diff --git a/poetry.lock b/poetry.lock
index 9bff30e7..5038cde2 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,31 @@
-# This file is automatically @generated by Poetry 2.1.2 and should not be changed by hand.
+# This file is automatically @generated by Poetry 2.1.3 and should not be changed by hand.
+
+[[package]]
+name = "ag-ui-protocol"
+version = "0.1.10"
+description = ""
+optional = false
+python-versions = "<4.0,>=3.9"
+groups = ["main"]
+files = [
+    {file = "ag_ui_protocol-0.1.10-py3-none-any.whl", hash = "sha256:c81e6981f30aabdf97a7ee312bfd4df0cd38e718d9fc10019c7d438128b93ab5"},
+    {file = "ag_ui_protocol-0.1.10.tar.gz", hash = "sha256:3213991c6b2eb24bb1a8c362ee270c16705a07a4c5962267a083d0959ed894f4"},
+]
+
+[package.dependencies]
+pydantic = ">=2.11.2,<3.0.0"
+
+[[package]]
+name = "aiofiles"
+version = "24.1.0"
+description = "File support for asyncio."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5"},
+    {file = "aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c"},
+]
 
 [[package]]
 name = "aiohappyeyeballs"
@@ -182,19 +209,20 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.51.0"
+version = "0.72.1"
 description = "The official Python library for the anthropic API"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "anthropic-0.51.0-py3-none-any.whl", hash = "sha256:b8b47d482c9aa1f81b923555cebb687c2730309a20d01be554730c8302e0f62a"},
-    {file = "anthropic-0.51.0.tar.gz", hash = "sha256:6f824451277992af079554430d5b2c8ff5bc059cc2c968cdc3f06824437da201"},
+    {file = "anthropic-0.72.1-py3-none-any.whl", hash = "sha256:81e73cca55e8924776c8c4418003defe6bf9eaf0cd92beb94c8dbf537b95316f"},
+    {file = "anthropic-0.72.1.tar.gz", hash = "sha256:a6d1d660e1f4af91dddc732f340786d19acaffa1ae8e69442e56be5fa6539d51"},
 ]
 
 [package.dependencies]
 anyio = ">=3.5.0,<5"
 distro = ">=1.7.0,<2"
+docstring-parser = ">=0.15,<1"
 httpx = ">=0.25.0,<1"
 jiter = ">=0.4.0,<1"
 pydantic = ">=1.9.0,<3"
@@ -202,6 +230,7 @@ sniffio = "*"
 typing-extensions = ">=4.10,<5"
 
 [package.extras]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.9)"]
 bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
 vertex = ["google-auth[requests] (>=2,<3)"]
 
@@ -258,24 +287,6 @@ files = [
 [package.extras]
 dev = ["bandit (>=1.5.1)", "coverage (>=4.1)", "pydocstyle (>=3.0.0)", "vulture (>=1.0)"]
 
-[[package]]
-name = "asgiref"
-version = "3.8.1"
-description = "ASGI specs, helper code, and adapters"
-optional = false
-python-versions = ">=3.8"
-groups = ["main"]
-files = [
-    {file = "asgiref-3.8.1-py3-none-any.whl", hash = "sha256:3e1e3ecc849832fe52ccf2cb6686b7a55f82bb1d6aee72a58826471390335e47"},
-    {file = "asgiref-3.8.1.tar.gz", hash = "sha256:c343bd80a0bec947a9860adb4c432ffa7db769836c64238fc34bdc3fec84d590"},
-]
-
-[package.dependencies]
-typing-extensions = {version = ">=4", markers = "python_version < \"3.11\""}
-
-[package.extras]
-tests = ["mypy (>=0.800)", "pytest", "pytest-asyncio"]
-
 [[package]]
 name = "async-timeout"
 version = "4.0.3"
@@ -661,34 +672,34 @@ numpy = {version = ">=1.19.0", markers = "python_version >= \"3.9\""}
 
 [[package]]
 name = "boto3"
-version = "1.38.19"
+version = "1.40.71"
 description = "The AWS SDK for Python"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "boto3-1.38.19-py3-none-any.whl", hash = "sha256:d57d8040d04b8fefb7439062529653701cc90d5b2734cc4f1144fedb75ba94a7"},
-    {file = "boto3-1.38.19.tar.gz", hash = "sha256:fdd69f23e6216a508bbc1fbda9486791c161f3ecd5933ac7090d7290f6f2d0f5"},
+    {file = "boto3-1.40.71-py3-none-any.whl", hash = "sha256:4ac9ee8d1629e45d6b6adc727795d1fc9852e998cd1a73e4eda50f6120677bab"},
+    {file = "boto3-1.40.71.tar.gz", hash = "sha256:6d38e0250154552658be92a62cd48adf8ca8fd4abc181fb52d13371b53179503"},
 ]
 
 [package.dependencies]
-botocore = ">=1.38.19,<1.39.0"
+botocore = ">=1.40.71,<1.41.0"
 jmespath = ">=0.7.1,<2.0.0"
-s3transfer = ">=0.12.0,<0.13.0"
+s3transfer = ">=0.14.0,<0.15.0"
 
 [package.extras]
 crt = ["botocore[crt] (>=1.21.0,<2.0a0)"]
 
 [[package]]
 name = "botocore"
-version = "1.38.19"
+version = "1.40.71"
 description = "Low-level, data-driven core of boto 3."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "botocore-1.38.19-py3-none-any.whl", hash = "sha256:f937a20e75889215a99280ea0fdd4e1716ffede23e4f9af7bc9c64af9bc63e61"},
-    {file = "botocore-1.38.19.tar.gz", hash = "sha256:796b948c05017eb33385b798990cd91ed4af0e881eb9eb1ee6e17666be02abc9"},
+    {file = "botocore-1.40.71-py3-none-any.whl", hash = "sha256:4c05907b2a56b1f6fd70403fbae0f09a4758b95758192db5ff93c0e9940a11bb"},
+    {file = "botocore-1.40.71.tar.gz", hash = "sha256:7ed28c2e092fc0d67fbfba818fbdccc92426b452cc936bf034db6de717e0d068"},
 ]
 
 [package.dependencies]
@@ -697,7 +708,7 @@ 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 (==0.23.8)"]
+crt = ["awscrt (==0.27.6)"]
 
 [[package]]
 name = "build"
@@ -773,6 +784,104 @@ files = [
     {file = "certifi-2025.4.26.tar.gz", hash = "sha256:0a816057ea3cdefcef70270d2c515e4506bbc954f417fa5ade2021213bb8f0c6"},
 ]
 
+[[package]]
+name = "cffi"
+version = "2.0.0"
+description = "Foreign Function Interface for Python calling C code."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+markers = "platform_python_implementation != \"PyPy\""
+files = [
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 name = "charset-normalizer"
 version = "3.4.2"
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 grpcio = ">=1.58.0"
 httpx = ">=0.27.0"
 importlib-resources = "*"
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 kubernetes = ">=28.1.0"
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 numpy = ">=1.22.5"
 onnxruntime = ">=1.14.1"
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 tenacity = ">=8.2.3"
 tokenizers = ">=0.13.2"
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 typing-extensions = ">=4.5.0"
 uvicorn = {version = ">=0.18.3", extras = ["standard"]}
 
+[package.extras]
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+
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 python-versions = "*"
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 [[package]]
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+version = "5.20.0"
 description = ""
 optional = false
 python-versions = "<4.0,>=3.9"
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 [[package]]
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 [[package]]
 name = "cron-validator"
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 python-dateutil = "*"
 pytz = "*"
 
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+    {file = "cryptography-46.0.3-pp311-pypy311_pp73-manylinux_2_34_aarch64.whl", hash = "sha256:9394673a9f4de09e28b5356e7fff97d778f8abad85c9d5ac4a4b7e25a0de7717"},
+    {file = "cryptography-46.0.3-pp311-pypy311_pp73-manylinux_2_34_x86_64.whl", hash = "sha256:94cd0549accc38d1494e1f8de71eca837d0509d0d44bf11d158524b0e12cebf9"},
+    {file = "cryptography-46.0.3-pp311-pypy311_pp73-win_amd64.whl", hash = "sha256:6b5063083824e5509fdba180721d55909ffacccc8adbec85268b48439423d78c"},
+    {file = "cryptography-46.0.3.tar.gz", hash = "sha256:a8b17438104fed022ce745b362294d9ce35b4c2e45c1d958ad4a4b019285f4a1"},
+]
+
+[package.dependencies]
+cffi = {version = ">=2.0.0", markers = "python_full_version >= \"3.9.0\" and platform_python_implementation != \"PyPy\""}
+typing-extensions = {version = ">=4.13.2", markers = "python_full_version < \"3.11.0\""}
+
+[package.extras]
+docs = ["sphinx (>=5.3.0)", "sphinx-inline-tabs", "sphinx-rtd-theme (>=3.0.0)"]
+docstest = ["pyenchant (>=3)", "readme-renderer (>=30.0)", "sphinxcontrib-spelling (>=7.3.1)"]
+nox = ["nox[uv] (>=2024.4.15)"]
+pep8test = ["check-sdist", "click (>=8.0.1)", "mypy (>=1.14)", "ruff (>=0.11.11)"]
+sdist = ["build (>=1.0.0)"]
+ssh = ["bcrypt (>=3.1.5)"]
+test = ["certifi (>=2024)", "cryptography-vectors (==46.0.3)", "pretend (>=0.7)", "pytest (>=7.4.0)", "pytest-benchmark (>=4.0)", "pytest-cov (>=2.10.1)", "pytest-xdist (>=3.5.0)"]
+test-randomorder = ["pytest-randomly"]
+
 [[package]]
 name = "cycler"
 version = "0.12.1"
@@ -1602,6 +1809,23 @@ docs = ["myst-parser (==0.18.0)", "sphinx (==5.1.1)"]
 ssh = ["paramiko (>=2.4.3)"]
 websockets = ["websocket-client (>=1.3.0)"]
 
+[[package]]
+name = "docstring-parser"
+version = "0.17.0"
+description = "Parse Python docstrings in reST, Google and Numpydoc format"
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+files = [
+    {file = "docstring_parser-0.17.0-py3-none-any.whl", hash = "sha256:cf2569abd23dce8099b300f9b4fa8191e9582dda731fd533daf54c4551658708"},
+    {file = "docstring_parser-0.17.0.tar.gz", hash = "sha256:583de4a309722b3315439bb31d64ba3eebada841f2e2cee23b99df001434c912"},
+]
+
+[package.extras]
+dev = ["pre-commit (>=2.16.0) ; python_version >= \"3.9\"", "pydoctor (>=25.4.0)", "pytest"]
+docs = ["pydoctor (>=25.4.0)"]
+test = ["pytest"]
+
 [[package]]
 name = "durationpy"
 version = "0.10"
@@ -1657,31 +1881,32 @@ tools = ["hypothesis (>=6.22.0,<6.108.7)"]
 
 [[package]]
 name = "eth-account"
-version = "0.11.3"
+version = "0.13.7"
 description = "eth-account: Sign Ethereum transactions and messages with local private keys"
 optional = false
 python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "eth_account-0.11.3-py3-none-any.whl", hash = "sha256:16cf58aabc65171fc206489899b7e5546e3215e1a4debc12dbd55345c979081e"},
-    {file = "eth_account-0.11.3.tar.gz", hash = "sha256:a712a9534638a7cfaa4cc069f1b9d5cefeee70362cfc3a7b0a2534ee61ce76c9"},
+    {file = "eth_account-0.13.7-py3-none-any.whl", hash = "sha256:39727de8c94d004ff61d10da7587509c04d2dc7eac71e04830135300bdfc6d24"},
+    {file = "eth_account-0.13.7.tar.gz", hash = "sha256:5853ecbcbb22e65411176f121f5f24b8afeeaf13492359d254b16d8b18c77a46"},
 ]
 
 [package.dependencies]
 bitarray = ">=2.4.0"
-ckzg = ">=0.4.3,<2"
+ckzg = ">=2.0.0"
 eth-abi = ">=4.0.0-b.2"
-eth-keyfile = ">=0.6.0"
+eth-keyfile = ">=0.7.0,<0.9.0"
 eth-keys = ">=0.4.0"
-eth-rlp = ">=0.3.0"
+eth-rlp = ">=2.1.0"
 eth-utils = ">=2.0.0"
-hexbytes = ">=0.1.0,<0.4.0"
+hexbytes = ">=1.2.0"
+pydantic = ">=2.0.0"
 rlp = ">=1.0.0"
 
 [package.extras]
-dev = ["build (>=0.9.0)", "bumpversion (>=0.5.3)", "coverage", "hypothesis (>=4.18.0,<5)", "ipython", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)", "tox (>=4.0.0)", "twine", "wheel"]
-docs = ["sphinx (>=6.0.0)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)"]
-test = ["coverage", "hypothesis (>=4.18.0,<5)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
+dev = ["build (>=0.9.0)", "bump_my_version (>=0.19.0)", "coverage", "hypothesis (>=6.22.0,<6.108.7)", "ipython", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)", "tox (>=4.0.0)", "twine", "wheel"]
+docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)"]
+test = ["coverage", "hypothesis (>=6.22.0,<6.108.7)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
 
 [[package]]
 name = "eth-bloom"
@@ -1727,25 +1952,24 @@ test = ["pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
 
 [[package]]
 name = "eth-keyfile"
-version = "0.9.1"
+version = "0.8.1"
 description = "eth-keyfile: A library for handling the encrypted keyfiles used to store ethereum private keys"
 optional = false
 python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "eth_keyfile-0.9.1-py3-none-any.whl", hash = "sha256:9789c3b4fa0bb6e2616cdc2bdd71b8755b42947d78ef1e900a0149480fabb5c2"},
-    {file = "eth_keyfile-0.9.1.tar.gz", hash = "sha256:c7a8bc6af4527d1ab2eb1d1b949d59925252e17663eaf90087da121327b51df6"},
+    {file = "eth_keyfile-0.8.1-py3-none-any.whl", hash = "sha256:65387378b82fe7e86d7cb9f8d98e6d639142661b2f6f490629da09fddbef6d64"},
+    {file = "eth_keyfile-0.8.1.tar.gz", hash = "sha256:9708bc31f386b52cca0969238ff35b1ac72bd7a7186f2a84b86110d3c973bec1"},
 ]
 
 [package.dependencies]
 eth-keys = ">=0.4.0"
 eth-utils = ">=2"
-py_ecc = ">=5.2.0"
 pycryptodome = ">=3.6.6,<4"
 
 [package.extras]
-dev = ["build (>=0.9.0)", "bump_my_version (>=0.19.0)", "ipython", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "towncrier (>=24,<25)", "tox (>=4.0.0)", "twine", "wheel"]
-docs = ["towncrier (>=24,<25)"]
+dev = ["build (>=0.9.0)", "bumpversion (>=0.5.3)", "ipython", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "towncrier (>=21,<22)", "tox (>=4.0.0)", "twine", "wheel"]
+docs = ["towncrier (>=21,<22)"]
 test = ["pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
 
 [[package]]
@@ -1772,70 +1996,70 @@ test = ["asn1tools (>=0.146.2)", "eth-hash[pysha3]", "factory-boy (>=3.0.1)", "h
 
 [[package]]
 name = "eth-rlp"
-version = "1.0.1"
+version = "2.2.0"
 description = "eth-rlp: RLP definitions for common Ethereum objects in Python"
 optional = false
-python-versions = ">=3.8, <4"
+python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "eth-rlp-1.0.1.tar.gz", hash = "sha256:d61dbda892ee1220f28fb3663c08f6383c305db9f1f5624dc585c9cd05115027"},
-    {file = "eth_rlp-1.0.1-py3-none-any.whl", hash = "sha256:dd76515d71654277377d48876b88e839d61553aaf56952e580bb7cebef2b1517"},
+    {file = "eth_rlp-2.2.0-py3-none-any.whl", hash = "sha256:5692d595a741fbaef1203db6a2fedffbd2506d31455a6ad378c8449ee5985c47"},
+    {file = "eth_rlp-2.2.0.tar.gz", hash = "sha256:5e4b2eb1b8213e303d6a232dfe35ab8c29e2d3051b86e8d359def80cd21db83d"},
 ]
 
 [package.dependencies]
 eth-utils = ">=2.0.0"
-hexbytes = ">=0.1.0,<1"
+hexbytes = ">=1.2.0"
 rlp = ">=0.6.0"
-typing-extensions = {version = ">=4.0.1", markers = "python_version <= \"3.11\""}
+typing_extensions = {version = ">=4.0.1", markers = "python_version <= \"3.10\""}
 
 [package.extras]
-dev = ["build (>=0.9.0)", "bumpversion (>=0.5.3)", "eth-hash[pycryptodome]", "ipython", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)", "tox (>=4.0.0)", "twine", "wheel"]
-docs = ["sphinx (>=6.0.0)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)"]
+dev = ["build (>=0.9.0)", "bump_my_version (>=0.19.0)", "eth-hash[pycryptodome]", "ipython", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)", "tox (>=4.0.0)", "twine", "wheel"]
+docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)"]
 test = ["eth-hash[pycryptodome]", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
 
 [[package]]
 name = "eth-typing"
-version = "3.5.2"
+version = "5.2.1"
 description = "eth-typing: Common type annotations for ethereum python packages"
 optional = false
-python-versions = ">=3.7.2, <4"
+python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "eth-typing-3.5.2.tar.gz", hash = "sha256:22bf051ddfaa35ff827c30090de167e5c5b8cc6d343f7f35c9b1c7553f6ab64d"},
-    {file = "eth_typing-3.5.2-py3-none-any.whl", hash = "sha256:1842e628fb1ffa929b94f89a9d33caafbeb9978dc96abb6036a12bc91f1c624b"},
+    {file = "eth_typing-5.2.1-py3-none-any.whl", hash = "sha256:b0c2812ff978267563b80e9d701f487dd926f1d376d674f3b535cfe28b665d3d"},
+    {file = "eth_typing-5.2.1.tar.gz", hash = "sha256:7557300dbf02a93c70fa44af352b5c4a58f94e997a0fd6797fb7d1c29d9538ee"},
 ]
 
 [package.dependencies]
-typing-extensions = ">=4.0.1"
+typing_extensions = ">=4.5.0"
 
 [package.extras]
-dev = ["black (>=23)", "build (>=0.9.0)", "bumpversion (>=0.5.3)", "flake8 (==6.0.0)", "flake8-bugbear (==23.3.23)", "ipython", "isort (>=5.10.1)", "mypy (==0.971)", "pydocstyle (>=6.0.0)", "pytest (>=7.0.0)", "pytest-watch (>=4.1.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=5.0.0)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)", "tox (>=4.0.0)", "twine", "types-setuptools", "wheel"]
-docs = ["sphinx (>=5.0.0)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)"]
-lint = ["black (>=23)", "flake8 (==6.0.0)", "flake8-bugbear (==23.3.23)", "isort (>=5.10.1)", "mypy (==0.971)", "pydocstyle (>=6.0.0)", "types-setuptools"]
+dev = ["build (>=0.9.0)", "bump_my_version (>=0.19.0)", "ipython", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)", "tox (>=4.0.0)", "twine", "wheel"]
+docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)"]
 test = ["pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
 
