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3401238 d2ae5b9 3401238 84a655c 5c26cb0 828a8c2 c61f23a 9e4b131 3401238 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 | import os
import pandas as pd
from smolagents import tool, CodeAgent, DuckDuckGoSearchTool, HfApiModel, LiteLLMModel, InferenceClientModel
# Tools
@tool
def add(a: int, b: int) -> float:
"""Divide a and b for calculations.
Args:
a: first number
b: second number
"""
res = a * b
print(f"Tool call: add({a}, {b}) -> {res}")
return res
@tool
def reverse(s: str) -> str:
"""Reverse a string for calculations.
Args:
s: string to reverse
"""
ret = ''.join(reversed(s))
print(f"Tool call: reverse({s}) -> {ret}")
return ret
@tool
def transcribe_audio(file_path: str) -> str:
"""Transcribe an audio file to text using Hugging Face's ASR model.
Args:
file_path: path to the audio file
"""
from transformers import pipeline
transcriber = pipeline("automatic-speech-recognition", model="facebook/wav2vec2-base-960h")
transcription = transcriber(file_path)
return transcription["text"]
@tool
def read_excel(file_path: str) -> pd.DataFrame:
"""Read an Excel file and return its content as a DataFrame.
Args:
file_path: path to the Excel file
"""
return pd.read_excel(file_path)
tools = [
add,
reverse,
DuckDuckGoSearchTool(),
transcribe_audio,
read_excel,
]
# LLM
llm = InferenceClientModel(model_id='meta-llama/Llama-3.3-70B-Instruct',
token=os.getenv('TOGETHER_KEY'),
provider="together")
# Agent
class BasicAgent:
def __init__(self):
self.agent = CodeAgent(tools=tools, model=llm)
def __call__(self, question: str) -> str:
print(f"Agent received question (first 30 chars): {question[:30]}...")
answer = self.agent.run(question)
print(f"Agent answer: {answer}")
return answer |