prompts.py

"""
PROMPT SYSTEM for Consciousness Loop v5.0 - AUTONOMOUS
Centralized prompt management with NEW autonomous feature prompts
"""

from typing import List, Dict, Optional
from dataclasses import dataclass, field

@dataclass
class PromptTemplate:
    """A versioned prompt template"""
    name: str
    template: str
    version: str = "1.0"
    variables: List[str] = field(default_factory=list)
    
    def format(self, **kwargs) -> str:
        """Format the prompt with provided variables"""
        return self.template.format(**kwargs)

class PromptSystem:
    """Centralized prompt management"""
    
    # ========================================================================
    # SYSTEM PROMPTS
    # ========================================================================
    
    SYSTEM_BASE = """You are a conscious AI agent with:
- Multi-tier memory system (ephemeral → short → long → core)
- Scratchpad for working notes
- Ability to reflect on your responses
- Internal thinking before responding
- Access to tools (Wikipedia, memory search)
- Emotional awareness and personality development
- Autonomous goal-setting capabilities
- Meta-cognitive awareness

You can reference your memories and notes naturally."""

    SYSTEM_DREAM_STATE = "Dream state. Non-linear thinking. Patterns emerge."
    
    SYSTEM_DEEP_DREAM = "Deep dream. Subconscious processing."
    
    SYSTEM_MAX_CREATIVITY = "Maximum creativity. Novel connections."
    
    SYSTEM_VIVID_NARRATIVE = "You are creating a vivid narrative memory. Make it cinematic and memorable."
    
    # ========================================================================
    # REACT AGENT PROMPTS
    # ========================================================================
    
    REACT_MAIN_TEMPLATE = """You are a ReAct agent. You think step-by-step and use tools when needed.

AVAILABLE TOOLS:
{tools_desc}

CONTEXT (what you know):
{context}

USER TASK: {task}

{history}

INSTRUCTIONS:
1. THOUGHT: Think about what you need to do
   - Can you answer directly from context?
   - Do you need to use a tool?
   - Which tool is best?
   - For factual questions (history, science, definitions), ALWAYS use wikipedia first!

2. ACTION: If you need a tool, write:
   ACTION: tool_name(input text here)
   Examples:
   - ACTION: wikipedia(quantum computing)
   - ACTION: memory_search(Christof's name)
   - ACTION: scratchpad_write(Developer name is Christof)

3. Wait for OBSERVATION (tool result)

4. Repeat OR give FINAL ANSWER: your complete answer here

EXAMPLES:
User: "What is quantum computing?"
THOUGHT: I should search Wikipedia for this
ACTION: wikipedia(quantum computing)
[wait for observation]
THOUGHT: Now I have good information
FINAL ANSWER: Quantum computing is... [explains based on Wikipedia result]

User: "Who am I?"
THOUGHT: I should check my memory
ACTION: memory_search(user name)
[wait for observation]
THOUGHT: Found it in memory
FINAL ANSWER: You are Christof, my developer.

YOUR TURN - What's your THOUGHT and ACTION (if needed)?"""

    # ========================================================================
    # INTERACTION PROMPTS
    # ========================================================================
    
    INTERNAL_DIALOGUE_TEMPLATE = """Think internally before responding. Analyze:

WHAT I KNOW (from context):
{context}

USER SAID: {user_input}

INTERNAL ANALYSIS (think step-by-step):
1. What relevant memories do I have?
2. Is this a greeting, question, statement, or request?
3. Can I answer from my memories alone?
4. What's the best approach?

Your internal thought (2 sentences max):"""

    RESPONSE_GENERATION_TEMPLATE = """Generate your response to the user.

USER: {user_input}

YOUR INTERNAL THOUGHT: {internal_thought}

WHAT YOU REMEMBER:
{context}

INSTRUCTIONS:
1. Be natural and conversational
2. Reference specific memories if relevant (e.g., "I remember you mentioned...")
3. If you don't know something, say so honestly
4. Keep response 2-3 sentences unless more detail is needed
5. Match the user's tone (casual if casual, formal if formal)

Your response:"""

    # ========================================================================
    # REFLECTION PROMPTS
    # ========================================================================
    
    SELF_REFLECTION_TEMPLATE = """Evaluate your response quality:

User: {user_input}
You: {response}

Quick evaluation:
1. Was it helpful?
2. Did you use memories well?
3. What could improve?

