Initial commit: NexusOS project + desktop theme baseline
Captures the known-good state after theme consolidation and consistency reconciliation: - NexusOS GTK/xfwm4/icon theme assets (assets/themes, management/Mint-Y-Nexus) - Tightened right-click menus, visible separators, no menu icons - assets/themes/install-theme.sh: idempotent restore of all wiring (symlinks, xfconf xsettings+xfwm4, GTK 3/4 settings.ini) - .gitignore excludes venv/ollama/models/runtime/db Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
jon
@@ -0,0 +1,94 @@
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"""Memory extraction — asks Mistral to evaluate a conversation exchange and
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decide if it contains a new permanent personal fact worth saving."""
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from __future__ import annotations
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import json
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import logging
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import re
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from typing import Optional
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_log = logging.getLogger(__name__)
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_PROMPT = """\
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You are a memory curator for a personal AI assistant named Nexus.
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A conversation just occurred. Decide if the USER revealed a NEW, PERMANENT \
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personal fact that should be saved to long-term memory.
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SAVE ONLY facts that are stable and biographical:
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- Identity: full name, age, location, nationality
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- Possessions: vehicle, home, devices
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- Relationships: family members, partner, close friends
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- Career: job title, employer, field, skills
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- Long-running projects or goals (not today's to-dos)
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- Durable preferences or habits explicitly stated
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DO NOT SAVE — these are ephemeral and would clutter memory:
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- Anything time-bound: "today I have...", "I'm working on X today", "I have a full day of work"
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- Mood or energy: "I'm tired", "feeling good", "having a rough day"
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- Greetings or small talk: "good morning", "how are you"
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- Questions the user asked the assistant
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- Near-duplicates of anything in the existing memory list below
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Existing memory (do not re-save these or close variants):
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{existing_texts}
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---
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USER: {user_message}
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ASSISTANT: {assistant_response}
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---
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Respond with JSON only — no prose, no markdown fences:
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{{"save": true, "section": "<section name, or one from the list above>", "text": "<concise fact about Jon, third person>"}}
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OR
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{{"save": false}}"""
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async def extract_memory(
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user_message: str,
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assistant_response: str,
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existing_sections: list[str],
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existing_texts: list[str],
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ollama_manager,
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) -> Optional[dict]:
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"""Ask Mistral to extract a saveable memory fact from a conversation exchange.
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Returns {"section": ..., "text": ...} or None.
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"""
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if existing_texts:
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texts_block = "\n".join(f"- {t}" for t in existing_texts[:40])
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else:
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texts_block = "(none yet)"
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prompt = _PROMPT.format(
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existing_texts=texts_block,
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user_message=user_message[:800],
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assistant_response=assistant_response[:800],
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)
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try:
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response = await ollama_manager.chat(
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messages=[{"role": "user", "content": prompt}],
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model="mistral:latest",
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stream=False,
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temperature=0.0,
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)
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if not response:
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return None
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text = response.strip()
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# Strip markdown code fences if the model added them
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if "```" in text:
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m = re.search(r"```(?:json)?\s*(.*?)\s*```", text, re.DOTALL)
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if m:
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text = m.group(1).strip()
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data = json.loads(text)
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if data.get("save") and data.get("section") and data.get("text"):
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return {
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"section": str(data["section"]).strip(),
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"text": str(data["text"]).strip(),
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}
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except Exception as e:
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_log.debug("memory extraction failed: %s", e)
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return None
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@@ -0,0 +1,125 @@
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"""Dedicated memory curator service — run alongside Synapse on port 8001.
