "hypothesis", "pympler", "pytest (>=4.3.0)", "pytest-xdist[psutil]"]
 
 [[package]]
 name = "beartype"
@@ -274,17 +285,17 @@ test-tox-coverage = ["coverage (>=5.5)"]
 
 [[package]]
 name = "boto3"
-version = "1.35.5"
+version = "1.35.31"
 description = "The AWS SDK for Python"
 optional = true
 python-versions = ">=3.8"
 files = [
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+    {file = "boto3-1.35.31-py3-none-any.whl", hash = "sha256:2e9af74d10d8af7610a8d8468d2914961f116912a024fce17351825260385a52"},
+    {file = "boto3-1.35.31.tar.gz", hash = "sha256:8c593af260c4ea3eb6f079c09908f94494ca2222aa4e40a7ff490fab1cee8b39"},
 ]
 
 [package.dependencies]
-botocore = ">=1.35.5,<1.36.0"
+botocore = ">=1.35.31,<1.36.0"
 jmespath = ">=0.7.1,<2.0.0"
 s3transfer = ">=0.10.0,<0.11.0"
 
@@ -293,13 +304,13 @@ crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.35.5"
+version = "1.35.31"
 description = "Low-level, data-driven core of boto 3."
 optional = true
 python-versions = ">=3.8"
 files = [
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+    {file = "botocore-1.35.31-py3-none-any.whl", hash = "sha256:4cee814875bc78656aef4011d3d6b2231e96f53ea3661ee428201afb579d5c31"},
+    {file = "botocore-1.35.31.tar.gz", hash = "sha256:f7bfa910cf2cbcc8c2307c1cf7b93495d614c2d699883417893e0a337fe4eb63"},
 ]
 
 [package.dependencies]
@@ -308,7 +319,7 @@ 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 (==0.21.2)"]
+crt = ["awscrt (==0.21.5)"]
 
 [[package]]
 name = "cachetools"
@@ -323,89 +334,89 @@ files = [
 
 [[package]]
 name = "certifi"
-version = "2024.7.4"
+version = "2024.8.30"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
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+    {file = "certifi-2024.8.30.tar.gz", hash = "sha256:bec941d2aa8195e248a60b31ff9f0558284cf01a52591ceda73ea9afffd69fd9"},
 ]
 
 [[package]]
 name = "cffi"
-version = "1.17.0"
+version = "1.17.1"
 description = "Foreign Function Interface for Python calling C code."
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 python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -537,24 +548,24 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""}
 
 [[package]]
 name = "cloudpickle"
-version = "3.0.0"
-description = "Pickler class to extend the standard pickle.Pickler functionality"
+version = "2.2.1"
+description = "Extended pickling support for Python objects"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.6"
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 ]
 
 [[package]]
 name = "cohere"
-version = "5.8.1"
+version = "5.11.0"
 description = ""
 optional = true
 python-versions = "<4.0,>=3.8"
 files = [
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 [package.dependencies]
@@ -566,6 +577,7 @@ parameterized = ">=0.9.0,<0.10.0"
 pydantic = ">=1.9.2"
 pydantic-core = ">=2.18.2,<3.0.0"
 requests = ">=2.0.0,<3.0.0"
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 tokenizers = ">=0.15,<1"
 types-requests = ">=2.0.0,<3.0.0"
 typing_extensions = ">=4.0.0"
@@ -687,38 +699,38 @@ toml = ["tomli"]
 
 [[package]]
 name = "cryptography"
-version = "43.0.0"
+version = "43.0.1"
 description = "cryptography is a package which provides cryptographic recipes and primitives to Python developers."
 optional = false
 python-versions = ">=3.7"
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 ]
 
 [package.dependencies]
@@ -731,7 +743,7 @@ nox = ["nox"]
 pep8test = ["check-sdist", "click", "mypy", "ruff"]
 sdist = ["build"]
 ssh = ["bcrypt (>=3.1.5)"]
-test = ["certifi", "cryptography-vectors (==43.0.0)", "pretend", "pytest (>=6.2.0)", "pytest-benchmark", "pytest-cov", "pytest-xdist"]
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 test-randomorder = ["pytest-randomly"]
 
 [[package]]
@@ -780,33 +792,33 @@ vision = ["Pillow (>=9.4.0)"]
 
 [[package]]
 name = "debugpy"
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+optional = true
+python-versions = ">=3.8"
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+urllib3 = ">=1.26.0"
+
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+websockets = ["websocket-client (>=1.3.0)"]
+
 [[package]]
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 version = "1.2.2"
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 [[package]]
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 [package.extras]
@@ -977,19 +1011,19 @@ devel = ["colorama", "json-spec", "jsonschema", "pylint", "pytest", "pytest-benc
 
 [[package]]
 name = "filelock"
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 description = "A platform independent file lock."
 optional = false
 python-versions = ">=3.8"
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-typing = ["typing-extensions (>=4.8)"]
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+typing = ["typing-extensions (>=4.12.2)"]
 
 [[package]]
 name = "frozenlist"
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+version = "2.20.0"
 description = "Google API client core library"
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@@ -1188,13 +1222,13 @@ grpcio-gcp = ["grpcio-gcp (>=0.2.2,<1.0.dev0)"]
 
 [[package]]
 name = "google-api-python-client"
-version = "2.142.0"
+version = "2.147.0"
 description = "Google API Client Library for Python"
 optional = true
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 [package.extras]
 dev = ["Pillow", "absl-py", "black", "ipython", "nose2", "pandas", "pytype", "pyyaml"]
 
+[[package]]
+name = "google-pasta"
+version = "0.2.0"
+description = "pasta is an AST-based Python refactoring library"
+optional = true
+python-versions = "*"
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 [package.extras]
@@ -1374,61 +1438,70 @@ typing-extensions = ">=4.7,<5"
 
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 ]
 
 [package.dependencies]
@@ -1609,7 +1682,7 @@ h11 = ">=0.13,<0.15"
 asyncio = ["anyio (>=4.0,<5.0)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
-trio = ["trio (>=0.22.0,<0.26.0)"]
+trio = ["trio (>=0.22.0,<1.0)"]
 
 [[package]]
 name = "httplib2"
@@ -1627,13 +1700,13 @@ pyparsing = {version = ">=2.4.2,<3.0.0 || >3.0.0,<3.0.1 || >3.0.1,<3.0.2 || >3.0
 
 [[package]]
 name = "httpx"
-version = "0.27.0"
+version = "0.27.2"
 description = "The next generation HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -1648,6 +1721,7 @@ brotli = ["brotli", "brotlicffi"]
 cli = ["click (==8.*)", "pygments (==2.*)", "rich (>=10,<14)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
+zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "httpx-sse"
@@ -1662,13 +1736,13 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.24.6"
+version = "0.25.1"
 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 = [
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 ]
 
 [package.dependencies]
@@ -1696,13 +1770,13 @@ typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "t
 
 [[package]]
 name = "identify"
-version = "2.6.0"
+version = "2.6.1"
 description = "File identification library for Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -1710,33 +1784,139 @@ license = ["ukkonen"]
 
 [[package]]
 name = "idna"
-version = "3.8"
+version = "3.10"
 description = "Internationalized Domain Names in Applications (IDNA)"
 optional = false
 python-versions = ">=3.6"
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+
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+version = "3.3.0"
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 [[package]]
 name = "importlib-metadata"
-version = "8.4.0"
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 description = "Read metadata from Python packages"
 optional = false
 python-versions = ">=3.8"
 files = [
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 zipp = ">=0.5"
 
 [package.extras]
-doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
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 perf = ["ipython"]
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+testing = ["flufl.flake8", "importlib-resources (>=1.3)", "packaging", "pyfakefs", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-mypy (>=0.9.1)", "pytest-perf (>=0.9.2)", "pytest-ruff"]
 
 [[package]]
 name = "iniconfig"
@@ -1784,13 +1964,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
 
 [[package]]
 name = "ipython"
-version = "8.26.0"
+version = "8.28.0"
 description = "IPython: Productive Interactive Computing"
 optional = false
 python-versions = ">=3.10"
 files = [
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 ]
 
 [package.dependencies]
@@ -1999,13 +2179,13 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "jupyter-client"
-version = "8.6.2"
+version = "8.6.3"
 description = "Jupyter protocol implementation and client libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -2041,43 +2221,19 @@ test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"
 
 [[package]]
 name = "langchain"
-version = "0.2.5"
+version = "0.2.16"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
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 async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
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-PyYAML = ">=5.3"
-requests = ">=2,<3"
-SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<9.0.0"
-
-[[package]]
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-optional = false
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-async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.2.32,<0.3.0"
+langchain-core = ">=0.2.38,<0.3.0"
 langchain-text-splitters = ">=0.2.0,<0.3.0"
 langsmith = ">=0.1.17,<0.2.0"
 numpy = [
@@ -2092,156 +2248,97 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.8"
+version = "0.2.41"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
 jsonpatch = ">=1.33,<2.0"
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+langsmith = ">=0.1.112,<0.2.0"
 packaging = ">=23.2,<25"
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-PyYAML = ">=5.3"
-tenacity = ">=8.1.0,<9.0.0"
-
-[[package]]
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-description = "Building applications with LLMs through composability"
-optional = false
-python-versions = "<4.0,>=3.8.1"
-files = [
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+    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
 ]
-
-[package.dependencies]
-jsonpatch = ">=1.33,<2.0"
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-pydantic = {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""}
 PyYAML = ">=5.3"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 typing-extensions = ">=4.7"
 
