Files
NexusOS/CLAUDE.md
T
AthenaandClaude Sonnet 5 cb3d3f0a1f feat: vendor Curry, preloaded and callable across the one universal wheel
Vendors curry_core.py from Athena-Pro/Curry (with the str.format()/format_map()
sandbox-escape fix from https://github.com/Athena-Pro/Curry/pull/4 already
applied) into synapse/, since Curry itself isn't a pip-installable package -
it's meant to be pointed at via a config path, which only works from a source
checkout. Vendoring a single self-contained, stdlib-only file ships it inside
NexusOS's own wheel with no extra dependency to reconcile.

synapse/curry_store.py opens it into a module-level singleton (curry_db) at
import time, the same pattern as memory.store.store and
playbooks.store.playbook_store, and main.py imports it so it's genuinely
initialized at process startup - preloaded, not lazy-on-first-use. Backed by
its own CURRY_DB file (nexus_config.py), separate from memory.db.

NexusOS builds exactly one wheel (py3-none-any, no compiled extensions) -
there is no separate Windows/macOS/Linux artifact; platform differences are
handled by requirement overlays at install time, not by building different
wheels. Verified the same wheel actually carries this correctly: built it,
confirmed twine check passes, confirmed synapse/curry_core.py and
curry_store.py are present in the archive (bin/check.sh's packaging gate now
asserts this too), then installed that exact wheel into a throwaway venv and
round-tripped a declare_constant/get_constant_latest call against it with no
source checkout present - proving "preloaded and ready to be called" holds
from the shipped artifact, not just editable-install execution.

Android/Termux is unaffected by this change in either direction: it already
has a separate, documented, pre-existing blocker in docs/TERMUX.md (no
published Android pydantic-core wheel) that has nothing to do with Curry,
which is pure stdlib and adds no new native/binary dependency.

Scope: preload only, nothing wired into a chat-facing tool yet - no model or
user-authored content reaches declare_function/call_function today.

Verified: 216 backend tests pass (4 new in test_curry_store.py, including a
regression test proving the vendored sandbox fix survived the copy); the 12
pre-existing C/C++/Rust toolchain failures are unrelated and unchanged.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
2026-08-25 21:40:41 -05:00

11 KiB

CLAUDE.md

This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.

What is NexusOS

NexusOS is a local AI assistant platform. It runs a Python/FastAPI backend (Synapse) that interfaces with a locally bundled Ollama instance, a dedicated memory microservice, and a React/Vite frontend. All AI inference runs through Ollama on localhost; no external AI provider is configured or called.

Running the Project

NexusOS runs single-process: the Synapse backend on port 8000 serves the built web UI (interface/web/dist) itself, so there is no separate Vite server at runtime. Ollama is started manually (sidebar Start AI / nexus-cli.sh start --ai), not on backend startup.

Windows (recommended):

powershell -ExecutionPolicy Bypass -File .\install-windows.ps1   # one-time native install
ncp web                                                          # memory :8001 + backend :8000 + UI

Linux full stack (dev):

./launch_nexus.sh

This activates the Promethean venv and starts the memory service on port 8001 and the Synapse backend on port 8000 (which also serves the built UI). It additionally starts a Vite dev server for frontend hot-reload — a Linux-dev convenience, unlike the single-process Windows/production path where the backend serves dist/ alone. It does not start Ollama.

macOS (community-supported):

./install-macos.sh   # one-time: Homebrew packages + venv + web build, via bin/sync.py
./launch_nexus.sh     # same script as Linux - it's plain bash, no Linux-only calls

No bundled Ollama binary (Linux x86-64 only) and no XFCE desktop branding — both already no-op on macOS via bin/sync.py's linux_stage(). Ollama is instead the Homebrew-installed native binary, picked up automatically because OllamaManager falls back to ollama on PATH when the bundled binary is absent; that gets full Metal GPU acceleration with no extra config.

