diff --git a/swarms/tools/main.py b/swarms/tools/main.py
index 0d3e444d..b71d3aaf 100644
--- a/swarms/tools/main.py
+++ b/swarms/tools/main.py
@@ -482,4 +482,831 @@ if __name__ == "__main__":
     )
     print(o)
 
-    time.sleep(10)  # see if timer has reset
\ No newline at end of file
+    time.sleep(10)  # see if timer has reset
+
+
+###################=> EDITOR/VERIFY
+from pathlib import Path
+
+
+def verify(func):
+    def wrapper(*args, **kwargs):
+        try:
+            filepath = args[0].filepath
+        except AttributeError:
+            raise Exception("This tool doesn't have filepath. Please check your code.")
+        if not str(Path(filepath).resolve()).startswith(str(Path().resolve())):
+            return "You can't access file outside of playground."
+        return func(*args, **kwargs)
+
+    return wrapper
+#=====================> EDITOR/END VERIFY
+
+
+###### EDITOR/WRITE.PY
+
+"""
+write protocol:
+
+<filepath>
+<content>
+"""
+import os
+
+
+
+class WriteCommand:
+    separator = "\n"
+
+    def __init__(self, filepath: str, content: int):
+        self.filepath: str = filepath
+        self.content: str = content
+        self.mode: str = "w"
+
+    def with_mode(self, mode: str) -> "WriteCommand":
+        self.mode = mode
+        return self
+
+    @verify
+    def execute(self) -> str:
+        dir_path = os.path.dirname(self.filepath)
+        if dir_path:
+            os.makedirs(dir_path, exist_ok=True)
+        with open(self.filepath, self.mode) as f:
+            f.write(self.content)
+        return self.content
+
+    @staticmethod
+    def from_str(command: str) -> "WriteCommand":
+        filepath = command.split(WriteCommand.separator)[0]
+        return WriteCommand(filepath, command[len(filepath) + 1 :])
+
+
+class CodeWriter:
+    @staticmethod
+    def write(command: str) -> str:
+        return WriteCommand.from_str(command).with_mode("w").execute()
+
+    @staticmethod
+    def append(command: str) -> str:
+        return WriteCommand.from_str(command).with_mode("a").execute()
+    
+#================> END 
+
+
+
+#============================> EDITOR/READ.PY
+"""
+read protocol:
+
+<filepath>|<start line>-<end line>
+"""
+from typing import List, Optional
+
+
+
+class Line:
+    def __init__(self, content: str, line_number: int, depth: int):
+        self.__content: str = content
+        self.__line_number: int = line_number
+        self.__depth: int = depth
+        self.__children: List[Line] = []
+
+    def get_content(self) -> str:
+        return self.__content
+
+    def get_depth(self) -> int:
+        return self.__depth
+
+    def append_child(self, child: "Line") -> None:
+        self.__children.append(child)
+
+    def find_by_lte_depth(self, depth: int) -> List["Line"]:
+        if self.__depth > depth:
+            return []
+
+        lines: List[Line] = [self]
+        for child in self.__children:
+            lines += child.find_by_lte_depth(depth)
+        return lines
+
+    def find_by_content(self, content: str) -> List["Line"]:
+        if content in self.__content:
+            return [self]
+
+        lines: List[Line] = []
+        for child in self.__children:
+            lines += child.find_by_content(content)
+        return lines
+
+    def find_last_lines(self) -> List["Line"]:
+        if len(self.__children) == 0:
+            return [self]
+        else:
+            return [self, *self.__children[-1].find_last_lines()]
+
+    def print(self, depth: int = 0) -> None:
+        print(f"{'  ' * depth}{self}", end="")
+        for child in self.__children:
+            child.print(depth + 1)
+
+    def __repr__(self):
+        return f"{self.__line_number}: {self.__content}"
+
+
+class CodeTree:
+    def __init__(self):
+        self.root: Line = Line("\n", -1, -1)
+
+    def append(self, content: str, line_number: int) -> None:
+        last_lines: List[Line] = self.root.find_last_lines()
