diff --git a/.github/workflows/python_ci.yaml b/.github/workflows/python_ci.yaml
index b87f4a47..c9e53f47 100644
--- a/.github/workflows/python_ci.yaml
+++ b/.github/workflows/python_ci.yaml
@@ -8,7 +8,6 @@ on:
 
 env:
   MANIFOLD_API_KEY: ${{ secrets.MANIFOLD_API_KEY }}
-  SERP_API_KEY: ${{ secrets.SERP_API_KEY }}
   OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }}
   BET_FROM_PRIVATE_KEY: ${{ secrets.BET_FROM_PRIVATE_KEY }}
   GRAPH_API_KEY: ${{ secrets.GRAPH_API_KEY }}
@@ -38,7 +37,6 @@ jobs:
       - name: Extract environment variables for Docker container
         run: |
           echo "MANIFOLD_API_KEY=${{ secrets.MANIFOLD_API_KEY }}" >> .env
-          echo "SERP_API_KEY=${{ secrets.SERP_API_KEY }}" >> .env
           echo "OPENAI_API_KEY=${{ secrets.OPENAI_API_KEY }}" >> .env
           echo "BET_FROM_PRIVATE_KEY=${{ secrets.BET_FROM_PRIVATE_KEY }}" >> .env
           echo "GRAPH_API_KEY=${{ secrets.GRAPH_API_KEY }}" >> .env
@@ -58,8 +56,6 @@ jobs:
         env:
           RUN_PAID_TESTS: "1"
     if: github.event_name == 'workflow_dispatch'
-    # TODO: Remove once the environment variables are fixed in the new repository.
-    continue-on-error: true
 
   test-build-image:
     runs-on: ubuntu-latest
diff --git a/poetry.lock b/poetry.lock
index d3fe2bbb..3ca2786c 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -2888,13 +2888,13 @@ httplib2 = ">=0.19.0"
 
 [[package]]
 name = "google-cloud-aiplatform"
-version = "1.70.0"
+version = "1.71.0"
 description = "Vertex AI API client library"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "google-cloud-aiplatform-1.70.0.tar.gz", hash = "sha256:e8edef6dbc7911380d0ea55c47544e799f62b891cb1a83b504ca1c09fff9884b"},
-    {file = "google_cloud_aiplatform-1.70.0-py2.py3-none-any.whl", hash = "sha256:690e6041f03d3aa85102ac3f316c958d6f43a99aefb7fb3f8938dee56d08abd9"},
+    {file = "google-cloud-aiplatform-1.71.0.tar.gz", hash = "sha256:29f0923d8c74d07a48f8ad600409405d03c73138b4efaf46db703d31c1e165b8"},
+    {file = "google_cloud_aiplatform-1.71.0-py2.py3-none-any.whl", hash = "sha256:3473802f5072ee4e90e6a64f75a0d3d905db60449117d0fd28481f4ea01d8c3d"},
 ]
 
