Add functionality to load and execute Python files; refactor test script for output capture

src/agent.py

@@ -105,8 +105,8 @@ if __name__ == "__main__":
     #question = """Examine the video at https://www.youtube.com/watch?v=1htKBjuUWec.\n\nWhat does Teal'c say in response to the question \"Isn't that hot?\""""
     # question = """Hi, I was out sick from my classes on Friday, so I'm trying to figure out what I need to study for my Calculus mid-term next week. My friend from class sent me an audio recording of Professor Willowbrook giving out the recommended reading for the test, but my headphones are broken :(\n\nCould you please listen to the recording for me and tell me the page numbers I'm supposed to go over? I've attached a file called Homework.mp3 that has the recording. Please provide just the page numbers as a comma-delimited list. And please provide the list in ascending order."""
     # question = """The attached Excel file contains the sales of menu items for a local fast-food chain. What were the total sales that the chain made from food (not including drinks)? Express your answer in USD with two decimal places."""
-    question = """What country had the least number of athletes at the 1928 Summer Olympics? If there's a tie for a number of athletes, return the first in alphabetical order. Give the IOC country code as your answer."""
-    task_id = "7bd855d8-463d-4ed5-93ca-5fe35145f733"
+    question = """What is the final numeric output from the attached Python code?"""
+    task_id = "f918266a-b3e0-4914-865d-4faa564f1aef"
     system_prompt = SystemMessage(content=get_prompt())
     messages = react_graph.invoke({
         "messages": [

src/tools.py

@@ -1,3 +1,9 @@
+import os
+import re
+import whisper
+import io
+
+import pandas as pd
 from langchain_community.tools import WikipediaQueryRun
 from langchain_community.utilities import WikipediaAPIWrapper
 from langchain_community.tools import DuckDuckGoSearchRun
@@ -15,11 +21,8 @@ from youtube_transcript_api import YouTubeTranscriptApi
 
 from pandasai.llm.openai import OpenAI
 from llama_index.readers.pandas_ai import PandasAIReader
+from contextlib import redirect_stdout, redirect_stderr
 
-import os
-import re
-import whisper
-import pandas as pd
 
 from .state import State
 
@@ -139,7 +142,36 @@ def route_question(state: State) -> str:
         return "question_reversed"
     else:
         return "question_not_reversed"
+
+@tool
+def load_and_execute_python_file(task_id: str) -> str:
+    """
+    Reads a Python file, executes it, and prints the result.
+    """
+    file_path = f"{task_id}.py"  # Assuming the file is named with the task_id
+    file_path = os.path.join('results', file_path)
+    try:
+        with open(file_path, 'r', encoding='utf-8') as f:
+            python_code = f.read()
+    except FileNotFoundError:
+        return f"Errore: file '{file_path}' non trovato."
     
+    stdout_buffer = io.StringIO()
+    stderr_buffer = io.StringIO()
+
+    # Redirige stdout e stderr per catturare tutto l'output
+    with redirect_stdout(stdout_buffer), redirect_stderr(stderr_buffer):
+        try:
+            exec(python_code, {"__name__": "__main__"})
+        except Exception as e:
+            # Qualsiasi eccezione viene catturata e mostrata nel buffer stderr
+            print(f"Errore durante l'esecuzione: {e}", file=stderr_buffer)
+
+    # Combina stdout e stderr
+    output = stdout_buffer.getvalue()
+    errors = stderr_buffer.getvalue()
+    return output + errors
+
 
 def get_avaiable_tools():
     """Returns a list of available tools."""
@@ -152,5 +184,6 @@ def get_avaiable_tools():
         web_search_tool,
         get_youtube_transcript,
         transcript_mp3_audio,
-        load_and_analyze_excel_file
+        load_and_analyze_excel_file,
+        load_and_execute_python_file
     ]

test.py

@@ -1,7 +1,28 @@
 from youtube_transcript_api import YouTubeTranscriptApi
 import pandas as pd
+from langchain_experimental.utilities import PythonREPL
+from langchain_core.tools import Tool
+from contextlib import redirect_stdout
+import io
 
 
+python_repl = PythonREPL()
+def read_python_file(file_path: str) -> str:
+    """Reads a Python file and returns its code as a string."""
+    with open(file_path, 'r', encoding='utf-8') as f:
+        return f.read()
+python_str = read_python_file('results/f918266a-b3e0-4914-865d-4faa564f1aef.py')
+# Prepara un buffer per catturare stdout
+f = io.StringIO()
+with redirect_stdout(f):
+    # Esegui il codice come se fosse in un file .py
+    exec(python_str, {"__name__": "__main__"})
+
+# Ottieni tutto ciò che è stato stampato
+output = f.getvalue()
+print("=== OUTPUT ===")
+print(output)
+
 # def get_youtube_transcript(video_url: str) -> list:
 #     """Fetches the transcript of a YouTube video."""
 #     ytt_api = YouTubeTranscriptApi()
@@ -13,6 +34,6 @@ import pandas as pd
 # print(transcript)
 
 # Leggi un file xlsx con pandas
-file_path = 'results/7bd855d8-463d-4ed5-93ca-5fe35145f733.xlsx'
-df = pd.read_excel(file_path)
-print(df)
+# file_path = 'results/7bd855d8-463d-4ed5-93ca-5fe35145f733.xlsx'
+# df = pd.read_excel(file_path)
+# print(df)