+        new_leading_spaces: int = self.__get_leading_spaces(content)
+
+        previous_line: Line = self.root
+        previous_leading_spaces: int = -1
+        for line in last_lines:
+            leading_spaces = self.__get_leading_spaces(line.get_content())
+            if (
+                previous_leading_spaces < new_leading_spaces
+                and new_leading_spaces <= leading_spaces
+            ):
+                break
+            previous_line, previous_leading_spaces = line, leading_spaces
+
+        new_line_depth: int = previous_line.get_depth() + 1
+        previous_line.append_child(Line(content, line_number, new_line_depth))
+
+    def find_from_root(self, depth: int) -> List[Line]:
+        return self.root.find_by_lte_depth(depth)
+
+    def find_from_parent(self, depth: int, parent_content: str) -> List[Line]:
+        lines: List[Line] = self.root.find_by_content(parent_content)
+        if len(lines) == 0:
+            return []
+        parent = lines[0]
+        return parent.find_by_lte_depth(depth + parent.get_depth())
+
+    def print(self):
+        print("Code Tree:")
+        print("=================================")
+        self.root.print()
+        print("=================================")
+
+    def __get_leading_spaces(self, content: str) -> int:
+        return len(content) - len(content.lstrip())
+
+
+class ReadCommand:
+    separator = "|"
+
+    def __init__(self, filepath: str, start: int, end: int):
+        self.filepath: str = filepath
+        self.start: int = start
+        self.end: int = end
+
+    @verify
+    def execute(self) -> str:
+        with open(self.filepath, "r") as f:
+            code = f.readlines()
+
+        if self.start == self.end:
+            code = code[self.start - 1]
+        else:
+            code = "".join(code[self.start - 1 : self.end])
+        return code
+
+    @staticmethod
+    def from_str(command: str) -> "ReadCommand":
+        filepath, line = command.split(ReadCommand.separator)
+        start, end = line.split("-")
+        return ReadCommand(filepath, int(start), int(end))
+
+
+class SummaryCommand:
+    separator = "|"
+
+    def __init__(self, filepath: str, depth: int, parent_content: Optional[str] = None):
+        self.filepath: str = filepath
+        self.depth: int = depth
+        self.parent_content: Optional[str] = parent_content
+
+    @verify
+    def execute(self) -> str:
+        with open(self.filepath, "r") as f:
+            code = f.readlines()
+
+        code_tree = CodeTree()
+        for i, line in enumerate(code):
+            if line.strip() != "":
+                code_tree.append(line, i + 1)
+
+        if self.parent_content is None:
+            lines = code_tree.find_from_root(self.depth)
+        else:
+            lines = code_tree.find_from_parent(self.depth, self.parent_content)
+        return "".join([str(line) for line in lines])
+
+    @staticmethod
+    def from_str(command: str) -> "SummaryCommand":
+        command_list: List[str] = command.split(SummaryCommand.separator)
+        filepath: str = command_list[0]
+        depth: int = int(command_list[1])
+        parent_content: str | None = command_list[2] if len(command_list) == 3 else None
+        return SummaryCommand(
+            filepath=filepath, depth=depth, parent_content=parent_content
+        )
+
+
+class CodeReader:
+    @staticmethod
+    def read(command: str) -> str:
+        return ReadCommand.from_str(command).execute()
+
+    @staticmethod
+    def summary(command: str) -> str:
+        return SummaryCommand.from_str(command).execute()
+
+
+if __name__ == "__main__":
+    summary = CodeReader.summary("read.py|1|class ReadCommand:")
+    print(summary)
+
+#============================> EDITOR/READ.PY END
+
+
+
+
+#=================================> EDITOR/PATCH.PY
+"""
+patch protocol:
+
+<filepath>|<line>,<col>|<line>,<col>|<content>
+---~~~+++===+++~~~---
+<filepath>|<line>,<col>|<line>,<col>|<content>
+---~~~+++===+++~~~---
+...
