Update main.py

revised and updated script correctly

main.py

@@ -1,45 +1,55 @@
 import gradio as gr
+import openai  # Assuming you're using OpenAI's API
+import requests
+from bs4 import BeautifulSoup
 
-# Placeholder function for chatbot response
+# Function for chatbot response
 def chatbot(input_text):
-    response = "Chatbot response: Hello! How can I help you today?"
+    # Implement a more advanced chatbot logic or integrate with a model
+    response = f"Chatbot response: {input_text}"
     return response
 
-# Function to generate responses using openAI API
+# Function to generate responses using OpenAI API
 def generate_openai_response(input_text):
-    # Placeholder function for generating responses using openAI API
-    response = "openAI response: This is an example response from openAI API."
-    return response
+    openai.api_key = "your-openai-api-key"  # Replace with your actual OpenAI API key
+    response = openai.Completion.create(
+        engine="text-davinci-003",
+        prompt=input_text,
+        max_tokens=150
+    )
+    return response.choices[0].text.strip()
 
 # Function to scrape information from URLs
 def scrape_url(url):
-    # Placeholder function for web scraping
-    scrapped_data = "Scrapped data from the URL: Example data"
-    return scrapped_data
+    try:
+        response = requests.get(url)
+        soup = BeautifulSoup(response.text, 'html.parser')
+        scrapped_data = soup.get_text()
+        return scrapped_data.strip()
+    except Exception as e:
+        return f"Error: {e}"
 
 # Function to analyze user-provided documents
 def analyze_document(document):
-    # Placeholder function for document analysis
-    analysis_result = "Analysis result of the document: Example analysis"
+    # Implement document analysis logic
+    analysis_result = f"Analysis result: {document[:100]}..."  # Just an example, adjust as needed
     return analysis_result
 
 # Function to execute code, equations, or scripts
 def execute_code(input_code):
-    # Placeholder function for code execution
-    execution_result = "Execution result of the code: Example output"
-    return execution_result
+    try:
+        exec_globals = {}
+        exec(input_code, exec_globals)
+        return exec_globals
+    except Exception as e:
+        return f"Execution error: {e}"
 
 # Creating Gradio interfaces for each functionality
-chatbot_interface = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="Chatbot")
-openai_interface = gr.Interface(fn=generate_openai_response, inputs="text", outputs="text", title="OpenAI API")
+chatbot_interface = gr.Interface(fn=chatbot, inputs="text", outputs="text", title="Custom Chatbot")
+openai_interface = gr.Interface(fn=generate_openai_response, inputs="text", outputs="text", title="OpenAI API Response")
 scrape_url_interface = gr.Interface(fn=scrape_url, inputs="text", outputs="text", title="Web Scraping")
 analyze_document_interface = gr.Interface(fn=analyze_document, inputs="text", outputs="text", title="Document Analysis")
-execute_code_interface = gr.Interface(fn=execute_code, inputs="text", outputs="text", title="Code Execution")
-
-# Launching all interfaces
-chatbot_interface.launch(share=True)
-openai_interface.launch(share=True)
-scrape_url_interface.launch(share=True)
-analyze_document_interface.launch(share=True)
-execute_code_interface.launch(share=True)
+execute_code_interface = gr.Interface(fn=execute_code, inputs="text", outputs="json", title="Code Execution")
 
+# Launching all interfaces together
+gr.TabbedInterface([chatbot_interface, openai_interface, scrape_url_interface, analyze_document_interface, execute_code_interface], ["Chatbot", "OpenAI", "Web Scraping", "Document Analysis", "Code Execution"]).launch(share=True)