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 newsapi import NewsApiClient
from smolagents.models import OpenAIServerModel

# Init
NEWSAPI_API_KEY='cbcbfa28426a47b2bda9d246cefbf588'
newsapi = NewsApiClient(api_key=NEWSAPI_API_KEY)

def retrieve_news(topic, api_key, page_size=3):
    url = f"https://newsapi.org/v2/everything?q={topic}&apiKey={api_key}&language=en&sortBy=publishedAt&pageSize={page_size}"
    response = requests.get(url)
    return response.json()

# Below is an example of a tool that does nothing. Amaze us with your creativity !
@tool
def get_news(topic:str)-> 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 returns the first news about a given topic 
    Args:
        topic: the topic you want to get news about. Should be one word
    """
    news = newsapi.get_top_headlines(q=topic,
                                     language='en')
    articles = "\n\n".join([f"Title: {article['title']}\nDescription: {article['description']}\nContent: {article['content']}\nLink: {article['url']}" for article in news['articles']])
    
    return articles

@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)}"

from tts_gen import TTSGenerator, translit2rus
import random

sample_rate = 16000
tts = TTSGenerator(sample_rate)
silero_voices = tts.get_all_voices()
import tempfile, os, uuid

def get_random_voice(voices):
    return voices[random.randint(0, len(voices)-1)]

def silero_voice_generator(sentence):
    voice_id = get_random_voice(silero_voices)
    return tts.generate_voice(text = sentence, speaker = voice_id)


@tool
def text_to_voice(sentence: str) -> bytes:
    """
    A tool that converts a sentence into a voice audio file and returns its binary content.
    
    Args:
        sentence: The sentence to convert to speech.
    
    Returns:
        A link to audio file to download.
    """
    voice = silero_voice_generator(sentence)
    temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".mp3")
    temp_file.write(voice.read())
    temp_file.close()  

    try:
        with open(temp_file.name, "rb") as f:
            response = requests.post(
                "https://catbox.moe/user/api.php",
                data={"reqtype": "fileupload"},
                files={"fileToUpload": f}
            )
        public_url = response.text.strip()
    except Exception as e:
        public_url = f"Upload failed, error: {str(e)}"
    
    os.remove(temp_file.name)
    return public_url

final_answer = FinalAnswerTool()
#model = HfApiModel(
#    max_tokens=2096,
#    temperature=0.5,
#    #model_id='https://wxknx1kg971u7k1n.us-east-1.aws.endpoints.huggingface.cloud',# it is possible that this model may be overloaded
#    model_id='Qwen/Qwen2.5-Coder-32B-Instruct',# it is possible that this model may be overloaded
#    #model_id='mistralai/Mistral-Small-24B-Instruct-2501',
#    #model_id="deepseek-ai/DeepSeek-V3",# it is possible that this model may be overloaded
#    custom_role_conversions=None,
#)

mistral_api_key = os.environ.get("MISTRAL_API_KEY", "NZmDhwQK9aiz8qj95ZHdWnKTEKd2vUk7")  # Set your API key in the environment
model = OpenAIServerModel(model_id='mistral-small-latest', api_base='https://api.mistral.ai/v1', api_key=mistral_api_key)


# 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_generation_tool, get_current_time_in_timezone, get_news, text_to_voice], ## 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()