import os
import gradio as gr
import requests
import inspect
import pandas as pd
# --- New Imports ---
import datetime
import pytz
import yaml
import secrets
import string
import re # Import re for visit_webpage
from smolagents import CodeAgent, DuckDuckGoSearchTool, OpenAIServerModel, load_tool, tool
from tools.final_answer import FinalAnswerTool
from smolagents.utils import truncate_content 
import dotenv

dotenv.load_dotenv()

OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")

# (Keep Constants as is)
# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

# --- Tool Definitions ---

# Tool: search (using DuckDuckGoSearchTool)
@tool
def search(query:str) -> str:
    """Perform a web query with the specified search string.
    Args:
        query: The search string to pass to the search engine.
    """
    # Note: DuckDuckGoSearchTool itself handles the import check now.
    search_tool_instance = DuckDuckGoSearchTool()
    return search_tool_instance(query)

# Tool: get_current_time_in_timezone
@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: get_open_meteo_weather
@tool
def get_open_meteo_weather(city: str) -> str:
    """
    Fetches the current weather for a given city using Open-Meteo's APIs.
    
    Args:
        city: The name of the city (e.g., "Berlin", "New York").
        
    Returns:
        A string summarizing the current weather conditions, or an error message.
    """
    try:
        # First, use the geocoding API to convert the city name to coordinates.
        geo_url = f"https://geocoding-api.open-meteo.com/v1/search?name={city}"
        geo_response = requests.get(geo_url)
        geo_response.raise_for_status()
        geo_data = geo_response.json()
        
        results = geo_data.get("results")
        if not results:
            return f"No coordinates found for city: {city}"
        
        # Use the first matching result.
        first_result = results[0]
        latitude = first_result.get("latitude")
        longitude = first_result.get("longitude")
        resolved_name = first_result.get("name", city)
        
        # Now, query the Open-Meteo weather API with the obtained coordinates.
        weather_url = (
            f"https://api.open-meteo.com/v1/forecast"
            f"?latitude={latitude}&longitude={longitude}&current_weather=true"
        )
        weather_response = requests.get(weather_url)
        weather_response.raise_for_status()
        weather_data = weather_response.json()
        
        current = weather_data.get("current_weather")
        if not current:
            return "Current weather data not available."
        
        temperature = current.get("temperature")
        windspeed = current.get("windspeed")
        winddirection = current.get("winddirection")
        weathercode = current.get("weathercode")
        weather_time = current.get("time")
        
        return (
            f"In {resolved_name} at {weather_time}, the temperature is {temperature}°C, "
            f"wind speed is {windspeed} km/h, wind direction is {winddirection}°, "
            f"weather code: {weathercode}."
        )
    except Exception as e:
        return f"Error fetching weather data: {str(e)}"

# Tool: get_random_joke
@tool
def get_random_joke() -> str:
    """
    Fetches a random joke from the Official Joke API.
    
    Returns:
        A string containing the joke's setup and punchline, or an error message.
    """
    try:
        # The API endpoint for a random joke:
        url = "https://official-joke-api.appspot.com/random_joke"
        response = requests.get(url)
        response.raise_for_status()
        joke_data = response.json()
        
        setup = joke_data.get("setup")
        punchline = joke_data.get("punchline")
        if not setup or not punchline:
            return "Couldn't find a complete joke."
        return f"{setup} - {punchline}"
    except Exception as e:
        return f"Error fetching joke: {str(e)}"

# Tool: generate_password
@tool
def generate_password(length: int = 16, use_punctuation: bool = True) -> str:
    """
    Generates a secure random password with at least 16 characters.
    
    Args:
        length: The desired length of the password (must be at least 16; default is 16).
        use_punctuation: Whether to include punctuation symbols in the password (default is True).
        
    Returns:
        A randomly generated password as a string.
        
    Raises:
        ValueError: If the requested length is less than 16.
    """
    if length < 16:
        # Instead of raising an error, return a message for Gradio
        return "Error: Password length must be at least 16 characters"
    
    # Build the alphabet from which to choose characters.
    alphabet = string.ascii_letters + string.digits
    if use_punctuation:
        alphabet += string.punctuation
    
    # Generate a secure random password using secrets.choice.
    password = ''.join(secrets.choice(alphabet) for _ in range(length))
    return password

# Tool: VisitWebpageTool
@tool
def visit_webpage(url: str) -> str:
    """Visits a webpage at the given url and reads its content as a markdown string.
    Use this to browse webpages.
    Args:
        url: The url of the webpage to visit.
    """
    try:
        # Send a GET request to the URL with a 20-second timeout
        response = requests.get(url, timeout=20)
        response.raise_for_status()  # Raise an exception for bad status codes

        # Convert the HTML content to Markdown
        # Ensure markdownify is imported
        from markdownify import markdownify
        markdown_content = markdownify(response.text).strip()