+---~~~+++===+++~~~---
+
+let say original code is:
+```
+import requests
+
+def crawl_news(keyword):
+    url = f"https://www.google.com/search?q={keyword}+news"
+    response = requests.get(url)
+
+    news = []
+    for result in response:
+        news.append(result.text)
+
+    return news
+```
+
+and we want to change it to:
+```
+import requests
+from bs4 import BeautifulSoup
+
+def crawl_news(keyword):
+    url = f"https://www.google.com/search?q={keyword}+news"
+    html = requests.get(url).text
+    soup = BeautifulSoup(html, "html.parser")
+    news_results = soup.find_all("div", class_="BNeawe vvjwJb AP7Wnd")
+
+    news_titles = []
+    for result in news_results:
+        news_titles.append(result.text)
+
+    return news_titles
+```
+
+then the command will be:
+test.py|2,1|2,1|from bs4 import BeautifulSoup
+
+---~~~+++===+++~~~---
+test.py|5,5|5,33|html = requests.get(url).text
+    soup = BeautifulSoup(html, "html.parser")
+    news_results = soup.find_all("div", class_="BNeawe vvjwJb AP7Wnd")
+---~~~+++===+++~~~---
+test.py|7,5|9,13|news_titles = []
+    for result in news_results:
+        news_titles
+---~~~+++===+++~~~---
+test.py|11,16|11,16|_titles
+"""
+
+import os
+import re
+from typing import Tuple
+
+from .verify import verify
+
+
+class Position:
+    separator = ","
+
+    def __init__(self, line: int, col: int):
+        self.line: int = line
+        self.col: int = col
+
+    def __str__(self):
+        return f"(Ln {self.line}, Col {self.col})"
+
+    @staticmethod
+    def from_str(pos: str) -> "Position":
+        line, col = pos.split(Position.separator)
+        return Position(int(line) - 1, int(col) - 1)
+
+
+class PatchCommand:
+    separator = "|"
+
+    def __init__(self, filepath: str, start: Position, end: Position, content: str):
+        self.filepath: str = filepath
+        self.start: Position = start
+        self.end: Position = end
+        self.content: str = content
+
+    def read_lines(self) -> list[str]:
+        with open(self.filepath, "r") as f:
+            lines = f.readlines()
+        return lines
+
+    def write_lines(self, lines: list[str]) -> int:
+        with open(self.filepath, "w") as f:
+            f.writelines(lines)
+        return sum([len(line) for line in lines])
+
+    @verify
+    def execute(self) -> Tuple[int, int]:
+        lines = self.read_lines()
+        before = sum([len(line) for line in lines])
+
+        lines[self.start.line] = (
+            lines[self.start.line][: self.start.col]
+            + self.content
+            + lines[self.end.line][self.end.col :]
+        )
+        lines = lines[: self.start.line + 1] + lines[self.end.line + 1 :]
+
+        after = self.write_lines(lines)
+
+        written = len(self.content)
+        deleted = before - after + written
+
+        return written, deleted
+
+    @staticmethod
+    def from_str(command: str) -> "PatchCommand":
+        match = re.search(
+            r"(.*)\|([0-9]*),([0-9]*)\|([0-9]*),([0-9]*)(\||\n)(.*)",
+            command,
+            re.DOTALL,
+        )
+        filepath = match.group(1)
+        start_line = match.group(2)
+        start_col = match.group(3)
+        end_line = match.group(4)
+        end_col = match.group(5)
+        content = match.group(7)
+        return PatchCommand(
+            filepath,
+            Position.from_str(f"{start_line},{start_col}"),
+            Position.from_str(f"{end_line},{end_col}"),
+            content,
+        )
+
+
+class CodePatcher:
+    separator = "\n---~~~+++===+++~~~---\n"
+
+    @staticmethod
+    def sort_commands(commands: list[PatchCommand]) -> list[PatchCommand]:
+        return sorted(commands, key=lambda c: c.start.line, reverse=True)
+
+    @staticmethod
+    def patch(bulk_command: str) -> Tuple[int, int]:
+        commands = [
+            PatchCommand.from_str(command)
+            for command in bulk_command.split(CodePatcher.separator)
+            if command != ""