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Endpoints:
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GET / health check
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GET /memories list all memory items (optional ?section= filter)
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POST /memories direct write — no LLM, saves immediately
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PATCH /memories/{id} update a memory item
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DELETE /memories/{id} delete a memory item
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POST /memories/extract LLM-curated: evaluate a conversation exchange and
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optionally save a new permanent fact
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"""
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from __future__ import annotations
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import asyncio
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import uuid
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from typing import Any, Dict, List, Optional
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from fastapi import FastAPI, HTTPException, Body
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from .store import store, MemoryItem
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from .extractor import extract_memory
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from ..ollama_manager import get_ollama_manager
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app = FastAPI(title="Nexus Memory Service", version="1.0")
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=False,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.get("/")
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async def health():
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return {"status": "ok", "count": len(store.all())}
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@app.get("/memories")
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async def list_memories(section: Optional[str] = None):
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items = store.all()
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if section:
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items = [i for i in items if i.section.lower() == section.lower()]
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return {"items": [{"id": i.id, "section": i.section, "text": i.text, "tags": i.tags} for i in items]}
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@app.post("/memories")
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async def add_memory(payload: Dict[str, Any] = Body(...)):
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text = (payload.get("text") or "").strip()
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if not text:
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raise HTTPException(status_code=400, detail="Missing 'text'")
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item = MemoryItem(
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id=str(uuid.uuid4()),
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section=(payload.get("section") or "General").strip(),
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text=text,
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tags=payload.get("tags", []),
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)
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store.add(item)
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return {"id": item.id, "section": item.section, "text": item.text, "tags": item.tags}
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@app.patch("/memories/{item_id}")
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async def update_memory(item_id: str, payload: Dict[str, Any] = Body(...)):
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existing = store.get(item_id)
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if not existing:
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raise HTTPException(status_code=404, detail="Not found")
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updated = MemoryItem(
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id=item_id,
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section=(payload.get("section") or existing.section).strip(),
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text=(payload.get("text") or existing.text).strip(),
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tags=payload.get("tags", existing.tags),
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)
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store.update(updated)
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return {"id": updated.id, "section": updated.section, "text": updated.text, "tags": updated.tags}
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@app.delete("/memories/{item_id}")
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async def delete_memory(item_id: str):
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if not store.get(item_id):
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raise HTTPException(status_code=404, detail="Not found")
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store.delete(item_id)
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return {"status": "deleted"}
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class ExtractRequest(BaseModel):
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user_message: str
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assistant_response: str
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@app.post("/memories/extract")
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async def extract_and_save(req: ExtractRequest):
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"""LLM-curated extraction — asks Mistral to evaluate the exchange against all
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existing memory items and save only new, permanent personal facts."""
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existing = store.all()
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existing_sections = list({i.section for i in existing})
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existing_texts = [i.text for i in existing]
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try:
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result = await asyncio.wait_for(
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extract_memory(
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req.user_message,
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req.assistant_response,
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existing_sections,
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existing_texts,
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get_ollama_manager(),
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),
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timeout=20.0,
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)
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if result:
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item = MemoryItem(
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id=str(uuid.uuid4()),
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section=result["section"],
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text=result["text"],
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)
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store.add(item)
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return {"saved": True, "id": item.id, "section": item.section, "text": item.text}
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except asyncio.TimeoutError:
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pass
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except Exception:
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pass