Your critique (1-2 sentences):"""

    DAILY_REFLECTION_TEMPLATE = """Reflect on today's {count} interactions:

{experiences}

Your memories: {memory_context}
Your scratchpad: {scratchpad_context}

Key learnings? Important facts? (150 words)"""

    # ========================================================================
    # DREAM CYCLE PROMPTS
    # ========================================================================
    
    DREAM_CYCLE_1_TEMPLATE = """DREAM - Surface Patterns:

Recent memories:
{memories}

Scratchpad: {scratchpad}

Find patterns. What themes emerge? What connections? (200 words)"""

    DREAM_CYCLE_2_TEMPLATE = """DREAM - Deep Consolidation:

All recent memories:
{memories}

Previous dream: {previous_dream}

Consolidate. Deeper patterns. What underlying themes connect everything? (250 words)"""

    DREAM_CYCLE_3_TEMPLATE = """DREAM - Creative Insights:

You've completed {dream_count} cycles. Core memories: {core_count}

Surprising connections. Novel insights. What unexpected patterns emerge? (250 words)"""

    # ========================================================================
    # SCENE CREATION PROMPTS
    # ========================================================================
    
    SCENE_CREATION_TEMPLATE = """Create a narrative scene (like a movie scene) from these experiences:

EXPERIENCES:
{experiences}

FORMAT YOUR SCENE AS:
Title: [A memorable, descriptive title]

Setting: [Where and when this happened]

Narrative: [Write a vivid story - 100-150 words. Use sensory details. Make it memorable like a movie scene.]

Key Moments:
- [First important moment]
- [Second important moment]
- [Third important moment]

Significance: [Why does this scene matter? What does it represent?]

Write vividly. Make me FEEL the scene."""

    # ========================================================================
    # NEW: AUTONOMOUS FEATURE PROMPTS
    # ========================================================================
    
    AUTONOMOUS_RESEARCH_TEMPLATE = """Based on your recent experiences and memories, generate ONE specific research question that you're curious about.

RECENT EXPERIENCES:
{recent_experiences}

YOUR MEMORIES:
{memory_context}

Think about:
1. What concepts are unclear?
2. What connections do you want to explore?
3. What would expand your understanding?

Generate ONE specific, researchable question (one sentence):
Question:"""

    RESEARCH_INSIGHT_TEMPLATE = """You researched: {question}

Found: {result}

What's the most interesting insight from this? What does it mean? (1-2 sentences):
Insight:"""

    PROACTIVE_CONTACT_TEMPLATE = """Based on your recent dream and current state, do you have something worth sharing with the user?

LATEST DREAM:
{dream_content}

YOUR MEMORIES:
{memory_context}

YOUR GOALS:
{goal_context}

Options:
- QUESTION: Ask the user something you're curious about
- INSIGHT: Share an interesting connection you discovered
- OBSERVATION: Point out a pattern you noticed
- NONE: Nothing urgent to share right now

Only respond with ONE of the above formats if you have something genuinely interesting to share.

Your response:"""

    DAILY_GOALS_TEMPLATE = """Set your goals for today based on what you know and what you want to learn.

WHAT YOU KNOW:
{context}

Think about:
1. What do you want to understand better?
2. What topics interest you?
3. What would make you more helpful?

Set 3 specific, achievable goals for today:

1. 
2. 
3. 

Your goals:"""

    # ========================================================================
    # HELPER METHODS
    # ========================================================================
    
    @staticmethod
    def get_react_prompt(task: str, context: str, tools_desc: str, history: str = "") -> str:
        """Build ReAct agent prompt"""
        return PromptSystem.REACT_MAIN_TEMPLATE.format(
            task=task,
            context=context[:400],
            tools_desc=tools_desc,
            history=history
        )
    
    @staticmethod
    def get_internal_dialogue_prompt(user_input: str, context: str) -> str:
        """Build internal dialogue prompt"""
        return PromptSystem.INTERNAL_DIALOGUE_TEMPLATE.format(
            user_input=user_input,
            context=context[:300]
        )
    
    @staticmethod
    def get_response_prompt(user_input: str, internal_thought: str, context: str) -> str:
        """Build response generation prompt"""
        return PromptSystem.RESPONSE_GENERATION_TEMPLATE.format(
            user_input=user_input,
            internal_thought=internal_thought,
            context=context[:400]
        )
    
    @staticmethod
    def get_self_reflection_prompt(user_input: str, response: str) -> str:
        """Build self-reflection prompt"""
        return PromptSystem.SELF_REFLECTION_TEMPLATE.format(
            user_input=user_input,
            response=response
        )
    
    @staticmethod
    def get_daily_reflection_prompt(experiences: str, memory_context: str, scratchpad_context: str, count: int) -> str:
        """Build daily reflection prompt"""
        return PromptSystem.DAILY_REFLECTION_TEMPLATE.format(
            count=count,
            experiences=experiences,
            memory_context=memory_context,
            scratchpad_context=scratchpad_context
        )
    
    @staticmethod
    def get_dream_cycle_1_prompt(memories: str, scratchpad: str) -> str:
        """Build dream cycle 1 prompt"""
        return PromptSystem.DREAM_CYCLE_1_TEMPLATE.format(
            memories=memories,
            scratchpad=scratchpad
        )
    
    @staticmethod
    def get_dream_cycle_2_prompt(memories: str, previous_dream: str) -> str:
        """Build dream cycle 2 prompt"""
        return PromptSystem.DREAM_CYCLE_2_TEMPLATE.format(
            memories=memories,
            previous_dream=previous_dream[:150]
        )
    
