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| import gradio as gr | |
| import openai | |
| # Set up your OpenAI API credentials | |
| openai.api_key = "apikey" | |
| # Define the function to search for quotes | |
| def search_quotes(query): | |
| response = openai.Completion.create( | |
| engine="text-davinci-003", | |
| prompt=f"Search for quotes based on: {query}", | |
| max_tokens=100, | |
| n=5, | |
| stop=None, | |
| temperature=0.5, | |
| ) | |
| quotes = response.choices[0].text.strip().split("\n") | |
| return quotes | |
| # Define the function to search for authors | |
| def search_author(author): | |
| # Code to search for author information and generate a picture | |
| author_info = f"Author: {author}\nBio: Lorem ipsum dolor sit amet, consectetur adipiscing elit." | |
| return author_info | |
| # Define the Gradio interface | |
| def gradio_interface(query): | |
| if query.startswith("author:"): | |
| author = query[7:].strip() | |
| author_info = search_author(author) | |
| return author_info | |
| elif query.startswith("tag:"): | |
| tag = query[4:].strip() | |
| quotes = search_quotes(tag) | |
| return quotes | |
| else: | |
| quotes = search_quotes(query) | |
| return quotes | |
| # Create the Gradio app | |
| inputs = gr.inputs.Textbox(label="Chat with me!") | |
| outputs = gr.outputs.Textbox() | |
| gr.Interface( | |
| fn=gradio_interface, | |
| inputs=inputs, | |
| outputs=outputs, | |
| layout="vertical", | |
| theme="compact", | |
| ).launch() | |