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

from agent import BasicAgent

--- Constants ---

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

def run_and_submit_all(profile: gr.OAuthProfile | None):
"""
Fetches all questions, runs BasicAgent on them, submits all answers,
and displays the results.
"""
space_id = os.getenv("SPACE_ID")

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
try:
    agent = BasicAgent()
except Exception as e:
    print(f"Error instantiating agent: {e}")
    return f"Error initializing agent: {e}", None

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 the 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")
    file_name = item.get("file_name")  # may be empty string
    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, task_id=task_id, file_name=file_name, api_url=api_url)
        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 ---

with gr.Blocks() as demo:
gr.Markdown("# GAIA Agent Evaluation Runner")
gr.Markdown(
"""
Instructions:

    1. Add your `HF_TOKEN` (and any other needed keys) as a Secret in this Space's Settings.
    2. Log in with the button below (this sets your HF username for submission).
    3. Click "Run Evaluation & Submit All Answers".

    ---
    This will take a few minutes — the agent has to work through all 20 questions.
    """
)

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)
space_host_startup = os.getenv("SPACE_HOST")
space_id_startup = os.getenv("SPACE_ID")

if space_host_startup:
    print(f"✅ SPACE_HOST found: {space_host_startup}")
else:
    print("ℹ️ SPACE_HOST environment variable not found (running locally?).")

if space_id_startup:
    print(f"✅ SPACE_ID found: {space_id_startup}")
else:
    print("ℹ️ SPACE_ID environment variable not found (running locally?).")

print("-" * (60 + len(" App Starting ")) + "\n")
print("Launching Gradio Interface...")
demo.launch(debug=True, share=False)