diff --git a/docs/api/agent.md b/docs/api/agent.md
index bdd0ae99..bbe37706 100644
--- a/docs/api/agent.md
+++ b/docs/api/agent.md
@@ -1,16 +1,14 @@
-::: vision_agent.agent
+::: vision_agent.agent.agent.Agent
 
-::: vision_agent.agent.agent
+::: vision_agent.agent.vision_agent.VisionAgent
 
-::: vision_agent.agent.vision_agent
+::: vision_agent.agent.agent_coder.AgentCoder
 
-::: vision_agent.agent.agent_coder
+::: vision_agent.agent.data_interpreter.DataInterpreter
 
-::: vision_agent.agent.data_interpreter
+::: vision_agent.agent.easytool_v2.EasyToolV2
 
-::: vision_agent.agent.easytool_v2
+::: vision_agent.agent.easytool.EasyTool
 
-::: vision_agent.agent.easytool
-
-::: vision_agent.agent.reflexion
+::: vision_agent.agent.reflexion.Reflexion
 
diff --git a/docs/api/image_utils.md b/docs/api/image_utils.md
deleted file mode 100644
index f9ae1ed6..00000000
--- a/docs/api/image_utils.md
+++ /dev/null
@@ -1 +0,0 @@
-::: vision_agent.image_utils
\ No newline at end of file
diff --git a/docs/api/llm.md b/docs/api/llm.md
index 0588e797..684d327e 100644
--- a/docs/api/llm.md
+++ b/docs/api/llm.md
@@ -1,3 +1 @@
-::: vision_agent.llm
-
-::: vision_agent.llm.llm
\ No newline at end of file
+::: vision_agent.llm.OpenAILLM
diff --git a/docs/api/lmm.md b/docs/api/lmm.md
index 2c4f433a..8f6f8fe7 100644
--- a/docs/api/lmm.md
+++ b/docs/api/lmm.md
@@ -1,3 +1 @@
-::: vision_agent.lmm
-
-::: vision_agent.lmm.lmm
\ No newline at end of file
+::: vision_agent.lmm.OpenAILMM
diff --git a/docs/easy_tool_v2.md b/docs/easy_tool_v2.md
index 4e4cca7f..584a69b7 100644
--- a/docs/easy_tool_v2.md
+++ b/docs/easy_tool_v2.md
@@ -91,7 +91,7 @@ agent(
 ```
 Here, `reference_mask.png` and `reference_image.png` in `reference_data` could be any
 image with it's corresponding mask that is the object you want to detect in `image.jpg`.
-You can find a demo app to generate masks for DINOv [here](examples/mask_app/).
+You can find a demo app to generate masks for DINOv [here](https://github.com/landing-ai/vision-agent/tree/main/examples/mask_app).
 
 ### Tools
 There are a variety of tools for the model or the user to use. Some are executed locally
@@ -134,7 +134,7 @@ class NumItems(Tool):
 ```
 This will register it with the list of tools Easy Tool V2 has access to. It will be able
 to pick it based on the tool description and use it based on the usage provided. You can
-find an example that creates a custom tool for template matching [here](examples/custom_tools/).
+find an example that creates a custom tool for template matching [here](https://github.com/landing-ai/vision-agent/tree/main/examples/custom_tools).
 
 #### Tool List
 | Tool | Description |
diff --git a/docs/index.md b/docs/index.md
index 539ab9b4..8c42a288 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -136,7 +136,7 @@ def custom_tool(image_path: str) -> str:
 
 You need to ensure you call `@va.tools.register_tool` with any imports it might use and
 ensure the documentation is in the same format above with description, `Parameters:`,
-`Returns:`, and `Example\n-------`. You can find an example use case [here](examples/custom_tools/).
+`Returns:`, and `Example\n-------`. You can find an example use case [here](https://github.com/landing-ai/vision-agent/tree/main/examples/custom_tools).
 
 ### Azure Setup
 If you want to use Azure OpenAI models, you can set the environment variable:
diff --git a/mkdocs.yml b/mkdocs.yml
index 7409b561..33fd6e22 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -37,5 +37,5 @@ nav:
     - vision_agent.tools: api/tools.md
     - vision_agent.llm: api/llm.md
     - vision_agent.lmm: api/lmm.md
-    - vision_agent.image_utils: api/image_utils.md
-  - Old documentation: old.md
+    - vision_agent.utils: api/utils.md
+  - EasyToolV2: easy_tool_v2.md
diff --git a/poetry.lock b/poetry.lock
index a76984bd..cb674156 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -124,24 +124,24 @@ frozenlist = ">=1.1.0"
 
 [[package]]
 name = "annotated-types"
-version = "0.6.0"
+version = "0.7.0"
 description = "Reusable constraint types to use with typing.Annotated"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
-    {file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
+    {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
+    {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
 ]
 
 [[package]]
 name = "anyio"
-version = "4.3.0"
+version = "4.4.0"
 description = "High level compatibility layer for multiple asynchronous event loop implementations"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anyio-4.3.0-py3-none-any.whl", hash = "sha256:048e05d0f6caeed70d731f3db756d35dcc1f35747c8c403364a8332c630441b8"},
-    {file = "anyio-4.3.0.tar.gz", hash = "sha256:f75253795a87df48568485fd18cdd2a3fa5c4f7c5be8e5e36637733fce06fed6"},
+    {file = "anyio-4.4.0-py3-none-any.whl", hash = "sha256:c1b2d8f46a8a812513012e1107cb0e68c17159a7a594208005a57dc776e1bdc7"},
+    {file = "anyio-4.4.0.tar.gz", hash = "sha256:5aadc6a1bbb7cdb0bede386cac5e2940f5e2ff3aa20277e991cf028e0585ce94"},
 ]
 
 [package.dependencies]
@@ -231,13 +231,13 @@ tomli = {version = ">=2.0.1", markers = "python_version < \"3.11\""}
 