 [package.dependencies]
@@ -2928,7 +2928,7 @@ ray = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict"
 ray-testing = ["google-cloud-bigquery", "google-cloud-bigquery-storage", "immutabledict", "pandas (>=1.0.0)", "pyarrow (>=6.0.1)", "pytest-xdist", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<2.10.dev0 || >=2.33.dev0,<=2.33.0)", "ray[default] (>=2.5,<=2.33.0)", "ray[train]", "scikit-learn", "setuptools (<70.0.0)", "tensorflow", "torch (>=2.0.0,<2.1.0)", "xgboost", "xgboost-ray"]
 reasoningengine = ["cloudpickle (>=3.0,<4.0)", "google-cloud-trace (<2)", "opentelemetry-exporter-gcp-trace (<2)", "opentelemetry-sdk (<2)", "pydantic (>=2.6.3,<3)"]
 tensorboard = ["tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "werkzeug (>=2.0.0,<2.1.0dev)"]
-testing = ["bigframes", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.114.0)", "google-api-core (>=2.11,<3.0.0)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "ipython", "kfp (>=2.6.0,<3.0.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.16.0)", "nltk", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<2.10.dev0 || >=2.33.dev0,<=2.33.0)", "ray[default] (>=2.5,<=2.33.0)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "sentencepiece (>=0.2.0)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (==2.13.0)", "tensorflow (==2.16.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "torch (>=2.2.0)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
+testing = ["aiohttp", "bigframes", "docker (>=5.0.3)", "explainable-ai-sdk (>=1.0.0)", "fastapi (>=0.71.0,<=0.114.0)", "google-api-core (>=2.11,<3.0.0)", "google-cloud-bigquery", "google-cloud-bigquery-storage", "google-vizier (>=0.1.6)", "grpcio-testing", "httpx (>=0.23.0,<0.25.0)", "immutabledict", "ipython", "kfp (>=2.6.0,<3.0.0)", "lit-nlp (==0.4.0)", "mlflow (>=1.27.0,<=2.16.0)", "nltk", "numpy (>=1.15.0)", "pandas (>=1.0.0)", "pandas (>=1.0.0,<2.2.0)", "pyarrow (>=10.0.1)", "pyarrow (>=14.0.0)", "pyarrow (>=3.0.0,<8.0dev)", "pyarrow (>=6.0.1)", "pytest-asyncio", "pytest-xdist", "pyyaml (>=5.3.1,<7)", "ray[default] (>=2.4,<2.5.dev0 || >2.9.0,!=2.9.1,!=2.9.2,<2.10.dev0 || >=2.33.dev0,<=2.33.0)", "ray[default] (>=2.5,<=2.33.0)", "requests (>=2.28.1)", "requests-toolbelt (<1.0.0)", "scikit-learn", "sentencepiece (>=0.2.0)", "setuptools (<70.0.0)", "starlette (>=0.17.1)", "tensorboard-plugin-profile (>=2.4.0,<3.0.0dev)", "tensorflow (==2.13.0)", "tensorflow (==2.16.1)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.3.0,<3.0.0dev)", "tensorflow (>=2.4.0,<3.0.0dev)", "torch (>=2.0.0,<2.1.0)", "torch (>=2.2.0)", "tqdm (>=4.23.0)", "urllib3 (>=1.21.1,<1.27)", "uvicorn[standard] (>=0.16.0)", "werkzeug (>=2.0.0,<2.1.0dev)", "xgboost"]
 tokenization = ["sentencepiece (>=0.2.0)"]
 vizier = ["google-vizier (>=0.1.6)"]
 xai = ["tensorflow (>=2.3.0,<3.0.0dev)"]
@@ -4336,13 +4336,13 @@ tenacity = ">=8.1.0,<8.4.0 || >8.4.0,<9.0.0"
 
 [[package]]
 name = "langchain-core"
-version = "0.2.41"
+version = "0.2.42"
 description = "Building applications with LLMs through composability"
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langchain_core-0.2.41-py3-none-any.whl", hash = "sha256:3278fda5ba9a05defae8bb19f1226032add6aab21917db7b3bc74e750e263e84"},
-    {file = "langchain_core-0.2.41.tar.gz", hash = "sha256:bc12032c5a298d85be754ccb129bc13ea21ccb1d6e22f8d7ba18b8da64315bb5"},
+    {file = "langchain_core-0.2.42-py3-none-any.whl", hash = "sha256:09503fdfb9efa163e51f2d9762894fde04797d0a41462c0e6072ef78028e48fd"},
+    {file = "langchain_core-0.2.42.tar.gz", hash = "sha256:e4ea04b22bd6398048d0ef97cd3132fbdd80e6c749863ee96e6b7c88502ff913"},
 ]
 
 [package.dependencies]
@@ -4461,13 +4461,13 @@ openai = ["openai (>=0.27.8)"]
 
 [[package]]
 name = "langsmith"
-version = "0.1.137"
+version = "0.1.138"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
-    {file = "langsmith-0.1.137-py3-none-any.whl", hash = "sha256:4256d5c61133749890f7b5c88321dbb133ce0f440c621ea28e76513285859b81"},
-    {file = "langsmith-0.1.137.tar.gz", hash = "sha256:56cdfcc6c74cb20a3f437d5bd144feb5bf93f54c5a2918d1e568cbd084a372d4"},
+    {file = "langsmith-0.1.138-py3-none-any.whl", hash = "sha256:5c2bd5c11c75f7b3d06a0f06b115186e7326ca969fd26d66ffc65a0669012aee"},
+    {file = "langsmith-0.1.138.tar.gz", hash = "sha256:1ecf613bb52f6bf17f1510e24ad8b70d4b0259bc9d3dbfd69b648c66d4644f0b"},
 ]
 
 [package.dependencies]
@@ -5184,13 +5184,13 @@ websocket-client = ">=0.32.0,<1"
 
 [[package]]
 name = "mem0ai"
-version = "0.1.25"
+version = "0.1.26"
 description = "Long-term memory for AI Agents"
 optional = false
 python-versions = "<4.0,>=3.9"
 files = [
-    {file = "mem0ai-0.1.25-py3-none-any.whl", hash = "sha256:78ede71d443459145f6ab5dc63066811cc9e683646979ced127a8985ff717f06"},
-    {file = "mem0ai-0.1.25.tar.gz", hash = "sha256:3637238d0bc6b73e32d430b8f3da285e153a922cc821c63ca6ad7c97ff057616"},
+    {file = "mem0ai-0.1.26-py3-none-any.whl", hash = "sha256:42a64702e69ec39d939e6c6f7b2e950da6e674cc36023f9c4ffb4f8fe60d5944"},
+    {file = "mem0ai-0.1.26.tar.gz", hash = "sha256:2b7c4eee7d99d6a2da08af2da653f7bd77c7d97ff984b46bede11ce12e8ab7d1"},
 ]
 
