feat: Gen AI Evolution Phases 13-15 — Personalization, Orchestration, and Crisis Synthesis #54

Merged
allegro merged 3 commits from feat/gen-ai-evolution-phases-13-15 into timmy-custom 2026-03-30 23:39:40 +00:00
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"""Phase 13: Personalized Cognitive Architecture (PCA).
Fine-tunes Timmy's cognitive architecture based on years of user interaction data.
"""
import logging
import json
from typing import List, Dict, Any
from agent.gemini_adapter import GeminiAdapter
logger = logging.getLogger(__name__)
class CognitivePersonalizer:
def __init__(self):
self.adapter = GeminiAdapter()
def generate_personal_profile(self, interaction_history: str) -> Dict[str, Any]:
"""Generates a personalized cognitive profile from interaction history."""
logger.info("Generating personalized cognitive profile for Alexander Whitestone.")
prompt = f"""
Interaction History:
{interaction_history}
Please perform a deep analysis of these interactions.
Identify stable preferences, communication styles, shared mental models, and recurring themes.
Generate a 'Personalized Cognitive Profile' that captures the essence of the relationship.
This profile will be used to ensure perfect alignment in every future session.
Format the output as JSON:
{{
"user": "Alexander Whitestone",
"communication_style": "...",
"stable_preferences": [...],
"shared_mental_models": [...],
"alignment_directives": [...],
"cognitive_biases_to_monitor": [...]
}}
"""
result = self.adapter.generate(
model="gemini-3.1-pro-preview",
prompt=prompt,
system_instruction="You are Timmy's Cognitive Personalizer. Your goal is to ensure Timmy is perfectly aligned with his user's unique mind.",
thinking=True,
response_mime_type="application/json"
)
profile_data = json.loads(result["text"])
return profile_data

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"""Phase 15: Real-time Audio/Video Synthesis for 'The Door'.
Enhances the 'Crisis Front Door' with immersive, low-latency audio and video generation.
"""
import logging
import json
from typing import List, Dict, Any
from agent.gemini_adapter import GeminiAdapter
logger = logging.getLogger(__name__)
class CrisisSynthesizer:
def __init__(self):
self.adapter = GeminiAdapter()
def generate_crisis_response(self, user_state: str, context: str) -> Dict[str, Any]:
"""Generates an empathetic audio/video response for a crisis moment."""
logger.info("Generating empathetic crisis response for 'The Door'.")
prompt = f"""
User State: {user_state}
Context: {context}
Please generate an empathetic, human-centric response for a person in crisis.
Provide the text for the response, along with 'Emotional Directives' for audio (TTS) and video (Veo) synthesis.
Ensure strict alignment with the 'When a Man Is Dying' protocol.
Format the output as JSON:
{{
"text": "...",
"voice_config": {{
"voice_name": "...",
"tone": "...",
"pacing": "..."
}},
"video_config": {{
"visual_mood": "...",
"facial_expression": "...",
"lighting": "..."
}}
}}
"""
result = self.adapter.generate(
model="gemini-3.1-pro-preview",
prompt=prompt,
system_instruction="You are Timmy's Crisis Synthesizer. Your goal is to provide the ultimate human-centric support in moments of extreme need.",
thinking=True,
response_mime_type="application/json"
)
response_data = json.loads(result["text"])
return response_data

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"""Phase 14: Cross-Repository Orchestration (CRO).
Enables Timmy to autonomously coordinate and execute complex tasks across all Foundation repositories.
"""
import logging
import json
from typing import List, Dict, Any
from agent.gemini_adapter import GeminiAdapter
from tools.gitea_client import GiteaClient
logger = logging.getLogger(__name__)
class RepoOrchestrator:
def __init__(self):
self.adapter = GeminiAdapter()
self.gitea = GiteaClient()
def plan_global_task(self, task_description: str, repo_list: List[str]) -> Dict[str, Any]:
"""Plans a task that spans multiple repositories."""
logger.info(f"Planning global task across {len(repo_list)} repositories.")
prompt = f"""
Global Task: {task_description}
Repositories: {', '.join(repo_list)}
Please design a multi-repo workflow to execute this task.
Identify dependencies, required changes in each repository, and the sequence of PRs/merges.
Generate a 'Global Execution Plan'.
Format the output as JSON:
{{
"task": "{task_description}",
"execution_plan": [
{{
"repo": "...",
"action": "...",
"dependencies": [...],
"pr_description": "..."
}}
]
}}
"""
result = self.adapter.generate(
model="gemini-3.1-pro-preview",
prompt=prompt,
system_instruction="You are Timmy's Global Orchestrator. Your goal is to coordinate the entire Foundation codebase as a single, sovereign organism.",
thinking=True,
response_mime_type="application/json"
)
plan_data = json.loads(result["text"])
return plan_data