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| from google import genai | |
| from google.genai import types | |
| import os | |
| 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.response should be concise" | |
| } | |
| 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=0.4, | |
| max_output_tokens=1024, | |
| ), | |
| contents = question | |
| ) | |
| return response.text | |
| demo = gr.Interface( | |
| fn=study_assistant, | |
| inputs=[gr.Textbox(label = "Question",lines =4 , placeholder="Ask a Question..."), | |
| gr.Radio(label = "Personalities" , choices = list(personalities.keys()), value = 'Friendly')], | |
| outputs = [gr.Textbox(label = "Answer", lines = 10)], | |
| title = 'Study Assistant', | |
| description='Ask a question to get simple explanation from AI along with analogies and real world examples' | |
| ) | |
| demo.launch(server_name="0.0.0.0", server_port=7860) | |