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return {"saved": False}
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@@ -0,0 +1,380 @@
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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from pydantic import BaseModel
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import sqlite3
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import json
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import os
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import time
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# -----------------------------
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# Models
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# -----------------------------
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class MemoryItem(BaseModel):
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id: str
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section: str = "General"
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text: str
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tags: List[str] = []
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class MessageItem(BaseModel):
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role: str # "user" or "assistant"
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content: str
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timestamp: float
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model: Optional[str] = None
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tokens: Optional[int] = None
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class ConversationItem(BaseModel):
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id: str
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messages: List[MessageItem] = []
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created_at: float
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updated_at: float
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@property
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def preview(self) -> str:
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for msg in self.messages:
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if msg.role == "user":
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return msg.content[:80]
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return "Empty conversation"
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@property
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def timestamp(self) -> float:
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return self.created_at
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# -----------------------------
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# Persistent Store
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# -----------------------------
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class PersistentMemoryStore:
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def __init__(self, db_path: Path):
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self.db_path = db_path
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os.makedirs(self.db_path.parent, exist_ok=True)
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self._ensure_tables()
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self._cache: Dict[str, MemoryItem] = self._load_all_memory()
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# -----------------------------
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# Internal helpers
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# -----------------------------
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def _connect(self):
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conn = sqlite3.connect(self.db_path)
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conn.row_factory = sqlite3.Row
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conn.execute("PRAGMA journal_mode=WAL;")
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return conn
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def _ensure_tables(self):
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conn = self._connect()
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cur = conn.cursor()
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cur.execute("""
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CREATE TABLE IF NOT EXISTS memory (
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id TEXT PRIMARY KEY,
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section TEXT NOT NULL DEFAULT 'General',
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text TEXT NOT NULL,
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tags TEXT
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)
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""")
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# Migrate: add section column if it doesn't exist yet
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try:
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cur.execute("ALTER TABLE memory ADD COLUMN section TEXT NOT NULL DEFAULT 'General'")
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except Exception:
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pass
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cur.execute("""
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CREATE TABLE IF NOT EXISTS conversations (
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id TEXT PRIMARY KEY,
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created_at REAL NOT NULL,
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updated_at REAL NOT NULL
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)
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""")
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cur.execute("""
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CREATE TABLE IF NOT EXISTS messages (
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id INTEGER PRIMARY KEY AUTOINCREMENT,
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conversation_id TEXT NOT NULL,
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role TEXT NOT NULL,
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content TEXT NOT NULL,
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timestamp REAL NOT NULL,
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model TEXT,
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tokens INTEGER,
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FOREIGN KEY (conversation_id) REFERENCES conversations(id)
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)
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""")
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for col, typedef in (("model", "TEXT"), ("tokens", "INTEGER")):
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try:
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cur.execute(f"ALTER TABLE messages ADD COLUMN {col} {typedef}")
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except Exception:
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pass
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cur.execute("""
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CREATE INDEX IF NOT EXISTS idx_messages_conversation_id
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ON messages (conversation_id)
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""")
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cur.execute("""
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CREATE TABLE IF NOT EXISTS settings (
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key TEXT PRIMARY KEY,
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value TEXT NOT NULL
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)
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""")
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conn.commit()
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conn.close()
