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from smolagents import CodeAgent,DuckDuckGoSearchTool, HfApiModel,load_tool,tool
import datetime
import requests
import pytz
import yaml
from tools.final_answer import FinalAnswerTool

from Gradio_UI import GradioUI

# 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 import to specify the return type
    #Keep this format for the description / args / 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 ?"

@tool
def get_current_time_in_timezone(timezone: str) -> str:
    """A tool that fetches the current local time in a specified timezone.
    Args:
        timezone: A string representing a valid timezone (e.g., 'America/New_York').
    """
    try:
        # Create timezone object
        tz = pytz.timezone(timezone)
        # Get current time in that timezone
        local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S")
        return f"The current local time in {timezone} is: {local_time}"
    except Exception as e:
        return f"Error fetching time for timezone '{timezone}': {str(e)}"

@tool
def image_generator(prompt: str) -> str:
    """A tool that generates an image based on a text prompt.
    Args:
        prompt: A text description of the image to generate.
    """
    try:
        # Use the imported image generation tool
        image_path = image_generation_tool(prompt=prompt)
        return image_path
    except Exception as e:
        return f"Error generating image: {str(e)}"

@tool
def translator(question: str, src_lang: str, tgt_lang: str) -> str:
    """A tool that translates text from one language to another.
    Args:
        question: The text to translate.
        src_lang: The source language of the text.
        tgt_lang: The target language to translate to.
    """
    try:
        # Import the deep_translator library
        from deep_translator import GoogleTranslator
        
        # Map common language names to language codes if needed
        language_map = {
            "english": "en", "french": "fr", "spanish": "es", "german": "de",
            "italian": "it", "portuguese": "pt", "russian": "ru", "japanese": "ja",
            "chinese": "zh-CN", "korean": "ko", "arabic": "ar", "hindi": "hi"
        }
        
        # Convert language names to codes if necessary
        src = language_map.get(src_lang.lower(), src_lang.lower())
        tgt = language_map.get(tgt_lang.lower(), tgt_lang.lower())
        
        # Perform the translation
        translated = GoogleTranslator(source=src, target=tgt).translate(question)
        
        return translated
    except Exception as e:
        return f"Error translating text: {str(e)}"

@tool
def search(query: str) -> str:
    """A tool that searches the web for information and returns a list of relevant pages.
    Args:
        query: The search query.
    """
    try:
        # Use DuckDuckGo search tool that's already imported
        search_tool = DuckDuckGoSearchTool()
        results = search_tool(query)
        
        # Check if results is empty
        if not results:
            return f"No result found for query \"{query}\"."
        
        # Handle different return formats
        formatted_results = []
        
        # Check if results is a list of strings or objects
        if isinstance(results, list):
            if results and isinstance(results[0], str):
                # Handle list of strings
                formatted_results = results[:5]  # Limit to top 5 results
            else:
                # Try to handle objects with title/url attributes
                for result in results[:5]:
                    try:
                        if hasattr(result, 'title') and hasattr(result, 'url'):
                            formatted_results.append(f"[{result.title}]({result.url})")
                        elif isinstance(result, dict) and 'title' in result and 'url' in result:
                            formatted_results.append(f"[{result['title']}]({result['url']})")
                        else:
                            formatted_results.append(str(result))
                    except:
                        formatted_results.append(str(result))
        elif isinstance(results, str):
            # Handle string result
            return results
            
        return f"Found {len(formatted_results)} pages:\n" + "\n".join(formatted_results)
    except Exception as e:
        return f"Error searching the web: {str(e)}"

@tool
def web_search(query: str) -> str:
    """A tool that searches the web for information and returns detailed results.
    Args:
        query: The search query.
    """
    try:
        # Use DuckDuckGo search tool that's already imported
        search_tool = DuckDuckGoSearchTool()
        results = search_tool(query)
        
        # Check if results is empty
        if not results:
            return f"No results found for query \"{query}\"."
        
        # Handle different return formats
        if isinstance(results, str):
            return results
            
        combined_info = ""
        
        # Process up to 3 results
        count = 0
        for result in results:
            if count >= 3:
                break
                
            try:
                if hasattr(result, 'snippet'):
                    combined_info += f"Result {count+1}: {result.snippet}\n\n"
                elif isinstance(result, dict) and 'snippet' in result:
                    combined_info += f"Result {count+1}: {result['snippet']}\n\n"
                elif hasattr(result, 'title'):
                    combined_info += f"Result {count+1}: {result.title}\n\n"
                elif isinstance(result, dict) and 'title' in result:
                    combined_info += f"Result {count+1}: {result['title']}\n\n"
                else:
                    combined_info += f"Result {count+1}: {str(result)}\n\n"
                count += 1
            except:
                combined_info += f"Result {count+1}: {str(result)}\n\n"
                count += 1
        
        return combined_info.strip() if combined_info else "No detailed information found."
    except Exception as e:
        return f"Error searching the web: {str(e)}"

@tool
def visit_webpage(url: str) -> str:
    """A tool that visits a webpage and returns its content.
    Args:
        url: The URL of the webpage to visit.
    """
    try:
        # Add headers to mimic a browser request
        headers = {
            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.114 Safari/537.36'
        }
        
        # Make the request
        response = requests.get(url, headers=headers, timeout=10)
        response.raise_for_status()
        
        # Try to extract main content using a simple approach
        from bs4 import BeautifulSoup
        soup = BeautifulSoup(response.text, 'html.parser')
        
        # Remove script and style elements
        for script in soup(["script", "style"]):
            script.extract()
        
        # Get text
        text = soup.get_text()
        
        # Break into lines and remove leading and trailing space on each
        lines = (line.strip() for line in text.splitlines())
        # Break multi-headlines into a line each
        chunks = (phrase.strip() for line in lines for phrase in line.split("  "))
        # Remove blank lines
        text = '\n'.join(chunk for chunk in chunks if chunk)
        
        # Limit the length of the response
        max_length = 5000
        if len(text) > max_length:
            text = text[:max_length] + "... (content truncated)"
            
        return text
    except Exception as e:
        return f"Error visiting webpage: {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
model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',
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, image_generator, translator, get_current_time_in_timezone, search, web_search, visit_webpage], ## add your tools here (don't remove final answer)
    max_steps=6,
    verbosity_level=1,
    grammar=None,
    planning_interval=None,
    name=None,
    description=None,
    prompt_templates=prompt_templates
)


GradioUI(agent).launch()