Individual services via CLI:

# From nexus-core/ with Promethean venv active:
source Promethean/bin/activate

# Backend (serves the built UI at :8000 too)
uvicorn synapse.main:sio_app --host 0.0.0.0 --port 8000 --reload

# Memory service
uvicorn synapse.memory.service:app --host 0.0.0.0 --port 8001 --reload

# Frontend DEV server (hot-reload) — only when editing the UI; production is the
# built dist/ served by the backend. Run `npm run build` to refresh dist/.
cd interface/web && npm run dev

Management CLI (nexus / ncp) — start/stop services with PID tracking, plus terminal access to the same features as the web UI (REST API on :8000):

./management/nexus-cli.sh start   # starts backend + frontend
./management/nexus-cli.sh stop
./management/nexus-cli.sh start --backend|-b / --frontend|-f / --memory|-m

# Interactive TUI (Hermes/OpenClaw-style; needs pip install 'nexusos-ai[tui]'):
nexus                             # bare command opens the Textual chat TUI
nexus tui                         # same, explicit

# Feature one-shots (dispatch to nexusos_cli/nexus_api.py — httpx):
nexus chat send "<message>"       # stream a reply (POST /chat/stream)
nexus memory list|add <text>|rm <id>
nexus playbook list|show <id>     # first playbook (*) is the active system prompt
nexus history [query]             # recent conversations
nexus monitor                     # ASCII status dashboard (no prompt)

The interactive TUI lives in nexusos_cli/tui_app.py (Textual, optional extra). One-shot subcommands and nexus monitor remain for scripts. The CLI package is nexusos_cli/ (what the wheel ships); management/ keeps desktop-only pieces — shell wrappers, Tk control panel, XFCE panel wiring. management/controlpanel.py (tkinter GUI, wired into the XFCE panel via bin/panel/nexus-popup.py) stays.

Checks (the release gate):

./bin/check.sh          # pytest + eslint + frontend tests + .ps1/.sh parse + wheel build

There is no hosted CI — the remote is self-hosted Gitea with no act_runner — so this script is the gate. Run it before tagging a release.

Frontend lint only:

cd interface/web && npm run lint

Frontend build:

cd interface/web && npm run build

Architecture

Python venv

All Python code runs inside Promethean/ (a local venv). Always activate it before running backend commands: source Promethean/bin/activate. Dependencies are layered: requirements-base.txt holds the GPU-agnostic core, and a thin overlay pins the right PyTorch build for the target — requirements-amd.txt (ROCm), requirements-nvidia.txt (CUDA, generated by bin/gen-nvidia-reqs.py), or requirements-windows.txt (CPU-only). bin/sync.py (requirements()) selects NVIDIA, AMD, CPU/Windows, or — via an explicit sys.platform == "darwin" check, since os.name alone can't tell macOS apart from Linux — requirements-base.txt with no overlay at all for macOS, from the host.

Synapse Backend (synapse/)

FastAPI app at synapse/main.py. Key responsibilities:

  • /chat/stream — chat with Ollama; streaming uses SSE (the only chat endpoint — the non-stream /chat was removed). After each exchange the stream endpoint calls the Memory Service to auto-extract persistent facts.
  • /playbooks — CRUD for playbooks stored as YAML files in data/playbooks/ via synapse/playbooks/store.py.
  • /memory — CRUD for persistent facts (proxies the same SQLite store as the memory service).
  • /models — lists, pulls, and deletes Ollama models by proxying Ollama's HTTP API.
  • /settings and /ollama — persist runtime settings and control Ollama lifecycle.
  • /conversations — persists, retrieves, edits, deletes, and exports full chat history from SQLite.
  • /icons — lists local application icons and applies NexusOS branding.

System prompt assembly (in main.py chat_stream_endpoint): the final system prompt is built by layering the active playbook instructions → reference playbook context → persistent memory facts → relevant past conversation snippets retrieved by store.search_conversations.

Memory Service (synapse/memory/)

A separate FastAPI app on port 8001. service.py exposes /memories/extract which calls extractor.py — an Ollama prompt that decides whether to persist a new fact from a conversation exchange. The main Synapse backend calls this asynchronously after each streaming response. Both services share the same SQLite database (synapse/memory/memory.db).

Playbook System (synapse/playbooks/ + synapse/playbook_manager.py)

Playbooks are ordered records (title, goal, instructions, tags), each persisted as a {id}.yaml file in data/playbooks/ by PlaybookFileStore (the dir is PLAYBOOK_DIR in nexus_config.py). The first playbook by order is the active system prompt; all subsequent playbooks are injected as reference context. PlaybookManager is the thin class the backend uses to retrieve them and assemble the system prompt.

