50 lines
1.8 KiB
Python
50 lines
1.8 KiB
Python
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# utils/kindness.py
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import random
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import globals
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from utils.llm import query_ollama # Adjust path as needed
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async def detect_and_react_to_kindness(message, after_reply=False, server_context=None):
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if message.id in globals.kindness_reacted_messages:
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return # Already reacted — skip
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content = message.content.lower()
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emoji = random.choice(globals.HEART_REACTIONS)
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# 1. Keyword-based detection
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if any(keyword in content for keyword in globals.KINDNESS_KEYWORDS):
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try:
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await message.add_reaction(emoji)
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globals.kindness_reacted_messages.add(message.id)
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message.kindness_reacted = True # Mark as done
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print("✅ Kindness detected via keywords. Reacted immediately.")
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except Exception as e:
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print(f"⚠️ Error adding reaction: {e}")
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return
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# 2. If not after_reply, defer model-based check
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if not after_reply:
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print("🗝️ No kindness via keywords. Deferring...")
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return
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# 3. Model-based detection
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try:
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prompt = (
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"The following message was sent to Miku the bot. "
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"Does it sound like the user is being explicitly kind or affectionate toward Miku? "
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"Answer with 'yes' or 'no' only.\n\n"
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f"Message: \"{message.content}\""
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)
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result = await query_ollama(prompt, user_id="kindness-check", guild_id=None, response_type="dm_response")
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if result.strip().lower().startswith("yes"):
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await message.add_reaction(emoji)
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globals.kindness_reacted_messages.add(message.id)
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print("✅ Kindness detected via model. Reacted.")
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else:
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print("🧊 No kindness detected.")
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except Exception as e:
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print(f"⚠️ Error during kindness analysis: {e}")
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