diff --git a/README.md b/README.md
index 85fb45d6..954ed93e 100644
--- a/README.md
+++ b/README.md
@@ -1,6 +1,5 @@
 <div align="center">
-    <img alt="vision_agent" height="200px" src="https://github.com/landing-ai/vision-agent/blob/main/assets/logo.jpg?raw=true"
-</div>
+    <img alt="vision_agent" height="200px" src="https://github.com/landing-ai/vision-agent/blob/main/assets/logo.jpg?raw=true">
 
 # 🔍🤖 Vision Agent
 
@@ -8,6 +7,7 @@
 ![ci_status](https://github.com/landing-ai/vision-agent/actions/workflows/ci_cd.yml/badge.svg)
 [![PyPI version](https://badge.fury.io/py/vision-agent.svg)](https://badge.fury.io/py/vision-agent)
 ![version](https://img.shields.io/pypi/pyversions/vision-agent)
+</div>
 
 
 Vision Agent is a library for that helps you to use multimodal models to organize and structure your image data. Check out our discord for roadmaps and updates! 
diff --git a/tests/test_llm.py b/tests/test_llm.py
index 74453a4b..a8070f30 100644
--- a/tests/test_llm.py
+++ b/tests/test_llm.py
@@ -1,8 +1,7 @@
 import pytest
 
 from vision_agent.llm.llm import OpenAILLM
-from vision_agent.tools import CLIP
-from vision_agent.tools.tools import GroundingDINO
+from vision_agent.tools import CLIP, GroundingDINO, GroundingSAM
 
 from .fixtures import openai_llm_mock  # noqa: F401
 
@@ -54,6 +53,6 @@ def test_generate_detector(openai_llm_mock):  # noqa: F811
 def test_generate_segmentor(openai_llm_mock):  # noqa: F811
     llm = OpenAILLM()
     prompt = "Can you generate a cat segmentor?"
-    segmentor = llm.generate_detector(prompt)
-    assert isinstance(segmentor, GroundingDINO)
+    segmentor = llm.generate_segmentor(prompt)
+    assert isinstance(segmentor, GroundingSAM)
     assert segmentor.prompt == "cat"
diff --git a/vision_agent/tools/tools.py b/vision_agent/tools/tools.py
index b539dfbb..de8960dd 100644
--- a/vision_agent/tools/tools.py
+++ b/vision_agent/tools/tools.py
@@ -55,7 +55,7 @@ class GroundingDINO(ImageTool):
         'Example 2: User Question: "Can you detect the person on the left?" {{"Parameters":{{"prompt": "person on the left"}}\n'
         'Exmaple 3: User Question: "Can you build me a tool that detects red shirts and green shirts?" {{"Parameters":{{"prompt": "red shirt. green shirt"}}}}\n'
         "The tool returns a list of dictionaries, each containing the following keys:\n"
-        "  - 'lable': The label of the detected object.\n"
+        "  - 'label': The label of the detected object.\n"
         "  - 'score': The confidence score of the detection.\n"
         "  - 'bbox': The bounding box of the detected object. The box coordinates are normalize to [0, 1]\n"
         "An example output would be: [{'label': ['car'], 'score': [0.99], 'bbox': [[0.1, 0.2, 0.3, 0.4]]}]\n"