diff --git a/.env.example b/.env.example
index f13ce77f..e170252c 100644
--- a/.env.example
+++ b/.env.example
@@ -35,4 +35,5 @@ REDIS_PORT=
 
 
 #dbs
-PINECONE_API_KEY=""
\ No newline at end of file
+PINECONE_API_KEY=""
+BING_COOKIE=""
\ No newline at end of file
diff --git a/docs/swarms/agents/idea_to_image.md b/docs/swarms/agents/idea_to_image.md
new file mode 100644
index 00000000..41d5b216
--- /dev/null
+++ b/docs/swarms/agents/idea_to_image.md
@@ -0,0 +1,124 @@
+# `Idea2Image` Documentation
+
+## Table of Contents
+
+1. [Introduction](#introduction)
+2. [Idea2Image Class](#idea2image-class)
+   - [Initialization Parameters](#initialization-parameters)
+3. [Methods and Usage](#methods-and-usage)
+   - [llm_prompt Method](#llm-prompt-method)
+   - [generate_image Method](#generate-image-method)
+4. [Examples](#examples)
+   - [Example 1: Generating an Image](#example-1-generating-an-image)
+5. [Additional Information](#additional-information)
+6. [References and Resources](#references-and-resources)
+
+---
+
+## 1. Introduction <a name="introduction"></a>
+
+Welcome to the documentation for the Swarms library, with a focus on the `Idea2Image` class. This comprehensive guide provides in-depth information about the Swarms library and its core components. Before we dive into the details, it's crucial to understand the purpose and significance of this library.
+
+### 1.1 Purpose
+
+The Swarms library aims to simplify interactions with AI models for generating images from text prompts. The `Idea2Image` class is designed to generate images from textual descriptions using the DALLE-3 model and the OpenAI GPT-4 language model.
+
+### 1.2 Key Features
+
+- **Image Generation:** Swarms allows you to generate images based on natural language prompts, providing a bridge between textual descriptions and visual content.
+
+- **Integration with DALLE-3:** The `Idea2Image` class leverages the power of DALLE-3 to create images that match the given textual descriptions.
+
+- **Language Model Integration:** The class integrates with OpenAI's GPT-3 for prompt refinement, enhancing the specificity of image generation.
+
+---
+
+## 2. Idea2Image Class <a name="idea2image-class"></a>
+
+The `Idea2Image` class is a fundamental module in the Swarms library, enabling the generation of images from text prompts.
+
+### 2.1 Initialization Parameters <a name="initialization-parameters"></a>
+
+Here are the initialization parameters for the `Idea2Image` class:
+
+- `image` (str): Text prompt for the image to generate.
+
+- `openai_api_key` (str): OpenAI API key. This key is used for prompt refinement with GPT-3. If not provided, the class will attempt to use the `OPENAI_API_KEY` environment variable.
+
+- `cookie` (str): Cookie value for DALLE-3. This cookie is used to interact with the DALLE-3 API. If not provided, the class will attempt to use the `BING_COOKIE` environment variable.
+
+- `output_folder` (str): Folder to save the generated images. The default folder is "images/".
+
+### 2.2 Methods <a name="methods-and-usage"></a>
+
+The `Idea2Image` class provides the following methods:
+
+- `llm_prompt()`: Returns a prompt for refining the image generation. This method helps improve the specificity of the image generation prompt.
+
+- `generate_image()`: Generates and downloads the image based on the prompt. It refines the prompt, opens the website with the query, retrieves image URLs, and downloads the images to the specified folder.
+
+---
+
+## 3. Methods and Usage <a name="methods-and-usage"></a>
+
+Let's explore the methods provided by the `Idea2Image` class and how to use them effectively.
+
+### 3.1 `llm_prompt` Method <a name="llm-prompt-method"></a>
+
+The `llm_prompt` method returns a refined prompt for generating the image. It's a critical step in improving the specificity and accuracy of the image generation process. The method provides a guide for refining the prompt, helping users describe the desired image more precisely.
+
+### 3.2 `generate_image` Method <a name="generate-image-method"></a>
+
+The `generate_image` method combines the previous methods to execute the whole process of generating and downloading images based on the provided prompt. It's a convenient way to automate the image generation process.
+
+---
+
+## 4. Examples <a name="examples"></a>
+
+Let's dive into practical examples to demonstrate the usage of the `Idea2Image` class.
+
+### 4.1 Example 1: Generating an Image <a name="example-1-generating-an-image"></a>
+
+In this example, we create an instance of the `Idea2Image` class and use it to generate an image based on a text prompt:
+
+```python
+from swarms.agents import Idea2Image
+
+# Create an instance of the Idea2Image class with your prompt and API keys
+idea2image = Idea2Image(
+    image="Fish hivemind swarm in light blue avatar anime in zen garden pond concept art anime art, happy fish, anime scenery",
+    openai_api_key="your_openai_api_key_here",
+    cookie="your_cookie_value_here",
+)
+
+# Generate and download the image
+idea2image.generate_image()
+```
+
+---
+
+## 5. Additional Information <a name="additional-information"></a>
+
+Here are some additional tips and information for using the Swarms library and the `Idea2Image` class effectively:
+
+- Refining the prompt is a crucial step to influence the style, composition, and mood of the generated image. Follow the provided guide in the `llm_prompt` method to create precise prompts.