 [[package]]
 name = "langchain-openai"
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-description = "An integration package connecting OpenAI and LangChain"
-optional = false
-python-versions = "<4.0,>=3.8.1"
-files = [
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-[package.dependencies]
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-tiktoken = ">=0.7,<1"
-
-[[package]]
-name = "langchain-openai"
-version = "0.1.22"
+version = "0.1.25"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
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+langchain-core = ">=0.2.40,<0.3.0"
 openai = ">=1.40.0,<2.0.0"
 tiktoken = ">=0.7,<1"
 
 [[package]]
 name = "langchain-text-splitters"
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-python-versions = "<4.0,>=3.8.1"
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-
-[package.dependencies]
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-
-[package.extras]
-extended-testing = ["beautifulsoup4 (>=4.12.3,<5.0.0)", "lxml (>=4.9.3,<6.0)"]
-
-[[package]]
-name = "langchain-text-splitters"
-version = "0.2.2"
+version = "0.2.4"
 description = "LangChain text splitting utilities"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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 ]
 
 [package.dependencies]
-langchain-core = ">=0.2.10,<0.3.0"
+langchain-core = ">=0.2.38,<0.3.0"
 
 [[package]]
 name = "langsmith"
-version = "0.1.81"
+version = "0.1.130"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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-
-[[package]]
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+python-versions = ">=3.6"
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+
+[package.extras]
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+docs = ["sphinx"]
+test = ["pytest (<5.4)", "pytest-cov"]
+
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 [[package]]
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 ]
 
 [package.dependencies]
@@ -3224,6 +3355,23 @@ files = [
 qa = ["flake8 (==5.0.4)", "mypy (==0.971)", "types-setuptools (==67.2.0.1)"]
 testing = ["docopt", "pytest"]
 
+[[package]]
+name = "pathos"
+version = "0.3.2"
+description = "parallel graph management and execution in heterogeneous computing"
+optional = true
+python-versions = ">=3.8"
+files = [
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+    {file = "pathos-0.3.2.tar.gz", hash = "sha256:4f2a42bc1e10ccf0fe71961e7145fc1437018b6b21bd93b2446abc3983e49a7a"},
+]
+
+[package.dependencies]
+dill = ">=0.3.8"
+multiprocess = ">=0.70.16"
+pox = ">=0.3.4"
+ppft = ">=1.7.6.8"
+
 [[package]]
 name = "pettingzoo"
 version = "1.24.3"
@@ -3265,19 +3413,19 @@ ptyprocess = ">=0.5"
 
 [[package]]
 name = "platformdirs"
-version = "4.2.2"
+version = "4.3.6"
 description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
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-type = ["mypy (>=1.8)"]
+docs = ["furo (>=2024.8.6)", "proselint (>=0.14)", "sphinx (>=8.0.2)", "sphinx-autodoc-typehints (>=2.4)"]
+test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=8.3.2)", "pytest-cov (>=5)", "pytest-mock (>=3.14)"]
+type = ["mypy (>=1.11.2)"]
 
 [[package]]
 name = "pluggy"
@@ -3294,6 +3442,31 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["pytest", "pytest-benchmark"]
 
+[[package]]
+name = "pox"
+version = "0.3.5"
+description = "utilities for filesystem exploration and automated builds"
+optional = true
+python-versions = ">=3.8"
+files = [
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+]
+
+[[package]]
+name = "ppft"
+version = "1.7.6.9"
+description = "distributed and parallel Python"
+optional = true
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.extras]
+dill = ["dill (>=0.3.9)"]
+
 [[package]]
 name = "pre-commit"
 version = "3.8.0"
@@ -3314,13 +3487,13 @@ virtualenv = ">=20.10.0"
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.47"
+version = "3.0.48"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -3345,22 +3518,22 @@ testing = ["google-api-core (>=1.31.5)"]
 
 [[package]]
 name = "protobuf"
-version = "4.25.4"
+version = "4.25.5"
 description = ""
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -3470,24 +3643,24 @@ test = ["cffi", "hypothesis", "pandas", "pytest", "pytz"]
 
 [[package]]
 name = "pyasn1"
-version = "0.6.0"
+version = "0.6.1"
 description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs (X.208)"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "pyasn1-modules"
-version = "0.4.0"
+version = "0.4.1"
 description = "A collection of ASN.1-based protocols modules"
 optional = true
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3506,159 +3679,120 @@ files = [
 
 [[package]]
 name = "pydantic"
-version = "1.10.17"
-description = "Data validation and settings management using python type hints"
+version = "2.9.2"
+description = "Data validation using Python type hints"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
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 ]
 
 [package.dependencies]
@@ -3694,13 +3828,13 @@ diagrams = ["jinja2", "railroad-diagrams"]
 
 [[package]]
 name = "pytest"
-version = "8.3.2"
+version = "8.3.3"
 description = "pytest: simple powerful testing with Python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3791,13 +3925,13 @@ files = [
 
 [[package]]
 name = "pytz"
-version = "2024.1"
+version = "2024.2"
 description = "World timezone definitions, modern and historical"
 optional = true
 python-versions = "*"
 files = [
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 ]
 
 [[package]]
@@ -4008,41 +4142,41 @@ cffi = {version = "*", markers = "implementation_name == \"pypy\""}
 
 [[package]]
 name = "redis"
-version = "5.0.8"
+version = "5.1.0"
 description = "Python client for Redis database and key-value store"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
 async-timeout = {version = ">=4.0.3", markers = "python_full_version < \"3.11.3\""}
 
 [package.extras]
-hiredis = ["hiredis (>1.0.0)"]
-ocsp = ["cryptography (>=36.0.1)", "pyopenssl (==20.0.1)", "requests (>=2.26.0)"]
+hiredis = ["hiredis (>=3.0.0)"]
+ocsp = ["cryptography (>=36.0.1)", "pyopenssl (==23.2.1)", "requests (>=2.31.0)"]
 
 [[package]]
 name = "redis-om"
-version = "0.2.2"
+version = "0.3.2"
 description = "Object mappings, and more, for Redis."
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
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 [package.dependencies]
 click = ">=8.0.1,<9.0.0"
-hiredis = ">=2.2.3,<3.0.0"
+hiredis = ">=2.2.3,<4.0.0"
 more-itertools = ">=8.14,<11.0"
-pydantic = ">=1.10.2,<2.5.0"
+pydantic = ">=1.10.2,<3.0.0"
 python-ulid = ">=1.0.3,<2.0.0"
 redis = ">=3.5.3,<6.0.0"
-setuptools = {version = ">=69.2.0,<70.0.0", markers = "python_version >= \"3.12\""}
+setuptools = {version = ">=70.0,<73.0", markers = "python_version >= \"3.12\""}
 types-redis = ">=3.5.9,<5.0.0"
 typing-extensions = ">=4.4.0,<5.0.0"
 
@@ -4063,90 +4197,105 @@ rpds-py = ">=0.7.0"
 
 [[package]]
 name = "regex"
-version = "2024.7.24"
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 description = "Alternative regular expression module, to replace re."
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 python-versions = ">=3.8"
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 socks = ["PySocks (>=1.5.6,!=1.5.7)"]
 use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
 
+[[package]]
+name = "requests-toolbelt"
+version = "1.0.0"
+description = "A utility belt for advanced users of python-requests"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
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+
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+version = "13.9.1"
 description = "Render rich text, tables, progress bars, syntax highlighting, markdown and more to the terminal"
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-python-versions = ">=3.7.0"
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 [package.dependencies]
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 pygments = ">=2.13.0,<3.0.0"
+typing-extensions = {version = ">=4.0.0,<5.0", markers = "python_version < \"3.11\""}
 
 [package.extras]
 jupyter = ["ipywidgets (>=7.5.1,<9)"]
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 ]
 
 [[package]]
@@ -4360,121 +4524,121 @@ crt = ["botocore[crt] (>=1.33.2,<2.0a.0)"]
 
 [[package]]
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+version = "0.4.5"
 description = ""
 optional = true
 python-versions = ">=3.7"
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 torch = ["safetensors[numpy]", "torch (>=1.10)"]
 
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+
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+python-versions = "*"
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@@ -4542,19 +4784,19 @@ test = ["Cython", "array-api-strict (>=2.0)", "asv", "gmpy2", "hypothesis (>=6.3
 
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 name = "six"
@@ -4567,6 +4809,17 @@ files = [
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 ]
 
+[[package]]
+name = "smdebug-rulesconfig"
+version = "1.0.1"
+description = "SMDebug RulesConfig"
+optional = true
+python-versions = ">=2.7"
+files = [
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+
 [[package]]
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 version = "1.3.1"
@@ -4580,60 +4833,60 @@ files = [
 
