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()