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Create code_agent.py
Browse files- code_agent.py +137 -0
code_agent.py
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"""
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Real `smolagents` CodeAgent integration for the final project.
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This module initializes a `CodeAgent` with standard tools and exposes a
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`run_agent(prompt)` function returning the final answer string.
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Notes:
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- Requires `smolagents` installed in the environment.
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- For serverless inference via Hugging Face, you must be logged in
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(`huggingface-cli login`) or have `HF_TOKEN` environment variable set,
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and have sufficient provider credits.
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"""
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from typing import List, Any
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import logging
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import os
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logger = logging.getLogger(__name__)
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logging.basicConfig(level=logging.INFO)
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from smolagents import (
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CodeAgent,
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InferenceClientModel,
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DuckDuckGoSearchTool,
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FinalAnswerTool,
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VisitWebpageTool,
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)
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# Get HF token from environment (set by huggingface-cli login or HF_TOKEN env var)
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HF_TOKEN = os.environ.get("HF_TOKEN")
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if not HF_TOKEN:
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logger.warning(
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"HF_TOKEN not found in environment. Run 'huggingface-cli login' or set HF_TOKEN env var. "
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"CodeAgent initialization will fail without valid credentials."
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)
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def make_code_agent(
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max_steps: int = 8,
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verbosity: int = 1,
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model_name: str | None = None,
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):
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"""Create and return a smolagents CodeAgent configured with standard tools.
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Args:
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max_steps: max reasoning steps for the agent.
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verbosity: logging/output verbosity level.
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model_name: HF model ID for serverless inference (e.g., 'allenai/Olmo-3-7B-Instruct').
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If None, uses the default InferenceClientModel.
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Returns:
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CodeAgent instance.
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Raises:
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Exception: if InferenceClientModel initialization fails (missing HF login/credits).
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"""
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tools: List[Any] = []
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# Standard tools from smolagents
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try:
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tools.append(DuckDuckGoSearchTool())
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except Exception as e:
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logger.debug("DuckDuckGoSearchTool unavailable: %s", e)
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try:
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tools.append(VisitWebpageTool())
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except Exception as e:
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logger.debug("VisitWebpageTool unavailable: %s", e)
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try:
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tools.append(FinalAnswerTool())
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except Exception as e:
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logger.debug("FinalAnswerTool unavailable: %s", e)
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# Initialize serverless inference model
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try:
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if model_name:
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try:
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model = InferenceClientModel(repo_id=model_name, token=HF_TOKEN)
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except Exception:
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try:
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model = InferenceClientModel(model_id=model_name, token=HF_TOKEN)
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except Exception:
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model = InferenceClientModel(token=HF_TOKEN)
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else:
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model = InferenceClientModel(token=HF_TOKEN)
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logger.info("InferenceClientModel initialized successfully with HF_TOKEN")
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except Exception as e:
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logger.error(
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"InferenceClientModel initialization failed (ensure HF_TOKEN is set and has credits): %s", e
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)
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raise
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agent = CodeAgent(tools=tools, model=model, max_steps=max_steps, verbosity_level=verbosity)
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return agent
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_AGENT_SINGLETON = None
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def get_agent():
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"""Get or create the singleton CodeAgent instance."""
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global _AGENT_SINGLETON
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if _AGENT_SINGLETON is None:
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_AGENT_SINGLETON = make_code_agent(model_name="allenai/Olmo-3-7B-Think")
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return _AGENT_SINGLETON
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def run_agent(prompt: str) -> str:
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"""Run the CodeAgent and return the final answer string.
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Args:
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prompt: the reasoning task/question for the agent.
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Returns:
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The agent's final answer as a string.
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Raises:
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Exception: if CodeAgent.run fails (e.g., no HF credentials or credits).
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"""
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agent = get_agent()
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res = agent.run(prompt)
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# Normalize response to string
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if isinstance(res, dict):
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for key in ("answer", "final_answer", "final"):
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if key in res and isinstance(res[key], str):
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return res[key].strip()
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return str(res)
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| 130 |
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if isinstance(res, str):
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return res.strip()
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return str(res)
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if __name__ == "__main__":
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print(run_agent("Give me a short list of 3 fruits."))
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