 [[package]]
 name = "eth-utils"
-version = "4.1.1"
+version = "5.3.1"
 description = "eth-utils: Common utility functions for python code that interacts with Ethereum"
 optional = false
 python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "eth_utils-4.1.1-py3-none-any.whl", hash = "sha256:ccbbac68a6d65cb6e294c5bcb6c6a5cec79a241c56dc5d9c345ed788c30f8534"},
-    {file = "eth_utils-4.1.1.tar.gz", hash = "sha256:71c8d10dec7494aeed20fa7a4d52ec2ce4a2e52fdce80aab4f5c3c19f3648b25"},
+    {file = "eth_utils-5.3.1-py3-none-any.whl", hash = "sha256:1f5476d8f29588d25b8ae4987e1ffdfae6d4c09026e476c4aad13b32dda3ead0"},
+    {file = "eth_utils-5.3.1.tar.gz", hash = "sha256:c94e2d2abd024a9a42023b4ddc1c645814ff3d6a737b33d5cfd890ebf159c2d1"},
 ]
 
 [package.dependencies]
 cytoolz = {version = ">=0.10.1", markers = "implementation_name == \"cpython\""}
 eth-hash = ">=0.3.1"
-eth-typing = ">=3.0.0"
+eth-typing = ">=5.0.0"
+pydantic = ">=2.0.0,<3"
 toolz = {version = ">0.8.2", markers = "implementation_name == \"pypy\""}
 
 [package.extras]
-dev = ["build (>=0.9.0)", "bumpversion (>=0.5.3)", "eth-hash[pycryptodome]", "hypothesis (>=4.43.0)", "ipython", "mypy (==1.5.1)", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)", "tox (>=4.0.0)", "twine", "wheel"]
-docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx-rtd-theme (>=1.0.0)", "towncrier (>=21,<22)"]
-test = ["hypothesis (>=4.43.0)", "mypy (==1.5.1)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
+dev = ["build (>=0.9.0)", "bump_my_version (>=0.19.0)", "eth-hash[pycryptodome]", "hypothesis (>=4.43.0)", "ipython", "mypy (==1.10.0)", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)", "sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)", "tox (>=4.0.0)", "twine", "wheel"]
+docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)"]
+test = ["hypothesis (>=4.43.0)", "mypy (==1.10.0)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
 
 [[package]]
 name = "eval-type-backport"
@@ -1872,25 +2096,19 @@ typing-extensions = {version = ">=4.6.0", markers = "python_version < \"3.13\""}
 test = ["pytest (>=6)"]
 
 [[package]]
-name = "fastapi"
-version = "0.115.12"
-description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
+name = "executing"
+version = "2.2.1"
+description = "Get the currently executing AST node of a frame, and other information"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "fastapi-0.115.12-py3-none-any.whl", hash = "sha256:e94613d6c05e27be7ffebdd6ea5f388112e5e430c8f7d6494a9d1d88d43e814d"},
-    {file = "fastapi-0.115.12.tar.gz", hash = "sha256:1e2c2a2646905f9e83d32f04a3f86aff4a286669c6c950ca95b5fd68c2602681"},
+    {file = "executing-2.2.1-py2.py3-none-any.whl", hash = "sha256:760643d3452b4d777d295bb167ccc74c64a81df23fb5e08eff250c425a4b2017"},
+    {file = "executing-2.2.1.tar.gz", hash = "sha256:3632cc370565f6648cc328b32435bd120a1e4ebb20c77e3fdde9a13cd1e533c4"},
 ]
 
-[package.dependencies]
-pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<2.1.0 || >2.1.0,<3.0.0"
-starlette = ">=0.40.0,<0.47.0"
-typing-extensions = ">=4.8.0"
-
 [package.extras]
-all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
-standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
+tests = ["asttokens (>=2.1.0)", "coverage", "coverage-enable-subprocess", "ipython", "littleutils", "pytest", "rich ; python_version >= \"3.11\""]
 
 [[package]]
 name = "fastavro"
@@ -2276,6 +2494,23 @@ gunicorn = {version = ">=22.0.0", markers = "platform_system != \"Windows\""}
 watchdog = ">=1.0.0"
 Werkzeug = ">=0.14,<4.0.0"
 
+[[package]]
+name = "genai-prices"
+version = "0.0.38"
+description = "Calculate prices for calling LLM inference APIs."
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "genai_prices-0.0.38-py3-none-any.whl", hash = "sha256:c1ddf9040877116e23c4e1dfb390f8e9683b533c758e5d756494e1a26159ea4f"},
+    {file = "genai_prices-0.0.38.tar.gz", hash = "sha256:27295d0db523cc5e98aea656a297b78c768cceeab03608a0dd5b029e095229ca"},
+]
+
+[package.dependencies]
+eval-type-backport = {version = ">=0.2", markers = "python_full_version < \"3.11.0\""}
+httpx = ">=0.28.1"
+pydantic = ">=2.10"
+
 [[package]]
 name = "gitdb"
 version = "4.0.12"
@@ -2462,6 +2697,32 @@ grpc-google-iam-v1 = ">=0.14.0,<1.0.0"
 proto-plus = ">=1.22.3,<2.0.0"
 protobuf = ">=3.20.2,<4.21.0 || >4.21.0,<4.21.1 || >4.21.1,<4.21.2 || >4.21.2,<4.21.3 || >4.21.3,<4.21.4 || >4.21.4,<4.21.5 || >4.21.5,<7.0.0"
 
+[[package]]
+name = "google-genai"
+version = "1.49.0"
+description = "GenAI Python SDK"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
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+
+[package.extras]
+aiohttp = ["aiohttp (<4.0.0)"]
+local-tokenizer = ["protobuf", "sentencepiece (>=0.2.0)"]
+
 [[package]]
 name = "googleapis-common-protos"
 version = "1.70.0"
@@ -2737,21 +2998,56 @@ hyperframe = ">=6.1,<7"
 
 [[package]]
 name = "hexbytes"
-version = "0.3.1"
+version = "1.3.1"
 description = "hexbytes: Python `bytes` subclass that decodes hex, with a readable console output"
 optional = false
-python-versions = ">=3.7, <4"
+python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
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+docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)"]
+test = ["eth_utils (>=2.0.0)", "hypothesis (>=3.44.24)", "pytest (>=7.0.0)", "pytest-xdist (>=2.4.0)"]
+
+[[package]]
+name = "hf-xet"
+version = "1.2.0"
+description = "Fast transfer of large files with the Hugging Face Hub."
+optional = false
+python-versions = ">=3.8"
+groups = ["main"]
+markers = "platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"arm64\" or platform_machine == \"aarch64\""
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 [package.extras]
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+tests = ["pytest"]
 
 [[package]]
 name = "hishel"
@@ -2920,19 +3216,21 @@ files = [
 
 [[package]]
 name = "huggingface-hub"
-version = "0.31.4"
+version = "0.36.0"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 groups = ["main"]
 files = [
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+    {file = "huggingface_hub-0.36.0.tar.gz", hash = "sha256:47b3f0e2539c39bf5cde015d63b72ec49baff67b6931c3d97f3f84532e2b8d25"},
 ]
 
 [package.dependencies]
+aiohttp = {version = "*", optional = true, markers = "extra == \"inference\""}
 filelock = "*"
 fsspec = ">=2023.5.0"
+hf-xet = {version = ">=1.1.3,<2.0.0", markers = "platform_machine == \"x86_64\" or platform_machine == \"amd64\" or platform_machine == \"arm64\" or platform_machine == \"aarch64\""}
 packaging = ">=20.9"
 pyyaml = ">=5.1"
 requests = "*"
@@ -2940,17 +3238,19 @@ tqdm = ">=4.42.1"
 typing-extensions = ">=3.7.4.3"
 
 [package.extras]
-all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 cli = ["InquirerPy (==0.3.4)"]
-dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "libcst (==1.4.0)", "mypy (==1.5.1)", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "ruff (>=0.9.0)", "soundfile", "ty", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)", "urllib3 (<2.0)"]
 fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
 hf-transfer = ["hf-transfer (>=0.1.4)"]
-hf-xet = ["hf-xet (>=1.1.1,<2.0.0)"]
+hf-xet = ["hf-xet (>=1.1.2,<2.0.0)"]
 inference = ["aiohttp"]
-quality = ["libcst (==1.4.0)", "mypy (==1.5.1)", "ruff (>=0.9.0)"]
+mcp = ["aiohttp", "mcp (>=1.8.0)", "typer"]
+oauth = ["authlib (>=1.3.2)", "fastapi", "httpx", "itsdangerous"]
+quality = ["libcst (>=1.4.0)", "mypy (==1.15.0) ; python_version >= \"3.9\"", "mypy (>=1.14.1,<1.15.0) ; python_version == \"3.8\"", "ruff (>=0.9.0)", "ty"]
 tensorflow = ["graphviz", "pydot", "tensorflow"]
 tensorflow-testing = ["keras (<3.0)", "tensorflow"]
-testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "fastapi", "gradio (>=4.0.0)", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "authlib (>=1.3.2)", "fastapi", "gradio (>=4.0.0)", "httpx", "itsdangerous", "jedi", "numpy", "pytest (>=8.1.1,<8.2.2)", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-mock", "pytest-rerunfailures (<16.0)", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
 torch = ["safetensors[torch]", "torch"]
 typing = ["types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "typing-extensions (>=4.8.0)"]
 
@@ -3052,6 +3352,18 @@ files = [
     {file = "iniconfig-2.1.0.tar.gz", hash = "sha256:3abbd2e30b36733fee78f9c7f7308f2d0050e88f0087fd25c2645f63c773e1c7"},
 ]
 
+[[package]]
+name = "invoke"
+version = "2.2.1"
+description = "Pythonic task execution"
+optional = false
+python-versions = ">=3.6"
+groups = ["main"]
+files = [
+    {file = "invoke-2.2.1-py3-none-any.whl", hash = "sha256:2413bc441b376e5cd3f55bb5d364f973ad8bdd7bf87e53c79de3c11bf3feecc8"},
+    {file = "invoke-2.2.1.tar.gz", hash = "sha256:515bf49b4a48932b79b024590348da22f39c4942dff991ad1fb8b8baea1be707"},
+]
+
 [[package]]
 name = "isort"
 version = "5.13.2"
@@ -3235,6 +3547,18 @@ files = [
     {file = "jsonpointer-3.0.0.tar.gz", hash = "sha256:2b2d729f2091522d61c3b31f82e11870f60b68f43fbc705cb76bf4b832af59ef"},
 ]
 
+[[package]]
+name = "jsonref"
+version = "1.1.0"
+description = "jsonref is a library for automatic dereferencing of JSON Reference objects for Python."
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "jsonref-1.1.0-py3-none-any.whl", hash = "sha256:590dc7773df6c21cbf948b5dac07a72a251db28b0238ceecce0a2abfa8ec30a9"},
+    {file = "jsonref-1.1.0.tar.gz", hash = "sha256:32fe8e1d85af0fdefbebce950af85590b22b60f9e95443176adbde4e1ecea552"},
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.23.0"
@@ -3392,31 +3716,25 @@ adal = ["adal (>=1.0.2)"]
 
 [[package]]
 name = "langchain"
-version = "0.3.25"
+version = "1.0.5"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = ">=3.9"
+python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 files = [
-    {file = "langchain-0.3.25-py3-none-any.whl", hash = "sha256:931f7d2d1eaf182f9f41c5e3272859cfe7f94fc1f7cef6b3e5a46024b4884c21"},
-    {file = "langchain-0.3.25.tar.gz", hash = "sha256:a1d72aa39546a23db08492d7228464af35c9ee83379945535ceef877340d2a3a"},
+    {file = "langchain-1.0.5-py3-none-any.whl", hash = "sha256:d59ce7303f1d9e4bca41855b20a1842f4470a22d09a64fb93fb0ff30a2d36d4b"},
+    {file = "langchain-1.0.5.tar.gz", hash = "sha256:7e0635b36a7f7a649be21fcce4c82b7428bcf72a5d14aacdf9f2636c4775f159"},
 ]
 
 [package.dependencies]
-async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
-langchain-core = ">=0.3.58,<1.0.0"
-langchain-text-splitters = ">=0.3.8,<1.0.0"
-langsmith = ">=0.1.17,<0.4"
+langchain-core = ">=1.0.4,<2.0.0"
+langgraph = ">=1.0.2,<1.1.0"
 pydantic = ">=2.7.4,<3.0.0"
-PyYAML = ">=5.3"
-requests = ">=2,<3"
-SQLAlchemy = ">=1.4,<3"
 
 [package.extras]
 anthropic = ["langchain-anthropic"]
 aws = ["langchain-aws"]
 azure-ai = ["langchain-azure-ai"]
-cohere = ["langchain-cohere"]
 community = ["langchain-community"]
 deepseek = ["langchain-deepseek"]
 fireworks = ["langchain-fireworks"]
@@ -3425,6 +3743,61 @@ google-vertexai = ["langchain-google-vertexai"]
 groq = ["langchain-groq"]
 huggingface = ["langchain-huggingface"]
 mistralai = ["langchain-mistralai"]
+model-profiles = ["langchain-model-profiles"]
+ollama = ["langchain-ollama"]
+openai = ["langchain-openai"]
+perplexity = ["langchain-perplexity"]
+together = ["langchain-together"]
+xai = ["langchain-xai"]
+
+[[package]]
+name = "langchain-chroma"
+version = "1.0.0"
+description = "An integration package connecting Chroma and LangChain."
+optional = false
+python-versions = "<4.0.0,>=3.10.0"
+groups = ["main"]
+files = [
+    {file = "langchain_chroma-1.0.0-py3-none-any.whl", hash = "sha256:b7adb991090f066f8d5e746a2d338de3116b192cec3990deef3052b7ea07324c"},
+    {file = "langchain_chroma-1.0.0.tar.gz", hash = "sha256:ee82c6fbd0c94e5e9942e3b9302f69deea6c58c0e957ff16de6066d896d7a34a"},
+]
+
+[package.dependencies]
+chromadb = ">=1.0.20,<2.0.0"
+langchain-core = ">=1.0.0,<2.0.0"
+numpy = {version = ">=1.26.0", markers = "python_version < \"3.13\""}
+
+[[package]]
+name = "langchain-classic"
+version = "1.0.0"
+description = "Building applications with LLMs through composability"
+optional = false
+python-versions = "<4.0.0,>=3.10.0"
+groups = ["main"]
+files = [
+    {file = "langchain_classic-1.0.0-py3-none-any.whl", hash = "sha256:97f71f150c10123f5511c08873f030e35ede52311d729a7688c721b4e1e01f33"},
+    {file = "langchain_classic-1.0.0.tar.gz", hash = "sha256:a63655609254ebc36d660eb5ad7c06c778b2e6733c615ffdac3eac4fbe2b12c5"},
+]
+
+[package.dependencies]
+async-timeout = {version = ">=4.0.0,<5.0.0", markers = "python_version < \"3.11\""}
+langchain-core = ">=1.0.0,<2.0.0"
+langchain-text-splitters = ">=1.0.0,<2.0.0"
+langsmith = ">=0.1.17,<1.0.0"
+pydantic = ">=2.7.4,<3.0.0"
+pyyaml = ">=5.3.0,<7.0.0"
+requests = ">=2.0.0,<3.0.0"
+sqlalchemy = ">=1.4.0,<3.0.0"
+
+[package.extras]
+anthropic = ["langchain-anthropic"]
+aws = ["langchain-aws"]
+deepseek = ["langchain-deepseek"]
+fireworks = ["langchain-fireworks"]
+google-genai = ["langchain-google-genai"]
+google-vertexai = ["langchain-google-vertexai"]
+groq = ["langchain-groq"]
+mistralai = ["langchain-mistralai"]
 ollama = ["langchain-ollama"]
 openai = ["langchain-openai"]
 perplexity = ["langchain-perplexity"]
@@ -3433,82 +3806,82 @@ xai = ["langchain-xai"]
 
 [[package]]
 name = "langchain-community"
-version = "0.3.24"
+version = "0.4.1"
 description = "Community contributed LangChain integrations."
 optional = false
-python-versions = ">=3.9"
+python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 files = [
-    {file = "langchain_community-0.3.24-py3-none-any.whl", hash = "sha256:b6cdb376bf1c2f4d2503aca20f8f35f2d5b3d879c52848277f20ce1950e7afaf"},
-    {file = "langchain_community-0.3.24.tar.gz", hash = "sha256:62d9e8cf9aadf35182ec3925f9ec1c8e5e84fb4f199f67a01aee496d289dc264"},
+    {file = "langchain_community-0.4.1-py3-none-any.whl", hash = "sha256:2135abb2c7748a35c84613108f7ebf30f8505b18c3c18305ffaecfc7651f6c6a"},
+    {file = "langchain_community-0.4.1.tar.gz", hash = "sha256:f3b211832728ee89f169ddce8579b80a085222ddb4f4ed445a46e977d17b1e85"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.8.3,<4.0.0"
-dataclasses-json = ">=0.5.7,<0.7"
+dataclasses-json = ">=0.6.7,<0.7.0"
 httpx-sse = ">=0.4.0,<1.0.0"
-langchain = ">=0.3.25,<1.0.0"
-langchain-core = ">=0.3.59,<1.0.0"
-langsmith = ">=0.1.125,<0.4"
+langchain-classic = ">=1.0.0,<2.0.0"
+langchain-core = ">=1.0.1,<2.0.0"
+langsmith = ">=0.1.125,<1.0.0"
 numpy = {version = ">=1.26.2", markers = "python_version < \"3.13\""}
-pydantic-settings = ">=2.4.0,<3.0.0"
-PyYAML = ">=5.3"
-requests = ">=2,<3"
-SQLAlchemy = ">=1.4,<3"
-tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10"
+pydantic-settings = ">=2.10.1,<3.0.0"
+PyYAML = ">=5.3.0,<7.0.0"
+requests = ">=2.32.5,<3.0.0"
+SQLAlchemy = ">=1.4.0,<3.0.0"
+tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.3.60"
+version = "1.0.4"
 description = "Building applications with LLMs through composability"
 optional = false
-python-versions = ">=3.9"
+python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 files = [
-    {file = "langchain_core-0.3.60-py3-none-any.whl", hash = "sha256:2ccdf06b12e699b1b0962bc02837056c075b4981c3d13f82a4d4c30bb22ea3dc"},
-    {file = "langchain_core-0.3.60.tar.gz", hash = "sha256:63dd1bdf7939816115399522661ca85a2f3686a61440f2f46ebd86d1b028595b"},
+    {file = "langchain_core-1.0.4-py3-none-any.whl", hash = "sha256:53caa351d9d73b56f5d9628980f36851cfa725977508098869fdc2d246da43b3"},
+    {file = "langchain_core-1.0.4.tar.gz", hash = "sha256:086d408bcbeedecb0b152201e0163b85e7a6d9b26e11a75cc577b7371291df4e"},
 ]
 
