import json
import os

class ConversationManager:
    def __init__(self, client, history_file="conversation_history.json"):
        self.client = client
        self.history_file = history_file
        self.conversation_history = self.load_history()

    def load_history(self):
        """Load conversation history from a file."""
        if os.path.exists(self.history_file):
            with open(self.history_file, "r") as file:
                return json.load(file)
        return []

    def save_history(self):
        """Save conversation history to a file."""
        with open(self.history_file, "w") as file:
            json.dump(self.conversation_history, file)

    def add_user_message(self, message):
        """Add a user message to the conversation history."""
        self.conversation_history.append({"role": "user", "content": message})
        self.save_history()

    def add_ai_message(self, message):
        """Add an AI message to the conversation history."""
        self.conversation_history.append({"role": "assistant", "content": message})
        self.save_history()

    def clear_history(self):
        """Clear the conversation history."""
        self.conversation_history = []
        self.save_history()

    def check_warning(self, max_prompts=4):
        """Check if the conversation history is getting too long."""
        user_prompts = [msg for msg in self.conversation_history if msg['role'] == 'user']
        return len(user_prompts) >= max_prompts

    def generate_ai_response(self, prompt):
        """Generate a response from the AI."""
        messages = [{"role": "system", "content": "You are a Django programming assistant."}]
        messages += self.conversation_history
        messages.append({"role": "user", "content": prompt})

        try:
            completion = self.client.chat.completions.create(
                model="meta/llama-3.3-70b-instruct",
                messages=messages,
                max_tokens=1024,
                temperature=0.5
            )
            return completion.choices[0].message.content
        except Exception as e:
            print(f"Error generating response: {e}")
            return None

    def summarize_history(self):
        """Summarize the conversation history."""
        if not self.conversation_history:
            return "No history to summarize."

        summary_prompt = "Summarize the following conversation history into a concise summary for context:"
        full_history = "\n".join(
            [f"{msg['role'].capitalize()}: {msg['content']}" for msg in self.conversation_history]
        )

        try:
            completion = self.client.chat.completions.create(
                model="meta/llama-3.3-70b-instruct",
                messages=[
                    {"role": "system", "content": "You are a summarization assistant."},
                    {"role": "user", "content": f"{summary_prompt}\n\n{full_history}"}
                ],
                max_tokens=8000
            )
            summary = completion.choices[0].message.content

            # Replace history with the summary
            self.conversation_history = [{"role": "system", "content": summary}]
            self.save_history()
            return summary
        except Exception as e:
            print(f"Error summarizing history: {e}")
            return "An error occurred while summarizing the conversation history."