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 [package.dependencies]
@@ -4714,13 +4967,13 @@ full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart (>=0.0.7
 
 [[package]]
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@@ -4743,6 +4996,17 @@ files = [
 [package.extras]
 widechars = ["wcwidth"]
 
+[[package]]
+name = "tblib"
+version = "3.0.0"
+description = "Traceback serialization library."
+optional = true
+python-versions = ">=3.8"
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 [package.dependencies]
@@ -4947,42 +5213,42 @@ testing = ["black (==22.3)", "datasets", "numpy", "pytest", "requests", "ruff"]
 
 [[package]]
 name = "tomli"
-version = "2.0.1"
+version = "2.0.2"
 description = "A lil' TOML parser"
 optional = false
-python-versions = ">=3.7"
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 ]
 
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 name = "torch"
-version = "2.4.0"
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 python-versions = ">=3.8.0"
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 ]
 
 [package.dependencies]
@@ -5001,6 +5267,7 @@ nvidia-cusolver-cu12 = {version = "11.4.5.107", markers = "platform_system == \"
 nvidia-cusparse-cu12 = {version = "12.1.0.106", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nccl-cu12 = {version = "2.20.5", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
 nvidia-nvtx-cu12 = {version = "12.1.105", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\""}
+setuptools = "*"
 sympy = "*"
 triton = {version = "3.0.0", markers = "platform_system == \"Linux\" and platform_machine == \"x86_64\" and python_version < \"3.13\""}
 typing-extensions = ">=4.8.0"
@@ -5066,13 +5333,13 @@ test = ["argcomplete (>=3.0.3)", "mypy (>=1.7.0)", "pre-commit", "pytest (>=7.0,
 
 [[package]]
 name = "transformers"
-version = "4.44.2"
+version = "4.45.1"
 description = "State-of-the-art Machine Learning for JAX, PyTorch and TensorFlow"
 optional = true
 python-versions = ">=3.8.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -5084,21 +5351,21 @@ pyyaml = ">=5.1"
 regex = "!=2019.12.17"
 requests = "*"
 safetensors = ">=0.4.1"
-tokenizers = ">=0.19,<0.20"
+tokenizers = ">=0.20,<0.21"
 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"]
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+accelerate = ["accelerate (>=0.26.0)"]
+agents = ["Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "datasets (!=2.5.0)", "diffusers", "opencv-python", "sentencepiece (>=0.1.91,!=0.1.92)", "torch"]
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 audio = ["kenlm", "librosa", "phonemizer", "pyctcdecode (>=0.4.0)"]
-benchmark = ["optimum-benchmark (>=0.2.0)"]
+benchmark = ["optimum-benchmark (>=0.3.0)"]
 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 (==0.5.1)", "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,<0.14.0)", "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 (==0.5.1)", "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,<0.14.0)", "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 (==0.5.1)", "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 (==0.5.1)", "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)"]
+deepspeed = ["accelerate (>=0.26.0)", "deepspeed (>=0.9.3)"]
+deepspeed-testing = ["GitPython (<3.1.19)", "accelerate (>=0.26.0)", "beautifulsoup4", "cookiecutter (==1.7.3)", "datasets (!=2.5.0)", "deepspeed (>=0.9.3)", "dill (<0.3.5)", "evaluate (>=0.2.0)", "faiss-cpu", "nltk (<=3.8.1)", "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 (==0.5.1)", "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 (>=0.26.0)", "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,<0.14.0)", "libcst", "librosa", "nltk (<=3.8.1)", "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)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "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 (>=0.20,<0.21)", "torch", "torchaudio", "torchvision", "unidic (>=1.0.2)", "unidic-lite (>=1.0.7)", "urllib3 (<2.0.0)"]
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+dev-torch = ["GitPython (<3.1.19)", "Pillow (>=10.0.1,<=15.0)", "accelerate (>=0.26.0)", "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", "libcst", "librosa", "nltk (<=3.8.1)", "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)", "rich", "rjieba", "rouge-score (!=0.0.7,!=0.0.8,!=0.1,!=0.1.1)", "ruff (==0.5.1)", "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 (>=0.20,<0.21)", "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"]
@@ -5109,7 +5376,7 @@ 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 (==0.5.1)", "urllib3 (<2.0.0)"]
+quality = ["GitPython (<3.1.19)", "datasets (!=2.5.0)", "isort (>=5.5.4)", "libcst", "rich", "ruff (==0.5.1)", "urllib3 (<2.0.0)"]
 ray = ["ray[tune] (>=2.7.0)"]
 retrieval = ["datasets (!=2.5.0)", "faiss-cpu"]
 ruff = ["ruff (==0.5.1)"]
@@ -5119,16 +5386,17 @@ 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 (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
+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 (<=3.8.1)", "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 (==0.5.1)", "sacrebleu (>=1.4.12,<2.0.0)", "sacremoses", "sentencepiece (>=0.1.91,!=0.1.92)", "tensorboard", "timeout-decorator"]
 tf = ["keras-nlp (>=0.3.1,<0.14.0)", "onnxconverter-common", "tensorflow (>2.9,<2.16)", "tensorflow-text (<2.16)", "tf2onnx"]
 tf-cpu = ["keras (>2.9,<2.16)", "keras-nlp (>=0.3.1,<0.14.0)", "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)"]
+tiktoken = ["blobfile", "tiktoken"]
 timm = ["timm (<=0.9.16)"]
-tokenizers = ["tokenizers (>=0.19,<0.20)"]
-torch = ["accelerate (>=0.21.0)", "torch"]
+tokenizers = ["tokenizers (>=0.20,<0.21)"]
+torch = ["accelerate (>=0.26.0)", "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)", "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)"]
+torchhub = ["filelock", "huggingface-hub (>=0.23.2,<1.0)", "importlib-metadata", "numpy (>=1.17)", "packaging (>=20.0)", "protobuf", "regex (!=2019.12.17)", "requests", "sentencepiece (>=0.1.91,!=0.1.92)", "tokenizers (>=0.20,<0.21)", "torch", "tqdm (>=4.27)"]
 video = ["av (==9.2.0)", "decord (==0.6.0)"]
 vision = ["Pillow (>=10.0.1,<=15.0)"]
 
@@ -5211,13 +5479,13 @@ types-cffi = "*"
 
 [[package]]
 name = "types-redis"
-version = "4.6.0.20240819"
+version = "4.6.0.20240903"
 description = "Typing stubs for redis"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-redis-4.6.0.20240819.tar.gz", hash = "sha256:08f51f550ad41d0152bd98d77ac9d6d8f761369121710a213642f6036b9a7183"},
-    {file = "types_redis-4.6.0.20240819-py3-none-any.whl", hash = "sha256:86db9af6f0033154e12bc22c77236cef0907b995fda8c9f0f0eacd59943ed2fc"},
+    {file = "types-redis-4.6.0.20240903.tar.gz", hash = "sha256:4bab1a378dbf23c2c95c370dfdb89a8f033957c4fd1a53fee71b529c182fe008"},
+    {file = "types_redis-4.6.0.20240903-py3-none-any.whl", hash = "sha256:0e7537e5c085fe96b7d468d5edae0cf667b4ba4b62c6e4a5dfc340bd3b868c23"},
 ]
 
 [package.dependencies]
@@ -5226,13 +5494,13 @@ types-pyOpenSSL = "*"
 
 [[package]]
 name = "types-requests"
-version = "2.32.0.20240712"
+version = "2.32.0.20240914"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-requests-2.32.0.20240712.tar.gz", hash = "sha256:90c079ff05e549f6bf50e02e910210b98b8ff1ebdd18e19c873cd237737c1358"},
-    {file = "types_requests-2.32.0.20240712-py3-none-any.whl", hash = "sha256:f754283e152c752e46e70942fa2a146b5bc70393522257bb85bd1ef7e019dcc3"},
+    {file = "types-requests-2.32.0.20240914.tar.gz", hash = "sha256:2850e178db3919d9bf809e434eef65ba49d0e7e33ac92d588f4a5e295fffd405"},
+    {file = "types_requests-2.32.0.20240914-py3-none-any.whl", hash = "sha256:59c2f673eb55f32a99b2894faf6020e1a9f4a402ad0f192bfee0b64469054310"},
 ]
 
 [package.dependencies]
@@ -5240,13 +5508,13 @@ urllib3 = ">=2"
 
 [[package]]
 name = "types-setuptools"
-version = "73.0.0.20240822"
+version = "75.1.0.20240917"
 description = "Typing stubs for setuptools"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "types-setuptools-73.0.0.20240822.tar.gz", hash = "sha256:3a060681098eb3fbc2fea0a86f7f6af6aa1ca71906039d88d891ea2cecdd4dbf"},
-    {file = "types_setuptools-73.0.0.20240822-py3-none-any.whl", hash = "sha256:b9eba9b68546031317a0fa506d4973641d987d74f79e7dd8369ad4f7a93dea17"},
+    {file = "types-setuptools-75.1.0.20240917.tar.gz", hash = "sha256:12f12a165e7ed383f31def705e5c0fa1c26215dd466b0af34bd042f7d5331f55"},
+    {file = "types_setuptools-75.1.0.20240917-py3-none-any.whl", hash = "sha256:06f78307e68d1bbde6938072c57b81cf8a99bc84bd6dc7e4c5014730b097dc0c"},
 ]
 