 [package.dependencies]
-jsonpatch = ">=1.33,<2.0"
-langsmith = ">=0.1.126,<0.4"
-packaging = ">=23.2,<25"
-pydantic = ">=2.7.4"
-PyYAML = ">=5.3"
+jsonpatch = ">=1.33.0,<2.0.0"
+langsmith = ">=0.3.45,<1.0.0"
+packaging = ">=23.2.0,<26.0.0"
+pydantic = ">=2.7.4,<3.0.0"
+pyyaml = ">=5.3.0,<7.0.0"
 tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<10.0.0"
-typing-extensions = ">=4.7"
+typing-extensions = ">=4.7.0,<5.0.0"
 
 [[package]]
 name = "langchain-openai"
-version = "0.3.17"
+version = "1.0.2"
 description = "An integration package connecting OpenAI and LangChain"
 optional = false
-python-versions = ">=3.9"
+python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 files = [
-    {file = "langchain_openai-0.3.17-py3-none-any.whl", hash = "sha256:d4d9cf945e2453ee5895ccd12fd8a3ea9131a0f6130dcc21427c77cc2206b1c0"},
-    {file = "langchain_openai-0.3.17.tar.gz", hash = "sha256:10bcdfac3edb3dea4a8aabb12f01566e5ff8756634cc52aa169c62e4c4b73801"},
+    {file = "langchain_openai-1.0.2-py3-none-any.whl", hash = "sha256:b3eb9b82752063b46452aa868d8c8bc1604e57631648c3bc325bba58d3aeb143"},
+    {file = "langchain_openai-1.0.2.tar.gz", hash = "sha256:621e8295c52db9a1fc74806a0bd227ea215c132c6c5e421d2982c9ee78468769"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.59,<1.0.0"
-openai = ">=1.68.2,<2.0.0"
-tiktoken = ">=0.7,<1"
+langchain-core = ">=1.0.2,<2.0.0"
+openai = ">=1.109.1,<3.0.0"
+tiktoken = ">=0.7.0,<1.0.0"
 
 [[package]]
 name = "langchain-text-splitters"
-version = "0.3.8"
+version = "1.0.0"
 description = "LangChain text splitting utilities"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = "<4.0.0,>=3.10.0"
 groups = ["main"]
 files = [
-    {file = "langchain_text_splitters-0.3.8-py3-none-any.whl", hash = "sha256:e75cc0f4ae58dcf07d9f18776400cf8ade27fadd4ff6d264df6278bb302f6f02"},
-    {file = "langchain_text_splitters-0.3.8.tar.gz", hash = "sha256:116d4b9f2a22dda357d0b79e30acf005c5518177971c66a9f1ab0edfdb0f912e"},
+    {file = "langchain_text_splitters-1.0.0-py3-none-any.whl", hash = "sha256:f00c8219d3468f2c5bd951b708b6a7dd9bc3c62d0cfb83124c377f7170f33b2e"},
+    {file = "langchain_text_splitters-1.0.0.tar.gz", hash = "sha256:d8580a20ad7ed10b432feb273e5758b2cc0902d094919629cec0e1ad691a6744"},
 ]
 
 [package.dependencies]
-langchain-core = ">=0.3.51,<1.0.0"
+langchain-core = ">=1.0.0,<2.0.0"
 
 [[package]]
 name = "langcodes"
@@ -3531,55 +3904,124 @@ test = ["pytest", "pytest-cov"]
 
 [[package]]
 name = "langfuse"
-version = "2.60.5"
+version = "3.9.3"
 description = "A client library for accessing langfuse"
 optional = false
-python-versions = "<4.0,>=3.9"
+python-versions = "<4.0,>=3.10"
 groups = ["main"]
 files = [
-    {file = "langfuse-2.60.5-py3-none-any.whl", hash = "sha256:fd27d52017f36d6fa5ca652615213a2535dc93dd88c3375eeb811af26384d285"},
-    {file = "langfuse-2.60.5.tar.gz", hash = "sha256:a33ecddc98cf6d12289372e63071b77b72230e7bc8260ee349f1465d53bf425b"},
+    {file = "langfuse-3.9.3-py3-none-any.whl", hash = "sha256:0afe88773f20fc67636d8a52dd3a5fb4e10f1c6e226f2c99ace8c65190fb5697"},
+    {file = "langfuse-3.9.3.tar.gz", hash = "sha256:8081691d40325b7022b07fc4e5884853c4a4ffe03b05c702490788b9a1a125df"},
 ]
 
 [package.dependencies]
-anyio = ">=4.4.0,<5.0.0"
 backoff = ">=1.10.0"
 httpx = ">=0.15.4,<1.0"
-idna = ">=3.7,<4.0"
-packaging = ">=23.2,<25.0"
+openai = ">=0.27.8"
+opentelemetry-api = ">=1.33.1,<2.0.0"
+opentelemetry-exporter-otlp-proto-http = ">=1.33.1,<2.0.0"
+opentelemetry-sdk = ">=1.33.1,<2.0.0"
+packaging = ">=23.2,<26.0"
 pydantic = ">=1.10.7,<3.0"
 requests = ">=2,<3"
 wrapt = ">=1.14,<2.0"
 
-[package.extras]
-langchain = ["langchain (>=0.0.309)"]
-llama-index = ["llama-index (>=0.10.12,<2.0.0)"]
-openai = ["openai (>=0.27.8)"]
+[[package]]
+name = "langgraph"
+version = "1.0.3"
+description = "Building stateful, multi-actor applications with LLMs"
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "langgraph-1.0.3-py3-none-any.whl", hash = "sha256:4a75146f09bd0d127a724876f4244f460c4c66353a993641bd641ed710cd010f"},
+    {file = "langgraph-1.0.3.tar.gz", hash = "sha256:873a6aae6be054ef52a05c463be363a46da9711405b1b14454d595f543b68335"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.1"
+langgraph-checkpoint = ">=2.1.0,<4.0.0"
+langgraph-prebuilt = ">=1.0.2,<1.1.0"
+langgraph-sdk = ">=0.2.2,<0.3.0"
+pydantic = ">=2.7.4"
+xxhash = ">=3.5.0"
+
+[[package]]
+name = "langgraph-checkpoint"
+version = "3.0.1"
+description = "Library with base interfaces for LangGraph checkpoint savers."
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "langgraph_checkpoint-3.0.1-py3-none-any.whl", hash = "sha256:9b04a8d0edc0474ce4eaf30c5d731cee38f11ddff50a6177eead95b5c4e4220b"},
+    {file = "langgraph_checkpoint-3.0.1.tar.gz", hash = "sha256:59222f875f85186a22c494aedc65c4e985a3df27e696e5016ba0b98a5ed2cee0"},
+]
+
+[package.dependencies]
+langchain-core = ">=0.2.38"
+ormsgpack = ">=1.12.0"
+
+[[package]]
+name = "langgraph-prebuilt"
+version = "1.0.2"
+description = "Library with high-level APIs for creating and executing LangGraph agents and tools."
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "langgraph_prebuilt-1.0.2-py3-none-any.whl", hash = "sha256:d9499f7c449fb637ee7b87e3f6a3b74095f4202053c74d33894bd839ea4c57c7"},
+    {file = "langgraph_prebuilt-1.0.2.tar.gz", hash = "sha256:9896dbabf04f086eb59df4294f54ab5bdb21cd78e27e0a10e695dffd1cc6097d"},
+]
+
+[package.dependencies]
+langchain-core = ">=1.0.0"
+langgraph-checkpoint = ">=2.1.0,<4.0.0"
+
+[[package]]
+name = "langgraph-sdk"
+version = "0.2.9"
+description = "SDK for interacting with LangGraph API"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "langgraph_sdk-0.2.9-py3-none-any.whl", hash = "sha256:fbf302edadbf0fb343596f91c597794e936ef68eebc0d3e1d358b6f9f72a1429"},
+    {file = "langgraph_sdk-0.2.9.tar.gz", hash = "sha256:b3bd04c6be4fa382996cd2be8fbc1e7cc94857d2bc6b6f4599a7f2a245975303"},
+]
+
+[package.dependencies]
+httpx = ">=0.25.2"
+orjson = ">=3.10.1"
 
 [[package]]
 name = "langsmith"
-version = "0.1.147"
-description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
+version = "0.4.42"
+description = "Client library to connect to the LangSmith Observability and Evaluation Platform."
 optional = false
-python-versions = "<4.0,>=3.8.1"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "langsmith-0.1.147-py3-none-any.whl", hash = "sha256:7166fc23b965ccf839d64945a78e9f1157757add228b086141eb03a60d699a15"},
-    {file = "langsmith-0.1.147.tar.gz", hash = "sha256:2e933220318a4e73034657103b3b1a3a6109cc5db3566a7e8e03be8d6d7def7a"},
+    {file = "langsmith-0.4.42-py3-none-any.whl", hash = "sha256:015b0a0c17eb1a61293e8cbb7d41778a4b37caddd267d54274ba94e4721b301b"},
+    {file = "langsmith-0.4.42.tar.gz", hash = "sha256:a6e808e47581403cb019b47c8c10627c1644f78ed4c03fa877d6ad661476c38f"},
 ]
 
 [package.dependencies]
 httpx = ">=0.23.0,<1"
-orjson = {version = ">=3.9.14,<4.0.0", markers = "platform_python_implementation != \"PyPy\""}
-pydantic = [
-    {version = ">=1,<3", markers = "python_full_version < \"3.12.4\""},
-    {version = ">=2.7.4,<3.0.0", markers = "python_full_version >= \"3.12.4\""},
-]
-requests = ">=2,<3"
-requests-toolbelt = ">=1.0.0,<2.0.0"
+orjson = {version = ">=3.9.14", markers = "platform_python_implementation != \"PyPy\""}
+packaging = ">=23.2"
+pydantic = ">=1,<3"
+requests = ">=2.0.0"
+requests-toolbelt = ">=1.0.0"
+zstandard = ">=0.23.0"
 
 [package.extras]
-langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2,<0.2.0)"]
+claude-agent-sdk = ["claude-agent-sdk (>=0.1.0) ; python_version >= \"3.10\""]
+langsmith-pyo3 = ["langsmith-pyo3 (>=0.1.0rc2)"]
+openai-agents = ["openai-agents (>=0.0.3)"]
+otel = ["opentelemetry-api (>=1.30.0)", "opentelemetry-exporter-otlp-proto-http (>=1.30.0)", "opentelemetry-sdk (>=1.30.0)"]
+pytest = ["pytest (>=7.0.0)", "rich (>=13.9.4)", "vcrpy (>=7.0.0)"]
+vcr = ["vcrpy (>=7.0.0)"]
 
 [[package]]
 name = "language-data"
@@ -3600,6 +4042,53 @@ marisa-trie = ">=1.1.0"
 build = ["build", "twine"]
 test = ["pytest", "pytest-cov"]
 
+[[package]]
+name = "logfire"
+version = "4.6.0"
+description = "The best Python observability tool! 🪵🔥"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "logfire-4.6.0-py3-none-any.whl", hash = "sha256:d322844db7a2f1935976f2852a07e3753489ecc4e83fa288173b05a453bb1cbf"},
+    {file = "logfire-4.6.0.tar.gz", hash = "sha256:974bc8f4efd3aa9df2d0c7b1d53b35dc4612ff5cee2be6c40dd65e5c26eab694"},
+]
+
+[package.dependencies]
+executing = ">=2.0.1"
+opentelemetry-exporter-otlp-proto-http = ">=1.21.0,<1.37.0"
+opentelemetry-instrumentation = ">=0.41b0"
+opentelemetry-instrumentation-httpx = {version = ">=0.42b0", optional = true, markers = "extra == \"httpx\""}
+opentelemetry-sdk = ">=1.21.0,<1.37.0"
+protobuf = ">=4.23.4"
+rich = ">=13.4.2"
+tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
+typing-extensions = ">=4.1.0"
+
+[package.extras]
+aiohttp = ["opentelemetry-instrumentation-aiohttp-client (>=0.42b0)"]
+aiohttp-client = ["opentelemetry-instrumentation-aiohttp-client (>=0.42b0)"]
+aiohttp-server = ["opentelemetry-instrumentation-aiohttp-server (>=0.55b0)"]
+asgi = ["opentelemetry-instrumentation-asgi (>=0.42b0)"]
+asyncpg = ["opentelemetry-instrumentation-asyncpg (>=0.42b0)"]
+aws-lambda = ["opentelemetry-instrumentation-aws-lambda (>=0.42b0)"]
+celery = ["opentelemetry-instrumentation-celery (>=0.42b0)"]
+django = ["opentelemetry-instrumentation-asgi (>=0.42b0)", "opentelemetry-instrumentation-django (>=0.42b0)"]
+fastapi = ["opentelemetry-instrumentation-fastapi (>=0.42b0)"]
+flask = ["opentelemetry-instrumentation-flask (>=0.42b0)"]
+httpx = ["opentelemetry-instrumentation-httpx (>=0.42b0)"]
+mysql = ["opentelemetry-instrumentation-mysql (>=0.42b0)"]
+psycopg = ["opentelemetry-instrumentation-psycopg (>=0.42b0)", "packaging"]
+psycopg2 = ["opentelemetry-instrumentation-psycopg2 (>=0.42b0)", "packaging"]
+pymongo = ["opentelemetry-instrumentation-pymongo (>=0.42b0)"]
+redis = ["opentelemetry-instrumentation-redis (>=0.42b0)"]
+requests = ["opentelemetry-instrumentation-requests (>=0.42b0)"]
+sqlalchemy = ["opentelemetry-instrumentation-sqlalchemy (>=0.42b0)"]
+sqlite3 = ["opentelemetry-instrumentation-sqlite3 (>=0.42b0)"]
+starlette = ["opentelemetry-instrumentation-starlette (>=0.42b0)"]
+system-metrics = ["opentelemetry-instrumentation-system-metrics (>=0.42b0)"]
+wsgi = ["opentelemetry-instrumentation-wsgi (>=0.42b0)"]
+
 [[package]]
 name = "logfire-api"
 version = "3.16.0"
@@ -4028,29 +4517,32 @@ dev = ["meson-python (>=0.13.1,<0.17.0)", "pybind11 (>=2.13.2,!=2.13.3)", "setup
 
 [[package]]
 name = "mcp"
-version = "1.9.0"
+version = "1.21.0"
 description = "Model Context Protocol SDK"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "mcp-1.9.0-py3-none-any.whl", hash = "sha256:9dfb89c8c56f742da10a5910a1f64b0d2ac2c3ed2bd572ddb1cfab7f35957178"},
-    {file = "mcp-1.9.0.tar.gz", hash = "sha256:905d8d208baf7e3e71d70c82803b89112e321581bcd2530f9de0fe4103d28749"},
+    {file = "mcp-1.21.0-py3-none-any.whl", hash = "sha256:598619e53eb0b7a6513db38c426b28a4bdf57496fed04332100d2c56acade98b"},
+    {file = "mcp-1.21.0.tar.gz", hash = "sha256:bab0a38e8f8c48080d787233343f8d301b0e1e95846ae7dead251b2421d99855"},
 ]
 
 [package.dependencies]
 anyio = ">=4.5"
-httpx = ">=0.27"
+httpx = ">=0.27.1"
 httpx-sse = ">=0.4"
-pydantic = ">=2.7.2,<3.0.0"
+jsonschema = ">=4.20.0"
+pydantic = ">=2.11.0,<3.0.0"
 pydantic-settings = ">=2.5.2"
+pyjwt = {version = ">=2.10.1", extras = ["crypto"]}
 python-multipart = ">=0.0.9"
+pywin32 = {version = ">=310", markers = "sys_platform == \"win32\""}
 sse-starlette = ">=1.6.1"
 starlette = ">=0.27"
-uvicorn = {version = ">=0.23.1", markers = "sys_platform != \"emscripten\""}
+uvicorn = {version = ">=0.31.1", markers = "sys_platform != \"emscripten\""}
 
 [package.extras]
-cli = ["python-dotenv (>=1.0.0)", "typer (>=0.12.4)"]
+cli = ["python-dotenv (>=1.0.0)", "typer (>=0.16.0)"]
 rich = ["rich (>=13.9.4)"]
 ws = ["websockets (>=15.0.1)"]
 
@@ -4098,24 +4590,27 @@ psutil = {version = ">=4.0.0", markers = "sys_platform != \"cygwin\""}
 
 [[package]]
 name = "mistralai"
-version = "1.7.0"
+version = "1.9.11"
 description = "Python Client SDK for the Mistral AI API."
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "mistralai-1.7.0-py3-none-any.whl", hash = "sha256:e0e75ab8508598d69ae19b14d9d7e905db6259a2de3cf9204946a27e9bf81c5d"},
-    {file = "mistralai-1.7.0.tar.gz", hash = "sha256:94e3eb23c1d3ed398a95352062fd8c92993cc3754ed18e9a35b60aa3db0bd103"},
+    {file = "mistralai-1.9.11-py3-none-any.whl", hash = "sha256:7a3dc2b8ef3fceaa3582220234261b5c4e3e03a972563b07afa150e44a25a6d3"},
+    {file = "mistralai-1.9.11.tar.gz", hash = "sha256:3df9e403c31a756ec79e78df25ee73cea3eb15f86693773e16b16adaf59c9b8a"},
 ]
 
 [package.dependencies]
 eval-type-backport = ">=0.2.0"
 httpx = ">=0.28.1"
+invoke = ">=2.2.0,<3.0.0"
 pydantic = ">=2.10.3"
 python-dateutil = ">=2.8.2"
+pyyaml = ">=6.0.2,<7.0.0"
 typing-inspection = ">=0.4.0"
 
 [package.extras]
+agents = ["authlib (>=1.5.2,<2.0)", "griffe (>=1.7.3,<2.0)", "mcp (>=1.0,<2.0) ; python_version >= \"3.10\""]
 gcp = ["google-auth (>=2.27.0)", "requests (>=2.32.3)"]
 
 [[package]]
@@ -4529,6 +5024,21 @@ pyspark = ["pyspark (>=3.5.0)"]
 pyspark-connect = ["pyspark[connect] (>=3.5.0)"]
 sqlframe = ["sqlframe (>=3.22.0)"]
 
