Update tools.py

tools.py

@@ -1,14 +1,8 @@
 import os
-import re
-from pathlib import Path
-import tempfile
-
 import openai
-import pandas as pd
-from tabulate import tabulate
-from smolagents.tools import Tool, PipelineTool
+from smolagents.tools import Tool
 
-# Load your OpenAI API key
+# Carica la tua chiave OpenAI
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
 SYSTEM_PROMPT = """You are a general AI assistant. I will ask you a question. Report your thoughts, and finish your answer with the following template:
@@ -31,6 +25,7 @@ class AnswerTool(Tool):
             {"role": "system", "content": SYSTEM_PROMPT},
             {"role": "user",   "content": question},
         ]
+        # Chiamata all'API v1
         resp = openai.chat.completions.create(
             model="gpt-4o",
             messages=messages,
@@ -41,48 +36,3 @@ class AnswerTool(Tool):
         if "FINAL ANSWER:" in text:
             return text.split("FINAL ANSWER:")[-1].strip()
         return text
-
-class SpeechToTextTool(PipelineTool):
-    """Transcribes audio files using OpenAI Whisper."""
-    name = "transcriber"
-    description = "Transcribes a local audio file to text using Whisper API."
-    inputs = {"audio": {"type": "string", "description": "Path to audio file."}}
-    output_type = "string"
-    default_checkpoint = "openai/whisper-1"
-
-    def __call__(self, audio: str) -> str:
-        return self._transcribe(audio)
-
-    @staticmethod
-    def _transcribe(audio_path: str) -> str:
-        path = Path(audio_path).expanduser().resolve()
-        if not path.is_file():
-            raise FileNotFoundError(f"Audio file not found: {path}")
-        with path.open("rb") as fp:
-            response = openai.audio.transcriptions.create(
-                file=fp,
-                model="whisper-1",
-                response_format="text"
-            )
-        return response  # already plain text
-
-class ExcelToTextTool(Tool):
-    """Renders an Excel worksheet as Markdown text."""
-    name = "excel_to_text"
-    description = "Read an Excel file and return a Markdown table."
-    inputs = {
-        "excel_path": {"type": "string", "description": "Path to Excel file."},
-        "sheet_name": {"type": "string", "description": "Sheet name or index as string.", "nullable": True},
-    }
-    output_type = "string"
-
-    def forward(self, excel_path: str, sheet_name: str = None) -> str:
-        path = Path(excel_path).expanduser().resolve()
-        if not path.exists():
-            return f"Error: Excel file not found at {path}"
-        # Determine sheet
-        sheet = 0 if not sheet_name or sheet_name == "" else (int(sheet_name) if sheet_name.isdigit() else sheet_name)
-        df = pd.read_excel(path, sheet_name=sheet)
-        if hasattr(df, "to_markdown"):
-            return df.to_markdown(index=False)
-        return tabulate(df, headers="keys", tablefmt="github", showindex=False)