+
+- Experiment with different prompts, variations, and editing techniques to create unique and interesting images.
+
+- You can combine separate DALLE-3 outputs into panoramas and murals by careful positioning and editing.
+
+- Consider sharing your creations and exploring resources in communities like Reddit r/dalle2 for inspiration and tools.
+
+- The `output_folder` parameter allows you to specify the folder where generated images will be saved. Ensure that you have the necessary permissions to write to that folder.
+
+---
+
+## 6. References and Resources <a name="references-and-resources"></a>
+
+For further information and resources related to the Swarms library and DALLE-3:
+
+- [DALLE-3 Unofficial API Documentation](https://www.bing.com/images/create): The official documentation for the DALLE-3 Unofficial API, where you can explore additional features and capabilities.
+
+- [OpenAI GPT-3 Documentation](https://beta.openai.com/docs/): The documentation for OpenAI's GPT-3, which is used for prompt refinement.
+
+This concludes the documentation for the Swarms library and the `Idea2Image` class. You now have a comprehensive guide on how to generate images from text prompts using DALLE-3 and GPT-3 with Swarms.
\ No newline at end of file
diff --git a/mkdocs.yml b/mkdocs.yml
index a5f21e06..8222283f 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -87,6 +87,7 @@ nav:
   - swarms.agents:
     - AbstractAgent: "swarms/agents/abstract_agent.md"
     - OmniModalAgent: "swarms/agents/omni_agent.md"
+    - Idea2Image: "swarms/agents/idea_to_image.md"
   - swarms.models:
     - Overview: "swarms/models/index.md"
     - HuggingFaceLLM: "swarms/models/hf.md"
diff --git a/pyproject.toml b/pyproject.toml
index 0480a343..11d24694 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -50,6 +50,7 @@ open-interpreter = "*"
 tabulate = "*"
 termcolor = "*"
 black = "*"
+dalle = "*"
 
 [tool.poetry.dev-dependencies]
 first_dependency = {git = "https://github.com/IDEA-Research/GroundingDINO.git"}
diff --git a/requirements.txt b/requirements.txt
index 6f6bcdf0..b390cc4c 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -51,6 +51,7 @@ transformers
 webdataset
 yapf
 autopep8
+dalle3
 
 
 mkdocs
diff --git a/swarms/agents/__init__.py b/swarms/agents/__init__.py
index 2701a476..62273928 100644
--- a/swarms/agents/__init__.py
+++ b/swarms/agents/__init__.py
@@ -1,9 +1,4 @@
 """Agent Infrastructure, models, memory, utils, tools"""
-
-# agents
-# from swarms.agents.profitpilot import ProfitPilot
-# from swarms.agents.aot import AoTAgent
-# from swarms.agents.multi_modal_visual_agent import MultiModalAgent
 from swarms.agents.omni_modal_agent import OmniModalAgent
 from swarms.agents.hf_agents import HFAgent
 
@@ -13,3 +8,5 @@ from swarms.agents.message import Message
 from swarms.agents.stream_response import stream
 from swarms.agents.base import AbstractAgent
 from swarms.agents.registry import Registry
+from swarms.agents.idea_to_image_agent import Idea2Image
+
diff --git a/swarms/agents/idea_to_image_agent.py b/swarms/agents/idea_to_image_agent.py
new file mode 100644
index 00000000..cede83e9
--- /dev/null
+++ b/swarms/agents/idea_to_image_agent.py
@@ -0,0 +1,111 @@
+import os
+import logging
+from dataclasses import dataclass
+from dalle3 import Dalle
+from swarms.models import OpenAIChat
+
+
+@dataclass
+class Idea2Image:
+    """
+    A class used to generate images from text prompts using DALLE-3.
+
+    ...
+
+    Attributes
+    ----------
+    image : str
+        Text prompt for the image to generate
+    openai_api_key : str
+        OpenAI API key
+    cookie : str
+        Cookie value for DALLE-3
+    output_folder : str
+        Folder to save the generated images
+
+    Methods
+    -------
+    llm_prompt():
+        Returns a prompt for refining the image generation
+    generate_image():
+        Generates and downloads the image based on the prompt
+
+
+    Usage:
+    ------
+    from dalle3 import Idea2Image
+
+    idea2image = Idea2Image(
+        image="Fish hivemind swarm in light blue avatar anime in zen garden pond concept art anime art, happy fish, anime scenery"
+    )
+    idea2image.run()
+    """
+
+    image: str
+    openai_api_key: str = os.getenv("OPENAI_API_KEY") or None
+    cookie: str = os.getenv("BING_COOKIE") or None
+    output_folder: str = "images/"
+
+    def __post_init__(self):
+        self.llm = OpenAIChat(openai_api_key=self.openai_api_key)
+        self.dalle = Dalle(self.cookie)
+
+    def llm_prompt(self):
+        LLM_PROMPT = f"""
+        Refine the USER prompt to create a more precise image tailored to the user's needs using
+        an image generator like DALLE-3. 