+        ]
+        commands = CodePatcher.sort_commands(commands)
+
+        written, deleted = 0, 0
+        for command in commands:
+            if command:
+                w, d = command.execute()
+                written += w
+                deleted += d
+        return written, deleted
+
+
+if __name__ == "__main__":
+    commands = """test.py|2,1|2,1|from bs4 import BeautifulSoup
+
+---~~~+++===+++~~~---
+test.py|5,5|5,33|html = requests.get(url).text
+    soup = BeautifulSoup(html, "html.parser")
+    news_results = soup.find_all("div", class_="BNeawe vvjwJb AP7Wnd")
+---~~~+++===+++~~~---
+test.py|7,5|9,13|news_titles = []
+    for result in news_results:
+        news_titles
+---~~~+++===+++~~~---
+test.py|11,16|11,16|_titles
+"""
+
+    example = """import requests
+
+def crawl_news(keyword):
+    url = f"https://www.google.com/search?q={keyword}+news"
+    response = requests.get(url)
+
+    news = []
+    for result in response:
+        news.append(result.text)
+
+    return news
+"""
+    testfile = "test.py"
+    with open(testfile, "w") as f:
+        f.write(example)
+
+    patcher = CodePatcher()
+    written, deleted = patcher.patch(commands)
+    print(f"written: {written}, deleted: {deleted}")
+
+####################### => EDITOR/PATCH.PY
+
+
+
+
+
+
+###################### EDITOR// INIT.PY
+
+
+class CodeEditor(BaseToolSet):
+    @tool(
+        name="CodeEditor.READ",
+        description="Read and understand code. "
+        f"Input should be filename and line number group. ex. test.py|1-10 "
+        "and the output will be code. ",
+    )
+    def read(self, inputs: str) -> str:
+        try:
+            output = CodeReader.read(inputs)
+        except Exception as e:
+            output = str(e)
+
+        logger.debug(
+            f"\nProcessed CodeEditor.READ, Input Commands: {inputs} "
+            f"Output Answer: {output}"
+        )
+        return output
+
+    @tool(
+        name="CodeEditor.SUMMARY",
+        description="Summary code. "
+        "Read the code structured into a tree. "
+        "If you set specific line, it will show the code from the specific line. "
+        "Input should be filename, depth, and specific line if you want. ex. test.py|2 or test.py|3|print('hello world') "
+        "and the output will be list of (line number: code). ",
+    )
+    def summary(self, inputs: str) -> str:
+        try:
+            output = CodeReader.summary(inputs)
+        except Exception as e:
+            output = str(e)
+
+        logger.debug(
+            f"\nProcessed CodeEditor.SUMMARY, Input Commands: {inputs} "
+            f"Output Answer: {output}"
+        )
+        return output
+
+    @tool(
+        name="CodeEditor.APPEND",
+        description="Append code to the existing file. "
+        "If the code is completed, use the Terminal tool to execute it, if not, append the code through the this tool. "
+        "Input should be filename and code to append. "
+        "Input code must be the code that should be appended, NOT whole code. "
+        "ex. test.py\nprint('hello world')\n "
+        "and the output will be last 3 lines.",
+    )
+    def append(self, inputs: str) -> str:
+        try:
+            code = CodeWriter.append(inputs)
+            output = "Last 3 line was:\n" + "\n".join(code.split("\n")[-3:])
+        except Exception as e:
+            output = str(e)
+
+        logger.debug(
+            f"\nProcessed CodeEditor.APPEND, Input: {inputs} "
+            f"Output Answer: {output}"
+        )
+        return output
+
+    @tool(
+        name="CodeEditor.WRITE",
+        description="Write code to create a new tool. "
+        "If the code is completed, use the Terminal tool to execute it, if not, append the code through the CodeEditor.APPEND tool. "
+        "Input should be formatted like: "
+        "<filename>\n<code>\n\n"
+        "Here is an example: "
+        "test.py\nmessage = 'hello world'\nprint(message)\n"
+        "\n"