        # Remove multiple line breaks
        markdown_content = re.sub(r"\n{3,}", "\n\n", markdown_content)

        # Truncate content (ensure truncate_content is imported from smolagents.utils)
        return truncate_content(markdown_content, 10000)

    except requests.exceptions.Timeout:
        return "The request timed out. Please try again later or check the URL."
    except requests.exceptions.RequestException as e:
        return f"Error fetching the webpage: {str(e)}"
    except Exception as e:
        return f"An unexpected error occurred: {str(e)}"

# --- User's Agent Definition ---
class MyCodeAgent:
    def __init__(self):
        print("Initializing MyCodeAgent...")
        try:
            # Load prompts
            with open("prompts.yaml", 'r') as stream:
                self.prompt_templates = yaml.safe_load(stream)
                print("Prompts loaded successfully.")

            # Initialize OpenAI Model
            openai_api_key = os.getenv("OPENAI_API_KEY")
            if not openai_api_key:
                # Raise an error if the key is missing, as the app cannot function without it.
                # Provide a clear message for the user.
                raise ValueError("Environment variable OPENAI_API_KEY is not set. Please set it to your OpenAI API key.")
            
            self.model = OpenAIServerModel(
                model_id="gpt-4.1", # Or use "gpt-4o" or another compatible model
                api_base="https://api.openai.com/v1", # Default OpenAI API base
                api_key=openai_api_key,
            )
            print(f"OpenAIServerModel initialized with model_id='{self.model.model_id}'.")

            # Load tools
            self.final_answer_tool = FinalAnswerTool()
            # Assuming 'agents-course/text-to-image' needs trust_remote_code
            self.image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) 
            print("Tools loaded.")

            # Initialize CodeAgent
            self.agent = CodeAgent(
                model=self.model,
                tools=[self.final_answer_tool, get_current_time_in_timezone, self.image_generation_tool, search, get_open_meteo_weather, get_random_joke, generate_password, visit_webpage],
                max_steps=15, # As per user's code
                verbosity_level=1, # As per user's code
                grammar=None,
                planning_interval=None,
                name=None,
                description=None,
                prompt_templates=self.prompt_templates,
                additional_authorized_imports=['pandas', 'numpy', 'openpyxl', 'xlrd']
            )
            print("CodeAgent initialized.")
            print("MyCodeAgent initialized successfully.")
        except Exception as e:
            print(f"Error during MyCodeAgent initialization: {e}")
            # Raise the exception to prevent the app from potentially running in a broken state
            raise

    def __call__(self, question: str) -> str:
        print(f"MyCodeAgent received question (first 50 chars): {question[:50]}...")
        try:
            response = self.agent(question)
            
            # Ensure the response is a string for submission
            if not isinstance(response, str):
                 print(f"Warning: Agent returned non-string type ({type(response)}). Converting to string.")
                 response = str(response)
            
            # Verarbeite die Antwort, um nur die kurze Version zu extrahieren
            if "### 1. Task outcome (short version):" in response:
                short_answer_start = response.find("### 1. Task outcome (short version):") + len("### 1. Task outcome (short version):")
                
                # Suche nach dem Ende der kurzen Antwort (dem Beginn des nächsten Abschnitts)
                next_section = response.find("### 2.", short_answer_start)
                if next_section != -1:
                    short_answer = response[short_answer_start:next_section].strip()
                else:
                    short_answer = response[short_answer_start:].strip()
                
                # Bereinige die Antwort von unnötigen Formatierungen
                short_answer = short_answer.strip()
                print(f"Extrahierte kurze Antwort: {short_answer}")
                
                # Verwende die vollständige Antwort nur für Debugging-Zwecke
                print(f"Vollständige Antwort für Debugging: {response[:100]}...")
                
                return short_answer
            
            print(f"MyCodeAgent returning answer (first 100 chars): {response[:100]}...")
            return response
        except Exception as e:
            print(f"Error during MyCodeAgent execution: {e}")
            # Return an error message instead of crashing the Gradio app
            return f"AGENT_EXECUTION_ERROR: {e}"


def run_and_submit_all( profile: gr.OAuthProfile | None):
    """
    Fetches all questions, runs the MyCodeAgent on them, submits all answers,
    and displays the results.
    """
    # --- Determine HF Space Runtime URL and Repo URL ---
    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code

    if profile:
        username= f"{profile.username}"
        print(f"User logged in: {username}")
    else:
        print("User not logged in.")
        return "Please Login to Hugging Face with the button.", None

    api_url = DEFAULT_API_URL
    questions_url = f"{api_url}/questions"
    submit_url = f"{api_url}/submit"

    # 1. Instantiate Agent ( modify this part to create your agent)
    try:
        agent = MyCodeAgent()
    except Exception as e:
        print(f"Error instantiating agent: {e}")
        return f"Error initializing agent: {e}", None
    # In the case of an app running as a hugging Face space, this link points toward your codebase ( usefull for others so please keep it public)
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    print(agent_code)