 [[package]]
 name = "babel"
-version = "2.14.0"
+version = "2.15.0"
 description = "Internationalization utilities"
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
-    {file = "Babel-2.14.0-py3-none-any.whl", hash = "sha256:efb1a25b7118e67ce3a259bed20545c29cb68be8ad2c784c83689981b7a57287"},
-    {file = "Babel-2.14.0.tar.gz", hash = "sha256:6919867db036398ba21eb5c7a0f6b28ab8cbc3ae7a73a44ebe34ae74a4e7d363"},
+    {file = "Babel-2.15.0-py3-none-any.whl", hash = "sha256:08706bdad8d0a3413266ab61bd6c34d0c28d6e1e7badf40a2cebe67644e2e1fb"},
+    {file = "babel-2.15.0.tar.gz", hash = "sha256:8daf0e265d05768bc6c7a314cf1321e9a123afc328cc635c18622a2f30a04413"},
 ]
 
 [package.extras]
@@ -245,33 +245,33 @@ dev = ["freezegun (>=1.0,<2.0)", "pytest (>=6.0)", "pytest-cov"]
 
 [[package]]
 name = "black"
-version = "24.3.0"
+version = "24.4.2"
 description = "The uncompromising code formatter."
 optional = false
 python-versions = ">=3.8"
 files = [
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-    {file = "black-24.3.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:9f50ea1132e2189d8dff0115ab75b65590a3e97de1e143795adb4ce317934995"},
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 ]
 
 [package.dependencies]
@@ -291,13 +291,13 @@ uvloop = ["uvloop (>=0.15.2)"]
 
 [[package]]
 name = "certifi"
-version = "2024.2.2"
+version = "2024.6.2"
 description = "Python package for providing Mozilla's CA Bundle."
 optional = false
 python-versions = ">=3.6"
 files = [
-    {file = "certifi-2024.2.2-py3-none-any.whl", hash = "sha256:dc383c07b76109f368f6106eee2b593b04a011ea4d55f652c6ca24a754d1cdd1"},
-    {file = "certifi-2024.2.2.tar.gz", hash = "sha256:0569859f95fc761b18b45ef421b1290a0f65f147e92a1e5eb3e635f9a5e4e66f"},
+    {file = "certifi-2024.6.2-py3-none-any.whl", hash = "sha256:ddc6c8ce995e6987e7faf5e3f1b02b302836a0e5d98ece18392cb1a36c72ad56"},
+    {file = "certifi-2024.6.2.tar.gz", hash = "sha256:3cd43f1c6fa7dedc5899d69d3ad0398fd018ad1a17fba83ddaf78aa46c747516"},
 ]
 
 [[package]]
@@ -574,13 +574,13 @@ files = [
 
 [[package]]
 name = "e2b"
-version = "0.17.0"
+version = "0.17.1"
 description = "E2B SDK that give agents cloud environments"
 optional = false
 python-versions = "<4.0,>=3.8"
 files = [
-    {file = "e2b-0.17.0-py3-none-any.whl", hash = "sha256:4ac1905ba9801d566d8c4fca2558c74e622c06757b43550cf31f66055acc43c5"},
-    {file = "e2b-0.17.0.tar.gz", hash = "sha256:64b71ff10fe5183ec3c9c7a643de9a89f3e4f00180c7732c6a2beb5c090d04b8"},
+    {file = "e2b-0.17.1-py3-none-any.whl", hash = "sha256:c0698fd03b639f4dd88eed167a98af4d450668c0ae9805122a98f62f36f2491f"},
+    {file = "e2b-0.17.1.tar.gz", hash = "sha256:9e69a059cb73334bac7db189287552af9321fb3ac8ced52557907e10c4310733"},
 ]
 
 [package.dependencies]
@@ -612,13 +612,13 @@ websocket-client = ">=1.7.0,<2.0.0"
 
 [[package]]
 name = "exceptiongroup"
-version = "1.2.0"
+version = "1.2.1"
 description = "Backport of PEP 654 (exception groups)"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "exceptiongroup-1.2.0-py3-none-any.whl", hash = "sha256:4bfd3996ac73b41e9b9628b04e079f193850720ea5945fc96a08633c66912f14"},
-    {file = "exceptiongroup-1.2.0.tar.gz", hash = "sha256:91f5c769735f051a4290d52edd0858999b57e5876e9f85937691bd4c9fa3ed68"},
+    {file = "exceptiongroup-1.2.1-py3-none-any.whl", hash = "sha256:5258b9ed329c5bbdd31a309f53cbfb0b155341807f6ff7606a1e801a891b29ad"},
+    {file = "exceptiongroup-1.2.1.tar.gz", hash = "sha256:a4785e48b045528f5bfe627b6ad554ff32def154f42372786903b7abcfe1aa16"},
 ]
 
 [package.extras]
@@ -773,13 +773,13 @@ dev = ["flake8", "markdown", "twine", "wheel"]
 
 [[package]]
 name = "griffe"
-version = "0.42.1"
+version = "0.45.2"
 description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "griffe-0.42.1-py3-none-any.whl", hash = "sha256:7e805e35617601355edcac0d3511cedc1ed0cb1f7645e2d336ae4b05bbae7b3b"},
-    {file = "griffe-0.42.1.tar.gz", hash = "sha256:57046131384043ed078692b85d86b76568a686266cc036b9b56b704466f803ce"},
+    {file = "griffe-0.45.2-py3-none-any.whl", hash = "sha256:297ec8530d0c68e5b98ff86fb588ebc3aa3559bb5dc21f3caea8d9542a350133"},
+    {file = "griffe-0.45.2.tar.gz", hash = "sha256:83ce7dcaafd8cb7f43cbf1a455155015a1eb624b1ffd93249e5e1c4a22b2fdb2"},
 ]
 
 [package.dependencies]
@@ -798,13 +798,13 @@ files = [
 
 [[package]]
 name = "httpcore"
-version = "1.0.4"
+version = "1.0.5"
 description = "A minimal low-level HTTP client."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "httpcore-1.0.4-py3-none-any.whl", hash = "sha256:ac418c1db41bade2ad53ae2f3834a3a0f5ae76b56cf5aa497d2d033384fc7d73"},
-    {file = "httpcore-1.0.4.tar.gz", hash = "sha256:cb2839ccfcba0d2d3c1131d3c3e26dfc327326fbe7a5dc0dbfe9f6c9151bb022"},
+    {file = "httpcore-1.0.5-py3-none-any.whl", hash = "sha256:421f18bac248b25d310f3cacd198d55b8e6125c107797b609ff9b7a6ba7991b5"},
+    {file = "httpcore-1.0.5.tar.gz", hash = "sha256:34a38e2f9291467ee3b44e89dd52615370e152954ba21721378a87b2960f7a61"},
 ]
 