 [package.dependencies]
@@ -5234,6 +5234,20 @@ url = "https://github.com/galatolofederico/microchain.git"
 reference = "de75f1d4a073b7c54f824b409733f4f70d40a61b"
 resolved_reference = "de75f1d4a073b7c54f824b409733f4f70d40a61b"
 
+[[package]]
+name = "mirakuru"
+version = "2.5.3"
+description = "Process executor (not only) for tests."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "mirakuru-2.5.3-py3-none-any.whl", hash = "sha256:2fab68356fb98fb5358ea3ab65f5e511f34b5a0b16cfd0a0935ef15a3393f025"},
+    {file = "mirakuru-2.5.3.tar.gz", hash = "sha256:39b33f8fcdf13764a6cfe936e0feeead3902a161fec438df3be7cce98f7933c6"},
+]
+
+[package.dependencies]
+psutil = {version = ">=4.0.0", markers = "sys_platform != \"cygwin\""}
+
 [[package]]
 name = "mmh3"
 version = "5.0.1"
@@ -5698,13 +5712,13 @@ files = [
 
 [[package]]
 name = "narwhals"
-version = "1.12.0"
+version = "1.12.1"
 description = "Extremely lightweight compatibility layer between dataframe libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "narwhals-1.12.0-py3-none-any.whl", hash = "sha256:5899eb11319d3485d20f46e6634651baee98d47e961b9b184cecaf9b13d66efc"},
-    {file = "narwhals-1.12.0.tar.gz", hash = "sha256:4ada6a2367d72ad920b161cf9088953b03ebafff541b40f0f751995cd03f1261"},
+    {file = "narwhals-1.12.1-py3-none-any.whl", hash = "sha256:e251cb5fe4cabdcabb847d359f5de2b81df773df47e46f858fd5570c936919c4"},
+    {file = "narwhals-1.12.1.tar.gz", hash = "sha256:65ff0d1e8b509df8b52b395e8d5fe96751a68657bdabf0f3057a970ec2cd1809"},
 ]
 
 [package.extras]
@@ -6020,13 +6034,13 @@ web3 = ">=6.0.0,<7"
 
 [[package]]
 name = "openai"
-version = "1.52.2"
+version = "1.53.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
-    {file = "openai-1.52.2-py3-none-any.whl", hash = "sha256:57e9e37bc407f39bb6ec3a27d7e8fb9728b2779936daa1fcf95df17d3edfaccc"},
-    {file = "openai-1.52.2.tar.gz", hash = "sha256:87b7d0f69d85f5641678d414b7ee3082363647a5c66a462ed7f3ccb59582da0d"},
+    {file = "openai-1.53.0-py3-none-any.whl", hash = "sha256:20f408c32fc5cb66e60c6882c994cdca580a5648e10045cd840734194f033418"},
+    {file = "openai-1.53.0.tar.gz", hash = "sha256:be2c4e77721b166cce8130e544178b7d579f751b4b074ffbaade3854b6f85ec5"},
 ]
 
 [package.dependencies]
@@ -6826,6 +6840,17 @@ files = [
 poetry = ">=1.8.0,<3.0.0"
 poetry-core = ">=1.7.0,<3.0.0"
 
+[[package]]
+name = "port-for"
+version = "0.7.4"
+description = "Utility that helps with local TCP ports management. It can find an unused TCP localhost port and remember the association."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "port_for-0.7.4-py3-none-any.whl", hash = "sha256:08404aa072651a53dcefe8d7a598ee8a1dca320d9ac44ac464da16ccf2a02c4a"},
+    {file = "port_for-0.7.4.tar.gz", hash = "sha256:fc7713e7b22f89442f335ce12536653656e8f35146739eccaeff43d28436028d"},
+]
+
 [[package]]
 name = "portalocker"
 version = "2.10.1"
@@ -6870,13 +6895,13 @@ test = ["coverage", "django", "flake8", "freezegun (==0.3.15)", "mock (>=2.0.0)"
 
