Update tools.py

tools.py

@@ -1,8 +1,14 @@
 import os
+import re
+from pathlib import Path
+import tempfile
+
 import openai
-from smolagents.tools import Tool
+import pandas as pd
+from tabulate import tabulate
+from smolagents.tools import Tool, PipelineTool
 
-# Carica la tua chiave OpenAI
+# Load your OpenAI API key
 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:
@@ -25,7 +31,6 @@ 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,
@@ -36,3 +41,51 @@ 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)
+
+
+