import gradio as gr
from duckduckgo_search import DDGS
from datetime import datetime
import os
import asyncio
from openai import OpenAI  # Using standard OpenAI client
from agents import Agent, Runner, function_tool  # Assuming agents package is installed

# Set up environment variables
# For Hugging Face Spaces, set these in the Settings > Repository secrets
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")  # You'll need to add this to HF Spaces secrets

# Get current date for default value
default_date = datetime.now().strftime("%Y-%m-%d")

# Configure OpenAI client to use HuggingFace or OpenAI API
client = OpenAI(
    api_key=OPENAI_API_KEY,
    # If using OpenAI directly
    # If using a different API endpoint (e.g., HF Inference API), uncomment and adjust:
    # base_url="https://api-inference.huggingface.co/models/meta-llama/Llama-3.2-70b-instruct"
)

# Define the model - assuming the agents library supports standard OpenAI client
from agents import OpenAIChatCompletionsModel  # Adjust import if needed

model = OpenAIChatCompletionsModel(
    model="gpt-4o-mini",  # Using GPT-4o-mini for better performance at a lower cost
    openai_client=client
)

# News search tool
@function_tool
def get_news_articles(topic, language="English", search_date=None):
    # Use provided date or default to current date
    if not search_date:
        search_date = datetime.now().strftime("%Y-%m")
    else:
        # Convert from date picker format (YYYY-MM-DD) to YYYY-MM format
        search_date = search_date[:7]  # Just get YYYY-MM portion
        
    print(f"Running DuckDuckGo news search for {topic} in {language} for date {search_date}...")
    
    # Map common languages to their search keywords
    language_keywords = {
        "English": "",  # Default, no special keyword needed
        "Hindi": "हिंदी",
        "Spanish": "español",
        "French": "français",
        "German": "deutsch",
        "Japanese": "日本語",
        "Chinese": "中文",
        "Russian": "русский",
        "Arabic": "العربية",
        "Portuguese": "português",
        "Italian": "italiano",
        "Dutch": "nederlands",
        "Korean": "한국어",
        "Turkish": "türkçe",
        "Kannada": "ಕನ್ನಡ",
        "Tamil": "தமிழ்",
        "Telugu": "తెలుగు",
        "Bengali": "বাংলা",
        "Marathi": "मराठी"
    }
    
    # Get language keyword if available
    lang_keyword = language_keywords.get(language, language)
    
    # Add language to search query if it's not English
    search_query = f"{topic} {lang_keyword} {search_date}" if language != "English" else f"{topic} {search_date}"
    
    # DuckDuckGo search
    ddg_api = DDGS()
    results = ddg_api.text(search_query, max_results=5)
    if results:
        news_results = "\n\n".join([f"Title: {result['title']}\nURL: {result['href']}\nDescription: {result['body']}" for result in results])
        return news_results
    else:
        return f"Could not find news results for {topic} in {language} for {search_date}."

# Create agents
news_agent = Agent(
    name="News Agent",
    instructions="You provide the latest news articles for a given topic using DuckDuckGo search. You can search for news in different languages when specified.",
    tools=[get_news_articles],
    model=model
)

editor_agent = Agent(
     name="Editor Assistant",
     instructions="Rewrite and give me a news article ready for publishing. Each news story should be in a separate section. Maintain the original language of the news stories. If the content is in a language other than English, edit and format in that same language.",
     model=model
)

# Workflow function for Gradio
def fetch_and_edit_news(topic, language, search_date):
    try:
        # Create a new event loop for this thread
        loop = asyncio.new_event_loop()
        asyncio.set_event_loop(loop)
        
        # Step 1: Run the news agent
        news_result = Runner.run_sync(
            news_agent,
            f"Get me the news about {topic} in {language} for date {search_date}")
        
        raw_news = news_result.final_output
        
        # Step 2: Pass news to editor for final review
        editor_news_response = Runner.run_sync(
            editor_agent,
            f"Please edit the following news in {language} language. Maintain the original language: \n\n{raw_news}")
        
        edited_news = editor_news_response.final_output
        
        return edited_news
        
    except Exception as e:
        # Return the error message for debugging
        return f"Error: {str(e)}\n\nThis could be due to API key issues or problems with the openai-agents package. Please check the logs for more details."

# Create Gradio interface
with gr.Blocks(title="Multilingual AI News Generator") as demo:
    gr.Markdown("# Multilingual AI News Generator")
    gr.Markdown("Enter a topic, select a language, and choose a date to receive curated and edited news articles")
    
    with gr.Row():
        topic_input = gr.Textbox(label="News Topic", placeholder="Enter a topic (e.g., AI, Climate Change, Sports)")
        language_dropdown = gr.Dropdown(
            choices=[
                "English", "Hindi", "Spanish", "French", "German", 
                "Japanese", "Chinese", "Russian", "Arabic", "Portuguese",
                "Italian", "Dutch", "Korean", "Turkish", "Kannada",
                "Tamil", "Telugu", "Bengali", "Marathi"
            ],
            label="Language",
            value="English"
        )
        date_picker = gr.Textbox(
            label="Search Date",
            placeholder="YYYY-MM-DD",
            value=default_date
        )
        submit_btn = gr.Button("Generate News Article")
    
    output_box = gr.Textbox(label="Generated News Article", lines=20)
    
    submit_btn.click(
        fn=fetch_and_edit_news,
        inputs=[topic_input, language_dropdown, date_picker],
        outputs=output_box
    )

# Launch the app
if __name__ == "__main__":
    demo.launch()