+[[package]]
+name = "nexus-rpc"
+version = "1.1.0"
+description = "Nexus Python SDK"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "nexus_rpc-1.1.0-py3-none-any.whl", hash = "sha256:d1b007af2aba186a27e736f8eaae39c03aed05b488084ff6c3d1785c9ba2ad38"},
+    {file = "nexus_rpc-1.1.0.tar.gz", hash = "sha256:d65ad6a2f54f14e53ebe39ee30555eaeb894102437125733fb13034a04a44553"},
+]
+
+[package.dependencies]
+typing-extensions = ">=4.12.2"
+
 [[package]]
 name = "numpy"
 version = "1.26.4"
@@ -4630,14 +5140,14 @@ sympy = "*"
 
 [[package]]
 name = "openai"
-version = "1.79.0"
+version = "1.109.1"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "openai-1.79.0-py3-none-any.whl", hash = "sha256:d5050b92d5ef83f869cb8dcd0aca0b2291c3413412500eec40c66981b3966992"},
-    {file = "openai-1.79.0.tar.gz", hash = "sha256:e3b627aa82858d3e42d16616edc22aa9f7477ee5eb3e6819e9f44a961d899a4c"},
+    {file = "openai-1.109.1-py3-none-any.whl", hash = "sha256:6bcaf57086cf59159b8e27447e4e7dd019db5d29a438072fbd49c290c7e65315"},
+    {file = "openai-1.109.1.tar.gz", hash = "sha256:d173ed8dbca665892a6db099b4a2dfac624f94d20a93f46eb0b56aae940ed869"},
 ]
 
 [package.dependencies]
@@ -4651,6 +5161,7 @@ tqdm = ">4"
 typing-extensions = ">=4.11,<5"
 
 [package.extras]
+aiohttp = ["aiohttp", "httpx-aiohttp (>=0.1.8)"]
 datalib = ["numpy (>=1)", "pandas (>=1.2.3)", "pandas-stubs (>=1.1.0.11)"]
 realtime = ["websockets (>=13,<16)"]
 voice-helpers = ["numpy (>=2.0.2)", "sounddevice (>=0.5.1)"]
@@ -4708,66 +5219,65 @@ opentelemetry-proto = "1.33.1"
 opentelemetry-sdk = ">=1.33.1,<1.34.0"
 
 [[package]]
-name = "opentelemetry-instrumentation"
-version = "0.54b1"
-description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
+name = "opentelemetry-exporter-otlp-proto-http"
+version = "1.33.1"
+description = "OpenTelemetry Collector Protobuf over HTTP Exporter"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "opentelemetry_instrumentation-0.54b1-py3-none-any.whl", hash = "sha256:a4ae45f4a90c78d7006c51524f57cd5aa1231aef031eae905ee34d5423f5b198"},
-    {file = "opentelemetry_instrumentation-0.54b1.tar.gz", hash = "sha256:7658bf2ff914b02f246ec14779b66671508125c0e4227361e56b5ebf6cef0aec"},
+    {file = "opentelemetry_exporter_otlp_proto_http-1.33.1-py3-none-any.whl", hash = "sha256:ebd6c523b89a2ecba0549adb92537cc2bf647b4ee61afbbd5a4c6535aa3da7cf"},
+    {file = "opentelemetry_exporter_otlp_proto_http-1.33.1.tar.gz", hash = "sha256:46622d964a441acb46f463ebdc26929d9dec9efb2e54ef06acdc7305e8593c38"},
 ]
 
 [package.dependencies]
-opentelemetry-api = ">=1.4,<2.0"
-opentelemetry-semantic-conventions = "0.54b1"
-packaging = ">=18.0"
-wrapt = ">=1.0.0,<2.0.0"
+deprecated = ">=1.2.6"
+googleapis-common-protos = ">=1.52,<2.0"
+opentelemetry-api = ">=1.15,<2.0"
+opentelemetry-exporter-otlp-proto-common = "1.33.1"
+opentelemetry-proto = "1.33.1"
+opentelemetry-sdk = ">=1.33.1,<1.34.0"
+requests = ">=2.7,<3.0"
 
 [[package]]
-name = "opentelemetry-instrumentation-asgi"
+name = "opentelemetry-instrumentation"
 version = "0.54b1"
-description = "ASGI instrumentation for OpenTelemetry"
+description = "Instrumentation Tools & Auto Instrumentation for OpenTelemetry Python"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "opentelemetry_instrumentation_asgi-0.54b1-py3-none-any.whl", hash = "sha256:84674e822b89af563b283a5283c2ebb9ed585d1b80a1c27fb3ac20b562e9f9fc"},
-    {file = "opentelemetry_instrumentation_asgi-0.54b1.tar.gz", hash = "sha256:ab4df9776b5f6d56a78413c2e8bbe44c90694c67c844a1297865dc1bd926ed3c"},
+    {file = "opentelemetry_instrumentation-0.54b1-py3-none-any.whl", hash = "sha256:a4ae45f4a90c78d7006c51524f57cd5aa1231aef031eae905ee34d5423f5b198"},
+    {file = "opentelemetry_instrumentation-0.54b1.tar.gz", hash = "sha256:7658bf2ff914b02f246ec14779b66671508125c0e4227361e56b5ebf6cef0aec"},
 ]
 
 [package.dependencies]
-asgiref = ">=3.0,<4.0"
-opentelemetry-api = ">=1.12,<2.0"
-opentelemetry-instrumentation = "0.54b1"
+opentelemetry-api = ">=1.4,<2.0"
 opentelemetry-semantic-conventions = "0.54b1"
-opentelemetry-util-http = "0.54b1"
-
-[package.extras]
-instruments = ["asgiref (>=3.0,<4.0)"]
+packaging = ">=18.0"
+wrapt = ">=1.0.0,<2.0.0"
 
 [[package]]
-name = "opentelemetry-instrumentation-fastapi"
+name = "opentelemetry-instrumentation-httpx"
 version = "0.54b1"
-description = "OpenTelemetry FastAPI Instrumentation"
+description = "OpenTelemetry HTTPX Instrumentation"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "opentelemetry_instrumentation_fastapi-0.54b1-py3-none-any.whl", hash = "sha256:fb247781cfa75fd09d3d8713c65e4a02bd1e869b00e2c322cc516d4b5429860c"},
-    {file = "opentelemetry_instrumentation_fastapi-0.54b1.tar.gz", hash = "sha256:1fcad19cef0db7092339b571a59e6f3045c9b58b7fd4670183f7addc459d78df"},
+    {file = "opentelemetry_instrumentation_httpx-0.54b1-py3-none-any.whl", hash = "sha256:99b8e43ebf1d945ca298d84d32298ba26d1c3431738cea9f69a26c442661745f"},
+    {file = "opentelemetry_instrumentation_httpx-0.54b1.tar.gz", hash = "sha256:37e1cd0190f98508d960ec1667c9f148f8c8ad9a6cab127b57c9ad92c37493c3"},
 ]
 
 [package.dependencies]
 opentelemetry-api = ">=1.12,<2.0"
 opentelemetry-instrumentation = "0.54b1"
-opentelemetry-instrumentation-asgi = "0.54b1"
 opentelemetry-semantic-conventions = "0.54b1"
 opentelemetry-util-http = "0.54b1"
+wrapt = ">=1.0.0,<2.0.0"
 
 [package.extras]
-instruments = ["fastapi (>=0.58,<1.0)"]
+instruments = ["httpx (>=0.18.0)"]
 
 [[package]]
 name = "opentelemetry-proto"
@@ -4911,6 +5421,64 @@ files = [
     {file = "orjson-3.10.18.tar.gz", hash = "sha256:e8da3947d92123eda795b68228cafe2724815621fe35e8e320a9e9593a4bcd53"},
 ]
 
+[[package]]
+name = "ormsgpack"
+version = "1.12.0"
+description = ""
+optional = false
+python-versions = ">=3.10"
+groups = ["main"]
+files = [
+    {file = "ormsgpack-1.12.0-cp310-cp310-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:e08904c232358b94a682ccfbb680bc47d3fd5c424bb7dccb65974dd20c95e8e1"},
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+]
+
 [[package]]
 name = "overrides"
 version = "7.7.0"
@@ -5180,6 +5748,23 @@ files = [
 dev = ["pre-commit", "tox"]
 testing = ["coverage", "pytest", "pytest-benchmark"]
 
+[[package]]
+name = "poly-eip712-structs"
+version = "0.0.1"
+description = "A python library for EIP712 objects"
+optional = false
+python-versions = ">=3.9.10"
+groups = ["main"]
+files = [
+    {file = "poly_eip712_structs-0.0.1-py3-none-any.whl", hash = "sha256:11e714e8c25c64d22dcb8a606c87cf052e7154caf701652d29687ddaf7dee342"},
+    {file = "poly_eip712_structs-0.0.1.tar.gz", hash = "sha256:d9193766fde497b1ee01c79a50092733a34b7a94bed090deb5d3c1b1e41f6d8c"},
+]
+
+[package.dependencies]
+eth-utils = ">=4.1.1"
+pycryptodome = ">=3.20.0"
+pytest = "*"
+
 [[package]]
 name = "port-for"
 version = "0.7.4"
@@ -5219,24 +5804,24 @@ test = ["anthropic", "coverage", "django", "flake8", "freezegun (==1.5.1)", "lan
 
 [[package]]
 name = "prediction-market-agent-tooling"
-version = "0.66.4"
+version = "0.69.19"
 description = "Tools to benchmark, deploy and monitor prediction market agents."
 optional = false
 python-versions = "<3.13,>=3.10"
 groups = ["main"]
 files = [
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 autoflake = ">=2.2.1,<3.0.0"
 base58 = ">=1.0.2,<2.0"
-cowdao-cowpy = "1.0.0rc5"
+cowdao-cowpy = "1.0.1"
 cron-validator = ">=1.0.8,<2.0.0"
-eth-account = ">=0.8.0,<0.12.0"
+eth-account = ">=0.13.0,<0.14.0"
 eth-keys = ">=0.6.1,<0.7.0"
-eth-typing = ">=3.0.0,<4.0.0"
+eth-typing = ">=5.0.0,<6.0.0"
 functions-framework = ">=3.5.0,<4.0.0"
 google-api-python-client = {version = "2.95.0", optional = true, markers = "extra == \"google\""}
 google-cloud-functions = ">=1.16.0,<2.0.0"
@@ -5245,10 +5830,10 @@ google-cloud-secret-manager = ">=2.18.2,<3.0.0"
 hishel = ">=0.0.31,<0.0.32"
 httpx = ">=0.25.2,<1.0.0"
 isort = ">=5.13.2,<6.0.0"
-langchain = {version = ">=0.3.0,<0.4.0", optional = true, markers = "extra == \"langchain\""}
+langchain = {version = ">=1.0.0,<2.0.0", optional = true, markers = "extra == \"langchain\""}
 langchain-community = ">=0.0.19"
-langchain-openai = {version = ">=0.3.0,<0.4.0", optional = true, markers = "extra == \"langchain\""}
-langfuse = ">=2.42.0,<3.0.0"
+langchain-openai = {version = ">=1.0.0,<2.0.0", optional = true, markers = "extra == \"langchain\""}
+langfuse = ">=3.0.0,<4.0.0"
 loguru = ">=0.7.2,<0.8.0"
 loky = ">=3.4.1,<4.0.0"
 numpy = ">=1.26.4,<2.0.0"
@@ -5257,14 +5842,16 @@ prompt-toolkit = ">=3.0.43,<4.0.0"
 proto-plus = ">=1.0.0,<2.0.0"
 protobuf = ">=5.0.0,<6.0.0"
 psycopg2-binary = ">=2.9.9,<3.0.0"
+py-clob-client = ">=0.24.0,<0.25.0"
 pydantic = ">=2.6.1,<3.0.0"
+pydantic-ai = ">=1.0.3,<2.0.0"
 pydantic-settings = ">=2.4.0,<3.0.0"
 pymongo = ">=4.8.0,<5.0.0"
 pytest-postgresql = ">=6.1.1,<7.0.0"
 python-dateutil = ">=2.9.0.post0,<3.0.0"
 python-json-logger = ">=3.3.0,<4.0.0"
-safe-cli = ">=1.0.0,<2.0.0"
-safe-eth-py = ">=6.0.0b41,<7.0.0"
+safe-cli = ">=1.5.0,<2.0.0"
+safe-eth-py = ">=7.8.0,<8.0.0"
 scikit-learn = ">=1.3.1,<2.0.0"
 sqlmodel = ">=0.0.22,<0.0.23"
 streamlit = ">=1.31.0,<2.0.0"
@@ -5277,11 +5864,11 @@ types-cachetools = ">=5.5.0.20240820,<6.0.0.0"
 types-python-dateutil = ">=2.9.0.20240906,<3.0.0.0"
 types-pytz = ">=2024.1.0.20240203,<2025.0.0.0"
 types-requests = ">=2.31.0.0,<3.0.0.0"
-web3 = ">=6.15.1,<7.0.0"
+web3 = ">=6,<8"
 
 [package.extras]
 google = ["google-api-python-client (==2.95.0)"]
-langchain = ["langchain (>=0.3.0,<0.4.0)", "langchain-openai (>=0.3.0,<0.4.0)"]
+langchain = ["langchain (>=1.0.0,<2.0.0)", "langchain-openai (>=1.0.0,<2.0.0)"]
 openai = ["openai (>=1.0.0,<2.0.0)"]
 optuna = ["optuna (>=4.1.0,<5.0.0)"]
 
@@ -5620,6 +6207,25 @@ files = [
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 ]
 
+[[package]]
+name = "py-clob-client"
+version = "0.24.0"
+description = "Python client for the Polymarket CLOB"
+optional = false
+python-versions = ">=3.9.10"
+groups = ["main"]
+files = [
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+
+[package.dependencies]
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+eth-utils = ">=4.1.1"
+poly_eip712_structs = ">=0.0.1"
+py-order-utils = ">=0.3.2"
+python-dotenv = "*"
+requests = "*"
+
 [[package]]
 name = "py-ecc"
 version = "8.0.0"
@@ -5673,6 +6279,24 @@ eth = ["cached-property (>=1.5.1)", "ckzg (>=0.4.3)", "eth-bloom (>=1.0.3)", "et
 eth-extra = ["blake2b-py (>=0.2.0)", "coincurve (>=18.0.0)"]
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+[[package]]
+name = "py-order-utils"
+version = "0.3.2"
+description = "Python utilities used to generate and sign orders from Polymarket's Exchange"
+optional = false
+python-versions = ">=3.9.10"
+groups = ["main"]
+files = [
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+
+[package.dependencies]
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+eth-utils = ">=4.1.1"
+poly-eip712-structs = "*"
+pytest = "*"
+
 [[package]]
 name = "pyarrow"
 version = "20.0.0"
@@ -5823,19 +6447,236 @@ websockets = ["websockets (>=12.0,<13)"]
 websurfer = ["beautifulsoup4", "markdownify", "pathvalidate", "pdfminer.six"]
 
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-version = "0.9.7"
-description = "Handlebars.js templating for Python 3 and 2"
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+]
+
 [[package]]
 name = "pydantic"
 version = "2.11.4"
@@ -5911,71 +6803,89 @@ timezone = ["tzdata ; python_version >= \"3.9\" and platform_system == \"Windows
 
 [[package]]
 name = "pydantic-ai"
-version = "0.1.11"
+version = "1.5.0"
 description = "Agent Framework / shim to use Pydantic with LLMs"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "pydantic_ai-0.1.11-py3-none-any.whl", hash = "sha256:168bed025d1fd4759d7bab1c38aae5484ad14830625f0d8acd4f8235ee14dcb4"},
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+    {file = "pydantic_ai-1.5.0-py3-none-any.whl", hash = "sha256:f6d9a3741edfb8a59789fd7b30a56917326e5f7d26c2a84e8fecf8fca99bac82"},
+    {file = "pydantic_ai-1.5.0.tar.gz", hash = "sha256:e16bda3c6e0c117f16013c654b4bcff04efb2d8482a9a220926d1faed37902ae"},
 ]
 
 [package.dependencies]
-pydantic-ai-slim = {version = "0.1.11", extras = ["anthropic", "bedrock", "cli", "cohere", "evals", "groq", "mcp", "mistral", "openai", "vertexai"]}
+pydantic-ai-slim = {version = "1.5.0", extras = ["ag-ui", "anthropic", "bedrock", "cli", "cohere", "evals", "google", "groq", "huggingface", "logfire", "mcp", "mistral", "openai", "retries", "temporal", "vertexai"]}
 
 [package.extras]
-examples = ["pydantic-ai-examples (==0.1.11)"]
-logfire = ["logfire (>=3.11.0)"]
+a2a = ["fasta2a (>=0.4.1)"]
+dbos = ["pydantic-ai-slim[dbos] (==1.5.0)"]
+examples = ["pydantic-ai-examples (==1.5.0)"]
+prefect = ["pydantic-ai-slim[prefect] (==1.5.0)"]
 
 [[package]]
 name = "pydantic-ai-slim"
-version = "0.1.11"
+version = "1.5.0"
 description = "Agent Framework / shim to use Pydantic with LLMs, slim package"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
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-    {file = "pydantic_ai_slim-0.1.11.tar.gz", hash = "sha256:f5c442fdadb2751abec2a580529e4b0699cf6287373e614d6f6a72cffd0fec38"},
+    {file = "pydantic_ai_slim-1.5.0-py3-none-any.whl", hash = "sha256:5c896dd7e2b7945a339565441269a10fb5103501ca11ae18acb0f72ace2e535e"},
+    {file = "pydantic_ai_slim-1.5.0.tar.gz", hash = "sha256:e75f9fecde384296f7cd5ce47b320f96df893395f4d6542ed03c43424a3cc2e2"},
 ]
 
