app.py

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 trending_topic_analyzer(topic: str, hours_back: int) -> str:
    """A tool that analyzes trending topics and provides timestamped insights with web search data
    
    Args:
        topic: The topic or keyword to analyze 
        hours_back: How many hours back to consider for the analysis
    """
    # Initialize search tool
    search_tool = DuckDuckGoSearchTool()
    
    # Get current time in UTC
    utc_now = datetime.datetime.now(pytz.UTC)
    time_threshold = utc_now - datetime.timedelta(hours=hours_back)
    
    try:
        # Perform search for recent content about the topic
        search_query = f"{topic} after:{time_threshold.strftime('%Y-%m-%d')}"
        search_results = search_tool.run(search_query)
        
        # Process search results
        if not search_results:
            return f"No recent data found for '{topic}' in the last {hours_back} hours"
            
        # Analyze basic statistics
        result_count = len(search_results)
        timestamp = utc_now.strftime("%Y-%m-%d %H:%M:%S UTC")
        
        # Extract key information from top results
        summary = []
        for i, result in enumerate(search_results[:3], 1):  # Top 3 results
            title = result.get('title', 'No title')
            snippet = result.get('snippet', 'No description')[:100] + "..."
            summary.append(f"{i}. {title}\n   {snippet}")
        
        # Compile the analysis
        analysis = f"Trending Topic Analysis for '{topic}'\n"
        analysis += f"Generated at: {timestamp}\n"
        analysis += f"Timeframe: Last {hours_back} hours\n"
        analysis += f"Number of relevant results: {result_count}\n\n"
        analysis += "Top Recent Mentions:\n"
        analysis += "\n".join(summary)
        analysis += "\n\nStatus: Analysis completed successfully"
        
        return analysis
        
    except Exception as e:
        error_time = utc_now.strftime("%Y-%m-%d %H:%M:%S UTC")
        return f"Error analyzing topic '{topic}' at {error_time}: {str(e)}"

@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)}"


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,
)


# 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, trending_topic_analyzer], ## 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()