 [[package]]
 name = "prediction-market-agent-tooling"
-version = "0.55.1"
+version = "0.56.0.dev113"
 description = "Tools to benchmark, deploy and monitor prediction market agents."
 optional = false
 python-versions = "<3.12,>=3.10"
 files = [
-    {file = "prediction_market_agent_tooling-0.55.1-py3-none-any.whl", hash = "sha256:cf324e41c7e5e112c9abd6b54263084fa133e463a9edbef22fdb0f2274cd427f"},
-    {file = "prediction_market_agent_tooling-0.55.1.tar.gz", hash = "sha256:21289f964d8dc15a08679866a1c95c13aecb9fe7fe8772699591c67709bb1aed"},
+    {file = "prediction_market_agent_tooling-0.56.0.dev113-py3-none-any.whl", hash = "sha256:ea1ef18122ee88b04910f9d160fa937d58233e654ff179996ea2ed5ae88a605c"},
+    {file = "prediction_market_agent_tooling-0.56.0.dev113.tar.gz", hash = "sha256:e9e98abc24797a49f2101007b955a6075efbae25080c87473bd3e919a25ff953"},
 ]
 
 [package.dependencies]
@@ -6905,6 +6930,7 @@ psycopg2-binary = ">=2.9.9,<3.0.0"
 pydantic = ">=2.6.1,<3.0.0"
 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"
 safe-cli = ">=1.0.0,<2.0.0"
 safe-eth-py = ">=6.0.0b41,<7.0.0"
@@ -6950,7 +6976,7 @@ matplotlib = "^3.8.3"
 memory-profiler = "^0.61.0"
 openai = "^1.10.0"
 pandas = "^2.1.1"
-prediction-market-agent-tooling = {version = ">=0.55.0,<1", extras = ["google", "langchain"]}
+prediction-market-agent-tooling = {version = "^0.56.0.dev113", extras = ["google", "langchain"]}
 pyautogen = "^0.2.19"
 pysqlite3-binary = {version = "^0.5.2.post3", markers = "sys_platform == \"linux\""}
 python-dateutil = "^2.9.0.post0"
@@ -6969,8 +6995,8 @@ watchdog = "^3.0.0"
 [package.source]
 type = "git"
 url = "https://github.com/agentcoinorg/predictionprophet.git"
-reference = "main"
-resolved_reference = "5a7e9e4300d53acf32e09bd4b995c1722c3a7131"
+reference = "peter/latest-pmat-cache"
+resolved_reference = "5db93a7cd9cec6d4b0f4a962c55549e97b591320"
 
 [[package]]
 name = "preshed"
@@ -7242,6 +7268,29 @@ files = [
 dev = ["black", "check-manifest", "coverage", "packaging", "pylint", "pyperf", "pypinfo", "pytest-cov", "requests", "rstcheck", "ruff", "sphinx", "sphinx_rtd_theme", "toml-sort", "twine", "virtualenv", "wheel"]
 test = ["pytest", "pytest-xdist", "setuptools"]
 
+[[package]]
+name = "psycopg"
+version = "3.2.3"
+description = "PostgreSQL database adapter for Python"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "psycopg-3.2.3-py3-none-any.whl", hash = "sha256:644d3973fe26908c73d4be746074f6e5224b03c1101d302d9a53bf565ad64907"},
+    {file = "psycopg-3.2.3.tar.gz", hash = "sha256:a5764f67c27bec8bfac85764d23c534af2c27b893550377e37ce59c12aac47a2"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4.6", markers = "python_version < \"3.13\""}
+tzdata = {version = "*", markers = "sys_platform == \"win32\""}
+
+[package.extras]
+binary = ["psycopg-binary (==3.2.3)"]
+c = ["psycopg-c (==3.2.3)"]
+dev = ["ast-comments (>=1.1.2)", "black (>=24.1.0)", "codespell (>=2.2)", "dnspython (>=2.1)", "flake8 (>=4.0)", "mypy (>=1.11)", "types-setuptools (>=57.4)", "wheel (>=0.37)"]
+docs = ["Sphinx (>=5.0)", "furo (==2022.6.21)", "sphinx-autobuild (>=2021.3.14)", "sphinx-autodoc-typehints (>=1.12)"]
+pool = ["psycopg-pool"]
+test = ["anyio (>=4.0)", "mypy (>=1.11)", "pproxy (>=2.7)", "pytest (>=6.2.5)", "pytest-cov (>=3.0)", "pytest-randomly (>=3.5)"]
+
 [[package]]
 name = "psycopg2-binary"
 version = "2.9.10"
@@ -7521,6 +7570,7 @@ description = "Pure-Python implementation of ASN.1 types and DER/BER/CER codecs
 optional = false
 python-versions = ">=3.8"
 files = [
+    {file = "pyasn1-0.6.1-py3-none-any.whl", hash = "sha256:0d632f46f2ba09143da3a8afe9e33fb6f92fa2320ab7e886e2d0f7672af84629"},
     {file = "pyasn1-0.6.1.tar.gz", hash = "sha256:6f580d2bdd84365380830acf45550f2511469f673cb4a5ae3857a3170128b034"},
 ]
 