 [package.dependencies]
-anthropic = {version = ">=0.49.0", optional = true, markers = "extra == \"anthropic\""}
+ag-ui-protocol = {version = ">=0.1.8", optional = true, markers = "extra == \"ag-ui\""}
+anthropic = {version = ">=0.70.0", optional = true, markers = "extra == \"anthropic\""}
 argcomplete = {version = ">=3.5.0", optional = true, markers = "extra == \"cli\""}
-boto3 = {version = ">=1.35.74", optional = true, markers = "extra == \"bedrock\""}
-cohere = {version = ">=5.13.11", optional = true, markers = "platform_system != \"Emscripten\" and extra == \"cohere\""}
-eval-type-backport = ">=0.2.0"
+boto3 = {version = ">=1.39.0", optional = true, markers = "extra == \"bedrock\""}
+cohere = {version = ">=5.18.0", optional = true, markers = "platform_system != \"Emscripten\" and extra == \"cohere\""}
 exceptiongroup = {version = "*", markers = "python_version < \"3.11\""}
+genai-prices = ">=0.0.35"
 google-auth = {version = ">=2.36.0", optional = true, markers = "extra == \"vertexai\""}
+google-genai = {version = ">=1.46.0", optional = true, markers = "extra == \"google\""}
 griffe = ">=1.3.2"
-groq = {version = ">=0.15.0", optional = true, markers = "extra == \"groq\""}
+groq = {version = ">=0.25.0", optional = true, markers = "extra == \"groq\""}
 httpx = ">=0.27"
-mcp = {version = ">=1.6.0", optional = true, markers = "python_version >= \"3.10\" and extra == \"mcp\""}
-mistralai = {version = ">=1.2.5", optional = true, markers = "extra == \"mistral\""}
-openai = {version = ">=1.75.0", optional = true, markers = "extra == \"openai\""}
+huggingface-hub = {version = ">=0.33.5", extras = ["inference"], optional = true, markers = "extra == \"huggingface\""}
+logfire = {version = ">=3.14.1", extras = ["httpx"], optional = true, markers = "extra == \"logfire\""}
+mcp = {version = ">=1.12.3", optional = true, markers = "extra == \"mcp\""}
+mistralai = {version = ">=1.9.10", optional = true, markers = "extra == \"mistral\""}
+openai = {version = ">=1.107.2", optional = true, markers = "extra == \"openai\""}
 opentelemetry-api = ">=1.28.0"
 prompt-toolkit = {version = ">=3", optional = true, markers = "extra == \"cli\""}
 pydantic = ">=2.10"
-pydantic-evals = {version = "0.1.11", optional = true, markers = "extra == \"evals\""}
-pydantic-graph = "0.1.11"
+pydantic-evals = {version = "1.5.0", optional = true, markers = "extra == \"evals\""}
+pydantic-graph = "1.5.0"
+pyperclip = {version = ">=1.9.0", optional = true, markers = "extra == \"cli\""}
 requests = {version = ">=2.32.2", optional = true, markers = "extra == \"vertexai\""}
 rich = {version = ">=13", optional = true, markers = "extra == \"cli\""}
+starlette = {version = ">=0.45.3", optional = true, markers = "extra == \"ag-ui\""}
+temporalio = {version = "1.18.0", optional = true, markers = "extra == \"temporal\""}
+tenacity = {version = ">=8.2.3", optional = true, markers = "extra == \"retries\""}
 typing-inspection = ">=0.4.0"
 
 [package.extras]
-anthropic = ["anthropic (>=0.49.0)"]
-bedrock = ["boto3 (>=1.35.74)"]
-cli = ["argcomplete (>=3.5.0)", "prompt-toolkit (>=3)", "rich (>=13)"]
-cohere = ["cohere (>=5.13.11) ; platform_system != \"Emscripten\""]
-duckduckgo = ["duckduckgo-search (>=7.0.0)"]
-evals = ["pydantic-evals (==0.1.11)"]
-groq = ["groq (>=0.15.0)"]
-logfire = ["logfire (>=3.11.0)"]
-mcp = ["mcp (>=1.6.0) ; python_version >= \"3.10\""]
-mistral = ["mistralai (>=1.2.5)"]
-openai = ["openai (>=1.75.0)"]
+a2a = ["fasta2a (>=0.4.1)"]
+ag-ui = ["ag-ui-protocol (>=0.1.8)", "starlette (>=0.45.3)"]
+anthropic = ["anthropic (>=0.70.0)"]
+bedrock = ["boto3 (>=1.39.0)"]
+cli = ["argcomplete (>=3.5.0)", "prompt-toolkit (>=3)", "pyperclip (>=1.9.0)", "rich (>=13)"]
+cohere = ["cohere (>=5.18.0) ; platform_system != \"Emscripten\""]
+dbos = ["dbos (>=1.14.0)"]
+duckduckgo = ["ddgs (>=9.0.0)"]
+evals = ["pydantic-evals (==1.5.0)"]
+google = ["google-genai (>=1.46.0)"]
+groq = ["groq (>=0.25.0)"]
+huggingface = ["huggingface-hub[inference] (>=0.33.5)"]
+logfire = ["logfire[httpx] (>=3.14.1)"]
+mcp = ["mcp (>=1.12.3)"]
+mistral = ["mistralai (>=1.9.10)"]
+openai = ["openai (>=1.107.2)"]
+prefect = ["prefect (>=3.4.21)"]
+retries = ["tenacity (>=8.2.3)"]
 tavily = ["tavily-python (>=0.5.0)"]
+temporal = ["temporalio (==1.18.0)"]
 vertexai = ["google-auth (>=2.36.0)", "requests (>=2.32.2)"]
 
 [[package]]
@@ -6092,56 +7002,55 @@ typing-extensions = ">=4.6.0,<4.7.0 || >4.7.0"
 
 [[package]]
 name = "pydantic-evals"
-version = "0.1.11"
+version = "1.5.0"
 description = "Framework for evaluating stochastic code execution, especially code making use of LLMs"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "pydantic_evals-0.1.11-py3-none-any.whl", hash = "sha256:8d6e45c90b24d0dc7fd553766f303eee4fa005ed02d5165ae1835bc95b81d760"},
-    {file = "pydantic_evals-0.1.11.tar.gz", hash = "sha256:8ff21c42f060415e3ef0f511f3bfefedd8b98a0ccf5b2368e2570218ab79f042"},
+    {file = "pydantic_evals-1.5.0-py3-none-any.whl", hash = "sha256:02b833b1e239ff18a70fcb1209812f282ba59f0cb7830badf7324e078ccbb888"},
+    {file = "pydantic_evals-1.5.0.tar.gz", hash = "sha256:f5b1e6606d152b211e4b59eee10a49d976e0f092030cc3f7b86441e713b3a1c6"},
 ]
 
 [package.dependencies]
 anyio = ">=0"
-eval-type-backport = {version = ">=0", markers = "python_version < \"3.11\""}
-logfire-api = ">=1.2.0"
+logfire-api = ">=3.14.1"
 pydantic = ">=2.10"
-pydantic-ai-slim = "0.1.11"
+pydantic-ai-slim = "1.5.0"
 pyyaml = ">=6.0.2"
 rich = ">=13.9.4"
 
 [package.extras]
-logfire = ["logfire (>=2.3)"]
+logfire = ["logfire (>=3.14.1)"]
 
 [[package]]
 name = "pydantic-graph"
-version = "0.1.11"
+version = "1.5.0"
 description = "Graph and state machine library"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "pydantic_graph-0.1.11-py3-none-any.whl", hash = "sha256:a48612e79a0883f2539c6798f399c59073305e0b64be26fd3fd6bc499fc3de49"},
-    {file = "pydantic_graph-0.1.11.tar.gz", hash = "sha256:1d7ef9f330bab3aa76835211651e170464ae3419566e6b950c51b3ff5930cdb4"},
+    {file = "pydantic_graph-1.5.0-py3-none-any.whl", hash = "sha256:d850955c5273bd91b8e540a965139fa07dfb093fa9e963f5df554b5edbd74836"},
+    {file = "pydantic_graph-1.5.0.tar.gz", hash = "sha256:747802da8603c83254fb32ec3ec1a0fa1c085e3655521af3fc57c1b2335e2ab9"},
 ]
 
 [package.dependencies]
 httpx = ">=0.27"
-logfire-api = ">=1.2.0"
+logfire-api = ">=3.14.1"
 pydantic = ">=2.10"
 typing-inspection = ">=0.4.0"
 
 [[package]]
 name = "pydantic-settings"
-version = "2.9.1"
+version = "2.12.0"
 description = "Settings management using Pydantic"
 optional = false
-python-versions = ">=3.9"
+python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "pydantic_settings-2.9.1-py3-none-any.whl", hash = "sha256:59b4f431b1defb26fe620c71a7d3968a710d719f5f4cdbbdb7926edeb770f6ef"},
-    {file = "pydantic_settings-2.9.1.tar.gz", hash = "sha256:c509bf79d27563add44e8446233359004ed85066cd096d8b510f715e6ef5d268"},
+    {file = "pydantic_settings-2.12.0-py3-none-any.whl", hash = "sha256:fddb9fd99a5b18da837b29710391e945b1e30c135477f484084ee513adb93809"},
+    {file = "pydantic_settings-2.12.0.tar.gz", hash = "sha256:005538ef951e3c2a68e1c08b292b5f2e71490def8589d4221b95dab00dafcfd0"},
 ]
 
 [package.dependencies]
@@ -6204,14 +7113,35 @@ files = [
 windows-terminal = ["colorama (>=0.4.6)"]
 
 [[package]]
-name = "pymeta3"
-version = "0.5.1"
-description = "Pattern-matching language based on OMeta for Python 3 and 2"
+name = "pyjwt"
+version = "2.10.1"
+description = "JSON Web Token implementation in Python"
 optional = false
-python-versions = "*"
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "PyJWT-2.10.1-py3-none-any.whl", hash = "sha256:dcdd193e30abefd5debf142f9adfcdd2b58004e644f25406ffaebd50bd98dacb"},
+    {file = "pyjwt-2.10.1.tar.gz", hash = "sha256:3cc5772eb20009233caf06e9d8a0577824723b44e6648ee0a2aedb6cf9381953"},
+]
+
+[package.dependencies]
+cryptography = {version = ">=3.4.0", optional = true, markers = "extra == \"crypto\""}
+
+[package.extras]
+crypto = ["cryptography (>=3.4.0)"]
+dev = ["coverage[toml] (==5.0.4)", "cryptography (>=3.4.0)", "pre-commit", "pytest (>=6.0.0,<7.0.0)", "sphinx", "sphinx-rtd-theme", "zope.interface"]
+docs = ["sphinx", "sphinx-rtd-theme", "zope.interface"]
+tests = ["coverage[toml] (==5.0.4)", "pytest (>=6.0.0,<7.0.0)"]
+
+[[package]]
+name = "pymerkle"
+version = "5.0.3"
+description = "merkle-tree cryptography"
+optional = false
+python-versions = ">=3.6"
 groups = ["main"]
 files = [
-    {file = "PyMeta3-0.5.1.tar.gz", hash = "sha256:18bda326d9a9bbf587bfc0ee0bc96864964d78b067288bcf55d4d98681d05bcb"},
+    {file = "pymerkle-5.0.3.tar.gz", hash = "sha256:5de1ee59882eec729b98074f074910c177d19939a0a5502ded0af396a67aca21"},
 ]
 
 [[package]]
@@ -6294,6 +7224,22 @@ snappy = ["python-snappy"]
 test = ["pytest (>=8.2)", "pytest-asyncio (>=0.24.0)"]
 zstd = ["zstandard"]
 
+[[package]]
+name = "pymultihash"
+version = "0.8.2"
+description = "Python implementation of the multihash specification"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "pymultihash-0.8.2-py3-none-any.whl", hash = "sha256:f7fa840b24bd6acbd6b073fcd330f10e15619387297babf1dd13ca4dae6e8209"},
+    {file = "pymultihash-0.8.2.tar.gz", hash = "sha256:49c75a1ae9ecc6d22d259064d4597b3685da3f0258f4ded632e03a3a79af215b"},
+]
+
+[package.extras]
+blake2 = ["pyblake2"]
+sha3 = ["pysha3"]
+
 [[package]]
 name = "pyparsing"
 version = "3.2.3"
@@ -6309,6 +7255,18 @@ files = [
 [package.extras]
 diagrams = ["jinja2", "railroad-diagrams"]
 
+[[package]]
+name = "pyperclip"
+version = "1.11.0"
+description = "A cross-platform clipboard module for Python. (Only handles plain text for now.)"
+optional = false
+python-versions = "*"
+groups = ["main"]
+files = [
+    {file = "pyperclip-1.11.0-py3-none-any.whl", hash = "sha256:299403e9ff44581cb9ba2ffeed69c7aa96a008622ad0c46cb575ca75b5b84273"},
+    {file = "pyperclip-1.11.0.tar.gz", hash = "sha256:244035963e4428530d9e3a6101a1ef97209c6825edab1567beac148ccc1db1b6"},
+]
+
 [[package]]
 name = "pypika"
 version = "0.48.9"
@@ -6409,24 +7367,6 @@ pytest = ">=8.2,<9"
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1)"]
 testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
-[[package]]
-name = "pytest-mock"
-version = "3.14.0"
-description = "Thin-wrapper around the mock package for easier use with pytest"
-optional = false
-python-versions = ">=3.8"
-groups = ["main"]
-files = [
-    {file = "pytest-mock-3.14.0.tar.gz", hash = "sha256:2719255a1efeceadbc056d6bf3df3d1c5015530fb40cf347c0f9afac88410bd0"},
-    {file = "pytest_mock-3.14.0-py3-none-any.whl", hash = "sha256:0b72c38033392a5f4621342fe11e9219ac11ec9d375f8e2a0c164539e0d70f6f"},
-]
-
-[package.dependencies]
-pytest = ">=6.2.5"
-
-[package.extras]
-dev = ["pre-commit", "pytest-asyncio", "tox"]
-
 [[package]]
 name = "pytest-postgresql"
 version = "6.1.1"
@@ -6740,19 +7680,19 @@ files = [
 
 [[package]]
 name = "requests"
-version = "2.32.3"
+version = "2.32.5"
 description = "Python HTTP for Humans."
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "requests-2.32.3-py3-none-any.whl", hash = "sha256:70761cfe03c773ceb22aa2f671b4757976145175cdfca038c02654d061d6dcc6"},
-    {file = "requests-2.32.3.tar.gz", hash = "sha256:55365417734eb18255590a9ff9eb97e9e1da868d4ccd6402399eaf68af20a760"},
+    {file = "requests-2.32.5-py3-none-any.whl", hash = "sha256:2462f94637a34fd532264295e186976db0f5d453d1cdd31473c85a6a161affb6"},
+    {file = "requests-2.32.5.tar.gz", hash = "sha256:dbba0bac56e100853db0ea71b82b4dfd5fe2bf6d3754a8893c3af500cec7d7cf"},
 ]
 
 [package.dependencies]
 certifi = ">=2017.4.17"
-charset-normalizer = ">=2,<4"
+charset_normalizer = ">=2,<4"
 idna = ">=2.5,<4"
 urllib3 = ">=1.21.1,<3"
 
@@ -6976,14 +7916,14 @@ pyasn1 = ">=0.1.3"
 
 [[package]]
 name = "s3transfer"
-version = "0.12.0"
+version = "0.14.0"
 description = "An Amazon S3 Transfer Manager"
 optional = false
 python-versions = ">=3.9"
 groups = ["main"]
 files = [
-    {file = "s3transfer-0.12.0-py3-none-any.whl", hash = "sha256:35b314d7d82865756edab59f7baebc6b477189e6ab4c53050e28c1de4d9cce18"},
-    {file = "s3transfer-0.12.0.tar.gz", hash = "sha256:8ac58bc1989a3fdb7c7f3ee0918a66b160d038a147c7b5db1500930a607e9a1c"},
+    {file = "s3transfer-0.14.0-py3-none-any.whl", hash = "sha256:ea3b790c7077558ed1f02a3072fb3cb992bbbd253392f4b6e9e8976941c7d456"},
+    {file = "s3transfer-0.14.0.tar.gz", hash = "sha256:eff12264e7c8b4985074ccce27a3b38a485bb7f7422cc8046fee9be4983e4125"},
 ]
 
 [package.dependencies]
@@ -6994,41 +7934,41 @@ crt = ["botocore[crt] (>=1.37.4,<2.0a.0)"]
 
 [[package]]
 name = "safe-cli"
-version = "1.4.0"
+version = "1.8.0"
 description = "Command Line Interface for Safe"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "safe_cli-1.4.0-py3-none-any.whl", hash = "sha256:c65e136de57433e06ce8d0a85339b49893731ac41127f1ab66fe1bf6feba2153"},
-    {file = "safe_cli-1.4.0.tar.gz", hash = "sha256:47f07d5dcfdc103cc08ad0a28f60b3d5e924f2b6ba4b32f49815ab026a090996"},
+    {file = "safe_cli-1.8.0-py3-none-any.whl", hash = "sha256:3724cbdfa9b651b7948f49b1622a948ef8aa7984ef909a0f11e13dedeeb984ef"},
+    {file = "safe_cli-1.8.0.tar.gz", hash = "sha256:c9c0e373ee2dd54729e77c9a7fd664d1e26d2e111656ca82743dfb2b805be409"},
 ]
 
 [package.dependencies]
 art = ">=6"
 colorama = ">=0.4"
-hexbytes = ">=0.2.3,<0.4.0"
+hexbytes = ">1"
 prompt-toolkit = ">=3"
 pygments = ">=2"
 requests = ">=2"
-safe-eth-py = ">=6.0.0b41"
+safe-eth-py = ">=7"
 tabulate = ">=0.8"
-typer = "0.12.5"
+typer = ">=0.14.0"
 
 [package.extras]
-ledger = ["ledgereth (==0.9.1)"]
-trezor = ["trezor (==0.13.9)"]
+ledger = ["ledgereth (==0.10.0)"]
+trezor = ["trezor (==0.13.10)"]
 
 [[package]]
 name = "safe-eth-py"
-version = "6.4.0"
+version = "7.15.0"
 description = "Safe Ecosystem Foundation utilities for Ethereum projects"
 optional = false
 python-versions = ">=3.10"
 groups = ["main"]
 files = [
-    {file = "safe_eth_py-6.4.0-py3-none-any.whl", hash = "sha256:a667e318c9cac7ba10747a9f372403a8800a06d67c0c9551972c9976253ae518"},
-    {file = "safe_eth_py-6.4.0.tar.gz", hash = "sha256:75363d171341e50abe7a55ca03e86382f6e70c8b50c492943985799ffcfa1c82"},
+    {file = "safe_eth_py-7.15.0-py3-none-any.whl", hash = "sha256:5b168717fbc6919f29b2df8d3566b22048d589dd6b89e57cd0c39fb4b5fb4f6c"},
+    {file = "safe_eth_py-7.15.0.tar.gz", hash = "sha256:8a48d7b8a6f7bb067c33adca828341c31b5dd180efe18db5a08729d242bb3727"},
 ]
 
 [package.dependencies]
@@ -7036,7 +7976,7 @@ packaging = "*"
 py-evm = ">=0.7.0a1"
 requests = ">=2"
 safe-pysha3 = ">=1.0.0"
-web3 = ">=6.2.0,<7.0.0"
+web3 = ">=7"
 