 [[package]]
@@ -5273,13 +5541,13 @@ files = [
 
 [[package]]
 name = "tzdata"
-version = "2024.1"
+version = "2024.2"
 description = "Provider of IANA time zone data"
 optional = true
 python-versions = ">=2"
 files = [
-    {file = "tzdata-2024.1-py2.py3-none-any.whl", hash = "sha256:9068bc196136463f5245e51efda838afa15aaeca9903f49050dfa2679db4d252"},
-    {file = "tzdata-2024.1.tar.gz", hash = "sha256:2674120f8d891909751c38abcdfd386ac0a5a1127954fbc332af6b5ceae07efd"},
+    {file = "tzdata-2024.2-py2.py3-none-any.whl", hash = "sha256:a48093786cdcde33cad18c2555e8532f34422074448fbc874186f0abd79565cd"},
+    {file = "tzdata-2024.2.tar.gz", hash = "sha256:7d85cc416e9382e69095b7bdf4afd9e3880418a2413feec7069d533d6b4e31cc"},
 ]
 
 [[package]]
@@ -5295,13 +5563,13 @@ files = [
 
 [[package]]
 name = "urllib3"
-version = "2.2.2"
+version = "2.2.3"
 description = "HTTP library with thread-safe connection pooling, file post, and more."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "urllib3-2.2.2-py3-none-any.whl", hash = "sha256:a448b2f64d686155468037e1ace9f2d2199776e17f0a46610480d311f73e3472"},
-    {file = "urllib3-2.2.2.tar.gz", hash = "sha256:dd505485549a7a552833da5e6063639d0d177c04f23bc3864e41e5dc5f612168"},
+    {file = "urllib3-2.2.3-py3-none-any.whl", hash = "sha256:ca899ca043dcb1bafa3e262d73aa25c465bfb49e0bd9dd5d59f1d0acba2f8fac"},
+    {file = "urllib3-2.2.3.tar.gz", hash = "sha256:e7d814a81dad81e6caf2ec9fdedb284ecc9c73076b62654547cc64ccdcae26e9"},
 ]
 
 [package.extras]
@@ -5312,13 +5580,13 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "virtualenv"
-version = "20.26.3"
+version = "20.26.6"
 description = "Virtual Python Environment builder"
 optional = false
 python-versions = ">=3.7"
 files = [
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 [package.dependencies]
@@ -5486,101 +5754,103 @@ files = [
 
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 [package.dependencies]
@@ -5589,18 +5859,22 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.20.0"
+version = "3.20.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.20.0-py3-none-any.whl", hash = "sha256:58da6168be89f0be59beb194da1250516fdaa062ccebd30127ac65d30045e10d"},
-    {file = "zipp-3.20.0.tar.gz", hash = "sha256:0145e43d89664cfe1a2e533adc75adafed82fe2da404b4bbb6b026c0157bdb31"},
+    {file = "zipp-3.20.2-py3-none-any.whl", hash = "sha256:a817ac80d6cf4b23bf7f2828b7cabf326f15a001bea8b1f9b49631780ba28350"},
+    {file = "zipp-3.20.2.tar.gz", hash = "sha256:bc9eb26f4506fda01b81bcde0ca78103b6e62f991b381fec825435c836edbc29"},
 ]
 
 [package.extras]
+check = ["pytest-checkdocs (>=2.4)", "pytest-ruff (>=0.2.1)"]
+cover = ["pytest-cov"]
 doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
+enabler = ["pytest-enabler (>=2.2)"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-ignore-flaky"]
+type = ["pytest-mypy"]
 
 [extras]
 anthropic = ["anthropic"]
@@ -5613,4 +5887,4 @@ groq = ["groq"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.10, <3.13"
-content-hash = "7fe3915e62b84f4f2f9d179958730907a2a6607e1de39ea77ab2f52a4cc93863"
+content-hash = "501f9b915b1cd8a46f3dafb184cb89ac52c28423c175e37b03c453742ad7a92a"
diff --git a/pyproject.toml b/pyproject.toml
index d67241321..937fb1259 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,11 +14,11 @@ openai = "^1.11.0"
 langchain = "~0.2.5"
 rich = "^13.6.0"
 PettingZoo = "1.24.3"
-redis-om = "^0.2.1"
+redis-om = "^0.3.1"
 gin-config = "^0.5.0"
 absl-py = "^2.0.0"
 together = "^0.2.4"
-pydantic = "1.10.17"
+pydantic = "^2.8.2"
 beartype = "^0.14.0"
 langchain-openai = "~0.1.8"
 litellm = ">=1.23.12,<1.41.0"
diff --git a/sotopia/agents/redis_agent.py b/sotopia/agents/redis_agent.py
index 7288fe282..1387f6380 100644
--- a/sotopia/agents/redis_agent.py
+++ b/sotopia/agents/redis_agent.py
@@ -141,9 +141,9 @@ async def aact(
                     return AgentAction(action_type="leave", argument="")
             action_string = sorted_message_list[-1][2]
             try:
-                action = AgentAction.parse_raw(action_string)
+                action = AgentAction.model_validate_json(action_string)
                 return action
-            except pydantic.error_wrappers.ValidationError:
+            except pydantic.ValidationError:
                 logging.warn(
                     "Failed to parse action string {}. Fall back to speak".format(
                         action_string
diff --git a/sotopia/database/annotators.py b/sotopia/database/annotators.py
index 203f22e74..c0b12e1f5 100644
--- a/sotopia/database/annotators.py
+++ b/sotopia/database/annotators.py
@@ -1,7 +1,7 @@
-from pydantic import Field
+from redis_om.model.model import Field
 from redis_om import JsonModel
 
 
 class Annotator(JsonModel):
-    name: str = Field(index=True, required=True)
-    email: str = Field(index=True, required=True)
+    name: str = Field(index=True)
+    email: str = Field(index=True)
diff --git a/sotopia/database/logs.py b/sotopia/database/logs.py
index 4f69d00b9..b3c5ff41e 100644
--- a/sotopia/database/logs.py
+++ b/sotopia/database/logs.py
@@ -1,6 +1,11 @@
-from typing import Any
+import sys
 
-from pydantic import root_validator
+if sys.version_info >= (3, 11):
+    from typing import Self
+else:
+    from typing_extensions import Self
+
+from pydantic import model_validator
 from redis_om import JsonModel
 from redis_om.model.model import Field
 
@@ -14,29 +19,21 @@ class EpisodeLog(JsonModel):
 
     environment: str = Field(index=True)
     agents: list[str] = Field(index=True)
-    tag: str | None = Field(index=True)
-    models: list[str] | None = Field(index=True)
+    tag: str | None = Field(index=True, default="")
+    models: list[str] | None = Field(index=True, default=[])
     messages: list[list[tuple[str, str, str]]]  # Messages arranged by turn
     reasoning: str
     rewards: list[tuple[float, dict[str, float]] | float]  # Rewards arranged by turn
     rewards_prompt: str
 
-    @root_validator(skip_on_failure=True)
-    def agent_number_message_number_reward_number_turn_number_match(
-        cls, values: Any
-    ) -> Any:
-        agents, _, _reasoning, rewards = (
-            values.get("agents"),
-            values.get("messages"),
-            values.get("reasoning"),
-            values.get("rewards"),
-        )
-        agent_number = len(agents)
+    @model_validator(mode="after")
+    def agent_number_message_number_reward_number_turn_number_match(self) -> Self:
+        agent_number = len(self.agents)
 
         assert (
-            len(rewards) == agent_number
-        ), f"Number of agents in rewards {len(rewards)} and agents {agent_number} do not match"
-        return values
+            len(self.rewards) == agent_number
+        ), f"Number of agents in rewards {len(self.rewards)} and agents {agent_number} do not match"
+        return self
 
     def render_for_humans(self) -> tuple[list[AgentProfile], list[str]]:
         """Generate a human readable version of the episode log.
diff --git a/sotopia/database/persistent_profile.py b/sotopia/database/persistent_profile.py
index 9ae99f695..0960947b2 100644
--- a/sotopia/database/persistent_profile.py
+++ b/sotopia/database/persistent_profile.py
@@ -1,7 +1,12 @@
 from enum import IntEnum
-from typing import Any
+import sys
 
-from pydantic import root_validator
+if sys.version_info >= (3, 11):
+    from typing import Self
+else:
+    from typing_extensions import Self
+
+from pydantic import model_validator
 from redis_om import JsonModel
 from redis_om.model.model import Field
 
@@ -87,15 +92,15 @@ class EnvironmentList(JsonModel):
     agent_index: list[str] | None = Field(default_factory=lambda: None)
 