+        "The output will be last 3 lines you wrote.",
+    )
+    def write(self, inputs: str) -> str:
+        try:
+            code = CodeWriter.write(inputs.lstrip())
+            output = "Last 3 line was:\n" + "\n".join(code.split("\n")[-3:])
+        except Exception as e:
+            output = str(e)
+
+        logger.debug(
+            f"\nProcessed CodeEditor.WRITE, Input: {inputs} " f"Output Answer: {output}"
+        )
+        return output
+
+    # @tool(
+    #     name="CodeEditor.PATCH",
+    #     description="Patch the code to correct the error if an error occurs or to improve it. "
+    #     "Input is a list of patches. The patch is separated by {seperator}. ".format(
+    #         seperator=CodePatcher.separator.replace("\n", "\\n")
+    #     )
+    #     + "Each patch has to be formatted like below.\n"
+    #     "<filepath>|<start_line>,<start_col>|<end_line>,<end_col>|<new_code>"
+    #     "Here is an example. If the original code is:\n"
+    #     "print('hello world')\n"
+    #     "and you want to change it to:\n"
+    #     "print('hi corca')\n"
+    #     "then the patch should be:\n"
+    #     "test.py|1,8|1,19|hi corca\n"
+    #     "Code between start and end will be replaced with new_code. "
+    #     "The output will be written/deleted bytes or error message. ",
+    # )
+    def patch(self, patches: str) -> str:
+        try:
+            w, d = CodePatcher.patch(patches)
+            output = f"successfully wrote {w}, deleted {d}"
+        except Exception as e:
+            output = str(e)
+
+        logger.debug(
+            f"\nProcessed CodeEditor.PATCH, Input Patch: {patches} "
+            f"Output Answer: {output}"
+        )
+        return output
+
+    @tool(
+        name="CodeEditor.DELETE",
+        description="Delete code in file for a new start. "
+        "Input should be filename."
+        "ex. test.py "
+        "Output will be success or error message.",
+    )
+    def delete(self, inputs: str) -> str:
+        try:
+            with open(filepath, "w") as f:
+                f.write("")
+            output = "success"
+        except Exception as e:
+            output = str(e)
+
+        logger.debug(
+            f"\nProcessed CodeEditor.DELETE, Input filename: {inputs} "
+            f"Output Answer: {output}"
+        )
+        return output
+    
+###################### EDITOR// INIT.PY END
+
+
+
+
+
+
+########################### MODELS
+import os
+import uuid
+
+import numpy as np
+import torch
+from diffusers import (
+    EulerAncestralDiscreteScheduler,
+    StableDiffusionInpaintPipeline,
+    StableDiffusionInstructPix2PixPipeline,
+    StableDiffusionPipeline,
+)
+from PIL import Image
+from transformers import (
+    BlipForQuestionAnswering,
+    BlipProcessor,
+    CLIPSegForImageSegmentation,
+    CLIPSegProcessor,
+)
+
+from logger import logger
+from utils import get_new_image_name
+
+
+class MaskFormer(BaseToolSet):
+    def __init__(self, device):
+        print("Initializing MaskFormer to %s" % device)
+        self.device = device
+        self.processor = CLIPSegProcessor.from_pretrained("CIDAS/clipseg-rd64-refined")
+        self.model = CLIPSegForImageSegmentation.from_pretrained(
+            "CIDAS/clipseg-rd64-refined"
+        ).to(device)
+
+    def inference(self, image_path, text):
+        threshold = 0.5
+        min_area = 0.02
+        padding = 20
+        original_image = Image.open(image_path)
+        image = original_image.resize((512, 512))
+        inputs = self.processor(
+            text=text, images=image, padding="max_length", return_tensors="pt"
+        ).to(self.device)
+        with torch.no_grad():
+            outputs = self.model(**inputs)
+        mask = torch.sigmoid(outputs[0]).squeeze().cpu().numpy() > threshold
+        area_ratio = len(np.argwhere(mask)) / (mask.shape[0] * mask.shape[1])
+        if area_ratio < min_area:
+            return None
+        true_indices = np.argwhere(mask)