 [package.extras]
 django = ["django (>=2)", "django-filter (>=2)", "djangorestframework (>=2)"]
@@ -7050,6 +7990,16 @@ python-versions = "*"
 groups = ["main"]
 files = [
     {file = "safe-pysha3-1.0.4.tar.gz", hash = "sha256:e429146b1edd198b2ca934a2046a65656c5d31b0ec894bbd6055127f4deaff17"},
+    {file = "safe_pysha3-1.0.4-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:91282e6197cb69d309d87c3682d4926b0316be1146c4e8845b1a8c685173da57"},
+    {file = "safe_pysha3-1.0.4-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:db16291ea5702dd080e3d3bd65e60aa8c50fb75ccbb58fb4342f44b2bb4dea4f"},
+    {file = "safe_pysha3-1.0.4-cp311-cp311-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:9e6253f44cc665d5a07c0bdff84ec9545e28410fac26295f0fac30fdce6245b0"},
+    {file = "safe_pysha3-1.0.4-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:3251f444cf3fd0cffadd71fd3f66cec0354c3c6f5553916c1d7f73fd99c2732b"},
+    {file = "safe_pysha3-1.0.4-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:941d3c3b19c71c764121e950f44df9bfed5b31d84d04bd1620e9a046a9cb6e17"},
+    {file = "safe_pysha3-1.0.4-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:c9f8bb82919a4afcefb9a034809b5f17b58e99b37da90937da2d366cd76bcca4"},
+    {file = "safe_pysha3-1.0.4-cp313-cp313-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:cde1eb8c19cd8f0a6e6bbf4903ed5119e700d1d856392435f31d5fed953c1f0a"},
+    {file = "safe_pysha3-1.0.4-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:224bc7b1fce08301cb4af7dd3d6c48ce1dfc7e97b9c0f1ac8d62aafb92e62a15"},
+    {file = "safe_pysha3-1.0.4-cp39-cp39-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:7c39621ea320dbf3ac600da8ce68615f8ed1bfb0cdba34e4aaf8d04513bf35e5"},
+    {file = "safe_pysha3-1.0.4-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:c13bca78d8307024f21ea73cd70115f392c21d1b431abc1b63a786217c888e7d"},
 ]
 
 [[package]]
@@ -7710,6 +8660,35 @@ httpx = "*"
 requests = "*"
 tiktoken = ">=0.5.1"
 
+[[package]]
+name = "temporalio"
+version = "1.18.0"
+description = "Temporal.io Python SDK"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "temporalio-1.18.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:ac5d30d8b010c9b042065ea1259da7638db1a0a25e81ee4be0671a393ed329c5"},
+    {file = "temporalio-1.18.0-cp39-abi3-macosx_11_0_arm64.whl", hash = "sha256:19315d192247230c9bd7c60a566c2b3a80ad4d9de891c6aa13df63d72d3ec169"},
+    {file = "temporalio-1.18.0-cp39-abi3-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a023b25033e48b2e43f623a78737047a45b8cb553f69f457d09272fce5c723da"},
+    {file = "temporalio-1.18.0-cp39-abi3-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:695211dddbcffc20077d5b3b9a9b41bd09f60393c4ff211bcc7d6d895d607cc1"},
+    {file = "temporalio-1.18.0-cp39-abi3-win_amd64.whl", hash = "sha256:e3f691bd0a01a22c0fe40e87b6236cc8a292628e3a5a490880d1bf94709249c9"},
+    {file = "temporalio-1.18.0.tar.gz", hash = "sha256:7ff7f833eb1e7697084b4ed9d86c3167cbff1ec77f1b40df774313a5d0fd5f6d"},
+]
+
+[package.dependencies]
+nexus-rpc = "1.1.0"
+protobuf = ">=3.20,<7.0.0"
+python-dateutil = {version = ">=2.8.2,<3", markers = "python_full_version < \"3.11.0\""}
+types-protobuf = ">=3.20"
+typing-extensions = ">=4.2.0,<5"
+
+[package.extras]
+grpc = ["grpcio (>=1.48.2,<2)"]
+openai-agents = ["eval-type-backport (>=0.2.2) ; python_full_version < \"3.10.0\"", "mcp (>=1.9.4,<2) ; python_full_version >= \"3.10.0\"", "openai-agents (>=0.3,<0.4)"]
+opentelemetry = ["opentelemetry-api (>=1.11.1,<2)", "opentelemetry-sdk (>=1.11.1,<2)"]
+pydantic = ["pydantic (>=2.0.0,<3)"]
+
 [[package]]
 name = "tenacity"
 version = "8.5.0"
@@ -7971,7 +8950,7 @@ description = "List processing tools and functional utilities"
 optional = false
 python-versions = ">=3.8"
 groups = ["main"]
-markers = "implementation_name == \"cpython\" or implementation_name == \"pypy\""
+markers = "implementation_name == \"pypy\" or implementation_name == \"cpython\""
 files = [
     {file = "toolz-1.0.0-py3-none-any.whl", hash = "sha256:292c8f1c4e7516bf9086f8850935c799a874039c8bcf959d47b600e4c44a6236"},
     {file = "toolz-1.0.0.tar.gz", hash = "sha256:2c86e3d9a04798ac556793bced838816296a2f085017664e4995cb40a1047a02"},
@@ -8047,14 +9026,14 @@ test = ["hypothesis (>=6.56.4,<7)", "pycryptodome", "pytest (>=7.0.0)", "pytest-
 
 [[package]]
 name = "typer"
-version = "0.12.5"
+version = "0.20.0"
 description = "Typer, build great CLIs. Easy to code. Based on Python type hints."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 groups = ["main"]
 files = [
-    {file = "typer-0.12.5-py3-none-any.whl", hash = "sha256:62fe4e471711b147e3365034133904df3e235698399bc4de2b36c8579298d52b"},
-    {file = "typer-0.12.5.tar.gz", hash = "sha256:f592f089bedcc8ec1b974125d64851029c3b1af145f04aca64d69410f0c9b722"},
+    {file = "typer-0.20.0-py3-none-any.whl", hash = "sha256:5b463df6793ec1dca6213a3cf4c0f03bc6e322ac5e16e13ddd622a889489784a"},
+    {file = "typer-0.20.0.tar.gz", hash = "sha256:1aaf6494031793e4876fb0bacfa6a912b551cf43c1e63c800df8b1a866720c37"},
 ]
 
 [package.dependencies]
@@ -8075,6 +9054,18 @@ files = [
     {file = "types_cachetools-5.5.0.20240820-py3-none-any.whl", hash = "sha256:efb2ed8bf27a4b9d3ed70d33849f536362603a90b8090a328acf0cd42fda82e2"},
 ]
 
+[[package]]
+name = "types-protobuf"
+version = "6.32.1.20251105"
+description = "Typing stubs for protobuf"
+optional = false
+python-versions = ">=3.9"
+groups = ["main"]
+files = [
+    {file = "types_protobuf-6.32.1.20251105-py3-none-any.whl", hash = "sha256:a15109d38f7cfefd2539ef86d3f93a6a41c7cad53924f8aa1a51eaddbb72a660"},
+    {file = "types_protobuf-6.32.1.20251105.tar.gz", hash = "sha256:641002611ff87dd9fedc38a39a29cacb9907ae5ce61489b53e99ca2074bef764"},
+]
+
 [[package]]
 name = "types-python-dateutil"
 version = "2.9.0.20250516"
@@ -8473,39 +9464,37 @@ wasabi = ">=0.9.1,<1.2.0"
 
 [[package]]
 name = "web3"
-version = "6.20.4"
-description = "web3.py"
+version = "7.14.0"
+description = "web3: A Python library for interacting with Ethereum"
 optional = false
-python-versions = ">=3.7.2"
+python-versions = "<4,>=3.8"
 groups = ["main"]
 files = [
-    {file = "web3-6.20.4-py3-none-any.whl", hash = "sha256:a6e1c428a54bf0fd398fbf006d00235898aed794476177ce73f7db177d2ad16c"},
-    {file = "web3-6.20.4.tar.gz", hash = "sha256:7f3cdceca369be3eb959ce3905783cd021a0786f40c60b01e40ae2ba538e6e3f"},
+    {file = "web3-7.14.0-py3-none-any.whl", hash = "sha256:a78c0a979bf11c47795f564512131c01b7598a276976f7031c55140f733e210a"},
+    {file = "web3-7.14.0.tar.gz", hash = "sha256:d82c78007c280e478b3920cd56658df17f2f76af584ee3318df6b60d4944b8a2"},
 ]
 
 [package.dependencies]
 aiohttp = ">=3.7.4.post0"
-ckzg = "<2"
-eth-abi = ">=4.0.0"
-eth-account = ">=0.8.0,<0.13"
+eth-abi = ">=5.0.1"
+eth-account = ">=0.13.6"
 eth-hash = {version = ">=0.5.1", extras = ["pycryptodome"]}
-eth-typing = ">=3.0.0,<4.2.0 || >4.2.0,<5.0.0"
-eth-utils = ">=2.1.0,<5"
-hexbytes = ">=0.1.0,<0.4.0"
-jsonschema = ">=4.0.0"
-lru-dict = ">=1.1.6,<1.3.0"
-protobuf = ">=4.21.6"
+eth-typing = ">=5.0.0"
+eth-utils = ">=5.0.0"
+hexbytes = ">=1.2.0"
+pydantic = ">=2.4.0"
 pyunormalize = ">=15.0.0"
 pywin32 = {version = ">=223", markers = "platform_system == \"Windows\""}
-requests = ">=2.16.0"
+requests = ">=2.23.0"
+types-requests = ">=2.0.0"
 typing-extensions = ">=4.0.1"
-websockets = ">=10.0.0,<14.0.0"
+websockets = ">=10.0.0,<16.0.0"
 
 [package.extras]
-dev = ["build (>=0.9.0)", "bumpversion", "eth-tester[py-evm] (>=0.11.0b1,<0.12.0b1) ; python_version > \"3.7\"", "eth-tester[py-evm] (>=0.9.0b1,<0.10.0b1) ; python_version <= \"3.7\"", "flaky (>=3.7.0)", "hypothesis (>=3.31.2)", "importlib-metadata (<5.0) ; python_version < \"3.8\"", "ipfshttpclient (==0.8.0a2)", "pre-commit (>=2.21.0)", "py-geth (>=3.14.0,<4)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.21.2,<0.23)", "pytest-mock (>=1.10)", "pytest-watch (>=4.2)", "pytest-xdist (>=1.29)", "setuptools (>=38.6.0)", "sphinx (>=5.3.0)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=21,<22)", "tox (>=3.18.0)", "tqdm (>4.32)", "twine (>=1.13)", "when-changed (>=0.3.0)"]
-docs = ["sphinx (>=5.3.0)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=21,<22)"]
-ipfs = ["ipfshttpclient (==0.8.0a2)"]
-tester = ["eth-tester[py-evm] (>=0.11.0b1,<0.12.0b1) ; python_version > \"3.7\"", "eth-tester[py-evm] (>=0.9.0b1,<0.10.0b1) ; python_version <= \"3.7\"", "py-geth (>=3.14.0,<4)"]
+dev = ["build (>=0.9.0)", "bump_my_version (>=0.19.0)", "eth-tester[py-evm] (>=0.13.0b1,<0.14.0b1)", "flaky (>=3.7.0)", "hypothesis (>=3.31.2)", "ipython", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "py-geth (>=5.1.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.18.1,<0.23)", "pytest-mock (>=1.10)", "pytest-xdist (>=2.4.0)", "setuptools (>=38.6.0)", "sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)", "tox (>=4.0.0)", "tqdm (>4.32)", "twine (>=1.13)", "wheel"]
+docs = ["sphinx (>=6.0.0)", "sphinx-autobuild (>=2021.3.14)", "sphinx_rtd_theme (>=1.0.0)", "towncrier (>=24,<25)"]
+test = ["eth-tester[py-evm] (>=0.13.0b1,<0.14.0b1)", "flaky (>=3.7.0)", "hypothesis (>=3.31.2)", "mypy (==1.10.0)", "pre-commit (>=3.4.0)", "py-geth (>=5.1.0)", "pytest (>=7.0.0)", "pytest-asyncio (>=0.18.1,<0.23)", "pytest-mock (>=1.10)", "pytest-xdist (>=2.4.0)", "tox (>=4.0.0)"]
+tester = ["eth-tester[py-evm] (>=0.13.0b1,<0.14.0b1)", "py-geth (>=5.1.0)"]
 
 [[package]]
 name = "websocket-client"
@@ -8743,6 +9732,156 @@ files = [
     {file = "wrapt-1.17.2.tar.gz", hash = "sha256:41388e9d4d1522446fe79d3213196bd9e3b301a336965b9e27ca2788ebd122f3"},
 ]
 
+[[package]]
+name = "xxhash"
+version = "3.6.0"
+description = "Python binding for xxHash"
+optional = false
+python-versions = ">=3.7"
+groups = ["main"]
+files = [
+    {file = "xxhash-3.6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:87ff03d7e35c61435976554477a7f4cd1704c3596a89a8300d5ce7fc83874a71"},
+    {file = "xxhash-3.6.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:f572dfd3d0e2eb1a57511831cf6341242f5a9f8298a45862d085f5b93394a27d"},
+    {file = "xxhash-3.6.0-cp310-cp310-manylinux1_i686.manylinux_2_28_i686.manylinux_2_5_i686.whl", hash = "sha256:89952ea539566b9fed2bbd94e589672794b4286f342254fad28b149f9615fef8"},
+    {file = "xxhash-3.6.0-cp310-cp310-manylinux2014_aarch64.manylinux_2_17_aarch64.manylinux_2_28_aarch64.whl", hash = "sha256:48e6f2ffb07a50b52465a1032c3cf1f4a5683f944acaca8a134a2f23674c2058"},
+    {file = "xxhash-3.6.0-cp310-cp310-manylinux2014_ppc64le.manylinux_2_17_ppc64le.manylinux_2_28_ppc64le.whl", hash = "sha256:b5b848ad6c16d308c3ac7ad4ba6bede80ed5df2ba8ed382f8932df63158dd4b2"},
+    {file = "xxhash-3.6.0-cp310-cp310-manylinux2014_s390x.manylinux_2_17_s390x.manylinux_2_28_s390x.whl", hash = "sha256:a034590a727b44dd8ac5914236a7b8504144447a9682586c3327e935f33ec8cc"},
+    {file = "xxhash-3.6.0-cp310-cp310-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl", hash = "sha256:8a8f1972e75ebdd161d7896743122834fe87378160c20e97f8b09166213bf8cc"},
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+]
+
+[package.extras]
+cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and python_version < \"3.14\"", "cffi (>=2.0.0b) ; platform_python_implementation != \"PyPy\" and python_version >= \"3.14\""]
+
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.10,<3.13"
-content-hash = "eed298081e18b62db6d7ef71a16b2d239d4755c2a100b77cc6a63d95c92af92e"
+content-hash = "2e53a8fbd09752bcea5614553a13adb9ec48997ea3a31de1be2afe802a6ba3be"
diff --git a/prediction_prophet/app.py b/prediction_prophet/app.py
index e81e5edd..aae4d3d5 100644
--- a/prediction_prophet/app.py
+++ b/prediction_prophet/app.py
@@ -7,7 +7,7 @@
 from pydantic_ai.models import KnownModelName
 from pydantic_ai.settings import ModelSettings
 from prediction_market_agent_tooling.tools.utils import secret_str_from_env
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_text_splitters import RecursiveCharacterTextSplitter
 from prediction_prophet.functions.create_embeddings_from_results import create_embeddings_from_results
 from prediction_prophet.functions.generate_subqueries import generate_subqueries
 from prediction_prophet.functions.prepare_report import prepare_report
@@ -18,8 +18,8 @@
 def research(
     goal: str,
     tavily_api_key: SecretStr,
-    model: KnownModelName = "gpt-4o",
-    temperature: float = 0.7, 
+    model: KnownModelName = "openai:gpt-4o",
+    temperature: float = 0.7,
     initial_subqueries_limit: int = 20,
     subqueries_limit: int = 4,
     scrape_content_split_chunk_size: int = 800,
@@ -30,19 +30,19 @@ def research(
 
     with st.status("Generating subqueries"):
         queries = generate_subqueries(query=goal, limit=initial_subqueries_limit, agent=agent)
-    
+
         stringified_queries = '\n- ' + '\n- '.join(queries)
         st.write(f"Generated subqueries: {stringified_queries}")
-        
+
     with st.status("Reranking subqueries"):
         queries = rerank_subqueries(queries=queries, goal=goal, agent=agent)[:subqueries_limit] if initial_subqueries_limit > subqueries_limit else queries
 
         stringified_queries = '\n- ' + '\n- '.join(queries)
         st.write(f"Reranked subqueries. Will use top {subqueries_limit}: {stringified_queries}")
-    
+
     with st.status("Searching the web"):
         search_results_with_queries = search(
-            queries, 
+            queries,
             lambda result: not result.url.startswith("https://www.youtube"),
             tavily_api_key=tavily_api_key
         )
@@ -52,14 +52,14 @@ def research(
 
         scrape_args = [result for (_, result) in search_results_with_queries]
         websites_to_scrape = set([result.url for result in scrape_args])
-        
+
         stringified_websites = '\n- ' + '\n- '.join(websites_to_scrape)
         st.write(f"Found the following relevant results: {stringified_websites}")
-    
+
     with st.status(f"Scraping web results"):
         scraped = scrape_results(scrape_args)
         scraped = [result for result in scraped if result.content != ""]
-        
+
         st.write(f"Scraped content from {len(scraped)} websites")
 
     text_splitter = RecursiveCharacterTextSplitter(
@@ -67,21 +67,21 @@ def research(
         chunk_size=scrape_content_split_chunk_size,
         chunk_overlap=scrape_content_split_chunk_overlap
     )
-    
+
     with st.status(f"Performing similarity searches"):
         collection = create_embeddings_from_results(scraped, text_splitter)
         st.write("Created embeddings")
 
         vector_result_texts: list[str] = []
         url_to_content_deemed_most_useful: dict[str, str] = {}
-        
+
         for query in queries:
             top_k_per_query_results = collection.similarity_search(query, k=top_k_per_query)
             vector_result_texts += [result.page_content for result in top_k_per_query_results if result.page_content not in vector_result_texts]
 
             for x in top_k_per_query_results:
                 url_to_content_deemed_most_useful[x.metadata["url"]] = x.metadata["content"]
-        
+
             st.write(f"Similarity searched for: {query}")
 
         st.write(f"Found {len(vector_result_texts)} relevant information chunks")
@@ -106,7 +106,7 @@ def research(
     st.title('Prediction Prophet')
     st.markdown("A web3 agent by [Agentcoin](https://www.agentcoin.tv/)")
     st.image('https://raw.githubusercontent.com/agentcoinorg/predictionprophet/main/docs/imgs/banner.png')
-    
+
     st.markdown('#')
     st.markdown('#')
     st.markdown('#')
@@ -116,7 +116,7 @@ def research(
     st.caption('View the source code on our [github](https://github.com/agentcoinorg/predictionprophet)')
     st.caption('Learn more on our [substack](https://www.agentcoin.tv/blog/prediction-prophet)')
     st.caption('Join our [discord](https://discord.com/invite/6gk85fetcT)')
-    
+
 