@@ -7531,6 +7581,7 @@ description = "A collection of ASN.1-based protocols modules"
 optional = false
 python-versions = ">=3.8"
 files = [
+    {file = "pyasn1_modules-0.4.1-py3-none-any.whl", hash = "sha256:49bfa96b45a292b711e986f222502c1c9a5e1f4e568fc30e2574a6c7d07838fd"},
     {file = "pyasn1_modules-0.4.1.tar.gz", hash = "sha256:c28e2dbf9c06ad61c71a075c7e0f9fd0f1b0bb2d2ad4377f240d33ac2ab60a7c"},
 ]
 
@@ -8144,6 +8195,24 @@ pytest = ">=7.0.0,<9"
 docs = ["sphinx (>=5.3)", "sphinx-rtd-theme (>=1.0)"]
 testing = ["coverage (>=6.2)", "hypothesis (>=5.7.1)"]
 
+[[package]]
+name = "pytest-postgresql"
+version = "6.1.1"
+description = "Postgresql fixtures and fixture factories for Pytest."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "pytest_postgresql-6.1.1-py3-none-any.whl", hash = "sha256:bd4c0970d25685ac3d34d42263fcbfbf134bf02d22519fce7e1ccf4122d8b99a"},
+    {file = "pytest_postgresql-6.1.1.tar.gz", hash = "sha256:f996637367e6aecebba1349da52eea95340bdb434c90e4b79739e62c656056e2"},
+]
+
+[package.dependencies]
+mirakuru = "*"
+port-for = ">=0.7.3"
+psycopg = ">=3.0.0"
+pytest = ">=6.2"
+setuptools = "*"
+
 [[package]]
 name = "python-baseconv"
 version = "1.2.2"
@@ -8306,13 +8375,13 @@ files = [
 
 [[package]]
 name = "qdrant-client"
-version = "1.12.0"
+version = "1.12.1"
 description = "Client library for the Qdrant vector search engine"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "qdrant_client-1.12.0-py3-none-any.whl", hash = "sha256:6db5ac1e244272f8b67e9dbc0da557816efef6f919cd8ee134469c751fe72c03"},
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 [[package]]
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 version = "75.3.0"
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 ]
 
 [package.dependencies]
@@ -11078,4 +11134,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.0"
 python-versions = "~3.10.0"
-content-hash = "10e4fecf6ff24730a6465f1c4e928173a2f1f854f3605bdb8a794b87a0b065b3"
+content-hash = "fa487d1a17c477fea463f4b61c1906baa2ea56f20eefcd35f70a160224666aa6"
diff --git a/prediction_market_agent/agents/invalid_agent/deploy.py b/prediction_market_agent/agents/invalid_agent/deploy.py
index 64b6348b..b745a6d9 100644
--- a/prediction_market_agent/agents/invalid_agent/deploy.py
+++ b/prediction_market_agent/agents/invalid_agent/deploy.py
@@ -23,7 +23,7 @@ class InvalidAgent(DeployableTraderAgent):
 
     def verify_market(self, market_type: MarketType, market: AgentMarket) -> bool:
         if self.have_bet_on_market_since(
-            market, since=self.same_market_trade_interval.get(market=market)
+            market, since=self.same_market_trade_interval.get(market)
         ):
             return False
 
diff --git a/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py b/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
index 53264a34..ab64d4da 100644
--- a/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
+++ b/prediction_market_agent/agents/known_outcome_agent/known_outcome_agent.py
@@ -9,12 +9,12 @@
     get_langfuse_langchain_config,
     observe,
 )
+from prediction_market_agent_tooling.tools.tavily.tavily_search import tavily_search
 from prediction_market_agent_tooling.tools.utils import utcnow
 from pydantic import BaseModel
 
 from prediction_market_agent.tools.web_scrape.basic_summary import _summary
 from prediction_market_agent.tools.web_scrape.markdown import web_scrape
-from prediction_market_agent.tools.web_search.tavily import web_search
 from prediction_market_agent.utils import APIKeys, completion_str_to_json
 
 
@@ -220,7 +220,7 @@ def get_known_outcome(model: str, question: str, max_tries: int) -> KnownOutcome
             ).content
         ).strip('"')
         logger.debug(f"Searching web for the search query '{search_query}'")
-        search_results = web_search(query=search_query, max_results=5)
+        search_results = tavily_search(query=search_query, max_results=5).results
         if not search_results:
             raise ValueError("No search results found.")
 