+        mask_array = np.zeros_like(mask, dtype=bool)
+        for idx in true_indices:
+            padded_slice = tuple(
+                slice(max(0, i - padding), i + padding + 1) for i in idx
+            )
+            mask_array[padded_slice] = True
+        visual_mask = (mask_array * 255).astype(np.uint8)
+        image_mask = Image.fromarray(visual_mask)
+        return image_mask.resize(original_image.size)
+
+
+class ImageEditing(BaseToolSet):
+    def __init__(self, device):
+        print("Initializing ImageEditing to %s" % device)
+        self.device = device
+        self.mask_former = MaskFormer(device=self.device)
+        self.revision = "fp16" if "cuda" in device else None
+        self.torch_dtype = torch.float16 if "cuda" in device else torch.float32
+        self.inpaint = StableDiffusionInpaintPipeline.from_pretrained(
+            "runwayml/stable-diffusion-inpainting",
+            revision=self.revision,
+            torch_dtype=self.torch_dtype,
+        ).to(device)
+
+    @tool(
+        name="Remove Something From The Photo",
+        description="useful when you want to remove and object or something from the photo "
+        "from its description or location. "
+        "The input to this tool should be a comma separated string of two, "
+        "representing the image_path and the object need to be removed. ",
+    )
+    def inference_remove(self, inputs):
+        image_path, to_be_removed_txt = inputs.split(",")
+        return self.inference_replace(f"{image_path},{to_be_removed_txt},background")
+
+    @tool(
+        name="Replace Something From The Photo",
+        description="useful when you want to replace an object from the object description or "
+        "location with another object from its description. "
+        "The input to this tool should be a comma separated string of three, "
+        "representing the image_path, the object to be replaced, the object to be replaced with ",
+    )
+    def inference_replace(self, inputs):
+        image_path, to_be_replaced_txt, replace_with_txt = inputs.split(",")
+        original_image = Image.open(image_path)
+        original_size = original_image.size
+        mask_image = self.mask_former.inference(image_path, to_be_replaced_txt)
+        updated_image = self.inpaint(
+            prompt=replace_with_txt,
+            image=original_image.resize((512, 512)),
+            mask_image=mask_image.resize((512, 512)),
+        ).images[0]
+        updated_image_path = get_new_image_name(
+            image_path, func_name="replace-something"
+        )
+        updated_image = updated_image.resize(original_size)
+        updated_image.save(updated_image_path)
+
+        logger.debug(
+            f"\nProcessed ImageEditing, Input Image: {image_path}, Replace {to_be_replaced_txt} to {replace_with_txt}, "
+            f"Output Image: {updated_image_path}"
+        )
+
+        return updated_image_path
+
+
+class InstructPix2Pix(BaseToolSet):
+    def __init__(self, device):
+        print("Initializing InstructPix2Pix to %s" % device)
+        self.device = device
+        self.torch_dtype = torch.float16 if "cuda" in device else torch.float32
+        self.pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(
+            "timbrooks/instruct-pix2pix",
+            safety_checker=None,
+            torch_dtype=self.torch_dtype,
+        ).to(device)
+        self.pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(
+            self.pipe.scheduler.config
+        )
+
+    @tool(
+        name="Instruct Image Using Text",
+        description="useful when you want to the style of the image to be like the text. "
+        "like: make it look like a painting. or make it like a robot. "
+        "The input to this tool should be a comma separated string of two, "
+        "representing the image_path and the text. ",
+    )
+    def inference(self, inputs):
+        """Change style of image."""
