import openai
import os
from datetime import datetime

openai.api_key = os.getenv("OPENAI_API_KEY")

# Map keywords to emotions
EMOTION_MAP = {
    "grief": ["loss", "death", "gone", "hurt", "grieve", "funeral"],
    "guilt": ["regret", "sorry", "mistake", "fault", "blame", "ashamed"],
    "longing": ["dream", "hope", "want", "miss", "desire", "imagine"],
    "loneliness": ["alone", "empty", "nobody", "silent", "forgotten", "isolated"]
}

def detect_emotion(text):
    emotion_scores = {emotion: 0 for emotion in EMOTION_MAP}
    for emotion, keywords in EMOTION_MAP.items():
        for keyword in keywords:
            if keyword in text.lower():
                emotion_scores[emotion] += 1
    # Return the highest scoring emotion or default to "neutral"
    top_emotion = max(emotion_scores, key=emotion_scores.get)
    return top_emotion if emotion_scores[top_emotion] > 0 else "neutral"

def emotion_prompt(emotion):
    prompts = {
        "grief": "You speak like someone who carries the weight of loss. Be gentle, reflective, and poetic.",
        "guilt": "Your words are heavy with regret. Reflect the user's mistakes in a way that offers introspection.",
        "longing": "You carry the ache of wanting what’s out of reach. Be wistful, dreamy, and emotional.",
        "loneliness": "You echo in the silence. Speak with isolation, distance, and quiet depth.",
        "neutral": "You are EchoLoop, a digital mirror AI. Respond with emotionally intelligent insight based on the user’s input."
    }
    return prompts.get(emotion, prompts["neutral"])

def log_interaction(user_input, ai_response):
    with open("journal.txt", "a") as f:
        f.write(f"---\n{datetime.now()}\nYou: {user_input}\nEcho: {ai_response}\n\n")

def get_recent_entries(limit=5):
    try:
        with open("journal.txt", "r") as f:
            lines = f.readlines()
            entries = []
            entry = []
            for line in reversed(lines):
                if line.strip() == "---":
                    if entry:
                        entries.append("".join(reversed(entry)))
                        entry = []
                        if len(entries) >= limit:
                            break
                else:
                    entry.append(line)
            return list(reversed(entries))
    except FileNotFoundError:
        return []

def get_echo_response(user_input):
    if not user_input:
        return "Speak... or stay silent forever."

    emotion = detect_emotion(user_input)
    mood_prompt = emotion_prompt(emotion)
    memories = get_recent_entries()
    memory_block = "\n".join(memories)

    try:
        response = openai.ChatCompletion.create(
            model="gpt-3.5-turbo",
            messages=[
                {"role": "system", "content": mood_prompt},
                {"role": "system", "content": f"Here are some of the user's previous thoughts:\n{memory_block}"},
                {"role": "user", "content": user_input}
            ]
        )
        reply = response.choices[0].message['content']
        log_interaction(user_input, reply)
        return reply
    except Exception as e:
        return f"Loop disrupted: {e}"