import os
import gradio as gr
import requests
import pandas as pd

# --- LangChain & Dependency Imports ---
from groq import Groq
from langchain_groq import ChatGroq
from langchain.agents import AgentExecutor, create_tool_calling_agent
from langchain_tavily import TavilySearch 
from langchain_core.prompts import ChatPromptTemplate
from langchain.tools import Tool

# --- Constants ---
DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"

# --- Agent Definition ---
class SimpleAgent:
    def __init__(self, groq_api_key: str, tavily_api_key: str):
        print("Initializing SimpleAgent...")
        self.llm = ChatGroq(model_name="llama3-70b-8192", groq_api_key=groq_api_key, temperature=0.0)
        
        # The agent has ONLY ONE tool: web_search
        self.tools = [
            TavilySearch(name="web_search", max_results=3, tavily_api_key=tavily_api_key, description="A search engine for finding up-to-date information on the internet."),
        ]
        
        # A simple, direct prompt
        prompt = ChatPromptTemplate.from_messages([
            ("system", (
                "You are a helpful assistant. You have access to one tool: a web search engine. "
                "Use it when you need to find current information or facts. "
                "After using the tool, provide ONLY the final, concise answer."
            )),
            ("human", "{input}"),
            ("placeholder", "{agent_scratchpad}"),
        ])
        
        agent = create_tool_calling_agent(self.llm, self.tools, prompt)
        self.agent_executor = AgentExecutor(agent=agent, tools=self.tools, verbose=True, handle_parsing_errors=True)
        print("SimpleAgent Initialized.")

    def __call__(self, question: str) -> str:
        print(f"Agent received question: {question[:50]}...")
        try:
            response = self.agent_executor.invoke({"input": question})
            return response.get("output", "Agent failed to produce an answer.")
        except Exception as e:
            return f"Agent execution failed with an error: {e}"

# --- Main Application Logic ---
def run_and_submit_all(profile: gr.OAuthProfile | None):
    space_id = os.getenv("SPACE_ID")
    if not profile: return "Please Login to Hugging Face with the button.", None
    username = profile.username
    print(f"User logged in: {username}")
    
    try:
        groq_api_key = os.getenv("GROQ_API_KEY")
        tavily_api_key = os.getenv("TAVILY_API_KEY")
        if not all([groq_api_key, tavily_api_key]): raise ValueError("GROQ or TAVILY API key is missing.")
        agent = SimpleAgent(groq_api_key=groq_api_key, tavily_api_key=tavily_api_key)
    except Exception as e: return f"Error initializing agent: {e}", None
    
    questions_url = f"{DEFAULT_API_URL}/questions"
    try:
        response = requests.get(questions_url, timeout=20)
        response.raise_for_status()
        questions_data = response.json()
    except Exception as e: return f"Error fetching questions: {e}", None
    
    results_log, answers_payload = [], []
    for item in questions_data:
        task_id, q_text = item.get("task_id"), item.get("question")
        if not task_id or not q_text: continue
        answer = agent(question=q_text)
        answers_payload.append({"task_id": task_id, "submitted_answer": answer})
        results_log.append({"Task ID": task_id, "Question": q_text, "Submitted Answer": answer})
    
    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
    submission_data = {"username": username, "agent_code": agent_code, "answers": answers_payload}
    submit_url = f"{DEFAULT_API_URL}/submit"
    try:
        response = requests.post(submit_url, json=submission_data, timeout=300)
        response.raise_for_status()
        result_data = response.json()
        final_status = (f"Submission Successful!\nUser: {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.')}")
        return final_status, pd.DataFrame(results_log)
    except Exception as e: return f"Submission Failed: {e}", pd.DataFrame(results_log)

# --- Gradio Interface ---
with gr.Blocks() as demo:
    gr.Markdown("# Simple Agent Runner (Web Search Only)")
    gr.Markdown("This agent can only search the web. Let's establish a stable baseline.")
    gr.LoginButton()
    run_button = gr.Button("Run Evaluation & Submit All Answers")
    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
    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)
    for key in ["GROQ_API_KEY", "TAVILY_API_KEY"]:
        print(f"✅ {key} secret is set." if os.getenv(key) else f"⚠️ WARNING: {key} secret is not set.")
    print("-"*(60 + len(" App Starting ")) + "\n")
    demo.launch(debug=True, share=False)