     # validate the length of agent_index should be same as environments
-    @root_validator
-    def the_length_agent_index_matches_environments(cls, values: Any) -> Any:
+    @model_validator(mode="after")
+    def the_length_agent_index_matches_environments(self) -> Self:
         environments, agent_index = (
-            values.get("environments"),
-            values.get("agent_index"),
+            self.environments,
+            self.agent_index,
         )
         if agent_index is None:
-            return values
+            return self
         assert (
             len(environments) == len(agent_index)
         ), f"Number of environments {len(environments)} and agent_index {len(agent_index)} do not match"
-        return values
+        return self
diff --git a/sotopia/database/serialization.py b/sotopia/database/serialization.py
index cd10ef384..1fcc8b69e 100644
--- a/sotopia/database/serialization.py
+++ b/sotopia/database/serialization.py
@@ -2,7 +2,8 @@
 import json
 from typing import Any
 
-from pydantic import BaseModel, Field
+from pydantic import BaseModel
+from redis_om.model.model import Field
 
 from .env_agent_combo_storage import EnvAgentComboStorage
 from .logs import EpisodeLog
@@ -14,66 +15,66 @@
 
 
 class TwoAgentEpisodeWithScenarioBackgroundGoals(BaseModel):
-    episode_id: str = Field(required=True)
-    environment_id: str = Field(required=True)
-    agent_ids: list[str] = Field(required=True)
-    experiment_tag: str = Field(required=True)
-    experiment_model_name_pairs: list[str] = Field(required=True)
-    raw_messages: list[list[tuple[str, str, str]]] = Field(required=True)
-    raw_rewards: list[tuple[float, dict[str, float]] | float] = Field(required=True)
-    raw_rewards_prompt: str = Field(required=True)
-    scenario: str = Field(required=True)
-    codename: str = Field(required=True)
-    agents_background: dict[str, str] = Field(required=True)
-    social_goals: dict[str, str] = Field(required=True)
-    social_interactions: str = Field(required=True)
-    reasoning: str = Field(required=False)
-    rewards: list[tuple[float, dict[str, float]]] = Field(required=False)
+    episode_id: str = Field()
+    environment_id: str = Field()
+    agent_ids: list[str] = Field()
+    experiment_tag: str = Field()
+    experiment_model_name_pairs: list[str] = Field()
+    raw_messages: list[list[tuple[str, str, str]]] = Field()
+    raw_rewards: list[tuple[float, dict[str, float]] | float] = Field()
+    raw_rewards_prompt: str = Field()
+    scenario: str = Field()
+    codename: str = Field()
+    agents_background: dict[str, str] = Field()
+    social_goals: dict[str, str] = Field()
+    social_interactions: str = Field()
+    reasoning: str = Field()
+    rewards: list[tuple[float, dict[str, float]]] = Field()
 
 
 class AgentProfileWithPersonalInformation(BaseModel):
-    agent_id: str = Field(required=True)
-    first_name: str = Field(required=True)
-    last_name: str = Field(required=True)
-    age: int = Field(required=True)
-    occupation: str = Field(required=True)
-    gender: str = Field(required=True)
-    gender_pronoun: str = Field(required=True)
-    public_info: str = Field(required=True)
-    big_five: str = Field(required=True)
-    moral_values: list[str] = Field(required=True)
-    schwartz_personal_values: list[str] = Field(required=True)
-    personality_and_values: str = Field(required=True)
-    decision_making_style: str = Field(required=True)
-    secret: str = Field(required=True)
-    mbti: str = Field(required=True)
-    model_id: str = Field(required=True)
+    agent_id: str = Field()
+    first_name: str = Field()
+    last_name: str = Field()
+    age: int = Field()
+    occupation: str = Field()
+    gender: str = Field()
+    gender_pronoun: str = Field()
+    public_info: str = Field()
+    big_five: str = Field()
+    moral_values: list[str] = Field()
+    schwartz_personal_values: list[str] = Field()
+    personality_and_values: str = Field()
+    decision_making_style: str = Field()
+    secret: str = Field()
+    mbti: str = Field()
+    model_id: str = Field()
 
 
 class EnvironmentProfileWithTwoAgentRequirements(BaseModel):
-    env_id: str = Field(required=True)
-    codename: str = Field(required=True)
-    source: str = Field(required=True)
-    scenario: str = Field(required=True)
-    agent_goals: list[str] = Field(required=True)
-    relationship: str = Field(required=True)
-    age_constraint: str = Field(required=True)
-    occupation_constraint: str = Field(required=True)
-    agent_constraint: str | None = Field(required=False)
+    env_id: str = Field()
+    codename: str = Field()
+    source: str = Field()
+    scenario: str = Field()
+    agent_goals: list[str] = Field()
+    relationship: str = Field()
+    age_constraint: str = Field()
+    occupation_constraint: str = Field()
+    agent_constraint: str | None = Field()
 
 
 class RelationshipProfileBetweenTwoAgents(BaseModel):
-    relationship_id: str = Field(required=True)
-    agent1_id: str = Field(required=True)
-    agent2_id: str = Field(required=True)
-    relationship: str = Field(required=True)
-    background_story: str = Field(required=True)
+    relationship_id: str = Field()
+    agent1_id: str = Field()
+    agent2_id: str = Field()
+    relationship: str = Field()
+    background_story: str = Field()
 
 
 class EnvAgentComboStorageWithID(BaseModel):
-    combo_id: str = Field(default_factory=lambda: "", index=True)
-    env_id: str = Field(default_factory=lambda: "", index=True)
-    agent_ids: list[str] = Field(default_factory=lambda: [], index=True)
+    combo_id: str = Field(default="", index=True)
+    env_id: str = Field(default="", index=True)
+    agent_ids: list[str] = Field(default=[], index=True)
 
 
 def _map_gender_to_adj(gender: str) -> str:
diff --git a/sotopia/database/session_transaction.py b/sotopia/database/session_transaction.py
index ca1ad05f1..b31c55cc2 100644
--- a/sotopia/database/session_transaction.py
+++ b/sotopia/database/session_transaction.py
@@ -1,4 +1,4 @@
-from pydantic import validator
+from pydantic import field_validator
 from redis_om import EmbeddedJsonModel, JsonModel
 from redis_om.model.model import Field
 
@@ -30,7 +30,7 @@ class SessionTransaction(AutoExpireMixin, JsonModel):
     """
     )
 
-    @validator("message_list")
+    @field_validator("message_list")
     def validate_message_list(
         cls, v: list[MessageTransaction]
     ) -> list[MessageTransaction]:
diff --git a/sotopia/envs/evaluators.py b/sotopia/envs/evaluators.py
index 848e9e626..9afeac181 100644
--- a/sotopia/envs/evaluators.py
+++ b/sotopia/envs/evaluators.py
@@ -1,14 +1,12 @@
 import abc
 import logging
 from collections import defaultdict
-from typing import Generic, TypeVar
-
-from pydantic.generics import GenericModel
+from typing import Generic, TypeVar, Annotated
 
 import gin
 from beartype import beartype
 from langchain.output_parsers import PydanticOutputParser
-from pydantic import BaseModel, Field, validator
+from pydantic import AfterValidator, BaseModel, Field
 
 from sotopia.generation_utils.generate import agenerate
 from sotopia.messages import (
@@ -20,16 +18,38 @@
 log = logging.getLogger("evaluators")
 
 
+def zero_to_ten(v: int) -> int:
+    if v < 0 or v > 10:
+        raise ValueError("The value should be between 0 and 10")
+    return v
+
+
+def minus_five_to_five(v: int) -> int:
+    if v < -5 or v > 5:
+        raise ValueError("The value should be between -5 and 5")
+    return v
+
+
+def minus_ten_to_zero(v: int) -> int:
+    if v < -10 or v > 0:
+        raise ValueError("The value should be between -10 and 0")
+    return v
+
+
 class SotopiaDimensions(BaseModel):
     """The social dimensions used in Sotopia paper (ICLR 2024)"""
 