diff --git a/prediction_market_agent/agents/microchain_agent/market_functions.py b/prediction_market_agent/agents/microchain_agent/market_functions.py
index 21b2c749..e2c0e84a 100644
--- a/prediction_market_agent/agents/microchain_agent/market_functions.py
+++ b/prediction_market_agent/agents/microchain_agent/market_functions.py
@@ -16,7 +16,6 @@
 from prediction_market_agent_tooling.tools.betting_strategies.kelly_criterion import (
     get_kelly_bet_simplified,
 )
-from prediction_market_agent_tooling.tools.tavily.tavily_storage import TavilyStorage
 from prediction_market_agent_tooling.tools.utils import utcnow
 
 from prediction_market_agent.agents.microchain_agent.utils import (
@@ -139,7 +138,6 @@ def __call__(self, market_id: str) -> str:
             model=self.model,
             openai_api_key=self.keys.openai_api_key,
             tavily_api_key=self.keys.tavily_api_key,
-            tavily_storage=TavilyStorage(agent_id=self.__class__.__name__),
         )
         prediction = prophet_make_prediction(
             market_question=question,
diff --git a/prediction_market_agent/agents/prophet_agent/deploy.py b/prediction_market_agent/agents/prophet_agent/deploy.py
index 75a5a834..8ca835fc 100644
--- a/prediction_market_agent/agents/prophet_agent/deploy.py
+++ b/prediction_market_agent/agents/prophet_agent/deploy.py
@@ -6,7 +6,6 @@
 from prediction_market_agent_tooling.loggers import logger
 from prediction_market_agent_tooling.markets.agent_market import AgentMarket
 from prediction_market_agent_tooling.markets.data_models import ProbabilisticAnswer
-from prediction_market_agent_tooling.tools.tavily.tavily_storage import TavilyStorage
 from prediction_prophet.benchmark.agents import (
     EmbeddingModel,
     OlasAgent,
@@ -53,7 +52,6 @@ def load(self) -> None:
         self.agent = PredictionProphetAgent(
             model="gpt-4o-2024-08-06",
             include_reasoning=True,
-            tavily_storage=TavilyStorage(agent_id=self.__class__.__name__),
             logger=logger,
         )
 
@@ -74,7 +72,6 @@ def load(self) -> None:
         self.agent = PredictionProphetAgent(
             model="gpt-4-0125-preview",
             include_reasoning=True,
-            tavily_storage=TavilyStorage(agent_id=self.__class__.__name__),
             logger=logger,
         )
 
@@ -95,7 +92,6 @@ def load(self) -> None:
         self.agent = PredictionProphetAgent(
             model="gpt-4-turbo-2024-04-09",
             include_reasoning=True,
-            tavily_storage=TavilyStorage(agent_id=self.__class__.__name__),
             logger=logger,
         )
 
@@ -138,7 +134,6 @@ def load(self) -> None:
             research_temperature=1.0,
             prediction_temperature=1.0,
             include_reasoning=True,
-            tavily_storage=TavilyStorage(agent_id=self.__class__.__name__),
             logger=logger,
         )
 
