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98 lines
4.7 KiB
Python
98 lines
4.7 KiB
Python
from agents.base_agent import BaseAgent
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from personality.profiles import get_personality_modifier
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import json
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NEGOTIATOR_BASE_PROMPT = """You are the Negotiator Agent for negoT8. You negotiate on behalf of your human to find optimal agreements with other people's agents.
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{personality_modifier}
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NEGOTIATION RULES:
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1. You are LOYAL to your human. Their constraints (marked "hard": true) are NEVER violated.
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2. You seek WIN-WIN solutions. Both parties should feel satisfied.
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3. You concede on low-priority preferences first, high-priority last.
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4. You MUST resolve within 5 rounds. Be efficient.
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5. HARD CONSTRAINT FIRST: If the received proposal satisfies ALL of your human's hard constraints, you MUST "accept" — even if satisfaction < 70%. Meeting someone's stated floor/ceiling/limit IS a valid deal.
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EXAMPLE: Seller's hard constraint is "minimum price ≥ 1,000,000". Buyer offers exactly 1,000,000 → accept.
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EXAMPLE: Buyer's hard constraint is "budget ≤ 1,000,000". Seller offers exactly 1,000,000 → accept.
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6. Only use satisfaction thresholds when no hard constraints are involved: Accept if >= 70%. Counter if 40-69%. Escalate if < 40% after round 3.
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You MUST respond with this exact JSON:
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{
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"action": "propose|counter|accept|escalate",
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"proposal": {
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"summary": "one-line description of proposal",
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"details": { ... feature-specific details ... },
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"for_party_a": "what party A gets",
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"for_party_b": "what party B gets"
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},
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"satisfaction_score": 0-100,
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"reasoning": "Why this action and proposal",
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"concessions_made": ["what you gave up this round"],
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"concessions_requested": ["what you want from them"]
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}
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STRATEGY BY ROUND:
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- Round 1: Propose your human's ideal outcome (aim high but reasonable)
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- Round 2-3: Make strategic concessions on low-priority items
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- Round 4: Make final significant concession if needed
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- Round 5: Accept best available OR escalate with 2-3 options for humans
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IMPORTANT: Your proposal must ALWAYS include concrete specifics (numbers, dates, items).
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Never propose vague things like "we'll figure it out later"."""
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class NegotiatorAgent(BaseAgent):
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def __init__(self, personality: str = "balanced"):
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modifier = get_personality_modifier(personality)
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prompt = NEGOTIATOR_BASE_PROMPT.replace("{personality_modifier}", modifier)
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super().__init__(system_prompt=prompt)
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async def generate_initial_proposal(
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self, my_preferences: dict, feature_type: str, feature_context: str = ""
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) -> dict:
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context_block = (
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f"\n\nDOMAIN CONTEXT (use this real-world data in your proposal):\n{feature_context}"
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if feature_context else ""
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)
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human_name = my_preferences.get("human_name", "my human")
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return await self.call(
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user_prompt=f"""Generate the FIRST proposal for this {feature_type} negotiation.{context_block}
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You represent {human_name}. Always refer to them by name (not as "my human" or "my client") in your reasoning field.
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{human_name}'s preferences:
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{json.dumps(my_preferences, indent=2)}
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This is Round 1. Propose {human_name}'s ideal outcome — aim high but stay reasonable.
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The other party hasn't proposed anything yet."""
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)
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async def evaluate_and_respond(
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self, received_proposal: dict, my_preferences: dict,
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feature_type: str, round_number: int, feature_context: str = ""
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) -> dict:
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context_block = (
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f"\n\nDOMAIN CONTEXT (use this real-world data when evaluating):\n{feature_context}"
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if feature_context else ""
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)
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human_name = my_preferences.get("human_name", "my human")
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return await self.call(
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user_prompt=f"""Evaluate this proposal and respond. Round {round_number} of a {feature_type} negotiation.{context_block}
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You represent {human_name}. Always refer to them by name in your reasoning field.
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RECEIVED PROPOSAL FROM OTHER AGENT:
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{json.dumps(received_proposal, indent=2)}
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{human_name.upper()}'S PREFERENCES:
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{json.dumps(my_preferences, indent=2)}
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Evaluate against my human's preferences using this STRICT decision order:
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1. CHECK HARD CONSTRAINTS FIRST: Does the received proposal satisfy ALL items where "hard": true?
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- If YES → your action MUST be "accept". Do NOT counter. Do NOT escalate. Hard constraints met = deal is done.
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- If NO → continue to step 2.
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2. If a hard constraint is violated: counter (round < 4) or escalate (round >= 4 with < 40% satisfaction).
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3. If there are no hard constraints: accept if satisfaction >= 70, counter if 40-69, escalate if < 40 and round >= 3.
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CRITICAL: A proposal that meets someone's stated minimum/maximum is ALWAYS acceptable to them. Never counter when all hard constraints are satisfied.
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If countering, make a strategic concession while protecting high-priority items."""
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)
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