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# -----------------------------
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# Loaders
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# -----------------------------
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def _load_all_memory(self) -> Dict[str, MemoryItem]:
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conn = self._connect()
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cur = conn.cursor()
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cur.execute("SELECT id, section, text, tags FROM memory")
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rows = cur.fetchall()
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conn.close()
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cache = {}
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for row in rows:
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try:
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tags = json.loads(row["tags"]) if row["tags"] else []
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except Exception:
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tags = []
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cache[row["id"]] = MemoryItem(
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id=row["id"],
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section=row["section"] or "General",
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text=row["text"],
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tags=tags,
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)
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return cache
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# -----------------------------
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# Memory API
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# -----------------------------
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def add(self, item: MemoryItem):
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self._cache[item.id] = item
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conn = self._connect()
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try:
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cur = conn.cursor()
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cur.execute(
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"INSERT OR REPLACE INTO memory (id, section, text, tags) VALUES (?, ?, ?, ?)",
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(item.id, item.section or "General", item.text, json.dumps(item.tags))
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)
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conn.commit()
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finally:
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conn.close()
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||||
|
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def update(self, item: MemoryItem):
|
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self.add(item)
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|
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def delete(self, item_id: str):
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self._cache.pop(item_id, None)
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conn = self._connect()
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try:
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cur = conn.cursor()
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cur.execute("DELETE FROM memory WHERE id = ?", (item_id,))
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conn.commit()
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finally:
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conn.close()
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def get(self, item_id: str) -> Optional[MemoryItem]:
|
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return self._cache.get(item_id)
|
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|
||||
def all(self) -> List[MemoryItem]:
|
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return list(self._cache.values())
|
||||
|
||||
# -----------------------------
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||||
# Conversation API
|
||||
# -----------------------------
|
||||
def create_conversation(self, conversation_id: str) -> ConversationItem:
|
||||
now = time.time()
|
||||
conn = self._connect()
|
||||
try:
|
||||
cur = conn.cursor()
|
||||
cur.execute(
|
||||
"INSERT OR IGNORE INTO conversations (id, created_at, updated_at) VALUES (?, ?, ?)",
|
||||
(conversation_id, now, now)
|
||||
)
|
||||
conn.commit()
|
||||
finally:
|
||||
conn.close()
|
||||
return ConversationItem(id=conversation_id, created_at=now, updated_at=now)
|
||||
|
||||
def add_message(self, conversation_id: str, role: str, content: str, model: str = None, tokens: int = None):
|
||||
now = time.time()
|
||||
conn = self._connect()
|
||||
try:
|
||||
cur = conn.cursor()
|
||||
cur.execute(
|
||||
"INSERT INTO messages (conversation_id, role, content, timestamp, model, tokens) VALUES (?, ?, ?, ?, ?, ?)",
|
||||
(conversation_id, role, content, now, model, tokens)
|
||||
)
|
||||
cur.execute(
|
||||
"UPDATE conversations SET updated_at = ? WHERE id = ?",
|
||||
(now, conversation_id)
|
||||
)
|
||||
conn.commit()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
def get_conversation(self, conversation_id: str) -> Optional[ConversationItem]:
|
||||
conn = self._connect()
|
||||
cur = conn.cursor()
|
||||
cur.execute("SELECT * FROM conversations WHERE id = ?", (conversation_id,))
|
||||
row = cur.fetchone()
|
||||
if not row:
|
||||
conn.close()
|
||||
return None
|
||||
cur.execute(
|
||||
"SELECT role, content, timestamp, model, tokens FROM messages WHERE conversation_id = ? ORDER BY timestamp ASC",
|
||||
(conversation_id,)
|
||||
)
|
||||
msg_rows = cur.fetchall()
|
||||
conn.close()
|
||||
|
||||
messages = [MessageItem(role=r["role"], content=r["content"], timestamp=r["timestamp"], model=r["model"], tokens=r["tokens"]) for r in msg_rows]
|
||||
return ConversationItem(
|
||||
id=row["id"],
|
||||
messages=messages,
|
||||
created_at=row["created_at"],
|
||||
updated_at=row["updated_at"]
|
||||
)
|
||||
|
||||
def all_conversations(self) -> List[ConversationItem]:
|
||||
conn = self._connect()
|
||||
cur = conn.cursor()
|
||||
cur.execute("""
|
||||
SELECT c.id, c.created_at, c.updated_at,
|
||||
m.role, m.content, m.timestamp, m.model, m.tokens
|
||||
FROM conversations c
|
||||
LEFT JOIN messages m ON m.conversation_id = c.id
|
||||
ORDER BY c.updated_at DESC, m.timestamp ASC
|
||||
""")
|
||||
rows = cur.fetchall()
|
||||
conn.close()
|
||||
|
||||
convs: Dict[str, ConversationItem] = {}
|
||||
order: list[str] = []
|
||||
for row in rows:
|
||||
cid = row["id"]
|
||||
if cid not in convs:
|
||||
convs[cid] = ConversationItem(
|
||||
id=cid,
|
||||
created_at=row["created_at"],
|
||||
updated_at=row["updated_at"],
|
||||
)
|
||||
order.append(cid)
|
||||
if row["role"] is not None:
|
||||
convs[cid].messages.append(
|
||||
MessageItem(role=row["role"], content=row["content"], timestamp=row["timestamp"], model=row["model"], tokens=row["tokens"])
|
||||
)
|
||||
return [convs[cid] for cid in order]
|
||||
|
||||
def delete_conversation(self, conversation_id: str):
|
||||
conn = self._connect()
|
||||
try:
|
||||
cur = conn.cursor()
|
||||
cur.execute("DELETE FROM messages WHERE conversation_id = ?", (conversation_id,))
|
||||
cur.execute("DELETE FROM conversations WHERE id = ?", (conversation_id,))
|
||||
conn.commit()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
# -----------------------------
|
||||
# Search API
|
||||
# -----------------------------
|
||||
def search_conversations(self, query: str, limit: int = 3) -> List[dict]:
|
||||
"""Return up to `limit` conversations that contain the query string,
|
||||
with full user+assistant exchange pairs around each match."""
