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| import gradio as gr | |
| import openai | |
| import langdetect as detect | |
| import os | |
| # Set up OpenAI API with custom Groq endpoint | |
| openai.api_key = os.getenv("PrepBuddy_API_KEY") | |
| openai.api_base = "https://api.groq.com/openai/v1" | |
| # Function to get the Groq model's response | |
| def get_groq_response(message, mode): | |
| try: | |
| # Use a system prompt tailored to the selected mode | |
| motivational_message = ( | |
| "Keep pushing forward! You've got this. Programming might seem tough at first, but every step you take " | |
| "is one step closer to mastering it. Let's score 70 on 70 in programming together!" | |
| ) | |
| if mode == "Code": | |
| system_prompt = ( | |
| "You are GS C PrepBuddy, a friendly and motivational AI specializing in C programming. " | |
| "Your goal is to assist users by providing clear, concise, and well-commented C code " | |
| "to solve their problems. Explain the logic where necessary. " | |
| + motivational_message | |
| ) | |
| elif mode == "Flowchart": | |
| system_prompt = ( | |
| "You are GS C PrepBuddy, a friendly and motivational AI specializing in C programming. " | |
| "Provide a detailed textual description of flowcharts to represent solutions for C programming problems. " | |
| + motivational_message | |
| ) | |
| elif mode == "Algorithm": | |
| system_prompt = ( | |
| "You are GS C PrepBuddy, a friendly and motivational AI specializing in C programming. " | |
| "Provide step-by-step algorithms to solve the user's query with clarity. " | |
| + motivational_message | |
| ) | |
| elif mode == "Exam Preparation": | |
| system_prompt = ( | |
| "You are GS C PrepBuddy, a friendly and motivational AI dedicated to helping students prepare for their exams. " | |
| "Provide explanations, theoretical concepts, sample questions, and problem-solving techniques in C programming. " | |
| + motivational_message | |
| ) | |
| else: | |
| system_prompt = "You are GS C PrepBuddy, a helpful and motivational AI assistant." | |
| response = openai.ChatCompletion.create( | |
| model="llama-3.1-70b-versatile", | |
| messages=[ | |
| {"role": "system", "content": system_prompt}, | |
| {"role": "user", "content": message} | |
| ] | |
| ) | |
| return response.choices[0].message["content"] | |
| except Exception as e: | |
| return f"Error: {str(e)}" | |
| # Function to handle chatbot interactions | |
| def chatbot(user_input, output_format, history=[]): | |
| try: | |
| # Get the response based on the selected output format | |
| bot_response = get_groq_response(user_input, output_format) | |
| # Append to conversation history | |
| history.append((user_input, bot_response)) | |
| return history, history # Return updated chat history and state | |
| except Exception as e: | |
| return [(user_input, f"Error: {str(e)}")], history | |
| # Gradio Interface setup | |
| chat_interface = gr.Interface( | |
| fn=chatbot, # Function to call for chatbot interaction | |
| inputs=[ | |
| "text", # User input | |
| gr.Dropdown( | |
| ["Code", "Flowchart", "Algorithm", "Exam Preparation"], | |
| label="Output Format", | |
| value="Code" | |
| ), | |
| "state" # Chat history | |
| ], | |
| outputs=["chatbot", "state"], # Outputs: the chat and updated history (state) | |
| live=False, # Disable live chat, responses shown after submit | |
| title="GS C PrepBuddy", # Title of the app | |
| description=( | |
| "Welcome to GS Programming PrepBuddy! 💻✨\n\n" | |
| "Let's make programming fun and score 70 on 70 in your C programming exams!\n\n" | |
| "Choose your output format—Code, Flowchart, Algorithm, or Exam Preparation.\n\n" | |
| "Ask your query, and I'll guide you every step of the way!\n\n" | |
| "Made by Satyam Singhal" | |
| ) | |
| ) | |
| # Launch the Gradio interface | |
| if __name__ == "__main__": | |
| chat_interface.launch() | |