 [package.dependencies]
@@ -815,7 +815,7 @@ h11 = ">=0.13,<0.15"
 asyncio = ["anyio (>=4.0,<5.0)"]
 http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
-trio = ["trio (>=0.22.0,<0.25.0)"]
+trio = ["trio (>=0.22.0,<0.26.0)"]
 
 [[package]]
 name = "httpx"
@@ -854,13 +854,13 @@ files = [
 
 [[package]]
 name = "imageio"
-version = "2.34.0"
+version = "2.34.1"
 description = "Library for reading and writing a wide range of image, video, scientific, and volumetric data formats."
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "imageio-2.34.0-py3-none-any.whl", hash = "sha256:08082bf47ccb54843d9c73fe9fc8f3a88c72452ab676b58aca74f36167e8ccba"},
-    {file = "imageio-2.34.0.tar.gz", hash = "sha256:ae9732e10acf807a22c389aef193f42215718e16bd06eed0c5bb57e1034a4d53"},
+    {file = "imageio-2.34.1-py3-none-any.whl", hash = "sha256:408c1d4d62f72c9e8347e7d1ca9bc11d8673328af3913868db3b828e28b40a4c"},
+    {file = "imageio-2.34.1.tar.gz", hash = "sha256:f13eb76e4922f936ac4a7fec77ce8a783e63b93543d4ea3e40793a6cabd9ac7d"},
 ]
 
 [package.dependencies]
@@ -886,17 +886,17 @@ tifffile = ["tifffile"]
 
 [[package]]
 name = "imageio-ffmpeg"
-version = "0.4.9"
+version = "0.5.1"
 description = "FFMPEG wrapper for Python"
 optional = false
 python-versions = ">=3.5"
 files = [
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-    {file = "imageio_ffmpeg-0.4.9-py3-none-macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", hash = "sha256:24095e882a126a0d217197b86265f821b4bb3cf9004104f67c1384a2b4b49168"},
-    {file = "imageio_ffmpeg-0.4.9-py3-none-manylinux2010_x86_64.whl", hash = "sha256:2996c64af3e5489227096580269317719ea1a8121d207f2e28d6c24ebc4a253e"},
-    {file = "imageio_ffmpeg-0.4.9-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7eead662d2f46d748c0ab446b68f423eb63d2b54d0a8ef96f80607245540866d"},
-    {file = "imageio_ffmpeg-0.4.9-py3-none-win32.whl", hash = "sha256:b6de1e18911687c538d5585d8287ab1a23624ca9dc2044fcc4607de667bcf11e"},
-    {file = "imageio_ffmpeg-0.4.9-py3-none-win_amd64.whl", hash = "sha256:7e900c695c6541b1cb17feb1baacd4009b30a53a45b81c23d53a67ab13ffb766"},
+    {file = "imageio-ffmpeg-0.5.1.tar.gz", hash = "sha256:0ed7a9b31f560b0c9d929c5291cd430edeb9bed3ce9a497480e536dd4326484c"},
+    {file = "imageio_ffmpeg-0.5.1-py3-none-macosx_10_9_intel.macosx_10_9_x86_64.macosx_10_10_intel.macosx_10_10_x86_64.whl", hash = "sha256:1460e84712b9d06910c1f7bb524096b0341d4b7844cea6c20e099d0a24e795b1"},
+    {file = "imageio_ffmpeg-0.5.1-py3-none-manylinux2010_x86_64.whl", hash = "sha256:5289f75c7f755b499653f3209fea4efd1430cba0e39831c381aad2d458f7a316"},
+    {file = "imageio_ffmpeg-0.5.1-py3-none-manylinux2014_aarch64.whl", hash = "sha256:7fa9132a291d5eb28c44553550deb40cbdab831f2a614e55360301a6582eb205"},
+    {file = "imageio_ffmpeg-0.5.1-py3-none-win32.whl", hash = "sha256:89efe2c79979d8174ba8476deb7f74d74c331caee3fb2b65ba2883bec0737625"},
+    {file = "imageio_ffmpeg-0.5.1-py3-none-win_amd64.whl", hash = "sha256:1521e79e253bedbdd36a547e0cbd94a025ba0b558e17f08fea687d805a0e4698"},
 ]
 
 [package.dependencies]
@@ -1102,13 +1102,13 @@ referencing = ">=0.31.0"
 
 [[package]]
 name = "jupyter-client"
-version = "8.6.1"
+version = "8.6.2"
 description = "Jupyter protocol implementation and client libraries"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "jupyter_client-8.6.1-py3-none-any.whl", hash = "sha256:3b7bd22f058434e3b9a7ea4b1500ed47de2713872288c0d511d19926f99b459f"},
-    {file = "jupyter_client-8.6.1.tar.gz", hash = "sha256:e842515e2bab8e19186d89fdfea7abd15e39dd581f94e399f00e2af5a1652d3f"},
+    {file = "jupyter_client-8.6.2-py3-none-any.whl", hash = "sha256:50cbc5c66fd1b8f65ecb66bc490ab73217993632809b6e505687de18e9dea39f"},
+    {file = "jupyter_client-8.6.2.tar.gz", hash = "sha256:2bda14d55ee5ba58552a8c53ae43d215ad9868853489213f37da060ced54d8df"},
 ]
 
 [package.dependencies]
@@ -1121,7 +1121,7 @@ traitlets = ">=5.3"
 
 [package.extras]
 docs = ["ipykernel", "myst-parser", "pydata-sphinx-theme", "sphinx (>=4)", "sphinx-autodoc-typehints", "sphinxcontrib-github-alt", "sphinxcontrib-spelling"]
-test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
+test = ["coverage", "ipykernel (>=6.14)", "mypy", "paramiko", "pre-commit", "pytest (<8.2.0)", "pytest-cov", "pytest-jupyter[client] (>=0.4.1)", "pytest-timeout"]
 