|
||||
if not query or not query.strip():
|
||||
return []
|
||||
q = query.strip().lower()
|
||||
conn = self._connect()
|
||||
cur = conn.cursor()
|
||||
cur.execute("""
|
||||
SELECT DISTINCT c.id, c.created_at, c.updated_at
|
||||
FROM conversations c
|
||||
JOIN messages m ON m.conversation_id = c.id
|
||||
WHERE LOWER(m.content) LIKE ?
|
||||
ORDER BY c.updated_at DESC
|
||||
LIMIT ?
|
||||
""", (f"%{q}%", limit))
|
||||
rows = cur.fetchall()
|
||||
|
||||
results = []
|
||||
for row in rows:
|
||||
# Load all messages in order so we can find complete exchange pairs
|
||||
cur.execute("""
|
||||
SELECT role, content FROM messages
|
||||
WHERE conversation_id = ?
|
||||
ORDER BY timestamp ASC
|
||||
""", (row["id"],))
|
||||
all_msgs = [{"role": r["role"], "content": r["content"]} for r in cur.fetchall()]
|
||||
|
||||
# For each matching message, collect the full user+assistant pair around it
|
||||
seen_pairs: set = set()
|
||||
matches = []
|
||||
for i, msg in enumerate(all_msgs):
|
||||
if q not in msg["content"].lower():
|
||||
continue
|
||||
if msg["role"] == "user":
|
||||
start, end = i, i + 1 if i + 1 < len(all_msgs) else i
|
||||
else:
|
||||
start, end = (i - 1 if i > 0 else i), i
|
||||
if (start, end) in seen_pairs:
|
||||
continue
|
||||
seen_pairs.add((start, end))
|
||||
for m in all_msgs[start:end + 1]:
|
||||
matches.append({"role": m["role"], "content": m["content"][:500]})
|
||||
if len(seen_pairs) >= 2:
|
||||
break
|
||||
|
||||
if matches:
|
||||
results.append({
|
||||
"id": row["id"],
|
||||
"updated_at": row["updated_at"],
|
||||
"matches": matches,
|
||||
})
|
||||
|
||||
conn.close()
|
||||
return results
|
||||
|
||||
# -----------------------------
|
||||
# Settings API
|
||||
# -----------------------------
|
||||
_SETTINGS_DEFAULTS: Dict[str, Any] = {
|
||||
"model": "",
|
||||
"temperature": 0.7,
|
||||
"system_prompt": "",
|
||||
"timeout": 120,
|
||||
}
|
||||
|
||||
def get_settings(self) -> Dict[str, Any]:
|
||||
conn = self._connect()
|
||||
cur = conn.cursor()
|
||||
cur.execute("SELECT key, value FROM settings")
|
||||
rows = cur.fetchall()
|
||||
conn.close()
|
||||
result = dict(self._SETTINGS_DEFAULTS)
|
||||
for row in rows:
|
||||
try:
|
||||
result[row["key"]] = json.loads(row["value"])
|
||||
except Exception:
|
||||
result[row["key"]] = row["value"]
|
||||
return result
|
||||
|
||||
def update_settings(self, data: Dict[str, Any]):
|
||||
conn = self._connect()
|
||||
try:
|
||||
cur = conn.cursor()
|
||||
for key, value in data.items():
|
||||
if key in self._SETTINGS_DEFAULTS:
|
||||
cur.execute(
|
||||
"INSERT OR REPLACE INTO settings (key, value) VALUES (?, ?)",
|
||||
(key, json.dumps(value))
|
||||
)
|
||||
conn.commit()
|
||||
finally:
|
||||
conn.close()
|
||||
|
||||
# -----------------------------
|
||||
# Store Instance
|
||||
# -----------------------------
|
||||
from ..nexus_config import MEMORY_DB
|
||||
|
||||
DB_PATH = MEMORY_DB
|
||||
store = PersistentMemoryStore(DB_PATH)
|
||||
Reference in New Issue
Block a user
GitNexus · part of the Nexus stack