Update app.py

app.py

@@ -4,20 +4,19 @@ import requests
 import pytz
 import yaml
 from tools.final_answer import FinalAnswerTool
+
 from Gradio_UI import GradioUI
-from diffusers import StableDiffusionPipeline
-import torch
 
 # Below is an example of a tool that does nothing. Amaze us with your creativity!
 @tool
-def my_custom_tool(arg1: str, arg2: int) -> str:  # it's important to specify the return type
-    """A tool that does nothing yet
+def my_custom_tool(arg1:str, arg2:int)-> str: # it's important to specify the return type
+    # Keep this format for the tool description / args description but feel free to modify the tool
+    """A tool that does nothing yet 
     Args:
         arg1: the first argument
         arg2: the second argument
     """
-    return "What magic will you build?"
-
+    return "What magic will you build ?"
 
 @tool
 def get_current_time_in_timezone(timezone: str) -> str:
@@ -35,50 +34,24 @@ def get_current_time_in_timezone(timezone: str) -> str:
         return f"Error fetching time for timezone '{timezone}': {str(e)}"
 
 
-@tool
-def generate_image_from_text(prompt: str) -> str:
-    """A tool that generates an image from a text prompt using Hugging Face's Stable Diffusion model.
-    Args:
-        prompt: A string representing the text prompt for image generation.
-    """
-    try:
-        # Load the Stable Diffusion pipeline
-        pipe = StableDiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5", torch_dtype=torch.float16)
-        pipe = pipe.to("cuda")
-
-        # Generate the image
-        image = pipe(prompt).images[0]
-
-        # Save the image to a file
-        image_path = f"generated_image_{datetime.datetime.now().strftime('%Y%m%d_%H%M%S')}.png"
-        image.save(image_path)
-
-        return f"Image generated successfully and saved to {image_path}"
-    except Exception as e:
-        return f"Error generating image: {str(e)}"
-
-
 final_answer = FinalAnswerTool()
-
-# If the agent does not answer, the model is overloaded, please use another model or the following Hugging Face Endpoint that also contains qwen2.5 coder:
-# model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud'
-
 model = HfApiModel(
-    max_tokens=2096,
-    temperature=0.5,
-    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',  # it is possible that this model may be overloaded
-    custom_role_conversions=None,
+max_tokens=2096,
+temperature=0.5,
+model_id='Qwen/Qwen2.5-Coder-32B-Instruct',
+custom_role_conversions=None,
 )
 
+
 # Import tool from Hub
 image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True)
 
 with open("prompts.yaml", 'r') as stream:
     prompt_templates = yaml.safe_load(stream)
-
+    
 agent = CodeAgent(
     model=model,
-    tools=[final_answer, generate_image_from_text],  ## add your tools here (don't remove final answer)
+    tools=[final_answer], # add your tools here (don't remove final_answer)
     max_steps=6,
     verbosity_level=1,
     grammar=None,
@@ -88,4 +61,5 @@ agent = CodeAgent(
     prompt_templates=prompt_templates
 )
 
+
 GradioUI(agent).launch()