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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) | |