    # 2. Fetch Questions
    print(f"Fetching questions from: {questions_url}")
    try:
        response = requests.get(questions_url, timeout=15)
        response.raise_for_status()
        questions_data = response.json()
        if not questions_data:
             print("Fetched questions list is empty.")
             return "Fetched questions list is empty or invalid format.", None
        print(f"Fetched {len(questions_data)} questions.")
    except requests.exceptions.RequestException as e:
        print(f"Error fetching questions: {e}")
        return f"Error fetching questions: {e}", None
    except requests.exceptions.JSONDecodeError as e:
         print(f"Error decoding JSON response from questions endpoint: {e}")
         print(f"Response text: {response.text[:500]}")
         return f"Error decoding server response for questions: {e}", None
    except Exception as e:
        print(f"An unexpected error occurred fetching questions: {e}")
        return f"An unexpected error occurred fetching questions: {e}", None

    # 3. Run your Agent
    results_log = []
    answers_payload = []
    print(f"Running agent on {len(questions_data)} questions...")
    for item in questions_data:
        task_id = item.get("task_id")
        question_text = item.get("question")
        if not task_id or question_text is None:
            print(f"Skipping item with missing task_id or question: {item}")
            continue
        try:
            submitted_answer = agent(question_text)
            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
        except Exception as e:
             print(f"Error running agent on task {task_id}: {e}")
             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})

    if not answers_payload:
        print("Agent did not produce any answers to submit.")
        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)

    # 4. Prepare Submission 
    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
    status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
    print(status_update)

    # 5. Submit
    print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
    try:
        response = requests.post(submit_url, json=submission_data, timeout=60)
        response.raise_for_status()
        result_data = response.json()
        final_status = (
            f"Submission Successful!\n"
            f"User: {result_data.get('username')}\n"
            f"Overall Score: {result_data.get('score', 'N/A')}% "
            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
            f"Message: {result_data.get('message', 'No message received.')}"
        )
        print("Submission successful.")
        results_df = pd.DataFrame(results_log)
        return final_status, results_df
    except requests.exceptions.HTTPError as e:
        error_detail = f"Server responded with status {e.response.status_code}."
        try:
            error_json = e.response.json()
            error_detail += f" Detail: {error_json.get('detail', e.response.text)}"
        except requests.exceptions.JSONDecodeError:
            error_detail += f" Response: {e.response.text[:500]}"
        status_message = f"Submission Failed: {error_detail}"
        print(status_message)
        results_df = pd.DataFrame(results_log)
        return status_message, results_df
    except requests.exceptions.Timeout:
        status_message = "Submission Failed: The request timed out."
        print(status_message)
        results_df = pd.DataFrame(results_log)
        return status_message, results_df
    except requests.exceptions.RequestException as e:
        status_message = f"Submission Failed: Network error - {e}"
        print(status_message)
        results_df = pd.DataFrame(results_log)
        return status_message, results_df
    except Exception as e:
        status_message = f"An unexpected error occurred during submission: {e}"
        print(status_message)
        results_df = pd.DataFrame(results_log)
        return status_message, results_df


# --- Build Gradio Interface using Blocks ---
with gr.Blocks() as demo:
    gr.Markdown("# Basic Agent Evaluation Runner")
    gr.Markdown(
        """
        **Instructions:**

        1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
        2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
        3.  Click 'Run Evaluation & Submit All Answers' to fetch questions, run your agent, submit answers, and see the score.

        ---
        **Disclaimers:**
        Once clicking on the "submit button, it can take quite some time ( this is the time for the agent to go through all the questions).
        This space provides a basic setup and is intentionally sub-optimal to encourage you to develop your own, more robust solution. For instance for the delay process of the submit button, a solution could be to cache the answers and submit in a seperate action or even to answer the questions in async.
        """
    )

    gr.LoginButton()

    run_button = gr.Button("Run Evaluation & Submit All Answers")

    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
    # Removed max_rows=10 from DataFrame constructor
    results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)

    run_button.click(
        fn=run_and_submit_all,
        outputs=[status_output, results_table]
    )

if __name__ == "__main__":
    print("\n" + "-"*30 + " App Starting " + "-"*30)
    # Check for SPACE_HOST and SPACE_ID at startup for information
    space_host_startup = os.getenv("SPACE_HOST")
    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup

    if space_host_startup:
        print(f"✅ SPACE_HOST found: {space_host_startup}")
        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
    else:
        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")

    if space_id_startup: # Print repo URLs if SPACE_ID is found
        print(f"✅ SPACE_ID found: {space_id_startup}")
        print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
    else:
        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")

    print("-"*(60 + len(" App Starting ")) + "\n")

    print("Launching Gradio Interface for MyCodeAgent Evaluation...")
    demo.launch(debug=True, share=False)