+
+        ###### FOLLOW THE GUIDE BELOW TO REFINE THE PROMPT ######
+
+        - Use natural language prompts up to 400 characters to describe the image you want to generate. Be as specific or vague as needed.
+
+        - Frame your photographic prompts like camera position, lighting, film type, year, usage context. This implicitly suggests image qualities.
+
+        - For illustrations, you can borrow photographic terms like "close up" and prompt for media, style, artist, animation style, etc.  
+
+        - Prompt hack: name a film/TV show genre + year to "steal the look" for costumes, lighting, etc without knowing technical details.
+
+        - Try variations of a prompt, make edits, and do recursive uncropping to create interesting journeys and zoom-out effects.
+
+        - Use an image editor like Photopea to uncrop DALL-E outputs and prompt again to extend the image.
+
+        - Combine separate DALL-E outputs into panoramas and murals with careful positioning/editing.
+
+        - Browse communities like Reddit r/dalle2 to get inspired and share your creations. See tools, free image resources, articles.
+
+        - Focus prompts on size, structure, shape, mood, aesthetics to influence the overall vibe and composition.
+
+        - Be more vague or detailed as needed - DALL-E has studied over 400M images and can riff creatively or replicate specific styles.
+
+        - Be descriptive, describe the art style at the end like fusing concept art with anime art or game art or product design art.
+
+        ###### END OF GUIDE ######
+
+        Prompt to refine: {self.image}
+        """
+        return LLM_PROMPT
+
+    def run(self):
+        """
+        Generates and downloads the image based on the prompt.
+
+        This method refines the prompt using the llm, opens the website with the query,
+        gets the image URLs, and downloads the images to the specified folder.
+        """
+        # Set up logging
+        logging.basicConfig(level=logging.INFO)
+
+        # Refine the prompt using the llm
+        image = self.llm_prompt()
+        refined_prompt = self.llm(image)
+        print(f"Refined prompt: {refined_prompt}")
+
+        # Open the website with your query
+        self.dalle.create(refined_prompt)
+
+        # Get the image URLs
+        urls = self.dalle.get_urls()
+
+        # Download the images to your specified folder
+        self.dalle.download(urls, self.output_folder)
+
diff --git a/tests/agents/idea_to_image.py b/tests/agents/idea_to_image.py
new file mode 100644
index 00000000..85efd025
--- /dev/null
+++ b/tests/agents/idea_to_image.py
@@ -0,0 +1,59 @@
+import pytest
+import os
+import shutil
+from swarms.idea2image import Idea2Image
+
+openai_key = os.getenv("OPENAI_API_KEY")
+dalle_cookie = os.getenv("BING_COOKIE")
+
+# Constants for testing
+TEST_PROMPT = "Happy fish."
+TEST_OUTPUT_FOLDER = "test_images/"
+OPENAI_API_KEY = openai_key
+DALLE_COOKIE = dalle_cookie
+
+@pytest.fixture(scope="module")
+def idea2image_instance():
+    # Create an instance of the Idea2Image class
+    idea2image = Idea2Image(
+        image=TEST_PROMPT,
+        openai_api_key=OPENAI_API_KEY,
+        cookie=DALLE_COOKIE,
+        output_folder=TEST_OUTPUT_FOLDER,
+    )
+    yield idea2image
+    # Clean up the test output folder after testing
+    if os.path.exists(TEST_OUTPUT_FOLDER):
+        shutil.rmtree(TEST_OUTPUT_FOLDER)
+
+def test_idea2image_instance(idea2image_instance):
+    # Check if the instance is created successfully
+    assert isinstance(idea2image_instance, Idea2Image)
+
+def test_llm_prompt(idea2image_instance):
+    # Test the llm_prompt method
+    prompt = idea2image_instance.llm_prompt()
+    assert isinstance(prompt, str)
+
+def test_generate_image(idea2image_instance):
+    # Test the generate_image method
+    idea2image_instance.generate_image()
+    # Check if the output folder is created
+    assert os.path.exists(TEST_OUTPUT_FOLDER)
+    # Check if files are downloaded (assuming DALLE-3 responds with URLs)
+    files = os.listdir(TEST_OUTPUT_FOLDER)
+    assert len(files) > 0
+
+def test_invalid_openai_api_key():
+    # Test with an invalid OpenAI API key
+    with pytest.raises(Exception) as exc_info:
+        Idea2Image(
+            image=TEST_PROMPT,
+            openai_api_key="invalid_api_key",
+            cookie=DALLE_COOKIE,
+            output_folder=TEST_OUTPUT_FOLDER,
+        )
+    assert "Failed to initialize OpenAIChat" in str(exc_info.value)
+
+if __name__ == "__main__":
+    pytest.main()