Create agent.py

agent.py

@@ -0,0 +1,74 @@
+import os
+import pandas as pd
+from smolagents import tool, CodeAgent, DuckDuckGoSearchTool, LiteLLMModel
+
+# 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 = LiteLLMModel(
+    model_id="gemini/gemini-2.0-flash",
+    api_key=os.getenv("GEMINI_API_KEY"),
+    max_tokens=8192,
+)
+
+# 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