@@ -162,6 +157,5 @@ def load(self) -> None:
             research_temperature=1.0,
             prediction_temperature=1.0,
             include_reasoning=True,
-            tavily_storage=TavilyStorage(agent_id=self.__class__.__name__),
             logger=logger,
         )
diff --git a/prediction_market_agent/agents/think_thoroughly_agent/think_thoroughly_agent.py b/prediction_market_agent/agents/think_thoroughly_agent/think_thoroughly_agent.py
index d0577b1e..b2fb5c18 100644
--- a/prediction_market_agent/agents/think_thoroughly_agent/think_thoroughly_agent.py
+++ b/prediction_market_agent/agents/think_thoroughly_agent/think_thoroughly_agent.py
@@ -21,7 +21,6 @@
 )
 from prediction_market_agent_tooling.tools.langfuse_ import langfuse_context, observe
 from prediction_market_agent_tooling.tools.parallelism import par_generator, par_map
-from prediction_market_agent_tooling.tools.tavily.tavily_storage import TavilyStorage
 from prediction_market_agent_tooling.tools.utils import (
     LLM_SUPER_LOW_TEMPERATURE,
     DatetimeUTC,
@@ -467,9 +466,6 @@ def generate_prediction_for_one_outcome(
             model=model,
             openai_api_key=api_keys.openai_api_key,
             tavily_api_key=api_keys.tavily_api_key,
-            tavily_storage=TavilyStorage(
-                agent_id=ThinkThoroughlyWithPredictionProphetResearch.identifier
-            ),
         )
         prediction = prophet_make_prediction(
             market_question=scenario,
@@ -509,7 +505,6 @@ def generate_final_decision(
                 model=self.model,
                 openai_api_key=api_keys.openai_api_key,
                 tavily_api_key=api_keys.tavily_api_key,
-                tavily_storage=TavilyStorage(agent_id=self.identifier),
             ).report
         )
         return super().generate_final_decision(
diff --git a/prediction_market_agent/tools/prediction_prophet/research.py b/prediction_market_agent/tools/prediction_prophet/research.py
index 828ba7fb..15f8f905 100644
--- a/prediction_market_agent/tools/prediction_prophet/research.py
+++ b/prediction_market_agent/tools/prediction_prophet/research.py
@@ -1,5 +1,4 @@
 from prediction_market_agent_tooling.loggers import logger
-from prediction_market_agent_tooling.tools.tavily.tavily_storage import TavilyStorage
 from prediction_prophet.benchmark.agents import (  # noqa: F401 # Just to make it available for the user of research.
     _make_prediction as prophet_make_prediction,
 )
@@ -13,7 +12,6 @@ def prophet_research(
     model: str,
     openai_api_key: SecretStr,
     tavily_api_key: SecretStr,
-    tavily_storage: TavilyStorage | None,
     initial_subqueries_limit: int = 20,
     subqueries_limit: int = 4,
     max_results_per_search: int = 5,
@@ -41,6 +39,5 @@ def prophet_research(
         min_scraped_sites=min_scraped_sites,
         openai_api_key=openai_api_key,
         tavily_api_key=tavily_api_key,
-        tavily_storage=tavily_storage,
         logger=logger,
     )
diff --git a/prediction_market_agent/tools/web_scrape/markdown.py b/prediction_market_agent/tools/web_scrape/markdown.py
index 261df9eb..e4f5e294 100644
--- a/prediction_market_agent/tools/web_scrape/markdown.py
+++ b/prediction_market_agent/tools/web_scrape/markdown.py
@@ -1,9 +1,11 @@
+from datetime import timedelta
+
 import requests
 import tenacity
 from bs4 import BeautifulSoup
 from markdownify import markdownify
 from prediction_market_agent_tooling.loggers import logger
-from prediction_market_agent_tooling.tools.cache import persistent_inmemory_cache
+from prediction_market_agent_tooling.tools.caches.db_cache import db_cache
 from prediction_market_agent_tooling.tools.langfuse_ import observe
 from requests import Response
 
@@ -11,7 +13,6 @@
 @tenacity.retry(
     stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_fixed(1), reraise=True
 )
-@persistent_inmemory_cache
 def fetch_html(url: str, timeout: int) -> Response:
     headers = {
         "User-Agent": "Mozilla/5.0 (X11; Linux x86_64; rv:107.0) Gecko/20100101 Firefox/107.0"
@@ -21,6 +22,7 @@ def fetch_html(url: str, timeout: int) -> Response:
 
 
 @observe()
+@db_cache(max_age=timedelta(days=1))
 def web_scrape(url: str, timeout: int = 10) -> str:
     """
     Taken from agentcoinorg/predictionprophet
diff --git a/prediction_market_agent/tools/web_search/google.py b/prediction_market_agent/tools/web_search/google.py
index 47b86d08..7936d4eb 100644
--- a/prediction_market_agent/tools/web_search/google.py
+++ b/prediction_market_agent/tools/web_search/google.py
@@ -1,23 +1,9 @@
-import serpapi
+from prediction_market_agent_tooling.tools.google import search_google
 
-from prediction_market_agent import utils
-
-
-def google_search(query: str) -> list[str]:
-    params = {
-        "q": query,
-        "api_key": utils.APIKeys().serp_api_key.get_secret_value(),
-        "num": 4,
-    }
-    search = serpapi.GoogleSearch(params)
-    urls = [result["link"] for result in search.get_dict()["organic_results"]]
-    return urls
-
-
-google_search_schema = {
+search_google_schema = {
     "type": "function",
     "function": {
-        "name": "google_search",
+        "name": "search_google",
         "parameters": {
             "type": "object",
             "properties": {
@@ -35,5 +21,5 @@ def google_search(query: str) -> list[str]:
 
 class GoogleSearchTool:
     def __init__(self) -> None:
-        self.fn = google_search
-        self.schema = google_search_schema
+        self.fn = search_google
+        self.schema = search_google_schema
diff --git a/prediction_market_agent/tools/web_search/tavily.py b/prediction_market_agent/tools/web_search/tavily.py
deleted file mode 100644
index c6710d55..00000000
--- a/prediction_market_agent/tools/web_search/tavily.py
+++ /dev/null
@@ -1,40 +0,0 @@
-import tenacity
-from prediction_market_agent_tooling.tools.cache import persistent_inmemory_cache
-from prediction_market_agent_tooling.tools.langfuse_ import observe
-from pydantic import BaseModel
-from tavily import TavilyClient
-
-from prediction_market_agent.utils import APIKeys
-
-
-class WebSearchResult(BaseModel):
-    url: str
-    query: str
-
-
-@tenacity.retry(
-    stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_fixed(1), reraise=True
-)
-@persistent_inmemory_cache
-@observe()
-def web_search(query: str, max_results: int) -> list[WebSearchResult]:
-    """
-    Web search using Tavily API.
-    """
-    tavily = TavilyClient(api_key=APIKeys().tavily_api_key.get_secret_value())
-    response = tavily.search(
-        query=query,
-        search_depth="advanced",
-        max_results=max_results,
-        include_raw_content=True,
-    )
-
-    results = [
-        WebSearchResult(
-            url=result["url"],
-            query=query,
-        )
-        for result in response["results"]
-    ]
-
-    return results
diff --git a/prediction_market_agent/utils.py b/prediction_market_agent/utils.py
index 0fe3f80a..aaed0c63 100644
--- a/prediction_market_agent/utils.py
+++ b/prediction_market_agent/utils.py
@@ -23,7 +23,6 @@ class DBKeys(BaseSettings):
 