 # TODO: find a better way to clear the history
 progress_placeholder = st.empty()
@@ -124,27 +124,27 @@ def research(
 if question := st.chat_input(placeholder='Will Twitter implement a new misinformation policy before the end of 2024?'):
     progress_placeholder.empty()
     time.sleep(0.1) # https://github.com/streamlit/streamlit/issues/5044
-    
+
     with progress_placeholder.container():
         st.chat_message("user").write(question)
-        
+
         with st.chat_message("assistant"):
             st.write(f"I will evaluate the probability of '{question}' occurring")
-            
+
             with st.status("Evaluating question") as status:
-                is_predictable = is_predictable_binary(question=question) 
+                is_predictable = is_predictable_binary(question=question)
                 if not is_predictable:
                     st.container().error(f"The agent thinks this question is not predictable.")
                     status.update(label="Error evaluating question", state="error", expanded=True)
                     st.stop()
-            
+
             report = research(
                 goal=question,
                 subqueries_limit=6,
                 top_k_per_query=15,
                 tavily_api_key=tavily_api_key,
             )
-                    
+
             with st.status("Making prediction"):
                 prediction = _make_prediction(market_question=question, additional_information=report, agent=Agent("gpt-4o", model_settings=ModelSettings(temperature=0.0)))
                 st.write(f"Probability: {prediction.p_yes * 100}%. Confidence: {prediction.confidence * 100}%")
@@ -153,6 +153,5 @@ def research(
                 if not prediction:
                     st.container().error("No prediction was generated.")
                     st.stop()
-                    
-            st.markdown(f"With **{prediction.confidence * 100}% confidence**, I'd say this outcome has a **{prediction.p_yes * 100}% probability** of happening")
 
+            st.markdown(f"With **{prediction.confidence * 100}% confidence**, I'd say this outcome has a **{prediction.p_yes * 100}% probability** of happening")
diff --git a/prediction_prophet/autonolas/research.py b/prediction_prophet/autonolas/research.py
index 3f2fc1ff..4eeec1c7 100644
--- a/prediction_prophet/autonolas/research.py
+++ b/prediction_prophet/autonolas/research.py
@@ -15,10 +15,10 @@
 from operator import itemgetter
 from enum import Enum
 from bs4 import BeautifulSoup, NavigableString
-from googleapiclient.discovery import build
 from prediction_prophet.functions.parallelism import THREADPOOL
 from pydantic_ai.exceptions import UnexpectedModelBehavior
 from pydantic import BaseModel, Field
+from prediction_market_agent_tooling.tools.utils import infer_model
 
 
 import requests
@@ -78,7 +78,7 @@
 in this scenario has only two possible outcomes: `Yes` or `No`. Each market has a closing date at which the outcome is evaluated. This date is typically stated within the market question.  \
 The closing date is considered to be 23:59:59 of the date provided in the market question. If the event specified in the market question has not occurred before the closing date, the market question's outcome is `No`. \
 If the event has happened before the closing date, the market question's outcome is `Yes`. You are provided an itemized list of information under the label "ADDITIONAL_INFORMATION", which is \
-sourced from a Google search engine query performed a few seconds ago and is meant to assist you in your probability estimation. You must adhere to the following 'INSTRUCTIONS'.  
+sourced from a Google search engine query performed a few seconds ago and is meant to assist you in your probability estimation. You must adhere to the following 'INSTRUCTIONS'.
 
 
 INSTRUCTIONS:
@@ -89,7 +89,7 @@
 * Consider the prediction market with the market question, the closing date and the outcomes in an isolated context that has no influence on the protagonists that are involved in the event in the real world, specified in the market question. The closing date is always arbitrarily set by the market creator and has no influence on the real world. So it is likely that the protagonists of the event in the real world are not even aware of the prediction market and do not care about the market's closing date.
 * The probability estimations of the market question outcomes must be as accurate as possible, as an inaccurate estimation will lead to financial loss for the user.
 * Utilize your training data and the information provided under "ADDITIONAL_INFORMATION" to generate probability estimations for the outcomes of the 'market question'.
-* Examine the itemized list under "ADDITIONAL_INFORMATION" thoroughly and use all the relevant information for your probability estimation. This data is sourced from a Google search engine query done a few seconds ago. 
+* Examine the itemized list under "ADDITIONAL_INFORMATION" thoroughly and use all the relevant information for your probability estimation. This data is sourced from a Google search engine query done a few seconds ago.
 * Use any relevant item in "ADDITIONAL_INFORMATION" in addition to your training data to make the probability estimation. You can assume that you have been provided with the most current and relevant information available on the internet. Still pay close attention on the release and modification timestamps provided in parentheses right before each information item. Some information might be outdated and not relevant anymore.
 * More recent information indicated by the timestamps provided in parentheses right before each information item overrides older information within ADDITIONAL_INFORMATION and holds more weight for your probability estimation.
 * If there exist contradicting information, evaluate the release and modification dates of those information and prioritize the information that is more recent and adjust your confidence in the probability estimation accordingly.
@@ -128,7 +128,7 @@
 Each market has a closing date at which the outcome is evaluated. This date is typically stated within the market question.  \
 The closing date is considered to be 23:59:59 of the date provided in the market question. \
 You are provided an itemized list of information under the label "ADDITIONAL_INFORMATION", which is \
-sourced from a Google search engine query performed a few seconds ago and is meant to assist you in your 'scalar_value' estimation. You must adhere to the following 'INSTRUCTIONS'. 
+sourced from a Google search engine query performed a few seconds ago and is meant to assist you in your 'scalar_value' estimation. You must adhere to the following 'INSTRUCTIONS'.
 
 
 INSTRUCTIONS:
@@ -137,7 +137,7 @@
 * Consider the prediction market with the market question, the closing date and the outcomes in an isolated context that has no influence on the protagonists that are involved in the event in the real world, specified in the market question. The closing date is always arbitrarily set by the market creator and has no influence on the real world. So it is likely that the protagonists of the event in the real world are not even aware of the prediction market and do not care about the market's closing date.
 * The 'scalar_value' estimations of the market question outcomes must be as accurate as possible, as an inaccurate estimation will lead to financial loss for the user.
 * Utilize your training data and the information provided under "ADDITIONAL_INFORMATION" to generate 'scalar_value' estimations for the outcomes of the 'market question'.
-* Examine the itemized list under "ADDITIONAL_INFORMATION" thoroughly and use all the relevant information for your 'scalar_value' estimation. This data is sourced from a Google search engine query done a few seconds ago. 
+* Examine the itemized list under "ADDITIONAL_INFORMATION" thoroughly and use all the relevant information for your 'scalar_value' estimation. This data is sourced from a Google search engine query done a few seconds ago.
 * Use any relevant item in "ADDITIONAL_INFORMATION" in addition to your training data to make the 'scalar_value' estimation. You can assume that you have been provided with the most current and relevant information available on the internet. Still pay close attention on the release and modification timestamps provided in parentheses right before each information item. Some information might be outdated and not relevant anymore.
 * More recent information indicated by the timestamps provided in parentheses right before each information item overrides older information within ADDITIONAL_INFORMATION and holds more weight for your 'scalar_value' estimation.
 * If there exist contradicting information, evaluate the release and modification dates of those information and prioritize the information that is more recent and adjust your confidence in the probability estimation accordingly.
@@ -171,7 +171,7 @@
 Each market has a closing date at which the outcome is evaluated. This date is typically stated within the market question.  \
 The closing date is considered to be 23:59:59 of the date provided in the market question. \
 You are provided an itemized list of information under the label "ADDITIONAL_INFORMATION", which is \
-sourced from a Google search engine query performed a few seconds ago and is meant to assist you in your probability estimation. You must adhere to the following 'INSTRUCTIONS'.  
+sourced from a Google search engine query performed a few seconds ago and is meant to assist you in your probability estimation. You must adhere to the following 'INSTRUCTIONS'.
 
 
 INSTRUCTIONS:
@@ -181,7 +181,7 @@
 * Consider the prediction market with the market question, the closing date and the outcomes in an isolated context that has no influence on the protagonists that are involved in the event in the real world, specified in the market question. The closing date is always arbitrarily set by the market creator and has no influence on the real world. So it is likely that the protagonists of the event in the real world are not even aware of the prediction market and do not care about the market's closing date.
 * The probability estimations of the market question outcomes must be as accurate as possible, as an inaccurate estimation will lead to financial loss for the user.
 * Utilize your training data and the information provided under "ADDITIONAL_INFORMATION" to generate probability estimations for the outcomes of the 'market question'.
-* Examine the itemized list under "ADDITIONAL_INFORMATION" thoroughly and use all the relevant information for your probability estimation. This data is sourced from a Google search engine query done a few seconds ago. 
+* Examine the itemized list under "ADDITIONAL_INFORMATION" thoroughly and use all the relevant information for your probability estimation. This data is sourced from a Google search engine query done a few seconds ago.
 * Use any relevant item in "ADDITIONAL_INFORMATION" in addition to your training data to make the probability estimation. You can assume that you have been provided with the most current and relevant information available on the internet. Still pay close attention on the release and modification timestamps provided in parentheses right before each information item. Some information might be outdated and not relevant anymore.
 * More recent information indicated by the timestamps provided in parentheses right before each information item overrides older information within ADDITIONAL_INFORMATION and holds more weight for your probability estimation.
 * If there exist contradicting information, evaluate the release and modification dates of those information and prioritize the information that is more recent and adjust your confidence in the probability estimation accordingly.
@@ -580,7 +580,7 @@ def truncate_additional_information(
     else:
         add_trunc_enc = add_enc[: -int(len_add_enc - max_add_tokens)]
         return enc.decode(add_trunc_enc)
-    
+
 
 def safe_get_urls_from_query(query: str, num: int = 3) -> List[str]:
     try:
@@ -878,13 +878,13 @@ def extract_similarity_scores(
 
     # Encode sentences using an embedding model
     similarities = par_map(
-        sentences, 
+        sentences,
         lambda sentence: (
-            doc_question.similarity(nlp(sentence)) if embedding_model == EmbeddingModel.spacy 
+            doc_question.similarity(nlp(sentence)) if embedding_model == EmbeddingModel.spacy
             else cosine_similarity(
-                [openai_embedding_cached(sentence)], 
+                [openai_embedding_cached(sentence)],
                 [openai_embedding_cached(doc_question.text)]
-            )[0][0] if embedding_model == EmbeddingModel.openai 
+            )[0][0] if embedding_model == EmbeddingModel.openai
             else None
         )
     )
@@ -1215,7 +1215,7 @@ def fetch_additional_information(
     if not agent._system_prompts and not agent._system_prompt_functions and not agent._system_prompt_dynamic_functions:
         agent.system_prompt()(lambda: "You are a helpful assistant.")
 
-    response = agent.run_sync(url_query_prompt).data
+    response = agent.run_sync(url_query_prompt).output
 
     # Parse the response content
     try:
@@ -1265,7 +1265,8 @@ def research(
 
     # Get the tiktoken base encoding
     assert agent.model is not None
-    enc = tiktoken.encoding_for_model(agent.model if isinstance(agent.model, str) else agent.model.model_name)
+    model_name = infer_model(agent.model if isinstance(agent.model, str) else agent.model.model_name)
+    enc = tiktoken.encoding_for_model(model_name)
 
     # Calculate the maximum number of tokens and words that can be consumed by the additional information string
     max_add_tokens = get_max_tokens_for_additional_information(
@@ -1294,7 +1295,7 @@ def research(
     # Spacy loads ~500MB into memory. Free it with force.
     del nlp
     gc.collect()
-    
+
     return additional_information
 
 
@@ -1306,7 +1307,7 @@ def make_prediction(
     include_reasoning: bool = False,
 ) -> Prediction:
     agent = agent or Agent(model="gpt-3.5-turbo-0125", model_settings=ModelSettings(temperature=0.7))
-    
+
     current_time_utc = datetime.now(timezone.utc)
     formatted_time_utc = current_time_utc.strftime("%Y-%m-%dT%H:%M:%S.%f")[:-6] + "Z"
 
@@ -1323,7 +1324,7 @@ def make_prediction(
     )
     result = agent.run_sync(prediction_prompt)
 
-    completion = result.data
+    completion = result.output
 
     logprobs = None
     messages = result.all_messages()
@@ -1331,7 +1332,7 @@ def make_prediction(
         vendor_details = messages[-1].vendor_details
         if vendor_details:
             logprobs = vendor_details.get("logprobs")
-    
+
     logger.info(f"Completion: {completion}")
     completion_clean = clean_completion_json(completion)
     logger.info(f"Completion cleaned: {completion_clean}")
@@ -1340,10 +1341,10 @@ def make_prediction(
         response: Prediction = json.loads(completion_clean)
     except json.decoder.JSONDecodeError as e:
         raise UnexpectedModelBehavior(f"The response from {agent=} could not be parsed as JSON: {completion_clean=}") from e
-    
+
     if logprobs:
         response['logprobs'] = LogprobsParser(skip_fields = ["reasoning"]).parse_logprobs(logprobs, Prediction) # type: ignore
-    
+
     return response
 
 
@@ -1356,7 +1357,7 @@ def make_prediction_categorical(
     include_reasoning: bool = False,
 ) -> CategoricalPrediction:
     agent = agent or Agent(model="gpt-3.5-turbo-0125", model_settings=ModelSettings(temperature=0.7))
-    
+
     current_time_utc = datetime.now(timezone.utc)
     formatted_time_utc = current_time_utc.strftime("%Y-%m-%dT%H:%M:%S.%f")[:-6] + "Z"
 
@@ -1374,7 +1375,7 @@ def make_prediction_categorical(
     )
     result = agent.run_sync(prediction_prompt)
 
-    completion = result.data
+    completion = result.output
     logger.info(f"Completion: {completion}")
     completion_clean = clean_completion_json(completion)
     logger.info(f"Completion cleaned: {completion_clean}")
@@ -1400,7 +1401,7 @@ def make_prediction_scalar(
     include_reasoning: bool = False,
 ) -> ScalarPrediction:
     agent = agent or Agent(model="gpt-3.5-turbo-0125", model_settings=ModelSettings(temperature=0.7))
-    
+
     current_time_utc = datetime.now(timezone.utc)
     formatted_time_utc = current_time_utc.strftime("%Y-%m-%dT%H:%M:%S.%f")[:-6] + "Z"
 
@@ -1418,10 +1419,10 @@ def make_prediction_scalar(
         timestamp=formatted_time_utc,
     )
     result = agent.run_sync(prediction_prompt)
-    completion = result.data
+    completion = result.output
 
     if agent.model and hasattr(agent.model, "_n") and agent.model._n > 1:
-        jsons = re.findall(r"\{[^{}]*\}", result.data, flags=re.S)
+        jsons = re.findall(r"\{[^{}]*\}", completion, flags=re.S)
 
         parsed: list[dict[str, Any]] = []
         for block in jsons:
@@ -1442,7 +1443,7 @@ def make_prediction_scalar(
         return responses
 
     else:
-        completion = result.data
+        completion = result.output
         logger.info(f"Completion: {completion}")
         completion_clean = clean_completion_json(completion)
         logger.info(f"Completion cleaned: {completion_clean}")
diff --git a/prediction_prophet/functions/create_embeddings_from_results.py b/prediction_prophet/functions/create_embeddings_from_results.py
index 1124e89e..a8211e4f 100644
--- a/prediction_prophet/functions/create_embeddings_from_results.py
+++ b/prediction_prophet/functions/create_embeddings_from_results.py
@@ -9,9 +9,9 @@
 
 import os
 from langchain_openai import OpenAIEmbeddings
-from langchain.vectorstores.chroma import Chroma
+from langchain_chroma import Chroma
 from prediction_prophet.models.WebScrapeResult import WebScrapeResult
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_text_splitters import RecursiveCharacterTextSplitter
 from pydantic.types import SecretStr
 from prediction_market_agent_tooling.config import APIKeys
 
@@ -19,7 +19,7 @@
 def create_embeddings_from_results(results: list[WebScrapeResult], text_splitter: RecursiveCharacterTextSplitter, api_key: SecretStr | None = None) -> Chroma:
     if api_key == None:
         api_key = APIKeys().openai_api_key
-    
+
     collection = Chroma(embedding_function=OpenAIEmbeddings(openai_api_key=api_key))
     texts = []
     metadatas = []
diff --git a/prediction_prophet/functions/debate_prediction.py b/prediction_prophet/functions/debate_prediction.py
index 60c518a9..6ae856b1 100644
--- a/prediction_prophet/functions/debate_prediction.py
+++ b/prediction_prophet/functions/debate_prediction.py
@@ -2,8 +2,8 @@
 import json
 
 from autogen import ConversableAgent
-from langchain.prompts import ChatPromptTemplate
-from langchain.schema.output_parser import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
 from langchain_openai import ChatOpenAI
 from prediction_market_agent_tooling.config import APIKeys
 from prediction_market_agent_tooling.markets.data_models import ProbabilisticAnswer
@@ -25,7 +25,7 @@
     - "p_no": Probability that the market questions outcome will be `No`. Ranging from 0 (lowest probability) to 1 (maximum probability).
     - "confidence": Indicating the confidence in the estimated probabilities you provided ranging from 0 (lowest confidence) to 1 (maximum confidence). Confidence can be calculated based on the quality and quantity of data used for the estimation.
     - "info_utility": Utility of the information provided in "ADDITIONAL_INFORMATION" to help you make the probability estimation ranging from 0 (lowest utility) to 1 (maximum utility).
-    
+
     Ensure p_yes + p_no equals 1.
 USER_PROMPT: {user_prompt}
 ADDITIONAL_INFORMATION:
@@ -66,7 +66,7 @@
    - "p_no": Probability that the market questions outcome will be `No`. Ranging from 0 (lowest probability) to 1 (maximum probability).
    - "confidence": Indicating the confidence in the estimated probabilities you provided ranging from 0 (lowest confidence) to 1 (maximum confidence). Confidence can be calculated based on the quality and quantity of data used for the estimation.
    - "info_utility": Utility of the information provided in "ADDITIONAL_INFORMATION" to help you make the probability estimation ranging from 0 (lowest utility) to 1 (maximum utility).
-    
+
 Return only the JSON and include nothing more in your response.
 
