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| # Import necessary libraries | |
| import gradio as gr | |
| import google.generativeai as genai | |
| # Configure Google API | |
| GOOGLE_API_KEY = 'AIzaSyAukxtFZ2tp0t9Xx-Fa0m3778xpoKEVuTY' | |
| genai.configure(api_key=GOOGLE_API_KEY) | |
| # Initialize the generative model | |
| model = genai.GenerativeModel('gemini-1.5-flash') | |
| # Upload the local .txt file | |
| myfile = genai.upload_file(path="./Pride and Prejudice.txt", display_name="novel.txt", mime_type="text/plain") | |
| # Function to handle user input and generate a response | |
| def generate_response(user_question): | |
| prompt = f"{user_question}" | |
| # Generate content using the model | |
| response = model.generate_content([prompt, myfile]) | |
| return response.text | |
| # Create a Gradio interface | |
| interface = gr.Interface( | |
| fn=generate_response, # Function to call | |
| inputs=gr.Textbox(label="Ask a question about Pride and Prejudice:"), # User input | |
| outputs=gr.Textbox(label="Response from the novel:"), # Output display | |
| title="Pride and Prejudice Q&A", # Title of the app | |
| description="Ask any question about 'Pride and Prejudice' and get a detailed response!" | |
| ) | |
| # Launch the app | |
| if __name__ == "__main__": | |
| interface.launch() |