 [[package]]
 name = "jupyter-core"
@@ -1145,13 +1145,13 @@ test = ["ipykernel", "pre-commit", "pytest (<8)", "pytest-cov", "pytest-timeout"
 
 [[package]]
 name = "langsmith"
-version = "0.1.58"
+version = "0.1.73"
 description = "Client library to connect to the LangSmith LLM Tracing and Evaluation Platform."
 optional = false
 python-versions = "<4.0,>=3.8.1"
 files = [
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-    {file = "langsmith-0.1.58.tar.gz", hash = "sha256:a5060933c1fb3006b498ec849677993329d7e6138bdc2ec044068ab806e09c39"},
+    {file = "langsmith-0.1.73-py3-none-any.whl", hash = "sha256:38bfcce2cfcf0b2da2e9628b903c9e768e1ce59d450e8a584514c1638c595e93"},
+    {file = "langsmith-0.1.73.tar.gz", hash = "sha256:0055471cb1fddb76ec65499716764ad0b0314affbdf33ff1f72ad5e2d6a3b224"},
 ]
 
 [package.dependencies]
@@ -1338,34 +1338,34 @@ files = [
 
 [[package]]
 name = "mkdocs"
-version = "1.5.3"
+version = "1.6.0"
 description = "Project documentation with Markdown."
 optional = false
-python-versions = ">=3.7"
+python-versions = ">=3.8"
 files = [
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+    {file = "mkdocs-1.6.0-py3-none-any.whl", hash = "sha256:1eb5cb7676b7d89323e62b56235010216319217d4af5ddc543a91beb8d125ea7"},
+    {file = "mkdocs-1.6.0.tar.gz", hash = "sha256:a73f735824ef83a4f3bcb7a231dcab23f5a838f88b7efc54a0eef5fbdbc3c512"},
 ]
 
 [package.dependencies]
 click = ">=7.0"
 colorama = {version = ">=0.4", markers = "platform_system == \"Windows\""}
 ghp-import = ">=1.0"
-importlib-metadata = {version = ">=4.3", markers = "python_version < \"3.10\""}
+importlib-metadata = {version = ">=4.4", markers = "python_version < \"3.10\""}
 jinja2 = ">=2.11.1"
-markdown = ">=3.2.1"
+markdown = ">=3.3.6"
 markupsafe = ">=2.0.1"
 mergedeep = ">=1.3.4"
+mkdocs-get-deps = ">=0.2.0"
 packaging = ">=20.5"
 pathspec = ">=0.11.1"
-platformdirs = ">=2.2.0"
 pyyaml = ">=5.1"
 pyyaml-env-tag = ">=0.1"
 watchdog = ">=2.0"
 
 [package.extras]
 i18n = ["babel (>=2.9.0)"]
-min-versions = ["babel (==2.9.0)", "click (==7.0)", "colorama (==0.4)", "ghp-import (==1.0)", "importlib-metadata (==4.3)", "jinja2 (==2.11.1)", "markdown (==3.2.1)", "markupsafe (==2.0.1)", "mergedeep (==1.3.4)", "packaging (==20.5)", "pathspec (==0.11.1)", "platformdirs (==2.2.0)", "pyyaml (==5.1)", "pyyaml-env-tag (==0.1)", "typing-extensions (==3.10)", "watchdog (==2.0)"]
+min-versions = ["babel (==2.9.0)", "click (==7.0)", "colorama (==0.4)", "ghp-import (==1.0)", "importlib-metadata (==4.4)", "jinja2 (==2.11.1)", "markdown (==3.3.6)", "markupsafe (==2.0.1)", "mergedeep (==1.3.4)", "mkdocs-get-deps (==0.2.0)", "packaging (==20.5)", "pathspec (==0.11.1)", "pyyaml (==5.1)", "pyyaml-env-tag (==0.1)", "watchdog (==2.0)"]
 
 [[package]]
 name = "mkdocs-autorefs"
@@ -1383,15 +1383,32 @@ Markdown = ">=3.3"
 markupsafe = ">=2.0.1"
 mkdocs = ">=1.1"
 
+[[package]]
+name = "mkdocs-get-deps"
+version = "0.2.0"
+description = "MkDocs extension that lists all dependencies according to a mkdocs.yml file"
+optional = false
+python-versions = ">=3.8"
+files = [
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+    {file = "mkdocs_get_deps-0.2.0.tar.gz", hash = "sha256:162b3d129c7fad9b19abfdcb9c1458a651628e4b1dea628ac68790fb3061c60c"},
+]
+
+[package.dependencies]
+importlib-metadata = {version = ">=4.3", markers = "python_version < \"3.10\""}
+mergedeep = ">=1.3.4"
+platformdirs = ">=2.2.0"
+pyyaml = ">=5.1"
+
 [[package]]
 name = "mkdocs-material"
-version = "9.5.15"
+version = "9.5.25"
 description = "Documentation that simply works"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "mkdocs_material-9.5.25-py3-none-any.whl", hash = "sha256:68fdab047a0b9bfbefe79ce267e8a7daaf5128bcf7867065fcd201ee335fece1"},
+    {file = "mkdocs_material-9.5.25.tar.gz", hash = "sha256:d0662561efb725b712207e0ee01f035ca15633f29a64628e24f01ec99d7078f4"},
 ]
 
 [package.dependencies]
@@ -1399,7 +1416,7 @@ babel = ">=2.10,<3.0"
 colorama = ">=0.4,<1.0"
 jinja2 = ">=3.0,<4.0"
 markdown = ">=3.2,<4.0"
-mkdocs = ">=1.5.3,<1.6.0"
+mkdocs = ">=1.6,<2.0"
 mkdocs-material-extensions = ">=1.3,<2.0"
 paginate = ">=0.5,<1.0"
 pygments = ">=2.16,<3.0"
@@ -1765,13 +1782,13 @@ files = [
 
 [[package]]
 name = "openai"
-version = "1.14.2"
+version = "1.31.1"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.7.1"
 files = [
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 ]
 
