AI-chatbot / main.py
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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)