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import os | |
from transformers import pipeline | |
# Assuming you still want to use your local Flan-T5 model | |
# from tools.search_tool import search_duckduckgo # REMOVE THIS LINE | |
# NEW IMPORTS for smolagents | |
from smolagents import CodeAgent, DuckDuckGoSearchTool | |
from smolagents import TransformersModel # To use your local Hugging Face model | |
class GaiaAgent: | |
def __init__(self, model_id: str = "google/flan-t5-large"): | |
# Initialize your LLM using smolagents's TransformersModel | |
# This allows smolagents to manage the interaction with your local model | |
self.llm_model = TransformersModel(model_id=model_id) | |
# Initialize the smolagents CodeAgent | |
# Pass the DuckDuckGoSearchTool directly to the agent's tools list | |
# You can add other tools here if needed | |
self.agent = CodeAgent( | |
model=self.llm_model, | |
tools=[DuckDuckGoSearchTool()], | |
# 'add_base_tools=True' can add common basic tools (like a Python interpreter) | |
# You might need to experiment with this. For now, let's keep it explicit. | |
add_base_tools=False, | |
verbose=True # This is helpful for debugging on Hugging Face Spaces logs | |
) | |
def process_task(self, task_description: str) -> str: | |
# The smolagents agent.run() method handles the entire process | |
# of planning, tool use, and generating a final answer. | |
try: | |
# The agent will decide when to use DuckDuckGoSearchTool based on the prompt | |
response = self.agent.run(task_description) | |
return response | |
except Exception as e: | |
return f"An error occurred during agent processing: {e}" | |