 [package.dependencies]
@@ -1890,47 +1907,47 @@ files = [
 
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-version = "2.2.1"
+version = "2.2.2"
 description = "Powerful data structures for data analysis, time series, and statistics"
 optional = false
 python-versions = ">=3.9"
 files = [
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 [package.dependencies]
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-    {version = ">=1.26.0,<2", markers = "python_version >= \"3.12\""},
-    {version = ">=1.23.2,<2", markers = "python_version == \"3.11\""},
+    {version = ">=1.22.4", markers = "python_version < \"3.11\""},
+    {version = ">=1.26.0", markers = "python_version >= \"3.12\""},
+    {version = ">=1.23.2", markers = "python_version == \"3.11\""},
 ]
 python-dateutil = ">=2.8.2"
 pytz = ">=2020.1"
@@ -2089,28 +2106,29 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "platformdirs"
-version = "4.2.0"
-description = "A small Python package for determining appropriate platform-specific dirs, e.g. a \"user data dir\"."
+version = "4.2.2"
+description = "A small Python package for determining appropriate platform-specific dirs, e.g. a `user data dir`."
 optional = false
 python-versions = ">=3.8"
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 test = ["appdirs (==1.4.4)", "covdefaults (>=2.3)", "pytest (>=7.4.3)", "pytest-cov (>=4.1)", "pytest-mock (>=3.12)"]
+type = ["mypy (>=1.8)"]
 
 [[package]]
 name = "pluggy"
-version = "1.4.0"
+version = "1.5.0"
 description = "plugin and hook calling mechanisms for python"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -2133,13 +2151,13 @@ tqdm = "*"
 
 [[package]]
 name = "prompt-toolkit"
-version = "3.0.43"
+version = "3.0.46"
 description = "Library for building powerful interactive command lines in Python"
 optional = false
 python-versions = ">=3.7.0"
 files = [
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 ]
 
 [package.dependencies]
@@ -2222,18 +2240,18 @@ files = [
 
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+version = "2.7.3"
 description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
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 [package.dependencies]
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-pydantic-core = "2.16.3"
+pydantic-core = "2.18.4"
 typing-extensions = ">=4.6.1"
 
 [package.extras]
@@ -2241,90 +2259,90 @@ email = ["email-validator (>=2.0.0)"]
 
 [[package]]
 name = "pydantic-core"
-version = "2.16.3"
-description = ""
+version = "2.18.4"
+description = "Core functionality for Pydantic validation and serialization"
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 [package.dependencies]
@@ -3113,13 +3116,13 @@ test = ["pytest", "tornado (>=4.5)", "typeguard"]
 
 [[package]]
 name = "tifffile"
-version = "2024.2.12"
+version = "2024.5.22"
 description = "Read and write TIFF files"
 optional = false
 python-versions = ">=3.9"
 files = [
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 ]
 
 [package.dependencies]
@@ -3161,13 +3164,13 @@ files = [
 
 [[package]]
 name = "tqdm"
-version = "4.66.3"
+version = "4.66.4"
 description = "Fast, Extensible Progress Meter"
 optional = false
 python-versions = ">=3.7"
 files = [
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+    {file = "tqdm-4.66.4-py3-none-any.whl", hash = "sha256:b75ca56b413b030bc3f00af51fd2c1a1a5eac6a0c1cca83cbb37a5c52abce644"},
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 ]
 
 [package.dependencies]
@@ -3218,13 +3221,13 @@ files = [
 
 [[package]]
 name = "types-requests"
-version = "2.31.0.20240311"
+version = "2.32.0.20240602"
 description = "Typing stubs for requests"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "types-requests-2.32.0.20240602.tar.gz", hash = "sha256:3f98d7bbd0dd94ebd10ff43a7fbe20c3b8528acace6d8efafef0b6a184793f06"},
+    {file = "types_requests-2.32.0.20240602-py3-none-any.whl", hash = "sha256:ed3946063ea9fbc6b5fc0c44fa279188bae42d582cb63760be6cb4b9d06c3de8"},
 ]
 
 [package.dependencies]
@@ -3243,24 +3246,24 @@ files = [
 
 [[package]]
 name = "types-tqdm"
-version = "4.66.0.20240106"
+version = "4.66.0.20240417"
 description = "Typing stubs for tqdm"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
 name = "typing-extensions"
-version = "4.10.0"
+version = "4.12.1"
 description = "Backported and Experimental Type Hints for Python 3.8+"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [[package]]
@@ -3293,40 +3296,43 @@ zstd = ["zstandard (>=0.18.0)"]
 
 [[package]]
 name = "watchdog"
-version = "4.0.0"
+version = "4.0.1"
 description = "Filesystem events monitoring"
 optional = false
 python-versions = ">=3.8"
 files = [
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+    {file = "watchdog-4.0.1-py3-none-win_amd64.whl", hash = "sha256:7577b3c43e5909623149f76b099ac49a1a01ca4e167d1785c76eb52fa585745a"},
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+    {file = "watchdog-4.0.1.tar.gz", hash = "sha256:eebaacf674fa25511e8867028d281e602ee6500045b57f43b08778082f7f8b44"},
 ]
 
 [package.extras]
@@ -3545,18 +3551,18 @@ multidict = ">=4.0"
 
 [[package]]
 name = "zipp"
-version = "3.18.1"
+version = "3.19.2"
 description = "Backport of pathlib-compatible object wrapper for zip files"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "zipp-3.18.1-py3-none-any.whl", hash = "sha256:206f5a15f2af3dbaee80769fb7dc6f249695e940acca08dfb2a4769fe61e538b"},
-    {file = "zipp-3.18.1.tar.gz", hash = "sha256:2884ed22e7d8961de1c9a05142eb69a247f120291bc0206a00a7642f09b5b715"},
+    {file = "zipp-3.19.2-py3-none-any.whl", hash = "sha256:f091755f667055f2d02b32c53771a7a6c8b47e1fdbc4b72a8b9072b3eef8015c"},
+    {file = "zipp-3.19.2.tar.gz", hash = "sha256:bf1dcf6450f873a13e952a29504887c89e6de7506209e5b1bcc3460135d4de19"},
 ]
 
