chore: tools (#2575)

# Description

Please include a summary of the changes and the related issue. Please
also include relevant motivation and context.

## Checklist before requesting a review

Please delete options that are not relevant.

- [ ] My code follows the style guidelines of this project
- [ ] I have performed a self-review of my code
- [ ] I have commented hard-to-understand areas
- [ ] I have ideally added tests that prove my fix is effective or that
my feature works
- [ ] New and existing unit tests pass locally with my changes
- [ ] Any dependent changes have been merged

## Screenshots (if appropriate):

backend/modules/brain/integrations/GPT4/Brain.py

@@ -24,6 +24,7 @@ from modules.chat.dto.outputs import GetChatHistoryOutput
 from modules.chat.service.chat_service import ChatService
 from openai import OpenAI
 from pydantic import BaseModel
+from modules.tools import ImageGeneratorTool
 
 
 class AgentState(TypedDict):
@@ -36,56 +37,6 @@ logger = get_logger(__name__)
 
 chat_service = ChatService()
 
-
-class ImageGenerationInput(BaseModelV1):
-    query: str = FieldV1(
-        ...,
-        title="description",
-        description="A detailled prompt to generate the image from. Takes into account the history of the chat.",
-    )
-
-
-class ImageGeneratorTool(BaseTool):
-    name = "image-generator"
-    description = "useful for when you need to generate an image from a prompt."
-    args_schema: Type[BaseModel] = ImageGenerationInput
-    return_direct = True
-
-    def _run(
-        self, query: str, run_manager: Optional[CallbackManagerForToolRun] = None
-    ) -> str:
-        client = OpenAI()
-
-        response = client.images.generate(
-            model="dall-e-3",
-            prompt=query,
-            size="1024x1024",
-            quality="standard",
-            n=1,
-        )
-        image_url = response.data[0].url
-        revised_prompt = response.data[0].revised_prompt
-        # Make the url a markdown image
-        return f"{revised_prompt} \n ![Generated Image]({image_url}) "
-
-    async def _arun(
-        self, query: str, run_manager: Optional[AsyncCallbackManagerForToolRun] = None
-    ) -> str:
-        """Use the tool asynchronously."""
-        client = OpenAI()
-        response = await run_manager.run_async(
-            client.images.generate,
-            model="dall-e-3",
-            prompt=query,
-            size="1024x1024",
-            quality="standard",
-            n=1,
-        )
-        image_url = response.data[0].url
-        # Make the url a markdown image
-        return f"![Generated Image]({image_url})"
-
-
 class GPT4Brain(KnowledgeBrainQA):
     """This is the Notion brain class. it is a KnowledgeBrainQA has the data is stored locally.
     It is going to call the Data Store internally to get the data.

backend/modules/tools/__init__.py

@@ -0,0 +1,2 @@
+from .image_generator import ImageGeneratorTool
+

backend/modules/tools/image_generator.py

@@ -0,0 +1,61 @@
+from typing import Optional, Type
+
+from langchain.callbacks.manager import (
+    AsyncCallbackManagerForToolRun,
+    CallbackManagerForToolRun,
+)
+from langchain.pydantic_v1 import BaseModel as BaseModelV1
+from langchain.pydantic_v1 import Field as FieldV1
+from langchain.tools import BaseTool
+from langchain_core.tools import BaseTool
+from openai import OpenAI
+from pydantic import BaseModel
+
+
+class ImageGenerationInput(BaseModelV1):
+    query: str = FieldV1(
+        ...,
+        title="description",
+        description="A detailled prompt to generate the image from. Takes into account the history of the chat.",
+    )
+
+
+class ImageGeneratorTool(BaseTool):
+    name = "image-generator"
+    description = "useful for when you need to generate an image from a prompt."
+    args_schema: Type[BaseModel] = ImageGenerationInput
+    return_direct = True
+
+    def _run(
+        self, query: str, run_manager: Optional[CallbackManagerForToolRun] = None
+    ) -> str:
+        client = OpenAI()
+
+        response = client.images.generate(
+            model="dall-e-3",
+            prompt=query,
+            size="1024x1024",
+            quality="standard",
+            n=1,
+        )
+        image_url = response.data[0].url
+        revised_prompt = response.data[0].revised_prompt
+        # Make the url a markdown image
+        return f"{revised_prompt} \n ![Generated Image]({image_url}) "
+
+    async def _arun(
+        self, query: str, run_manager: Optional[AsyncCallbackManagerForToolRun] = None
+    ) -> str:
+        """Use the tool asynchronously."""
+        client = OpenAI()
+        response = await run_manager.run_async(
+            client.images.generate,
+            model="dall-e-3",
+            prompt=query,
+            size="1024x1024",
+            quality="standard",
+            n=1,
+        )
+        image_url = response.data[0].url
+        # Make the url a markdown image
+        return f"![Generated Image]({image_url})"