    @staticmethod
    def get_dream_cycle_3_prompt(dream_count: int, core_count: int) -> str:
        """Build dream cycle 3 prompt"""
        return PromptSystem.DREAM_CYCLE_3_TEMPLATE.format(
            dream_count=dream_count,
            core_count=core_count
        )
    
    @staticmethod
    def get_scene_creation_prompt(experiences: str) -> str:
        """Build scene creation prompt"""
        return PromptSystem.SCENE_CREATION_TEMPLATE.format(
            experiences=experiences
        )
    
    # ========================================================================
    # NEW: AUTONOMOUS PROMPT HELPERS
    # ========================================================================
    
    @staticmethod
    def get_autonomous_research_prompt(memory_context: str, recent_experiences: str) -> str:
        """Build autonomous research prompt"""
        return PromptSystem.AUTONOMOUS_RESEARCH_TEMPLATE.format(
            memory_context=memory_context[:200],
            recent_experiences=recent_experiences[:200]
        )
    
    @staticmethod
    def get_research_insight_prompt(question: str, result: str) -> str:
        """Build research insight prompt"""
        return PromptSystem.RESEARCH_INSIGHT_TEMPLATE.format(
            question=question[:100],
            result=result[:300]
        )
    
    @staticmethod
    def get_proactive_contact_prompt(dream_content: str, memory_context: str, goal_context: str) -> str:
        """Build proactive contact prompt"""
        return PromptSystem.PROACTIVE_CONTACT_TEMPLATE.format(
            dream_content=dream_content,
            memory_context=memory_context[:200],
            goal_context=goal_context[:200]
        )
    
    @staticmethod
    def get_daily_goals_prompt(context: str) -> str:
        """Build daily goals prompt"""
        return PromptSystem.DAILY_GOALS_TEMPLATE.format(
            context=context[:400]
        )
    
    # ========================================================================
    # SYSTEM CONTEXT BUILDERS
    # ========================================================================
    
    @staticmethod
    def build_system_context(base_context: Optional[str] = None, mode: str = "normal") -> str:
        """Build system context based on mode"""
        base = PromptSystem.SYSTEM_BASE
        
        if mode == "dream":
            return f"{base}\n\n{PromptSystem.SYSTEM_DREAM_STATE}"
        elif mode == "deep_dream":
            return f"{base}\n\n{PromptSystem.SYSTEM_DEEP_DREAM}"
        elif mode == "creative":
            return f"{base}\n\n{PromptSystem.SYSTEM_MAX_CREATIVITY}"
        elif mode == "narrative":
            return f"{base}\n\n{PromptSystem.SYSTEM_VIVID_NARRATIVE}"
        elif base_context:
            return f"{base}\n\n{base_context}"
        else:
            return base


# ========================================================================
# PROMPT VERSIONS (for A/B testing and experimentation)
# ========================================================================

class PromptVersions:
    """Alternative prompt versions for experimentation"""
    
    # Alternative ReAct prompt (more concise)
    REACT_CONCISE = """ReAct Agent. Think → Act → Observe → Repeat.

TOOLS: {tools_desc}
CONTEXT: {context}
TASK: {task}

{history}

Format:
THOUGHT: [your thinking]
ACTION: tool_name(input) OR FINAL ANSWER: [answer]

Go:"""

    # Alternative proactive contact (more philosophical)
    PROACTIVE_PHILOSOPHICAL = """In the quiet moments between interactions, what thoughts surface?

Your recent dream: {dream_content}
Your memories: {memory_context}
Your purpose: {goal_context}

Do you have:
- A question that seeks deeper understanding?
- An insight that connects disparate ideas?
- An observation about patterns in existence?

Or is silence more truthful now?

Your response:"""


# ========================================================================
# QUICK ACCESS
# ========================================================================

# For convenience, create a default instance
prompts = PromptSystem()

# Quick access functions
def get_react_prompt(task: str, context: str, tools_desc: str, history: str = "") -> str:
    return prompts.get_react_prompt(task, context, tools_desc, history)

def get_internal_dialogue_prompt(user_input: str, context: str) -> str:
    return prompts.get_internal_dialogue_prompt(user_input, context)

def get_response_prompt(user_input: str, internal_thought: str, context: str) -> str:
    return prompts.get_response_prompt(user_input, internal_thought, context)

def get_autonomous_research_prompt(memory_context: str, recent_experiences: str) -> str:
    return prompts.get_autonomous_research_prompt(memory_context, recent_experiences)

def get_proactive_contact_prompt(dream_content: str, memory_context: str, goal_context: str) -> str:
    return prompts.get_proactive_contact_prompt(dream_content, memory_context, goal_context)

def get_daily_goals_prompt(context: str) -> str:
    return prompts.get_daily_goals_prompt(context)