 Information: {prediction_summary}
@@ -78,13 +78,13 @@
 You will debate other agents's predictions. You can update your prediction if other agents
 give you convincing arguments. Nonetheless, be strong in your position and argument back to defend your prediction.
 """
-    
+
 def make_debated_prediction(prompt: str, additional_information: str, api_key: SecretStr | None = None) -> ProbabilisticAnswer:
     if api_key == None:
         api_key = APIKeys().openai_api_key
-        
+
     formatted_time_utc = datetime.datetime.now(datetime.timezone.utc).isoformat(timespec='seconds') + "Z"
-    
+
     prediction_prompt = ChatPromptTemplate.from_template(template=PREDICTION_PROMPT)
 
     prediction_chain = (
@@ -98,7 +98,7 @@ def make_debated_prediction(prompt: str, additional_information: str, api_key: S
         "additional_information": additional_information,
         "timestamp": formatted_time_utc,
     } for _ in range(2)])
-    
+
     agents = [
         ConversableAgent(
             name=f"Predictor_Agent_{i}",
@@ -106,7 +106,7 @@ def make_debated_prediction(prompt: str, additional_information: str, api_key: S
             llm_config={"config_list": [{"model": "gpt-4-0125-preview", "api_key": api_key.get_secret_value()}]},
             human_input_mode="NEVER")
         for i in range(2) ]
-    
+
     chat_result = agents[0].initiate_chat(
         agents[1],
         message=DEBATE_PREDICTION.format(
@@ -119,7 +119,7 @@ def make_debated_prediction(prompt: str, additional_information: str, api_key: S
         summary_method="reflection_with_llm",
         max_turns=3,
     )
-            
+
     extraction_prompt = ChatPromptTemplate.from_template(template=EXTRACTION_PROMPT)
 
     extraction_chain = (
@@ -131,6 +131,6 @@ def make_debated_prediction(prompt: str, additional_information: str, api_key: S
     result = extraction_chain.invoke({
         "prediction_summary": chat_result.summary
     })
-    
+
 
     return ProbabilisticAnswer.model_validate(json.loads(result))
\ No newline at end of file
diff --git a/prediction_prophet/functions/generate_subqueries.py b/prediction_prophet/functions/generate_subqueries.py
index 32584ecd..8ef0516c 100644
--- a/prediction_prophet/functions/generate_subqueries.py
+++ b/prediction_prophet/functions/generate_subqueries.py
@@ -1,4 +1,4 @@
-from langchain.output_parsers import CommaSeparatedListOutputParser
+from langchain_core.output_parsers import CommaSeparatedListOutputParser
 from pydantic_ai import Agent
 from prediction_market_agent_tooling.tools.langfuse_ import observe
 
@@ -16,6 +16,6 @@ def generate_subqueries(query: str, limit: int, agent: Agent) -> list[str]:
         return [query]
 
     result = agent.run_sync(subquery_generation_template.format(query=query, search_limit=limit))
-    subqueries = CommaSeparatedListOutputParser().parse(result.data)
+    subqueries = CommaSeparatedListOutputParser().parse(result.output)
 
     return [query] + [subquery.strip('\"') for subquery in subqueries]
diff --git a/prediction_prophet/functions/prepare_report.py b/prediction_prophet/functions/prepare_report.py
index f4788c4c..03e9aeaa 100644
--- a/prediction_prophet/functions/prepare_report.py
+++ b/prediction_prophet/functions/prepare_report.py
@@ -1,8 +1,8 @@
 import typing as t
 from pydantic_ai import Agent
 from langchain_openai import ChatOpenAI
-from langchain.prompts import ChatPromptTemplate
-from langchain.schema.output_parser import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import StrOutputParser
 from prediction_prophet.functions.utils import trim_to_n_tokens
 from prediction_market_agent_tooling.config import APIKeys
 from pydantic.types import SecretStr
@@ -12,11 +12,11 @@
 def prepare_summary(goal: str, content: str, model: str, api_key: SecretStr | None = None, trim_content_to_tokens: t.Optional[int] = None) -> str:
     if api_key == None:
         api_key = APIKeys().openai_api_key
-    
+
     prompt_template = """Write comprehensive summary of the following web content, that provides relevant information to answer the question: '{goal}'.
 But cut the fluff and keep it up to the point.
 Write in bullet points.
-    
+
 Content:
 
 {content}
@@ -42,25 +42,25 @@ def prepare_summary(goal: str, content: str, model: str, api_key: SecretStr | No
 def prepare_report(goal: str, scraped: list[str], agent: Agent) -> str:
     evaluation_prompt_template = """You are a professional researcher. Your goal is to provide a relevant information report
     in order to make an informed prediction for the question: '{goal}'.
-    
+
     Here are the results of relevant web searches:
-    
+
     {search_results}
-    
+
     Prepare a full comprehensive report that provides relevant information to answer the aforementioned question.
     If that is not possible, state why.
     You will structure your report in the following sections:
-    
+
     - Introduction
     - Background
     - Findings and Analysis
     - Conclusion
     - Caveats
-    
+
     Don't limit yourself to just stating each finding; provide a thorough, full and comprehensive analysis of each finding.
     Use markdown syntax. Include as much relevant information as possible and try not to summarize.
     """
     result = agent.run_sync(evaluation_prompt_template.format(goal=goal, search_results="\n".join(scraped)))
-    response = result.data
+    response = result.output
 
     return response
diff --git a/prediction_prophet/functions/rephrase_question.py b/prediction_prophet/functions/rephrase_question.py
index 83da3757..4225edd7 100644
--- a/prediction_prophet/functions/rephrase_question.py
+++ b/prediction_prophet/functions/rephrase_question.py
@@ -3,7 +3,7 @@
 from pydantic import BaseModel
 from langchain_openai import ChatOpenAI
 from prediction_prophet.autonolas.research import clean_completion_json
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.prompts import ChatPromptTemplate
 
 
 QUESTION_REPHRASE_PROMPT = """We have the following question: `{question}`
@@ -41,13 +41,12 @@ def rephrase_question(
     messages = prompt.format_messages(question=question)
 
     max_tokens = 2 * len(tokenizer.encode(question)) + 50 # Max tokens as the question two times + some buffer for formatting.
-    completion = str(llm(messages, max_tokens=max_tokens).content)
+    completion = str(llm.invoke(messages, max_tokens=max_tokens).content)
 
     try:
         return RephrasedQuestion(
-            original_question=question, 
+            original_question=question,
             **json.loads(clean_completion_json(completion))
         )
     except json.decoder.JSONDecodeError as e:
         raise ValueError(f"Error in rephrase_question for `{question}`: {completion}") from e
-        
diff --git a/prediction_prophet/functions/rerank_results.py b/prediction_prophet/functions/rerank_results.py
index eb1ca73e..f044c584 100644
--- a/prediction_prophet/functions/rerank_results.py
+++ b/prediction_prophet/functions/rerank_results.py
@@ -1,6 +1,6 @@
 from langchain_openai import ChatOpenAI
-from langchain.output_parsers import CommaSeparatedListOutputParser
-from langchain.prompts import ChatPromptTemplate
+from langchain_core.output_parsers import CommaSeparatedListOutputParser
+from langchain_core.prompts import ChatPromptTemplate
 
 rerank_results_template = """
 I will present you with a list of text snippets gathered from web searches
diff --git a/prediction_prophet/functions/rerank_subqueries.py b/prediction_prophet/functions/rerank_subqueries.py
index b9059676..cf413ff7 100644
--- a/prediction_prophet/functions/rerank_subqueries.py
+++ b/prediction_prophet/functions/rerank_subqueries.py
@@ -1,6 +1,6 @@
 from pydantic_ai import Agent
 from prediction_market_agent_tooling.tools.langfuse_ import observe
-from langchain.output_parsers import CommaSeparatedListOutputParser
+from langchain_core.output_parsers import CommaSeparatedListOutputParser
 
 rerank_queries_template = """I will present you with a list of queries to search the web for, for answers to the question: {goal}.
 
@@ -13,6 +13,6 @@
 """
 @observe()
 def rerank_subqueries(queries: list[str], goal: str, agent: Agent) -> list[str]:
-    result = agent.run_sync(rerank_queries_template.format(goal=goal, queries="\n---query---\n".join(queries)))
-    responses = CommaSeparatedListOutputParser().parse(result.data)
+    result = agent.run_sync(rerank_queries_template.format(goal=goal, queries="\n---query---\n".join(queries)),)
+    responses = CommaSeparatedListOutputParser().parse(result.output)
     return responses
diff --git a/prediction_prophet/functions/research.py b/prediction_prophet/functions/research.py
index d2ce765b..6f8a0804 100644
--- a/prediction_prophet/functions/research.py
+++ b/prediction_prophet/functions/research.py
@@ -1,7 +1,7 @@
 import logging
 import typing as t
 
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_text_splitters import RecursiveCharacterTextSplitter
 from prediction_prophet.functions.create_embeddings_from_results import create_embeddings_from_results
 from prediction_prophet.functions.generate_subqueries import generate_subqueries
 from prediction_prophet.functions.prepare_report import prepare_report, prepare_summary
@@ -59,21 +59,21 @@ def research(
             f"equal to max_results_per_search ({max_results_per_search}) * "
             f"subqueries_limit ({subqueries_limit})."
         )
-    
+
     agent = agent or Agent("gpt-4o", model_settings=ModelSettings(temperature=0.7))
 
     logger.info("Started subqueries generation")
     all_queries = generate_subqueries(query=goal, limit=initial_subqueries_limit, agent=agent)
-    
+
     stringified_queries = '\n- ' + '\n- '.join(all_queries)
     logger.info(f"Generated subqueries: {stringified_queries}")
-    
+
     logger.info("Started subqueries reranking")
     queries = rerank_subqueries(queries=all_queries, goal=goal, agent=agent)[:subqueries_limit] if initial_subqueries_limit > subqueries_limit else all_queries
 
     stringified_queries = '\n- ' + '\n- '.join(queries)
     logger.info(f"Reranked subqueries. Will use top {subqueries_limit}: {stringified_queries}")
-    
+
     logger.info(f"Started web searching")
     search_results_with_queries = search(
         queries,
@@ -87,10 +87,10 @@ def research(
 
     scrape_args = [result for (_, result) in search_results_with_queries]
     websites_to_scrape = set(result.url for result in scrape_args)
-    
+
     stringified_websites = '\n- ' + '\n- '.join(websites_to_scrape)
     logger.info(f"Found the following relevant results: {stringified_websites}")
-    
+
     logger.info(f"Started scraping of web results")
     scraped = scrape_results(scrape_args) if not use_tavily_raw_content else [WebScrapeResult(
         query=result.query,
@@ -118,7 +118,7 @@ def research(
         chunk_size=scrape_content_split_chunk_size,
         chunk_overlap=scrape_content_split_chunk_overlap
     )
-    
+
     logger.info("Started embeddings creation")
     collection = create_embeddings_from_results(scraped, text_splitter, api_key=openai_api_key)
     logger.info("Embeddings created")
@@ -135,7 +135,7 @@ def research(
         for x in top_k_per_query_results:
             # `x.metadata["content"]` holds the whole url's web page, so it's ok to overwrite the value of the same url.
             url_to_content_deemed_most_useful[x.metadata["url"]] = x.metadata["content"]
-    
+
     stringified_urls = '\n- ' + '\n- '.join(url_to_content_deemed_most_useful.keys())
     logger.info(f"Found {len(vector_result_texts)} information chunks across the following sites: {stringified_urls}")
 
diff --git a/prediction_prophet/functions/summarize.py b/prediction_prophet/functions/summarize.py
index ff55cf23..fc9d660f 100644
--- a/prediction_prophet/functions/summarize.py
+++ b/prediction_prophet/functions/summarize.py
@@ -1,32 +1,33 @@
-from langchain.prompts import PromptTemplate
+from langchain_core.prompts import PromptTemplate
 from langchain_openai import ChatOpenAI
 
-from langchain.text_splitter import RecursiveCharacterTextSplitter
-from langchain.chains.llm import LLMChain
-from langchain.chains.combine_documents.reduce import ReduceDocumentsChain
-from langchain.chains.combine_documents.stuff import  StuffDocumentsChain
-from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChain
-from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+from langchain_classic.chains.llm import LLMChain
+from langchain_classic.chains.combine_documents.reduce import ReduceDocumentsChain
+from langchain_classic.chains.combine_documents.stuff import  StuffDocumentsChain
+from langchain_classic.chains.combine_documents.map_reduce import MapReduceDocumentsChain
+from langchain_text_splitters import RecursiveCharacterTextSplitter
+
 
 def summarize(objective: str, content: str) -> str:
-    llm = ChatOpenAI(temperature = 0, model_name="gpt-3.5-turbo-16k-0613")
-    
+    llm = ChatOpenAI(temperature=0, model_name="gpt-3.5-turbo")
+
     map_template = """
     The following is a set of documents
     {docs}
     Based on this list of docs, please provide a full comprehensive summary relevant to: {objective}
     Helpful Answer:
     """
-    
+
     map_prompt = PromptTemplate(template=map_template, input_variables=["docs", "objective"])
     map_chain = LLMChain(llm=llm, prompt=map_prompt)
-    
+
     reduce_template = """The following is set of summaries:
     {docs}
-    Take these and distill it into a final full comprehensive, summary relevant to: {objective}. 
+    Take these and distill it into a final full comprehensive, summary relevant to: {objective}.
     Helpful Answer:"""
     reduce_prompt = PromptTemplate(template=reduce_template, input_variables=["docs", "objective"])
-    
+
     # Run chain
     reduce_chain = LLMChain(llm=llm, prompt=reduce_prompt)
 
@@ -44,7 +45,7 @@ def summarize(objective: str, content: str) -> str:
         # The maximum number of tokens to group documents into.
         token_max=8000,
     )
-    
+
     map_reduce_chain = MapReduceDocumentsChain(
         # Map chain
         llm_chain=map_chain,
@@ -59,8 +60,7 @@ def summarize(objective: str, content: str) -> str:
 
     text_splitter = RecursiveCharacterTextSplitter(separators=["\n\n", "\n"], chunk_size = 10000, chunk_overlap=500)
     docs = text_splitter.create_documents([content])
-    
+
     response: str = map_reduce_chain.run(docs=docs, objective=objective)
-    
-    return response
 
+    return response
diff --git a/pyproject.toml b/pyproject.toml
index 1dc835c0..e680d239 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -7,21 +7,21 @@ readme = "README.md"
 
 [tool.poetry.dependencies]
 python = ">=3.10,<3.13"
-langchain = "^0.3.0"
+langchain = "^1.0.0"
 beautifulsoup4 = "^4,<4.13" # Bug in typing of newer version
 click = "^8.0.2"
 markdownify = "0.11.6"
 pandas = "^2.1.1"
 openai = "^1.10.0"
-chromadb = "^0.5.0"
+chromadb = "^1.0.0"
 spacy = "3.7.5"
 en_core_web_md = { url = "https://github.com/explosion/spacy-models/releases/download/en_core_web_md-3.7.1/en_core_web_md-3.7.1-py3-none-any.whl" }
 google-api-python-client = "2.95.0"
-tiktoken = "^0.7.0"
+tiktoken = ">=0.7.0"
 tabulate = "^0.9.0"
 pysqlite3-binary = {version="^0.5.2.post3", markers = "sys_platform == 'linux'"}
-langchain-openai = "^0.3.0"
-tenacity = "^8.2.3"
+langchain-openai = "^1.0.0"
+tenacity = ">=8.2.3"
 joblib = "^1.3.2"
 streamlit = "^1.30.0"
 watchdog = "^3.0.0"
@@ -30,13 +30,14 @@ scikit-learn = "^1.4.0"
 typer = ">=0.9.0,<1.0.0"
 types-requests = "^2.31.0.20240125"
 types-python-dateutil = "^2.9.0"
-prediction-market-agent-tooling = { version = ">=0.66.4,<1", extras = ["langchain", "google"] } 
-langchain-community = "^0.3.0"
+prediction-market-agent-tooling = { version = ">=0.69.19,<1", extras = ["langchain", "google"] }
+langchain-community = "^0.4.0"
 memory-profiler = "^0.61.0"
 matplotlib = "^3.8.3"
 pyautogen = "^0.3.1"
 python-dateutil = "^2.9.0.post0"
-pydantic-ai = "^0.1.3"
+pydantic-ai = "^1.0.0"
+langchain-chroma = "^1.0.0"
 
 [tool.poetry.group.dev.dependencies]
 mypy = "^1.8.0"
diff --git a/scripts/agent_app.py b/scripts/agent_app.py
index b5a4f35f..d8601e90 100644
--- a/scripts/agent_app.py
+++ b/scripts/agent_app.py
@@ -6,7 +6,7 @@
 import inspect
 import typing as t
 import streamlit as st
-from enum import Enum 
+from enum import Enum
 from prediction_market_agent_tooling.markets.markets import get_binary_markets, MarketType
 from prediction_market_agent_tooling.benchmark.agents import AbstractBenchmarkedAgent
 from prediction_prophet.benchmark.agents import AGENTS
@@ -22,7 +22,7 @@
 markets = get_binary_markets(42, market_source)
 
 # Select an agent from the list of available agents.
-agent_class_names = st.multiselect("Select agents", [agent_class.__name__ for agent_class in AGENTS]) 
+agent_class_names = st.multiselect("Select agents", [agent_class.__name__ for agent_class in AGENTS])
 if not agent_class_names:
     st.warning("Please select at least one agent.")
     st.stop()
@@ -55,15 +55,15 @@
 
 with st.expander("Show agent's parameters", expanded=False):
     for idx, (column, agent_class) in enumerate(zip(st.columns(len(agent_classes)), agent_classes)):
-        # Inspect the agent's __init__ method to get arguments it accepts, 
-        # ask the user to provide values for these arguments, 
+        # Inspect the agent's __init__ method to get arguments it accepts,
+        # ask the user to provide values for these arguments,
         # and fill in defaults where possible.
         inspect_class_init = inspect.getfullargspec(agent_class.__init__)
         class_arg_to_default_value = {
             arg_name: arg_default
             for arg_name, arg_default in zip(
                 # Only last arguments can have a default value, so we need to slice the args list.
-                inspect_class_init.args[-(len(inspect_class_init.defaults or [])):], 
+                inspect_class_init.args[-(len(inspect_class_init.defaults or [])):],
                 inspect_class_init.defaults or [],
             )
         }
@@ -74,20 +74,20 @@
         class_inputs: dict[str, t.Any] = {}
         for arg_name in inspect_class_init.args:
             # Skip these, no need to ask the user for them.
-            if arg_name in ("self", "agent_name", "max_workers"):
+            if arg_name in ("self", "agent_name", "max_workers", "logger"):
                 continue
             # We need SENTINEL to differentiate between not having the default value and when the default value is None.
             default_value = class_arg_to_default_value.get(arg_name, default_arguments.get(arg_name, SENTINTEL))
             input_type = type(default_value)
             class_inputs[arg_name]  = (
                 # Show checkbox for booleans.
-                column.checkbox(arg_name, default_value if default_value is not SENTINTEL else False, key=f"{idx}-{arg_name}") 
-                if input_type == bool 
+                column.checkbox(arg_name, default_value if default_value is not SENTINTEL else False, key=f"{idx}-{arg_name}")
+                if input_type == bool
                 else
                 # Number input for numbers.
                 column.number_input(arg_name, default_value if default_value is not SENTINTEL else 0, key=f"{idx}-{arg_name}")
                 if input_type in (int, float)
-                else 
+                else
                 # Convert strings to Enum, if the default value is an Enum.
                 input_type(str(column.text_input(arg_name, default_value, key=f"{idx}-{arg_name}")).replace(f"{default_value.__class__.__name__}.", ""))
                 if isinstance(default_value, Enum)
@@ -134,7 +134,7 @@
     with column.expander("Show agent's prediction", expanded=True):
         st.markdown(f"""## Prediction
 
-```       
+```
 {prediction.outcome_prediction}
 ```
 """)