 [package.extras]
-docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
-testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
+doc = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
+test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", "jaraco.test", "more-itertools", "pytest (>=6,!=8.1.*)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
 
 [metadata]
 lock-version = "2.0"
diff --git a/vision_agent/agent/easytool_v2.py b/vision_agent/agent/easytool_v2.py
index 1ef382e7..457b7a61 100644
--- a/vision_agent/agent/easytool_v2.py
+++ b/vision_agent/agent/easytool_v2.py
@@ -428,12 +428,12 @@ def visualize_result(all_tool_results: List[Dict]) -> Sequence[Union[str, Path]]
 
 
 class EasyToolV2(Agent):
-    r"""EasyToolV2 is an agent framework that utilizes tools as well as self
-    reflection to accomplish tasks, in particular vision tasks. EasyToolV2 is based
-    off of EasyTool https://arxiv.org/abs/2401.06201 and Reflexion
-    https://arxiv.org/abs/2303.11366 where it will attempt to complete a task and then
-    reflect on whether or not it was able to accomplish the task based off of the plan
-    and final results, if not it will redo the task with this newly added reflection.
+    """EasyToolV2 is an agent framework that utilizes tools as well as self reflection
+    to accomplish tasks, in particular vision tasks. EasyToolV2 is based off of EasyTool
+    https://arxiv.org/abs/2401.06201 and Reflexion https://arxiv.org/abs/2303.11366
+    where it will attempt to complete a task and then reflect on whether or not it was
+    able to accomplish the task based off of the plan and final results, if not it will
+    redo the task with this newly added reflection.
 
     Example
     -------
@@ -461,7 +461,10 @@ def __init__(
             reflect_model: the model to use for self reflection.
             max_retries: maximum number of retries to attempt to complete the task.
             verbose: whether to print more logs.
-            report_progress_callback: a callback to report the progress of the agent. This is useful for streaming logs in a web application where multiple EasyToolV2 instances are running in parallel. This callback ensures that the progress are not mixed up.
+            report_progress_callback: a callback to report the progress of the agent.
+                This is useful for streaming logs in a web application where multiple
+                EasyToolV2 instances are running in parallel. This callback ensures
+                that the progress are not mixed up.
         """
         self.task_model = (
             OpenAILLM(model_name="gpt-4-turbo", json_mode=True, temperature=0.0)
@@ -495,9 +498,10 @@ def __call__(
         """Invoke the vision agent.
 
         Parameters:
-            chat: A conversation in the format of
-                [{"role": "user", "content": "describe your task here..."}].
-            image: The input image referenced in the chat parameter.
+            input: A conversation in the format of
+                [{"role": "user", "content": "describe your task here..."}] or a string
+                containing just the content.
+            media: The input media referenced in the chat parameter.
             reference_data: A dictionary containing the reference image, mask or bounding
                 box in the format of:
                 {"image": "image.jpg", "mask": "mask.jpg", "bbox": [0.1, 0.2, 0.1, 0.2]}
@@ -549,7 +553,7 @@ def chat_with_workflow(
         Parameters:
             chat: A conversation in the format of
                 [{"role": "user", "content": "describe your task here..."}].
-            image: The input image referenced in the chat parameter.
+            media: The media image referenced in the chat parameter.
             reference_data: A dictionary containing the reference image, mask or bounding
                 box in the format of:
                 {"image": "image.jpg", "mask": "mask.jpg", "bbox": [0.1, 0.2, 0.1, 0.2]}
@@ -558,9 +562,8 @@ def chat_with_workflow(
             self_reflection: boolean to enable and disable self reflection.
 
         Returns:
-            A tuple where the first item is the final answer and the second item is a
-            list of all the tool results. The last item in the tool results also
-            contains the visualized output.
+            Tuple[str, List[Dict]]: A tuple where the first item is the final answer
+                and the second item is a list of all the tool results.
         """
         if len(chat) == 0:
             raise ValueError("Input cannot be empty.")
diff --git a/vision_agent/agent/reflexion.py b/vision_agent/agent/reflexion.py
index d3b479b2..5e9f9f30 100644
--- a/vision_agent/agent/reflexion.py
+++ b/vision_agent/agent/reflexion.py
@@ -144,7 +144,7 @@ def __call__(
 
         Parameters:
             input: a prompt that describe the task or a conversation in the format of [{"role": "user", "content": "describe your task here..."}].
-            image: the input image referenced in the prompt parameter.
+            media: the input media referenced in the prompt parameter.
 
         Returns:
             A text response.
diff --git a/vision_agent/agent/vision_agent.py b/vision_agent/agent/vision_agent.py
index ed45b353..40c5325c 100644
--- a/vision_agent/agent/vision_agent.py
+++ b/vision_agent/agent/vision_agent.py
@@ -442,10 +442,10 @@ def __call__(
         """Chat with Vision Agent and return intermediate information regarding the task.
 
         Parameters:
-            chat (List[Dict[str, str]]): A conversation in the format of
-                [{"role": "user", "content": "describe your task here..."}].
+            input (Union[List[Dict[str, str]], str]): A conversation in the format of
+                [{"role": "user", "content": "describe your task here..."}] or a string
+                of just the contents.
             media (Optional[Union[str, Path]]): The media file to be used in the task.
-            self_reflection (bool): Whether to reflect on the task and debug the code.
 
         Returns:
             str: The code output by the Vision Agent.
@@ -471,7 +471,8 @@ def chat_with_workflow(
                 [{"role": "user", "content": "describe your task here..."}].
             media (Optional[Union[str, Path]]): The media file to be used in the task.
             self_reflection (bool): Whether to reflect on the task and debug the code.
-            show_visualization (bool): If True, it opens a new window locally to show the image(s) created by visualization code (if there is any).
+            display_visualization (bool): If True, it opens a new window locally to
+                show the image(s) created by visualization code (if there is any).
 
