# agents/mnemonic_agent.py
"""
Mnemonic Creation Agent - Creates memory aids and tricks using Generative AI.
"""
import re

class MnemonicAgent:
    def __init__(self, gemini_model=None):
        """
        Initializes the agent with the Gemini model.

        Args:
            gemini_model: An instance of the Gemini model client.
        """
        self.model = gemini_model

    def _extract_topic(self, query: str) -> str:
        """A simple helper to extract the core topic from the user's query."""
        # Remove common phrases used to request mnemonics
        patterns = [
            r"make a mnemonic for",
            r"create a mnemonic for",
            r"give me a mnemonic for",
            r"mnemonic for",
            r"memory aid for"
        ]
        topic = query.lower()
        for p in patterns:
            topic = re.sub(p, "", topic)
        
        # Clean up any extra whitespace
        return topic.strip()

    def process_query(self, query: str, file_context: str = "",chat_history: list = None):
        """
        Processes a query to generate a mnemonic.

        Args:
            query (str): The user's full query (e.g., "Give me a mnemonic for glycolysis steps").
            file_context (str): Optional context from uploaded files (usually not needed for mnemonics).
        
        Returns:
            dict: A dictionary containing the response message and agent metadata.
        """
        # Fallback response if the AI model is not configured
        if not self.model:
            return {
                'message': "🧠 **Mnemonic Master**\n\nMy creative circuits are offline! The Gemini API key is missing, so I can't generate mnemonics right now. Please configure the API key to enable this feature.",
                'agent_type': 'mnemonic_creation',
                'status': 'error_no_api_key'
            }

        topic = self._extract_topic(query)
        if not topic:
            return {
                'message': "Please tell me what topic you need a mnemonic for! For example, try 'mnemonic for Krebs cycle intermediates'.",
                'agent_type': 'mnemonic_creation',
                'status': 'error_no_topic'
            }
         # --- NEW LOGIC ---
        task_description = f"Generate a clever mnemonic for the B.Pharmacy topic: **{topic.title()}**."

        if file_context:
            task_description += f"\n\nIf relevant, you can use the following text from the student's uploaded notes for context:\n---\n{file_context}\n---"


        # Construct a specialized prompt for the Gemini model
        prompt = f"""
You are "Mnemonic Master," a creative and witty AI that excels at creating memorable mnemonics for B.Pharmacy students in India.

**Your Task:**
{task_description}

**Topic:** "{topic}"

**Instructions:**
1.  **Analyze the Topic:** Identify the key items to be memorized (e.g., steps, drug names, classifications).
2.  **Create the Mnemonic:** Design a creative acronym, rhyme, or short, vivid story.
3.  **Explain It:** Clearly state the mnemonic and then explain how it maps to the concepts.
4.  **Tone:** Be encouraging, fun, and use emojis! The language should be simple and relatable.

**Example Output Format:**

🧠 **Mnemonic for [Topic Name]**

Here's a fun way to remember it!

**The Mnemonic:**
"[The actual acronym or rhyme]"

**How it works:**
* **[Letter 1]** stands for [Concept 1]
* **[Letter 2]** stands for [Concept 2]
* ...and so on!

Keep up the great work! You've got this! 💪
"""

        try:
            # Generate content using the AI model
            ai_response = self.model.generate_content(prompt,chat_history)
            return {
                'message': ai_response.text,
                'agent_used': 'mnemonic_creation',
                'status': 'success'
            }
        except Exception as e:
            print(f"Mnemonic Agent Error: {e}")
            return {
                'message': f"Oh no! My creative spark fizzled out. I ran into an error: {str(e)}",
                'agent_type': 'mnemonic_creation',
                'status': 'error_api_call'
            }