File size: 1,913 Bytes
52ecadc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
import gradio as gr

# Placeholder function for chatbot response
def chatbot(input_text):
    response = "Chatbot response: Hello! How can I help you today?"
    return response

# 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

# 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

# Function to analyze user-provided documents
def analyze_document(document):
    # Placeholder function for document analysis
    analysis_result = "Analysis result of the document: Example analysis"
    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

# 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")
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)