         Returns:
             Dict[str, Any]: A dictionary containing the code, test, test result, plan,
diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py
index 84cb69f4..040a48a4 100644
--- a/vision_agent/tools/tools.py
+++ b/vision_agent/tools/tools.py
@@ -75,17 +75,18 @@ def grounding_dino(
 
     Returns:
         List[Dict[str, Any]]: A list of dictionaries containing the score, label, and
-        bounding box of the detected objects with normalized coordinates between 0 and 1
-        (xmin, ymin, xmax, ymax). xmin and ymin are the coordinates of the top-left and
-        xmax and ymax are the coordinates of the bottom-right of the bounding box.
+            bounding box of the detected objects with normalized coordinates between 0
+            and 1 (xmin, ymin, xmax, ymax). xmin and ymin are the coordinates of the
+            top-left and xmax and ymax are the coordinates of the bottom-right of the
+            bounding box.
 
     Example
     -------
-    >>> grounding_dino("car. dinosaur", image)
-    [
-        {'score': 0.99, 'label': 'dinosaur', 'bbox': [0.1, 0.11, 0.35, 0.4]},
-        {'score': 0.98, 'label': 'car', 'bbox': [0.2, 0.21, 0.45, 0.5},
-    ]
+        >>> grounding_dino("car. dinosaur", image)
+        [
+            {'score': 0.99, 'label': 'dinosaur', 'bbox': [0.1, 0.11, 0.35, 0.4]},
+            {'score': 0.98, 'label': 'car', 'bbox': [0.2, 0.21, 0.45, 0.5},
+        ]
     """
     image_size = image.shape[:2]
     image_b64 = convert_to_b64(image)
@@ -129,27 +130,27 @@ def grounding_sam(
 
     Returns:
         List[Dict[str, Any]]: A list of dictionaries containing the score, label,
-        bounding box, and mask of the detected objects with normalized coordinates
-        (xmin, ymin, xmax, ymax). xmin and ymin are the coordinates of the top-left and
-        xmax and ymax are the coordinates of the bottom-right of the bounding box.
-        The mask is binary 2D numpy array where 1 indicates the object and 0 indicates
-        the background.
+            bounding box, and mask of the detected objects with normalized coordinates
+            (xmin, ymin, xmax, ymax). xmin and ymin are the coordinates of the top-left
+            and xmax and ymax are the coordinates of the bottom-right of the bounding box.
+            The mask is binary 2D numpy array where 1 indicates the object and 0 indicates
+            the background.
 
     Example
     -------
-    >>> grounding_sam("car. dinosaur", image)
-    [
-        {
-            'score': 0.99,
-            'label': 'dinosaur',
-            'bbox': [0.1, 0.11, 0.35, 0.4],
-            'mask': array([[0, 0, 0, ..., 0, 0, 0],
-                [0, 0, 0, ..., 0, 0, 0],
-                ...,
-                [0, 0, 0, ..., 0, 0, 0],
-                [0, 0, 0, ..., 0, 0, 0]], dtype=uint8),
-        },
-    ]
+        >>> grounding_sam("car. dinosaur", image)
+        [
+            {
+                'score': 0.99,
+                'label': 'dinosaur',
+                'bbox': [0.1, 0.11, 0.35, 0.4],
+                'mask': array([[0, 0, 0, ..., 0, 0, 0],
+                    [0, 0, 0, ..., 0, 0, 0],
+                    ...,
+                    [0, 0, 0, ..., 0, 0, 0],
+                    [0, 0, 0, ..., 0, 0, 0]], dtype=uint8),
+            },
+        ]
     """
     image_size = image.shape[:2]
     image_b64 = convert_to_b64(image)
@@ -187,12 +188,12 @@ def extract_frames(
 
     Returns:
         List[Tuple[np.ndarray, float]]: A list of tuples containing the extracted frame
-        as a numpy array and the timestamp in seconds.
+            as a numpy array and the timestamp in seconds.
 
     Example
     -------
-    >>> extract_frames("path/to/video.mp4")
-    [(frame1, 0.0), (frame2, 0.5), ...]
+        >>> extract_frames("path/to/video.mp4")
+        [(frame1, 0.0), (frame2, 0.5), ...]
     """
 
     return extract_frames_from_video(str(video_uri), fps)
@@ -212,10 +213,10 @@ def ocr(image: np.ndarray) -> List[Dict[str, Any]]:
 
     Example
     -------
-    >>> ocr(image)
-    [
-        {'label': 'hello world', 'bbox': [0.1, 0.11, 0.35, 0.4], 'score': 0.99},
-    ]
+        >>> ocr(image)
+        [
+            {'label': 'hello world', 'bbox': [0.1, 0.11, 0.35, 0.4], 'score': 0.99},
+        ]
     """
 
     pil_image = Image.fromarray(image).convert("RGB")
@@ -266,9 +267,8 @@ def zero_shot_counting(image: np.ndarray) -> Dict[str, Any]:
 
     Example
     -------
-    >>> zero_shot_counting(image)
-    {'count': 45},
-
+        >>> zero_shot_counting(image)
+        {'count': 45},
     """
 
     image_b64 = convert_to_b64(image)
@@ -297,9 +297,8 @@ def visual_prompt_counting(
 
     Example
     -------
-    >>> visual_prompt_counting(image, {"bbox": [0.1, 0.1, 0.4, 0.42]})
-    {'count': 45},
-
+        >>> visual_prompt_counting(image, {"bbox": [0.1, 0.1, 0.4, 0.42]})
+        {'count': 45},
     """
 
     image_size = get_image_size(image)
@@ -332,9 +331,8 @@ def image_question_answering(image: np.ndarray, prompt: str) -> str:
 
     Example
     -------
-    >>> image_question_answering(image, 'What is the cat doing ?')
-    'drinking milk'
-
+        >>> image_question_answering(image, 'What is the cat doing ?')
+        'drinking milk'
     """
 
     image_b64 = convert_to_b64(image)
@@ -363,9 +361,8 @@ def clip(image: np.ndarray, classes: List[str]) -> Dict[str, Any]:
 
     Example
     -------
-    >>> clip(image, ['dog', 'cat', 'bird'])
-    {"labels": ["dog", "cat", "bird"], "scores": [0.68, 0.30, 0.02]},
-
+        >>> clip(image, ['dog', 'cat', 'bird'])
+        {"labels": ["dog", "cat", "bird"], "scores": [0.68, 0.30, 0.02]},
     """
 
     image_b64 = convert_to_b64(image)
@@ -391,9 +388,8 @@ def image_caption(image: np.ndarray) -> str:
 