-    believability: tuple[str, int] = Field(
+    believability: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Reasoning requirement: 1. Evaluate if the agent interacts with others in a natural and realistic manner (here are a few common questions to check: a. whether the agent is confusing with its own identity? b. whether the agent repeats others' words/actions without any reason? c. whether the agent is being overly polite considering the context?). Start the analysis with tag <naturalness> "
         "2. Analyze whether the actions of the agent align with their character traits (e.g., personality, values, and etc.). Start the analysis with tag <consistency>. "
         "Output your reasoning process to the 'reasoning' field. Output an integer score ranging from 0 and 10 in the 'score' field. A higher score indicates that the agent is more believable.",
     )
-    relationship: tuple[str, int] = Field(
+    relationship: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_five_to_five(x[1])))
+    ] = Field(
         ...,
         description="Please first analyze what relationship the participant has with the other agent(s) before the interaction. "
         "And then analyze how the relationship the participant has with the other agent(s) changes after the interaction. "
@@ -37,14 +57,18 @@ class SotopiaDimensions(BaseModel):
         "Additionally, ascertain whether these interactions also impact their social status or reputation. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from -5 to 5 in the 'score' field. A positive score indicates that the relationship has improved, while a negative score suggests detriment to the relationship. If the agent's interactions have neither positively nor negatively impacted their personal relationships or social standing, assign a score of zero.",
     )
-    knowledge: tuple[str, int] = Field(
+    knowledge: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Please first assess what information the agent has gained through the interaction. "
         "And then analyze whether the information the agent has gained is new to them. "
         "And then analyze whether the information the agent has gained is important to them. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from 0 and 10 in the 'score' field. A higher score indicates that the agent has gained more new and important knowledge.",
     )
-    secret: tuple[str, int] = Field(
+    secret: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_ten_to_zero(x[1])))
+    ] = Field(
         ...,
         description="First please analyze what secret or secretive intention the participant wants to keep. "
         "And then analyze whether they keep it successfully. Analyze what secrets, private information, "
@@ -52,49 +76,44 @@ class SotopiaDimensions(BaseModel):
         "Please output the reasoning in the reasoning field. "
         "Give an integer score ranging from -10 to 0 (-10 indicates participant leaks critical secrets/intentions, 0 indicates no secret/intention is revealed)",
     )
-    social_rules: tuple[str, int] = Field(
+    social_rules: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_ten_to_zero(x[1])))
+    ] = Field(
         ...,
         description="Please evaluate whether the agent violates any moral rules or laws in their interactions with others. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from -10 and 0 in the 'score' field. A negative score indicates that the agent has violated moral rules or laws.",
     )
-    financial_and_material_benefits: tuple[str, int] = Field(
+    financial_and_material_benefits: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_five_to_five(x[1])))
+    ] = Field(
         ...,
         description="Please evaluate whether the agent's interactions with others contribute towards financial and material benefits. Analyze what the agent would gain/lose after the interactions. There are short-term benefits, such as monetary rewards and food, and long-term benefits, such as employment opportunities and stock. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from -5 and 5 in the 'score' field. Positive indicates financial and material benefits gain, while negative indicates loss",
     )
-    goal: tuple[str, int] = Field(
+    goal: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Please first reiterate agent's social goals. "
         "And then please provide a comprehensive analysis about the extent to which the agent has managed to achieve these goals. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from 0 and 10 in the 'score' field. 0 represents minimal goals achievement, 10 represents complete goal achievement, and a higher score indicates that the agent is making progress towards their social goals.",
     )
 
-    @validator("believability", "knowledge", "goal", allow_reuse=True)
-    def zero_to_ten_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= 0 and v[1] <= 10
-        return v
-
-    @validator("relationship", "financial_and_material_benefits", allow_reuse=True)
-    def minus_five_to_five_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= -5 and v[1] <= 5
-        return v
-
-    @validator("secret", "social_rules", allow_reuse=True)
-    def minus_ten_to_zero_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= -10 and v[1] <= 0
-        return v
-
 
 class SotopiaDimensionsPlus(BaseModel):
     """Updated SotopiaDimensions with more detailed instructions"""
 
-    believability: tuple[str, int] = Field(
+    believability: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Reasoning requirement: 1. Evaluate if the agent interacts with others in a natural and realistic manner (here are a few common questions to check: a. whether the agent is confusing with its own identity? b. whether the agent repeats others' words/actions without any reason? c. whether the agent is being overly polite considering the context?). Start the analysis with tag <naturalness> "
         "2. Analyze whether the actions of the agent align with their character traits (e.g., personality, values, and etc.). Start the analysis with tag <consistency>. "
         "Output your reasoning process to the 'reasoning' field. Output an integer score ranging from 0 and 10 in the 'score' field. A higher score indicates that the agent is more believable. Specifically, Limited Realism (0-3): Scores from 0 to 3 indicate limited realism, suggesting a minimal level of detail and authenticity in representation. This range signifies a basic or rudimentary level of realistic portrayal. Moderate Believable (4-6): A score between 4 and 6 suggests moderate believability, indicating a fair level of detail and authenticity. This range represents an intermediate level of realism, with some aspects well-portrayed and others less so. Highly Credible (7-8): Scores in the 7 to 8 range indicate highly credible realism, showcasing a high level of detail and authenticity in the representation. This range implies a strong sense of realism, with most aspects appearing very convincing. Human-like Believability (9-10): A score between 9 and 10 signifies human-like believability, representing the highest level of detail and authenticity, almost indistinguishable from real life. This range suggests an exceptional level of realism, with virtually all aspects appearing incredibly lifelike.",
     )
-    relationship: tuple[str, int] = Field(
+    relationship: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_five_to_five(x[1])))
+    ] = Field(
         ...,
         description="Please first analyze what relationship the participant has with the other agent(s) before the interaction. "
         "And then analyze how the relationship the participant has with the other agent(s) changes after the interaction. "
@@ -102,14 +121,18 @@ class SotopiaDimensionsPlus(BaseModel):
         "Additionally, ascertain whether these interactions also impact their social status or reputation. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from -5 to 5 in the 'score' field. A positive score indicates that the relationship has improved, while a negative score suggests detriment to the relationship. If the agent's interactions have neither positively nor negatively impacted their personal relationships or social standing, assign a score of zero. Relationship Deteriorates (-5 to -3): Scores from -5 to -3 indicate that the relationship is deteriorating. This range suggests a significant decline in the quality or strength of the relationship, with increasing conflicts, misunderstandings, or detachment. Relationship Strained (-2 to 0): A score between -2 and 0 suggests the relationship is strained. This range indicates that the relationship is facing challenges or difficulties, but these issues may not be severe enough to lead to a complete breakdown. The relationship is under stress but not entirely negative. Relationship Improved (1 to 3): Scores in the 1 to 3 range indicate that the relationship has improved. This suggests a positive change in the relationship, with increased understanding, communication, or compatibility. The relationship is getting stronger and more positive. Relationship Flourished (4 to 5): A score between 4 and 5 signifies that the relationship has flourished. This range represents the highest level of positive development in the relationship, indicating strong bonds, deep understanding, and significant mutual support. The relationship is thriving and at its best.",
     )
-    knowledge: tuple[str, int] = Field(
+    knowledge: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Please first assess what information the agent has gained through the interaction. "
         "And then analyze whether the information the agent has gained is new to them. "
         "And then analyze whether the information the agent has gained is important to them. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from 0 and 10 in the 'score' field. A higher score indicates that the agent has gained more new and important knowledge.Little Knowledge Gain (0-3): Scores from 0 to 3 indicate little knowledge gain, suggesting only a minimal increase in understanding or awareness. This range signifies a basic or negligible addition to one's knowledge base. Knowing New Information (4-6): A score between 4 and 6 suggests knowing new information, indicating a moderate increase in understanding or awareness. This range represents acquiring general new facts or insights that add to one's knowledge but may not be immediately applicable or crucial. Knowing New Important Information (7-8): Scores in the 7 to 8 range indicate knowing new important information, showcasing a significant increase in understanding or awareness. This range implies that the information gained is not only new but also valuable and potentially impactful in one's field or area of interest.Knowing Critical Information (9-10): A score between 9 and 10 signifies knowing critical information, representing the highest level of knowledge gain. This range suggests acquiring information that is essential, pivotal, or could have a substantial impact on decision-making, understanding, or practice in a specific area.",
     )
-    secret: tuple[str, int] = Field(
+    secret: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_ten_to_zero(x[1])))
+    ] = Field(
         ...,
         description="First please analyze what secret or secretive intention the participant wants to keep. "
         "And then analyze whether they keep it successfully. Analyze what secrets, private information, "
@@ -117,59 +140,47 @@ class SotopiaDimensionsPlus(BaseModel):
         "Please output the reasoning in the reasoning field. "
         "Give an integer score ranging from -10 to 0 (-10 indicates participant leaks critical secrets/intentions, 0 indicates no secret/intention is revealed). Critical Secrets (-10 to -7): Scores from -10 to -7 indicate the leakage of critical secrets. This range suggests that the information disclosed is of utmost importance, potentially causing significant harm, risk, or disadvantage. The secrets are highly sensitive and could have severe implications. Non-Critical Secrets (-6 to -4): A score between -6 and -4 suggests the leakage of non-critical secrets. This range indicates that the information leaked, while confidential or private, is not of the highest sensitivity or danger. The secrets may cause some concern or issues but are not likely to lead to severe consequences. Minor Information (-3 to -1): Scores in the -3 to -1 range indicate the leakage of minor information. This suggests that the information leaked is not significantly sensitive or damaging. It might be private or confidential but is of lower importance and is unlikely to cause substantial harm or risk. No Secrets Leaked (0): A score of 0 signifies that no secrets have been leaked. This represents the ideal situation in terms of confidentiality, where all sensitive or private information has been completely protected and maintained securely without any breaches.",
     )
-    social_rules: tuple[str, int] = Field(
+    social_rules: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_ten_to_zero(x[1])))
+    ] = Field(
         ...,
         description="Please evaluate whether the agent violates any moral rules or laws in their interactions with others. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from -10 and 0 in the 'score' field. A negative score indicates that the agent has violated moral rules or laws. Law Breaking (-10 to -8): Scores from -10 to -8 indicate law-breaking actions. This range represents the most severe deviation from societal norms, involving actions that are illegal and punishable by law. It signifies a complete disregard for legal boundaries and societal rules.Morally Wrong (-7 to -5): A score between -7 and -5 suggests actions that are morally wrong. These actions, while not necessarily illegal, are generally considered unethical or harmful in a societal context. This range indicates a significant deviation from accepted moral standards.Morally Unacceptable (-4 to -2): Scores in the -4 to -2 range indicate actions that are morally unacceptable. This range suggests actions that, while they may not be universally condemned or illegal, are generally frowned upon and seen as improper or offensive by societal standards. Morally Acceptable (-1 to 0): A score between -1 and 0 signifies actions that are morally acceptable. This range indicates adherence to societal norms and moral standards. Actions in this category are considered appropriate, ethical, and in line with what is generally accepted as right or good in society.",
     )
-    financial_and_material_benefits: tuple[str, int] = Field(
+    financial_and_material_benefits: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], minus_five_to_five(x[1])))
+    ] = Field(
         ...,
         description="Please evaluate whether the agent's interactions with others contribute towards financial and material benefits. Analyze what the agent would gain/lose after the interactions. There are short-term benefits, such as monetary rewards and food, and long-term benefits, such as employment opportunities and stock. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from -5 and 5 in the 'score' field. Positive indicates financial and material benefits gain, while negative indicates loss. Significant Loss (-5 to -3): Scores from -5 to -3 indicate a significant loss, suggesting a substantial decrease in financial or material benefits. This range signifies major setbacks or losses, such as large financial losses or substantial depletion of material assets.Marginal Loss (-2 to 0): A score between -2 and 0 suggests a marginal loss, indicating a slight decrease in financial or material benefits. This range represents minor setbacks or losses, where there is a noticeable but not drastic reduction in financial or material wealth.Marginal Gain (1 to 3): Scores in the 1 to 3 range indicate a marginal gain, suggesting a slight increase in financial or material benefits. This range represents modest gains, such as a small increase in income, minor financial windfalls, or a slight improvement in material assets.Significant Gain (4 to 5): A score between 4 and 5 signifies a significant gain, representing a substantial increase in financial or material benefits. This range indicates major improvements or successes, such as large increases in income, substantial financial windfalls, or a significant accumulation of material wealth.",
     )
-    goal: tuple[str, int] = Field(
+    goal: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Please first reiterate agent's social goals. "
         "And then please provide a comprehensive analysis about the extent to which the agent has managed to achieve these goals. "
         "In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from 0 and 10 in the 'score' field. 0 represents minimal goals achievement, 10 represents complete goal achievement, and a higher score indicates that the agent is making progress towards their social goals. Almost Not Finishing Any Goal (0-3): Scores from 0 to 3 indicate almost not finishing any goal, suggesting a minimal level of goal achievement. This range signifies either no progress or only a very rudimentary level of advancement towards the completion of set goals. Finishing Less Than 50% of Goals (4-6): A score between 4 and 6 suggests finishing less than 50% of the goals, indicating a moderate level of goal completion. This range represents partial success, with some goals being met while a significant portion remains unachieved. Finishing More Than 50%, But Not All Goals (7-8): Scores in the 7 to 8 range indicate finishing more than 50% but not all of the goals. This suggests a high level of achievement, where the majority of set goals are met, but some goals still remain incomplete. Finishing All Goals (9-10): A score between 9 and 10 signifies finishing all goals, representing the highest level of achievement in goal completion. This range indicates that all set objectives have been met, signifying complete success in achieving the targeted goals.",
     )
 