Ollama (ollama/bin/ollama)

A bundled Ollama binary lives at ollama/bin/ollama. OllamaManager in synapse/ollama_manager.py manages its lifecycle (start/stop/health-check) and selects the best available model. GPU detection uses Vulkan (vulkaninfo) to prefer discrete AMD/NVIDIA GPUs. The Ollama HTTP API is at http://127.0.0.1:11434 (overridable via OLLAMA_HOST env var).

Frontend (interface/web/)

React 19 + Vite. No routing library — App.jsx manages page state in a single currentPage useState. All API calls hit http://localhost:8000 (configured in src/config.js). Built to dist/ (gitignored) via npm run build and served by the backend at :8000 — the mount is in synapse/main.py (_DIST at /, guarded by is_dir()), so dist/ must be built for the UI to appear. Pages: Chatbot, Playbook editor, Conversation History, Models, Memory, Settings, Logs.

Code Tracks (synapse/tools.py + synapse/code_run.py)

Two separate tools, split by where the code runs:

  • render_preview — validates markup and returns a fence the chat renders in an opaque-origin sandbox="allow-scripts" iframe. Nothing executes server-side. Languages: PREVIEW_LANGS in synapse/tools.py, mirrored by interface/web/src/preview/languages.js.
  • run_snippet — compiles and runs a single file on the host via synapse/code_run.py, and returns a ```nexus-run fence carrying the source and its captured output. Languages: RUN_LANGS in synapse/code_run.py, mirrored by interface/web/src/preview/run-langs.js.

Each pair of registries is asserted equal by tests/test_tools.py — nothing couples them at runtime, so drift fails the check gate instead of silently degrading in the chat.

run_snippet is an action tool: action_tool_policy gates it (off by default, ask = per-call Approve/Deny in chat). Read the code_run.py module docstring before touching it — it runs code as the current user and is explicit about which of its five layers are load-bearing and which are only a tripwire.

Persistent Storage

Most data lands in synapse/memory/memory.db (SQLite, WAL mode). Tables: memory facts, conversations, messages, app settings. synapse/memory/store.py (PersistentMemoryStore) owns the schema and all queries. Playbooks are the exception — they live as YAML files in data/playbooks/ (see Playbook System). nexus_config.py defines all paths; it also ensures all required directories exist on import.

Curry (synapse/curry_core.py + synapse/curry_store.py)

curry_core.py is vendored, unmodified-except-for-one-fix, from Athena-Pro/Curry — an immutable, versioned fact store (constants, functions, model registrations, inference provenance) backed by its own SQLite file (CURRY_DB in nexus_config.py, separate from memory.db). curry_store.py opens it into a module-level singleton (curry_db) at import time — the same pattern as memory.store.store / playbooks.store.playbook_store — so it's preloaded and callable (curry_db.declare_constant(...), curry_db.call_function(...), etc.) from anywhere in the backend without extra setup. It ships inside the wheel (bin/check.sh's packaging gate asserts this) and has no external dependencies of its own. Nothing currently wires chat/model-authored content into it — it's available, not yet exposed as an action tool. Re-sync curry_core.py from upstream by hand, not by script; see the file's own docstring for what changed and why.

Logs & Runtime State

  • runtime/backend.log, runtime/frontend.log, runtime/memory.log — service stdout
  • runtime/logs/ollama.log, runtime/logs/chat.log
  • runtime/pids/backend.pid, runtime/pids/frontend.pid — used by the management CLI

Key Config

Concern Location
Ollama host OLLAMA_HOST env var (default http://127.0.0.1:11434)
All filesystem paths synapse/nexus_config.py Settings class
Frontend API base URL interface/web/src/config.js
Default chat/memory models synapse/nexus_config.py DEFAULT_CHAT_MODEL / DEFAULT_MEMORY_MODEL
Python dependencies (base) requirements-base.txt
Python dependencies (AMD/ROCm) requirements-amd.txt
Python dependencies (NVIDIA/CUDA) requirements-nvidia.txt (generated by bin/gen-nvidia-reqs.py)
Python dependencies (Windows/CPU) requirements-windows.txt