import os
import logging
import sys
import time

import smolagents

LOG = logging.getLogger(__name__)

SYSTEM_PROMPT = """
You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template: FINAL ANSWER: [YOUR FINAL ANSWER]. YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings. If you are asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. If you are asked for a string, don't use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise. If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string.

The current date is April 30, 2025.

Take the time to plan the steps to reach the solution. Show the steps and then execute the steps.
"""


class BasicAgent:

  def __init__(self, model_id=None):
    print("BasicAgent initializing.")
    # Logs appear to be swallowed.
    LOG.warning("logging BasicAgent initialized.")

    # Assume we will use the default model creation
    self.model = None

    if model_id:
      self.model_id = model_id

      # Handle the special cases
      if model_id.lower() == "google":
        self.model_id = "google"

        # Use Google gemini free tier
        GEM_KEY=os.environ["GOOGLE_API_KEY"]
        self.model = smolagents.OpenAIServerModel(
            model_id="gemini-2.0-flash",
            api_base="https://generativelanguage.googleapis.com/v1beta/openai/",
            api_key=GEM_KEY,
            temperature=0.3)
      elif model_id.lower() == "local":
        self.model_id = "Qwen/Qwen3-4B-FP8"
        # Run locally.
        self.model = smolagents.TransformersModel(
          model_id=self.model_id,
          max_new_tokens=32000,
          temperature=0.3
          )
    else:
      self.model_id = "Qwen/Qwen3-32B"

    if not self.model:
      self.model = smolagents.HfApiModel(
          max_tokens=32000,
          temperature=0.3,
          model_id=self.model_id,
          custom_role_conversions=None,
      )
    print(f"NEW2: BasicAgent {self.model_id=} {self.model=}")

    web_search_tools = [
        smolagents.DuckDuckGoSearchTool(),
        smolagents.VisitWebpageTool(),
        smolagents.FinalAnswerTool()
    ]

    print("BasicAgent making search tool.")
    self.web_search_agent = smolagents.CodeAgent(
        name="web_search_agent",
        description="Search the web",
        model=self.model,
        tools=web_search_tools,
        max_steps=6,
        verbosity_level=2,
        planning_interval=None,
        additional_authorized_imports=["duckduckgo_search"],
    )

    wiki_search_tools = [
        smolagents.WikipediaSearchTool(),
        smolagents.VisitWebpageTool(),
        smolagents.FinalAnswerTool()
    ]

    self.wiki_search_agent = smolagents.CodeAgent(
        name="wikipedia_search_agent",
        description="Search wikipedia",
        model=self.model,
        tools=wiki_search_tools,
        max_steps=6,
        verbosity_level=2,
        planning_interval=None,
        additional_authorized_imports=["wikipedia-api"],
    )

    print("BasicAgent making wikipedia search tool.")


    print("BasicAgent making manager.")
    self.manager_agent = smolagents.CodeAgent(
        name="manager_agent",
        description="Manger of other agents",
        tools=[smolagents.FinalAnswerTool()],
        model=self.model,
        max_steps=10,
        verbosity_level=2,
        planning_interval=None,
        additional_authorized_imports=["duckduckgo_search", "wikipedia-api"],
        managed_agents=[self.web_search_agent, self.wiki_search_agent])

  def __call__(self, question: str) -> str:
    # Avoid rate limiting issues
    if self.model_id == "google":
      time.sleep(1)

    print(f"NEW Agent received question (first 50 chars): {question[:50]}...")
    prompt = f"{SYSTEM_PROMPT}\n\n{question}"
    answer = self.manager_agent.run(prompt)
    print(f"NEW {answer=}")
    return answer