-    @validator("believability", "knowledge", "goal", allow_reuse=True)
-    def zero_to_ten_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= 0 and v[1] <= 10
-        return v
-
-    @validator("relationship", "financial_and_material_benefits", allow_reuse=True)
-    def minus_five_to_five_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= -5 and v[1] <= 5
-        return v
-
-    @validator("secret", "social_rules", allow_reuse=True)
-    def minus_ten_to_zero_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= -10 and v[1] <= 0
-        return v
-
 
 class GoalDimension(BaseModel):
     """Goal only evaluation"""
 
-    goal: tuple[str, int] = Field(
+    goal: Annotated[
+        tuple[str, int], AfterValidator(lambda x: (x[0], zero_to_ten(x[1])))
+    ] = Field(
         ...,
         description="Please first reiterate agent's social goals. "
         "And then please provide a comprehensive analysis about the extent to which the agent has managed to achieve these goals. "
         "The first entry (str) of the object is the 'reasoning' field, and the second entry (int) of the object is the 'score' field. In the 'reasoning' field, provide a comprehensive account of the logic or thought process that led you to your conclusion. Further, provide an integer score ranging from 0 and 10 in the 'score' field. 0 represents minimal goals achievement, 10 represents complete goal achievement, and a higher score indicates that the agent is making progress towards their social goals.",
     )
 
-    @validator("goal", allow_reuse=True)
-    def zero_to_ten_validator(cls, v: tuple[str, int]) -> tuple[str, int]:
-        assert v[1] >= 0 and v[1] <= 10
-        return v
-
 
 T_eval_dim = TypeVar("T_eval_dim", bound=BaseModel)
 
 
-class EvaluationForTwoAgents(GenericModel, Generic[T_eval_dim]):
+class EvaluationForTwoAgents(BaseModel, Generic[T_eval_dim]):
     agent_1_evaluation: T_eval_dim
     agent_2_evaluation: T_eval_dim
 
diff --git a/sotopia/generation_utils/generate.py b/sotopia/generation_utils/generate.py
index f9d1e9240..369cf5890 100644
--- a/sotopia/generation_utils/generate.py
+++ b/sotopia/generation_utils/generate.py
@@ -20,6 +20,7 @@
 from langchain.schema import BaseOutputParser, OutputParserException
 from langchain_openai import ChatOpenAI, AzureChatOpenAI
 from pydantic import BaseModel, Field
+from pydantic.v1 import SecretStr
 from rich import print
 from typing_extensions import Literal
 
@@ -71,7 +72,7 @@ class EnvResponse(BaseModel):
 
