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Browse files- app.py +38 -29
- browser.py +67 -8
- mini_agents.py +55 -14
app.py
CHANGED
@@ -3,7 +3,7 @@ import gradio as gr
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import requests
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import pandas as pd
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import datasets
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from mini_agents import
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from utils import get_full_file_path
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from smolagents.memory import ActionStep, PlanningStep, TaskStep, SystemPromptStep, FinalAnswerStep
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from typing import Optional
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@@ -43,43 +43,52 @@ columns = [
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class BasicAgent:
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def __init__(self):
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self.agent =
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print("Master Agent initialized.")
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print(f"Agent received question (first 50 chars): {question[:50]}...")
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def check_required_env_vars() -> tuple[bool, Optional[str]]:
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"""Check if required environment variables are set"""
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missing_vars = []
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# Check HF_TOKEN
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if not os.getenv("
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missing_vars.append("
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# Check SPACE_ID (only warn, not required)
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if not os.getenv("SPACE_ID"):
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@@ -117,7 +126,7 @@ def save_dataset_to_hub(df: pd.DataFrame, dataset_name: str) -> tuple[bool, str]
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dataset.push_to_hub(
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dataset_name,
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private=True,
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token=os.getenv("
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)
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return True, f"Successfully saved {len(df)} steps to {dataset_name}"
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import requests
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import pandas as pd
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import datasets
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from mini_agents import MasterAgentWrapper
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from utils import get_full_file_path
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from smolagents.memory import ActionStep, PlanningStep, TaskStep, SystemPromptStep, FinalAnswerStep
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from typing import Optional
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class BasicAgent:
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def __init__(self):
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self.agent = MasterAgentWrapper() # This is now the MasterAgentWrapper instance
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print("Master Agent initialized.")
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def __call__(self, question: str, task_id: str, df_agent_steps: pd.DataFrame) -> tuple[str, pd.DataFrame]:
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print(f"Agent received question (first 50 chars): {question[:50]}...")
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try:
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# Use the wrapper's run method which handles browser tools safely
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fixed_answer = self.agent.run(question)
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# Log steps
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all_steps = self.agent.master_agent.memory.get_full_steps()
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for step in all_steps:
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if isinstance(step, ActionStep):
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step_class = "ActionStep"
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elif isinstance(step, PlanningStep):
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step_class = "PlanningStep"
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elif isinstance(step, TaskStep):
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step_class = "TaskStep"
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elif isinstance(step, SystemPromptStep):
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step_class = "SystemPromptStep"
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elif isinstance(step, FinalAnswerStep):
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step_class = "FinalAnswerStep"
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else:
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step_class = "UnknownStep"
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step_dict = step.dict()
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df_agent_steps.loc[len(df_agent_steps)] = None
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df_agent_steps.at[len(df_agent_steps), 'task_id'] = task_id
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df_agent_steps.at[len(df_agent_steps), 'step_class'] = step_class
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for key, value in step_dict.items():
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df_agent_steps.at[len(df_agent_steps), key] = value
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print(f"Agent returning fixed answer: {fixed_answer}")
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return fixed_answer, df_agent_steps
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except Exception as e:
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print(f"Error in agent execution: {e}")
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raise
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def check_required_env_vars() -> tuple[bool, Optional[str]]:
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"""Check if required environment variables are set"""
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missing_vars = []
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# Check HF_TOKEN
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if not os.getenv("HUGGINGFACE_API_KEY"):
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missing_vars.append("HUGGINGFACE_API_KEY")
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# Check SPACE_ID (only warn, not required)
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if not os.getenv("SPACE_ID"):
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dataset.push_to_hub(
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dataset_name,
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private=True,
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token=os.getenv("HUGGINGFACE_API_KEY")
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)
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return True, f"Successfully saved {len(df)} steps to {dataset_name}"
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browser.py
CHANGED
@@ -1,16 +1,75 @@
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import subprocess
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from smolagents.tools import Tool
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from langchain_community.tools.playwright.utils import (
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create_async_playwright_browser,
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create_sync_playwright_browser
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)
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from langchain_community.agent_toolkits import PlayWrightBrowserToolkit
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import subprocess
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from contextlib import contextmanager
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from typing import List, Optional
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from threading import Lock
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from smolagents.tools import Tool
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from langchain_community.tools.playwright.utils import (
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create_async_playwright_browser,
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create_sync_playwright_browser
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)
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from langchain_community.agent_toolkits import PlayWrightBrowserToolkit
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class BrowserManager:
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_instance = None
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_lock = Lock()
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_browser_tools: Optional[List[Tool]] = None
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def __new__(cls):
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if cls._instance is None:
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with cls._lock:
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if cls._instance is None:
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cls._instance = super(BrowserManager, cls).__new__(cls)
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return cls._instance
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def __init__(self):
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if not hasattr(self, 'initialized'):