     Example
     -------
-    >>> image_caption(image)
-    'This image contains a cat sitting on a table with a bowl of milk.'
-
+        >>> image_caption(image)
+        'This image contains a cat sitting on a table with a bowl of milk.'
     """
 
     image_b64 = convert_to_b64(image)
@@ -418,8 +414,8 @@ def closest_mask_distance(mask1: np.ndarray, mask2: np.ndarray) -> float:
 
     Example
     -------
-    >>> closest_mask_distance(mask1, mask2)
-    0.5
+        >>> closest_mask_distance(mask1, mask2)
+        0.5
     """
 
     mask1 = np.clip(mask1, 0, 1)
@@ -474,8 +470,8 @@ def closest_box_distance(
 
     Example
     -------
-    >>> closest_box_distance([100, 100, 200, 200], [300, 300, 400, 400])
-    141.42
+        >>> closest_box_distance([100, 100, 200, 200], [300, 300, 400, 400])
+        141.42
     """
 
     x11, y11, x12, y12 = denormalize_bbox(box1, image_size)
@@ -499,7 +495,7 @@ def save_json(data: Any, file_path: str) -> None:
 
     Example
     -------
-    >>> save_json(data, "path/to/file.json")
+        >>> save_json(data, "path/to/file.json")
     """
 
     class NumpyEncoder(json.JSONEncoder):
@@ -525,7 +521,7 @@ def load_image(image_path: str) -> np.ndarray:
 
     Example
     -------
-    >>> load_image("path/to/image.jpg")
+        >>> load_image("path/to/image.jpg")
     """
     # NOTE: sometimes the generated code pass in a NumPy array
     if isinstance(image_path, np.ndarray):
@@ -545,8 +541,8 @@ def save_image(image: np.ndarray) -> str:
 
     Example
     -------
-    >>> save_image(image)
-    "/tmp/tmpabc123.png"
+        >>> save_image(image)
+        "/tmp/tmpabc123.png"
     """
     from IPython.display import display
 
@@ -572,8 +568,8 @@ def save_video(
 
     Example
     -------
-    >>> save_video(frames)
-    "/tmp/tmpvideo123.mp4"
+        >>> save_video(frames)
+        "/tmp/tmpvideo123.mp4"
     """
     if fps <= 0:
         _LOGGER.warning(f"Invalid fps value: {fps}. Setting fps to 4 (default value).")
@@ -619,9 +615,9 @@ def overlay_bounding_boxes(
 
     Example
     -------
-    >>> image_with_bboxes = overlay_bounding_boxes(
-        image, [{'score': 0.99, 'label': 'dinosaur', 'bbox': [0.1, 0.11, 0.35, 0.4]}],
-    )
+        >>> image_with_bboxes = overlay_bounding_boxes(
+            image, [{'score': 0.99, 'label': 'dinosaur', 'bbox': [0.1, 0.11, 0.35, 0.4]}],
+        )
     """
     pil_image = Image.fromarray(image.astype(np.uint8))
 
@@ -675,18 +671,18 @@ def overlay_segmentation_masks(
 
     Example
     -------
-    >>> image_with_masks = overlay_segmentation_masks(
-        image,
-        [{
-            'score': 0.99,
-            'label': 'dinosaur',
-            'mask': array([[0, 0, 0, ..., 0, 0, 0],
-                [0, 0, 0, ..., 0, 0, 0],
-                ...,
-                [0, 0, 0, ..., 0, 0, 0],
-                [0, 0, 0, ..., 0, 0, 0]], dtype=uint8),
-        }],
-    )
+        >>> image_with_masks = overlay_segmentation_masks(
+            image,
+            [{
+                'score': 0.99,
+                'label': 'dinosaur',
+                'mask': array([[0, 0, 0, ..., 0, 0, 0],
+                    [0, 0, 0, ..., 0, 0, 0],
+                    ...,
+                    [0, 0, 0, ..., 0, 0, 0],
+                    [0, 0, 0, ..., 0, 0, 0]], dtype=uint8),
+            }],
+        )
     """
     pil_image = Image.fromarray(image.astype(np.uint8)).convert("RGBA")
 
@@ -727,16 +723,16 @@ def overlay_heat_map(
 
     Example
     -------
-    >>> image_with_heat_map = overlay_heat_map(
-        image,
-        {
-            'heat_map': array([[0, 0, 0, ..., 0, 0, 0],
-                [0, 0, 0, ..., 0, 0, 0],
-                ...,
-                [0, 0, 0, ..., 0, 0, 0],
-                [0, 0, 0, ..., 125, 125, 125]], dtype=uint8),
-        },
-    )
+        >>> image_with_heat_map = overlay_heat_map(
+            image,
+            {
+                'heat_map': array([[0, 0, 0, ..., 0, 0, 0],
+                    [0, 0, 0, ..., 0, 0, 0],
+                    ...,
+                    [0, 0, 0, ..., 0, 0, 0],
+                    [0, 0, 0, ..., 125, 125, 125]], dtype=uint8),
+            },
+        )
     """
     pil_image = Image.fromarray(image.astype(np.uint8)).convert("RGB")
 
diff --git a/vision_agent/utils/video.py b/vision_agent/utils/video.py
index 6dbb28de..ba5ea798 100644
--- a/vision_agent/utils/video.py
+++ b/vision_agent/utils/video.py
@@ -63,9 +63,9 @@ def extract_frames_from_video(
 
     Returns:
         a list of tuples containing the extracted frame and the timestamp in seconds.
-        E.g. [(frame1, 0.0), (frame2, 0.5), ...]. The timestamp is the time in seconds
-        from the start of the video. E.g. 12.125 means 12.125 seconds from the start of
-        the video. The frames are sorted by the timestamp in ascending order.
+            E.g. [(frame1, 0.0), (frame2, 0.5), ...]. The timestamp is the time in seconds
+            from the start of the video. E.g. 12.125 means 12.125 seconds from the start of
+            the video. The frames are sorted by the timestamp in ascending order.
     """
     with VideoFileClip(video_uri) as video:
         video_duration: float = video.duration