+        logger.debug("===> Starting InstructPix2Pix Inference")
+        image_path, text = inputs.split(",")[0], ",".join(inputs.split(",")[1:])
+        original_image = Image.open(image_path)
+        image = self.pipe(
+            text, image=original_image, num_inference_steps=40, image_guidance_scale=1.2
+        ).images[0]
+        updated_image_path = get_new_image_name(image_path, func_name="pix2pix")
+        image.save(updated_image_path)
+
+        logger.debug(
+            f"\nProcessed InstructPix2Pix, Input Image: {image_path}, Instruct Text: {text}, "
+            f"Output Image: {updated_image_path}"
+        )
+
+        return updated_image_path
+
+
+class Text2Image(BaseToolSet):
+    def __init__(self, device):
+        print("Initializing Text2Image to %s" % device)
+        self.device = device
+        self.torch_dtype = torch.float16 if "cuda" in device else torch.float32
+        self.pipe = StableDiffusionPipeline.from_pretrained(
+            "runwayml/stable-diffusion-v1-5", torch_dtype=self.torch_dtype
+        )
+        self.pipe.to(device)
+        self.a_prompt = "best quality, extremely detailed"
+        self.n_prompt = (
+            "longbody, lowres, bad anatomy, bad hands, missing fingers, extra digit, "
+            "fewer digits, cropped, worst quality, low quality"
+        )
+
+    @tool(
+        name="Generate Image From User Input Text",
+        description="useful when you want to generate an image from a user input text and save it to a file. "
+        "like: generate an image of an object or something, or generate an image that includes some objects. "
+        "The input to this tool should be a string, representing the text used to generate image. ",
+    )
+    def inference(self, text):
+        image_filename = os.path.join("image", str(uuid.uuid4())[0:8] + ".png")
+        prompt = text + ", " + self.a_prompt
+        image = self.pipe(prompt, negative_prompt=self.n_prompt).images[0]
+        image.save(image_filename)
+
+        logger.debug(
+            f"\nProcessed Text2Image, Input Text: {text}, Output Image: {image_filename}"
+        )
+
+        return image_filename
+
+
+class VisualQuestionAnswering(BaseToolSet):
+    def __init__(self, device):
+        print("Initializing VisualQuestionAnswering to %s" % device)
+        self.torch_dtype = torch.float16 if "cuda" in device else torch.float32
+        self.device = device
+        self.processor = BlipProcessor.from_pretrained("Salesforce/blip-vqa-base")
+        self.model = BlipForQuestionAnswering.from_pretrained(
+            "Salesforce/blip-vqa-base", torch_dtype=self.torch_dtype
+        ).to(self.device)
+
+    @tool(
+        name="Answer Question About The Image",
+        description="useful when you need an answer for a question based on an image. "
+        "like: what is the background color of the last image, how many cats in this figure, what is in this figure. "
+        "The input to this tool should be a comma separated string of two, representing the image_path and the question",
+    )
+    def inference(self, inputs):
+        image_path, question = inputs.split(",")
+        raw_image = Image.open(image_path).convert("RGB")
+        inputs = self.processor(raw_image, question, return_tensors="pt").to(
+            self.device, self.torch_dtype
+        )
+        out = self.model.generate(**inputs)
+        answer = self.processor.decode(out[0], skip_special_tokens=True)
+
+        logger.debug(
+            f"\nProcessed VisualQuestionAnswering, Input Image: {image_path}, Input Question: {question}, "
+            f"Output Answer: {answer}"
+        )
+
+        return answer
+########################### MODELS