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# Run setup script
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subprocess.run(["bash", "scripts.sh"])
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self.initialized = True
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@contextmanager
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def get_browser_tools(self):
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"""Get browser tools in a context that ensures proper cleanup"""
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try:
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if self._browser_tools is None:
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with self._lock:
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if self._browser_tools is None:
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# Create browsers in the current context
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async_browser = create_async_playwright_browser()
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sync_browser = create_sync_playwright_browser()
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# Create toolkit and tools
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browser_toolkit = PlayWrightBrowserToolkit.from_browser(
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async_browser=async_browser,
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sync_browser=sync_browser
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)
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self._browser_tools = [
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Tool.from_langchain(tool)
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for tool in browser_toolkit.get_tools()
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]
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yield self._browser_tools
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except Exception as e:
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print(f"Error in browser context: {e}")
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# Reset tools on error
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self._browser_tools = None
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raise
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finally:
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# Cleanup if needed
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if self._browser_tools:
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for tool in self._browser_tools:
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if hasattr(tool, 'browser'):
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try:
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tool.browser.close()
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except:
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pass
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self._browser_tools = None
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# Create a singleton instance
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browser_manager = BrowserManager()
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# For backward compatibility, but prefer using browser_manager.get_browser_tools()
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def get_browser_tools():
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"""Get browser tools (use with context manager)"""
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return browser_manager.get_browser_tools()
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mini_agents.py
CHANGED
@@ -5,10 +5,12 @@ from tools import to_dataframe, to_json, get_dataframe_data, get_dataframe_colum
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from vlm_tools import image_processing, object_detection_tool, ocr_scan_tool, extract_images_from_video, get_image_from_file_path, get_video_from_file_path
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from audio_tools import transcribe_audio_tool, get_audio_from_file_path, noise_reduction, audio_segmentation, speaker_diarization
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from community_tools import community_tools, get_youtube_transcript_from_url
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from browser import
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import os
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import logging
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import yaml
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logging.basicConfig(level=logging.DEBUG)
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@@ -141,19 +143,58 @@ master_model = InferenceClientModel(
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token=os.getenv("HUGGINGFACE_API_KEY")
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)
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#TESTING 5
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from vlm_tools import image_processing, object_detection_tool, ocr_scan_tool, extract_images_from_video, get_image_from_file_path, get_video_from_file_path
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from audio_tools import transcribe_audio_tool, get_audio_from_file_path, noise_reduction, audio_segmentation, speaker_diarization
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from community_tools import community_tools, get_youtube_transcript_from_url
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from browser import browser_manager
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import os
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import logging
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import yaml
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from typing import List
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from smolagents.tools import Tool
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logging.basicConfig(level=logging.DEBUG)
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token=os.getenv("HUGGINGFACE_API_KEY")
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)
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class MasterAgentWrapper:
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"""Wrapper class to manage master agent with thread-safe browser tools"""
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def __init__(self):
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self.base_tools = [
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sort_list,
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get_youtube_transcript_from_url,
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read_python_file_from_path,
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*community_tools,
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tavily_search_tool
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]
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self.master_agent = CodeAgent(
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model=master_model,
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managed_agents=[audio_agent, vlm_agent, arithmetic_agent, pandas_agent],
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tools=self.base_tools, # Initialize without browser tools
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add_base_tools=True,
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max_steps=20,
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additional_authorized_imports=AUTHORIZED_IMPORTS,
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verbosity_level=logging.INFO,
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planning_interval=4,
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prompt_templates=PROMPT_TEMPLATE["master_agent"],
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name="master_agent",
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description="This agent is responsible for managing audio, vlm, arithmetic and pandas agents."
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)
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def run(self, question: str) -> str:
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"""Run the agent with thread-safe browser tools"""
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try:
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# Get browser tools in the correct context
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with browser_manager.get_browser_tools() as browser_tools:
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# Temporarily add browser tools for this run
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original_tools = self.master_agent.tools
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self.master_agent.tools = original_tools + browser_tools
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try:
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# Run the agent
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result = self.master_agent.run(question)
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return result
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finally:
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# Restore original tools
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self.master_agent.tools = original_tools
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except Exception as e:
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logging.error(f"Error in master agent run: {e}")
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raise
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# Create the wrapped master agent
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master_agent = MasterAgentWrapper()
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# For backward compatibility
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def run_master_agent(question: str) -> str:
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return master_agent.run(question)
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#TESTING 5
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