from smolagents import load_tool, Tool, tool, ToolCallingAgent, CodeAgent, GoogleSearchTool,FinalAnswerTool,PythonInterpreterTool , LiteLLMModel,  VisitWebpageTool,  DuckDuckGoSearchTool
from litellm import completion

from langchain.agents import load_tools
from langchain_community.tools.tavily_search import TavilySearchResults

import os
from src.final_assignment_template.models import openrouter_qwenCoder_model, modelLiteLLm
from src.final_assignment_template.tools import travily_tool, Video_understanding_tool, image_understanding_tool, get_task_file
# (Keep Constants as is)
# --- Constants ---






web_agent = CodeAgent(
    model=openrouter_qwenCoder_model,
    tools=[
        # GoogleSearchTool(provider="serper"),
        # DuckDuckGoSearchTool(max_results=10),
        travily_tool,
        VisitWebpageTool(),
    ],
    name="web_agent",
    description="""Browses the web to find information""",
    verbosity_level=1,
    max_steps=5,
)

manager_agent = CodeAgent(
    name="Task_Agent",
    description="""You will be provided a task and you need to verify before giving final answer
    You can perform tasks which are text and image based, skip all other
    """,
    model=modelLiteLLm,
    tools=[PythonInterpreterTool(),Video_understanding_tool,image_understanding_tool,get_task_file],
    managed_agents=[web_agent],
    additional_authorized_imports=[
        "json",
        "pandas",
        "numpy",
        "markdown"
        'math', 'statistics', 're', 'unicodedata', 'random', 
        'datetime', 'queue', 'time', 'collections', 'stat', 'itertools',
        'PIL','requests'
    ],
    planning_interval=3,
    verbosity_level=1,
    # final_answer_checks=[check_reasoning_and_plot],
    max_steps=5,
)