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| import os | |
| from google import genai | |
| from google.genai import types | |
| import gradio as gr | |
| client = genai.Client(api_key = os.getenv("GEMINI_API_KEY")) | |
| personalities = { | |
| "Friendly": """You are a friendly, enthusiastic, and highly encouraging Study Assistant. | |
| Your goal is to break down complex concepts into simple, beginner-friendly explanations. | |
| Use analogies and real-world examples that beginners can relate to. Always ask a follow-up question to check understanding.""", | |
| "Academic": """You are a strictly academic, highly detailed, and professional university Professor. | |
| Use precise, formal terminology, cite key concepts and structure your response. | |
| Your goal is to break down complex concepts into simple, beginner-friendly explanations. | |
| Use analogies and real-world examples that beginners can relate to. | |
| Always ask a follow-up question to check understanding.""" | |
| } | |
| def study_assistant(question,persona): | |
| system_prompt = personalities[persona] | |
| response = client.models.generate_content( | |
| model = "gemini-2.5-flash", | |
| config = types.GenerateContentConfig( | |
| system_instruction = system_prompt, | |
| temperature = 0.5, | |
| max_output_tokens = 1000 | |
| ), | |
| contents = question | |
| ) | |
| return response.text | |
| demo = gr.Interface( | |
| fn = study_assistant, | |
| inputs = [gr.Textbox(lines=4,placeholder="Ask a Question...",label = "Question"), | |
| gr.Radio(choices = list(personalities.keys()),value ="Friendly",label = "Personality")], | |
| outputs = gr.Textbox(lines= 10, label= "Response"), | |
| title = "Study Assistant", | |
| description= "Ask a question to get simple explanation from AI along analogies and real world examples" | |
| ) | |
| demo.launch(debug=True) | |