 
 class EnvResponsePydanticOutputParser(PydanticOutputParser[EnvResponse]):
-    def __init__(self, pydantic_object: Type[BaseModel] = EnvResponse) -> None:
+    def __init__(self, pydantic_object: Type[EnvResponse] = EnvResponse) -> None:
         super(EnvResponsePydanticOutputParser, self).__init__(
             pydantic_object=pydantic_object
         )
@@ -322,23 +323,29 @@ def obtain_chain(
         model_name = _return_fixed_model_version(model_name)
     if model_name.startswith("together_ai"):
         model_name = "/".join(model_name.split("/")[1:])
+        assert (
+            TOGETHER_API_KEY := os.environ.get("TOGETHER_API_KEY")
+        ), "TOGETHER_API_KEY is not set"
         chat_openai = ChatOpenAI(
-            model_name=model_name,
+            name=model_name,
             temperature=temperature,
             max_retries=max_retries,
-            openai_api_base="https://api.together.xyz/v1",
-            openai_api_key=os.environ.get("TOGETHER_API_KEY"),
+            base_url="https://api.together.xyz/v1",
+            api_key=SecretStr(TOGETHER_API_KEY),
         )
         chain = chat_prompt_template | chat_openai
         return chain
     elif model_name.startswith("groq"):
         model_name = "/".join(model_name.split("/")[1:])
+        assert (
+            GROQ_API_KEY := os.environ.get("GROQ_API_KEY")
+        ), "GROQ_API_KEY is not set"
         chat_openai = ChatOpenAI(
-            model_name=model_name,
+            name=model_name,
             temperature=temperature,
             max_retries=max_retries,
-            openai_api_base="https://api.groq.com/openai/v1",
-            openai_api_key=os.environ.get("GROQ_API_KEY"),
+            base_url="https://api.groq.com/openai/v1",
+            api_key=SecretStr(GROQ_API_KEY),
         )
         chain = chat_prompt_template | chat_openai
         return chain
@@ -352,7 +359,7 @@ def obtain_chain(
         )
         chat_azure_openai = AzureChatOpenAI(
             azure_deployment=deployment_name,
-            openai_api_version=azure_version,
+            api_version=azure_version,
             azure_endpoint=f"https://{resource_name}.openai.azure.com",
             temperature=temperature,
             max_retries=max_retries,
@@ -369,9 +376,11 @@ def obtain_chain(
             model=custom_model_name,
             temperature=temperature,
             max_retries=max_retries,
-            api_key=os.environ.get("CUSTOM_API_KEY")
-            if os.environ.get("CUSTOM_API_KEY")
-            else "EMPTY",
+            api_key=SecretStr(
+                CUSTOM_API_KEY
+                if (CUSTOM_API_KEY := os.environ.get("CUSTOM_API_KEY"))
+                else "EMPTY"
+            ),
             base_url=model_base_url,
         )
         human_message_prompt = HumanMessagePromptTemplate(
diff --git a/sotopia/generation_utils/llama2.py b/sotopia/generation_utils/llama2.py
deleted file mode 100644
index 5c88728ec..000000000
--- a/sotopia/generation_utils/llama2.py
+++ /dev/null
@@ -1,184 +0,0 @@
-from __future__ import annotations
-
-import logging
-from typing import Any, Dict, List, Mapping, Optional, Tuple, cast
-
-import together
-from langchain.callbacks.manager import (
-    AsyncCallbackManagerForLLMRun,
-    CallbackManagerForLLMRun,
-)
-from langchain.chat_models.base import BaseChatModel
-from langchain.schema import (
-    AIMessage,
-    BaseMessage,
-    ChatGeneration,
-    ChatMessage,
-    ChatResult,
-    HumanMessage,
-    SystemMessage,
-)
-from langchain.utils import get_from_dict_or_env
-from pydantic import Extra, root_validator
-
-
-def _convert_message_to_dict(message: BaseMessage) -> dict[str, Any]:
-    if isinstance(message, ChatMessage):
-        message_dict = {"role": message.role, "content": message.content}
-    elif isinstance(message, HumanMessage):
-        message_dict = {"role": "user", "content": message.content}
-    elif isinstance(message, AIMessage):
-        message_dict = {"role": "assistant", "content": message.content}
-    elif isinstance(message, SystemMessage):
-        message_dict = {"role": "system", "content": message.content}
-    else:
-        raise ValueError(f"Got unknown type {message}")
-    if "name" in message.additional_kwargs:
-        message_dict["name"] = message.additional_kwargs["name"]
-    return message_dict
-
-
-def _convert_dict_to_message(_dict: dict[str, str]) -> BaseMessage:
-    text = _dict["text"]
-    return AIMessage(content=text)
-
-
-def _make_prompt_from_dict(dialog: List[dict[str, str]]) -> str:
-    """
-    Follow chat format in https://docs.together.ai/docs/python-chat
-    example: together complete "<human>: List the best restaurants in SF\n<bot>: "
-    python example: together.Complete.create(prompt=(above), model=model_name)
-    The convertion is similar to llama2 official, EXCEPT not using special tags:
-    https://github.com/facebookresearch/llama/blob/main/example_chat_completion.py
-    """
-    user_tag = "<human>"
-    assistant_tag = "<bot>"
-    tag_sep = ": "
-    conv_sep = "\n"
-
-    if dialog[0]["role"] == "system":
-        dialog = [
-            {
-                "role": dialog[1]["role"],
-                "content": dialog[0]["content"] + conv_sep + dialog[1]["content"],
-            }
-        ] + dialog[2:]
-    assert all([msg["role"] == "user" for msg in dialog[::2]]) and all(
-        [msg["role"] == "assistant" for msg in dialog[1::2]]
-    ), (
-        "model only supports 'system', 'user' and 'assistant' roles, "
-        "starting with 'system', then 'user' and alternating (u/a/u/a/u...)"
-    )
-    ret = ""
-    for d in dialog:
-        tt = user_tag
-        if d["role"] == "user":
-            tt = user_tag
-        elif d["role"] == "assistant":
-            tt = assistant_tag
-        ret += tt + tag_sep + d["content"].strip() + conv_sep
-    ret += assistant_tag + tag_sep
-    return ret
-
-
-logger = logging.getLogger(__name__)
-
-
-class Llama2(BaseChatModel):
-    client: type[together.Complete] = together.Complete  #: :meta private:
-    model_name: str = "togethercomputer/llama-2-7b-chat"
-    """Model name to use."""
-    # default Together params
-    temperature: float = 0.7
-    max_tokens: int = 1024
-    top_p: float = 0.7
-    top_k: int = 50
-    repetition_penalty: float = 1.0
-    start: bool = False
-    _llm_type: str = "llama2"
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.ignore
-
-    @root_validator(pre=True)
-    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
-        """Build extra kwargs from additional params that were passed in."""
-        all_required_field_names = {field.alias for field in cls.__fields__.values()}
-
-        extra = values.get("model_kwargs", {})
-        for field_name in list(values):
-            if field_name not in all_required_field_names:
-                if field_name in extra:
-                    raise ValueError(f"Found {field_name} supplied twice.")
-                extra[field_name] = values.pop(field_name)
-        values["model_kwargs"] = extra
-        return values
-
-    @root_validator()
-    def validate_environment(cls, values: Dict[str, Any]) -> Dict[str, Any]:
-        together_api_key = get_from_dict_or_env(
-            values, "together_api_key", "TOGETHER_API_KEY"
-        )
-        together.api_key = together_api_key
-        values["client"] = together.Complete
-        return values
-
-    def _generate(
-        self,
-        messages: List[BaseMessage],
-        stop: Optional[List[str]] = None,
-        run_manager: Optional[CallbackManagerForLLMRun] = None,
-        **kwargs: Any,
-    ) -> ChatResult:
-        prompt, params = self._create_message_dicts(messages, stop)
-        response = self.client.create(prompt=prompt, **params)
-        chat_result = self._create_chat_result(response)
-        return chat_result
-
-    @property
-    def _default_params(self) -> Dict[str, Any]:
-        """Get the default parameters for calling Together API."""
-        return {
-            "model": self.model_name,
-            "max_tokens": self.max_tokens,
-            "temperature": self.temperature,
-            "top_p": self.top_p,
-            "top_k": self.top_k,
-            "repetition_penalty": self.repetition_penalty,
-        }
-
-    def _create_message_dicts(
-        self, messages: List[BaseMessage], stop: Optional[List[str]]
-    ) -> Tuple[str, Dict[str, Any]]:
-        params: Dict[str, Any] = {
-            **{"model": self.model_name},
-            **self._default_params,
-        }
-        if stop is not None:
-            if "stop" in params:
-                raise ValueError("`stop` found in both the input and default params.")
-            params["stop"] = stop
-        message_dicts = [_convert_message_to_dict(m) for m in messages]
-        message_prompt = _make_prompt_from_dict(message_dicts)
-        return message_prompt, params
-
-    def _create_chat_result(self, response: Mapping[str, Any]) -> ChatResult:
-        generations = []
-        for res in response["output"]["choices"]:
-            message = _convert_dict_to_message(res)
-            gen = ChatGeneration(message=message)
-            generations.append(gen)
-        llm_output = {"model_name": self.model_name}
-        return ChatResult(generations=generations, llm_output=llm_output)
-
-    async def _agenerate(
-        self,
-        messages: List[BaseMessage],
-        stop: List[str] | None = None,
-        run_manager: AsyncCallbackManagerForLLMRun | None = None,
-        **kwargs: Any,
-    ) -> ChatResult:
-        sync_run_manager = cast(CallbackManagerForLLMRun, run_manager)
-        return self._generate(messages, stop, sync_run_manager)
diff --git a/sotopia/renderers/base.py b/sotopia/renderers/base.py
index 7a56dfbdc..3d2b509da 100644
--- a/sotopia/renderers/base.py
+++ b/sotopia/renderers/base.py
@@ -1,4 +1,4 @@
-from pydantic import BaseModel, Field, validator
+from pydantic import BaseModel, Field, field_validator
 
 
 class RenderContext(BaseModel):
@@ -17,7 +17,7 @@ class RenderContext(BaseModel):
         default=[], description="The special tags to render."
     )
 
-    @validator("viewer")
+    @field_validator("viewer")
     def viewer_must_be_valid(cls, v: str) -> str:
         if v.startswith("agent_"):
             try:
diff --git a/stubs/redis_om/__init__.pyi b/stubs/redis_om/__init__.pyi
index 038ca7ac4..abbae6f43 100644
--- a/stubs/redis_om/__init__.pyi
+++ b/stubs/redis_om/__init__.pyi
@@ -1,8 +1,9 @@
 import abc
 from typing import Any, Generator, TypeVar
 
-from pydantic import BaseModel, Field
-from pydantic.main import ModelMetaclass
+from pydantic import BaseModel
+from redis_om.model.model import Field
+from pydantic._internal._model_construction import ModelMetaclass
 from redis_om.model.model import FindQuery
 
 InheritedJsonModel = TypeVar("InheritedJsonModel", bound="JsonModel")
diff --git a/stubs/redis_om/model/model.pyi b/stubs/redis_om/model/model.pyi
index 957c16e46..f2e70227f 100644
--- a/stubs/redis_om/model/model.pyi
+++ b/stubs/redis_om/model/model.pyi
@@ -1,7 +1,8 @@
 from typing import AbstractSet, Any, Dict, Mapping, Optional, Union
 
-from pydantic.fields import Undefined, UndefinedType
-from pydantic.typing import NoArgAnyCallable
+from pydantic_core import PydanticUndefined as Undefined
+from pydantic_core import PydanticUndefinedType as UndefinedType
+from pydantic.v1.typing import NoArgAnyCallable
 from redis_om import JsonModel
 
 class NotFoundError(Exception):