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

# from huggingface_hub import login

# login()

@tool
def lookup_wikipedia_page(search_query: str) -> str:
    """Looks up the exact Wikipedia page title for a given search query, allowing to get the exact page title for subsequent wikipedia views tool
    Args:
        search_query: The search term to find the Wikipedia page for
    """
    try:
        # Use Wikipedia's API to search for pages
        url = "https://en.wikipedia.org/w/api.php"
        params = {
            "action": "query",
            "format": "json",
            "list": "search",
            "srsearch": search_query,
            "srlimit": 1
        }
        
        response = requests.get(url, params=params)
        
        if response.status_code == 200:
            data = response.json()
            if data["query"]["search"]:
                # Return the exact page title
                return data["query"]["search"][0]["title"]
            else:
                return f"No Wikipedia pages found for '{search_query}'"
        else:
            return f"Error searching Wikipedia: {response.status_code}"
            
    except Exception as e:
        return f"Error processing request: {str(e)}"


@tool
def get_wikipedia_views(article_title: str, window_size_in_days: int) -> str:
    """Fetches view statistics for a Wikipedia article. The article title is the exact page title from the lookup_wikipedia_page tool.
    Args:
        article_title: The title of the Wikipedia article to get views for
        window_size_in_days: The number of days to get views for
    """
    try:
        
        # Clean article title for URL
        article_title = article_title.replace(' ', '_')
        
        # Construct API URL
        # First get the page ID using the API
        id_url = "https://en.wikipedia.org/w/api.php"
        id_params = {
            "action": "query",
            "format": "json", 
            "titles": article_title,
            "prop": "pageviews",
            "pvipdays": window_size_in_days
        }

        # Get the response data
        id_response = requests.get(id_url, params=id_params)
        if id_response.status_code != 200:
            return f"Error getting page ID: {id_response.status_code}"
            
        id_data = id_response.json()
        
        # Check if pages data exists
        if "pages" not in id_data["query"]:
            return f"Could not find page '{article_title}'"
            
        # Get the first page's data
        page_data = next(iter(id_data["query"]["pages"].values()))
        
        if "pageviews" not in page_data:
            return f"No pageview data available for '{article_title}'"
            
        # Calculate total views
        total_views = sum(views for views in page_data["pageviews"].values() if views is not None)
        
        return f"The article '{article_title}' had {total_views} views in the last {window_size_in_days} days"
        
    except Exception as e:
        return f"Error processing request: {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, lookup_wikipedia_page, get_wikipedia_views], ## 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()