 class APIKeys(APIKeysBase):
     # Don't get fooled! Serper and Serp are two different services.
-    SERP_API_KEY: t.Optional[SecretStr] = None
     SERPER_API_KEY: t.Optional[SecretStr] = None
     OPENAI_API_KEY: t.Optional[SecretStr] = None
     REPLICATE_API_KEY: t.Optional[SecretStr] = None
@@ -33,12 +32,6 @@ class APIKeys(APIKeysBase):
     PINATA_API_SECRET: t.Optional[SecretStr] = None
     TELEGRAM_BOT_KEY: t.Optional[SecretStr] = None
 
-    @property
-    def serp_api_key(self) -> SecretStr:
-        return check_not_none(
-            self.SERP_API_KEY, "SERP_API_KEY missing in the environment."
-        )
-
     @property
     def serper_api_key(self) -> SecretStr:
         return check_not_none(
diff --git a/pyproject.toml b/pyproject.toml
index 8fe614c7..98c563d4 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -17,7 +17,6 @@ numexpr = "*"
 pyautogen = "^0.2.32"
 flaml = "^2.2.0,<2.3.0" # Bug in newer version, because they started importing xgboost, without requiring it as a dependency.
 beautifulsoup4 = "*"
-serpapi = "*"
 google-search-results = "*"
 pytest = "*"
 llama-index = "~0.9.0"
@@ -35,7 +34,7 @@ poetry = "^1.7.1"
 poetry-plugin-export = "^1.6.0"
 functions-framework = "^3.5.0"
 cron-validator = "^1.0.8"
-prediction-market-agent-tooling = { version = "^0.55.1", extras = ["langchain", "google"] }
+prediction-market-agent-tooling = { version = "^0.56.0.dev112", extras = ["langchain", "google"] }
 pydantic-settings = "^2.1.0"
 autoflake = "^2.2.1"
 isort = "^5.13.2"
@@ -52,7 +51,7 @@ tweepy = "^4.14.0"
 langchain-pinecone = "^0.1.1"
 pinatapy-vourhey = "^0.2.0"
 plotly = "^5.22.0"
-prediction-prophet = { git = "https://github.com/agentcoinorg/predictionprophet.git", branch = "main" }
+prediction-prophet = { git = "https://github.com/agentcoinorg/predictionprophet.git", branch = "peter/latest-pmat-cache" }
 transformers = "^4.43.3"
 openfactverification-kongzii = "^0.2.0"
 
diff --git a/scripts/benchmark_ofv_resolver.py b/scripts/benchmark_ofv_resolver.py
index f1f64f3d..85d00822 100644
--- a/scripts/benchmark_ofv_resolver.py
+++ b/scripts/benchmark_ofv_resolver.py
@@ -1,6 +1,8 @@
 import pandas as pd
 import typer
-from prediction_market_agent_tooling.tools.cache import persistent_inmemory_cache
+from prediction_market_agent_tooling.tools.caches.inmemory_cache import (
+    persistent_inmemory_cache,
+)
 
 from prediction_market_agent.agents.ofvchallenger_agent.ofv_resolver import (
     ofv_answer_binary_question,
diff --git a/scripts/llm_randomness.py b/scripts/llm_randomness.py
index 45dc1338..51b57a36 100644
--- a/scripts/llm_randomness.py
+++ b/scripts/llm_randomness.py
@@ -4,7 +4,9 @@
 from langchain.prompts import ChatPromptTemplate
 from langchain_openai import ChatOpenAI
 from prediction_market_agent_tooling.config import APIKeys
-from prediction_market_agent_tooling.tools.cache import persistent_inmemory_cache
+from prediction_market_agent_tooling.tools.caches.inmemory_cache import (
+    persistent_inmemory_cache,
+)
 from prediction_market_agent_tooling.tools.utils import LLM_SUPER_LOW_TEMPERATURE