updates

agent.py

@@ -23,6 +23,7 @@ load_dotenv()
 HUGGINGFACEHUB_API_TOKEN = os.getenv("HUGGINGFACEHUB_API_TOKEN")
 GEMINI_API_KEY = os.getenv("GEMINI_API_KEY")
 
+
 tools = [
     multiply, add, subtract, power, divide, modulus,
     square_root, floor_divide, absolute, logarithm,
@@ -117,7 +118,7 @@ You are an advanced AI agent equipped with multiple tools to solve complex, mult
 ### Information Retrieval
 - **web_search**: Search the web for information
 - **web_content_extract**: Extract content from web pages
-- **wikipedia_search**: Search Wikipedia for information
+- **wikipedia_search**: Search Wikipedia for information, whenever the question refers to wikipedia
 - **arvix_search**: Search academic papers on arXiv
 
 ### Utilities

tools.py

@@ -5,6 +5,8 @@ import os
 import urllib.parse
 from pathlib import Path
 from typing import Dict, Union
+from dotenv import load_dotenv
+
 
 import pandas
 import pytz
@@ -22,6 +24,10 @@ from langchain_google_genai import ChatGoogleGenerativeAI
 from langchain_openai import ChatOpenAI
 from langchain_tavily import TavilySearch
 
+load_dotenv()
+OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
+os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
+
 
 @tool
 def download_file(url: str, filename: str = None) -> str:
@@ -746,62 +752,56 @@ def analyze_csv_file(file_path: str, query: str) -> str:
         return f"Error analyzing CSV file: {str(e)}"
 
 
-vision_llm = ChatOpenAI(model="gpt-4o")
-
 @tool
 def extract_text(img_path: str) -> str:
     """
     Extract text from an image file using a multimodal model.
     
-    This allows me to properly analyze the contents.
+    This allowsto properly analyze the contents.
     """
+    vision_llm = ChatOpenAI(model="gpt-4o")
     all_text = ""
-    try:
-        # Read image and encode as base64
-        with open(img_path, "rb") as image_file:
-            image_bytes = image_file.read()
-
-        image_base64 = base64.b64encode(image_bytes).decode("utf-8")
-
-        # Prepare the prompt including the base64 image data
-        message = [
-            HumanMessage(
-                content=[
-                    {
-                        "type": "text",
-                        "text": (
-                            "Extract all the text from this image. "
-                            "Return only the extracted text, no explanations."
-                        ),
-                    },
-                    {
-                        "type": "image_url",
-                        "image_url": {
-                            "url": f"data:image/png;base64,{image_base64}"
-                        },
+    
+    # Read image and encode as base64
+    with open(img_path, "rb") as image_file:
+        image_bytes = image_file.read()
+
+    image_base64 = base64.b64encode(image_bytes).decode("utf-8")
+
+    # Prepare the prompt including the base64 image data
+    message = [
+        HumanMessage(
+            content=[
+                {
+                    "type": "text",
+                    "text": (
+                        "Extract all the text from this image. "
+                        "Return only the extracted text, no explanations."
+                    ),
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": f"data:image/png;base64,{image_base64}"
                     },
-                ]
-            )
-        ]
+                },
+            ]
+        )
+    ]
 
-        # Call the vision-capable model
-        response = vision_llm.invoke(message)
+    # Call the vision-capable model
+    response = vision_llm.invoke(message)
 
-        # Append extracted text
-        all_text += response.content + "\n\n"
+    # Append extracted text
+    all_text += response.content + "\n\n"
 
-        return all_text.strip()
-    except Exception as e:
-        # A butler should handle errors gracefully
-        error_msg = f"Error extracting text: {str(e)}"
-        print(error_msg)
-        return ""
+    return all_text.strip()
 
 
 @tool
 def reverse_sentence(text: str) -> str:
     """
-    Reverses the input text.
+    Reverses the input text. In case a question is written in reversed text, it can be corrected with this tool.
     Args:
         text (str): The input string to be reversed.
     Returns: