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from smolagents import (
CodeAgent,
LiteLLMModel,
Tool,
)
from typing import Callable
class MyAgent:
def __init__(
self,
provider: str = "litellm",
model_id: str = "gemini/gemini-2.0-flash-lite",
api_base: str | None = None,
api_key: str | None = None,
planning_interval: int = 3,
num_ctx: int = 8192,
tools: list[Tool] = [],
add_base_tools: bool = True,
temperature: float = 0.2,
additional_authorized_imports: list[str] = [],
step_callbacks: list[Callable] = [],
max_steps: int = 20,
verbosity_level: int = 2,
):
"""
Initializes the agent depending on the provider and model ID.
Args:
provider (str): The provider of the model (e.g., "litellm", "huggingface").
model_id (str): The ID of the model to be used.
tools (list[Tool]): The tools to be used by the agent.
api_base (str | None): The base URL of the API.
api_key (str | None): The API key.
planning_interval (int): The interval for planning.
num_ctx (int): The number of context tokens.
add_base_tools (bool): Whether to add base tools.
temperature (float): The temperature for the model.
additional_authorized_imports (list[str]): The additional authorized imports.
step_callbacks (list[Callable]): The step callbacks.
max_steps (int): The maximum steps.
verbosity_level (int): The verbosity level.
Returns:
None: None
"""
self.provider = provider
self.model_id = model_id
self.api_base = api_base
self.api_key = api_key
self.planning_interval = planning_interval
self.num_ctx = num_ctx
self.temperature = temperature
model = LiteLLMModel(
model_id=self.model_id,
api_base=self.api_base,
api_key=self.api_key,
num_ctx=self.num_ctx,
add_base_tools=add_base_tools,
temperature=self.temperature,
)
# Initialize the agent with the specified provider and model ID
if provider == "litellm":
self.agent = CodeAgent(
model=model,
tools=tools,
planning_interval=self.planning_interval,
additional_authorized_imports=additional_authorized_imports,
step_callbacks=step_callbacks,
max_steps=max_steps,
verbosity_level=verbosity_level,
)
else:
raise ValueError(f"Unsupported provider: {provider}")
print(f"Agent initialized with provider: {provider}, model ID: {model_id}")
def __call__(self, question: str) -> str:
"""
Given a question, run the agent and return the answer.
Args:
question (str): The question to be answered.
Returns:
str: The answer to the question.
"""
final_answer = self.agent.run(question)
print(f"Agent received question (last 50 chars): {question[-50:]}...")
print(f"Agent returning fixed answer: {final_answer}")
return final_answer
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