ollie is a 9p-based generative agent surface
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README.md

ollie

Ollie is an AI agent runtime. A small Go core handles the agent loop, tool dispatch, sandboxing, and multi-backend routing; frontends (terminal, acme, Emacs, KDE, browser) and orchestration (shell scripts, multi-agent workflows, cron) are external. The core is deliberately minimal — capabilities come from composing small pieces rather than building a monolithic framework.

Repository layout

Monorepo with Git submodules. Each submodule has its own Go module (except el which is Elisp and kde which is C++/Qt).

Directory Language Description
core/ Go Core library: agent loop, backends, tools, config, sandbox
9p/ Go 9P filesystem server (olliesrv)
dbus/ Go D-Bus session manager daemon (ollied)
acme/ Go Plan 9 acme editor frontend
httpgw/ Go HTTP-to-9P gateway (ollie-httpgw)
webui/ TypeScript Preact SPA browser frontend
kde/ C++/Qt6 KDE integration: plasmoid, standalone GUI, Kate plugin, KRunner, tray
el/ Elisp Emacs frontend (ellie.el)
agents/ JSON Agent config files (loaded at runtime)
prompts/ Markdown System prompt templates
tools/ Python/Bash Tool scripts (file_read, lsp_, memory_, etc.)
scripts/ Shell User-facing CLI scripts: session management, utilities, plumbing
sandbox/ YAML Landlock sandbox config
doc/ Markdown Architecture docs, usage guide
contrib/ Mixed Community scripts
experiments/ Mixed Trial notes

Features

Sessions

  • Create / kill / rename / list — full lifecycle management of concurrent agent sessions
  • Prompt submission with FIFO queue — prompts are queued and processed in order; multiple clients can submit without conflicts
  • State observation — each session exposes its current state (idle, thinking, calling: <tool>) with a blocking-wait primitive for efficient polling
  • Chat streaming — stream model output in real time via file tail or D-Bus signal
  • Session persistence — active sessions survive server restarts; state is checkpointed to ~/.local/share/ollie/sessions/
  • Plan / scratchpad — per-session markdown checklist that survives context compaction and is visible to peer agents
  • Environment inspection — read the effective environment variables for any session

Agent loop

  • Streaming tool calls — the core runs a turn loop: prompt the model, parse tool calls, dispatch them (in parallel where safe), feed results back, repeat until done
  • Automatic context compaction — long conversations are summarized transparently when approaching the context limit
  • System prompt templating — prompts are rendered from markdown templates with variable substitution; inspect the fully rendered prompt at any time

Backends

  • Multi-backend routing — Ollama (local), OpenAI-compatible, Anthropic, GitHub Copilot, Kiro; switch backends per-session
  • Model listing and switching — enumerate available models from any backend; switch models mid-session
  • Connection pooling — all sessions sharing the same API host multiplex over a single HTTP/2 connection; no redundant TLS handshakes
  • 24-hour model cache — model lists are cached at the backend level to avoid repeated API calls

Tools and sandboxing

  • Sandboxed execution — every tool call runs inside a Landlock sandbox with per-profile filesystem access rules
  • Extensible tools — tools are executable scripts with header metadata; add one by dropping a file in a directory
  • Elevation — commands that need to escape the sandbox can request elevation through a streaming protocol (frame-based, over unix socket)

Agents

  • Agent definitions — JSON configs that set personality, tools, backend preferences, and constraints
  • List and switch — enumerate available agents and assign one to any session

Multi-agent

  • Peer communication — bidirectional links between sessions; peers can submit prompts to each other
  • Orchestrator/worker patterns — subagent delegation, parallel fan-out, coordinated through session primitives
  • Domain skills — teach the agent your project’s conventions with a markdown file; loaded on demand

Background processes

  • Detach — start a long-running command and immediately background it; the agent continues working
  • Monitor — list running processes, read their output (64KB ring buffer), check status
  • Signal and dismiss — send TERM/KILL to a detached process; remove finished processes from the list

Stateless endpoints

  • Code completion — write cursor context (prefix, suffix, file path), read back code to insert; works from any editor or script
  • One-shot generation — write a prompt, read back a full LLM response; no session, no agent loop, no tools; scriptable from any language
  • Task routing — write a task description, the system classifies complexity against all available models and returns the best backend+model for the job

Frontends

  • Terminal — interactive CLI (b, bfg, sh)
  • Plan 9 acme — editor integration for acme
  • Emacs — ellie.el package
  • KDE — plasmoid, standalone GUI, Kate plugin, KRunner, system tray
  • Web UI — Preact SPA served by the HTTP gateway

Configuration

  • Per-session config — backend, model, agent, generation parameters; all readable and writable at runtime

Architecture

Ollie has two session manager backends. Both embed the same core library and expose the same features; they differ in interface philosophy and deployment context.

9P (olliesrv) D-Bus (ollied)
Interface Synthetic filesystem + D-Bus protocol adapter Desktop bus methods + signals
Frontends All (terminal, acme, Emacs, KDE, web) KDE only (plasmoid, GUI, Kate, KRunner, tray)
Network Native (mount over TCP) Local session bus
Dependencies None beyond Go runtime D-Bus daemon, desktop session

olliesrv is the primary server. It exposes sessions as a 9P synthetic filesystem and embeds a D-Bus protocol adapter that emits the same signals and methods that the KDE frontends expect. All frontends work with olliesrv.

ollied is a standalone D-Bus daemon that only supports the KDE frontends. It predates the 9P server's D-Bus adapter and remains available for deployments that don't need 9P.

Use whichever fits your environment — or both at once. Note that sessions are not shared between them; each backend manages its own session pool.


9P: everything is a file

The 9P server exposes the agent runtime as a synthetic filesystem. Every session is a directory; every operation is a read or write. It also embeds a D-Bus protocol adapter on org.ollie.SessionManager that streams StateChanged, ChatUpdated, and lifecycle signals to desktop clients — so the KDE plasmoid, standalone GUI, Kate plugin, and system tray all work without ollied.

There is no client library, no SDK, no protocol buffer — echo, cat, tail, and rm are the API.

# Create a session
echo "name=worker" > /mnt/ollie/s/new

# Submit a prompt
echo "fix the bug in main.go" > /mnt/ollie/s/worker/prompt

# Stream the response
tail -f /mnt/ollie/s/worker/chat

# Check state
cat /mnt/ollie/s/worker/state

# Kill a background process
echo "signal 12345 TERM" > /mnt/ollie/s/worker/ctl

# Get completions
echo '{"language":"go","code":"func he"}' > /mnt/ollie/s/worker/complete
cat /mnt/ollie/s/worker/complete

# One-shot generation (no session needed)
exec 3<>/mnt/ollie/generate; echo 'explain monads in one sentence' >&3; cat <&3; exec 3>&-

# Route a task to the best model
exec 3<>/mnt/ollie/route; echo 'redesign the auth system' >&3; cat <&3; exec 3>&-
# → backend=kiro model=claude-sonnet-4-20250514

Network transparency

9P is a network protocol. Mount the agent filesystem from any machine on the network:

9pfuse 'tcp!server:5640' /mnt/ollie

No SSH tunneling, no port forwarding for individual endpoints, no API gateway. One mount and every session, every tool, every config value is accessible as if local.

Container and headless deployment

The 9P server embeds the core library directly — no display server, no desktop dependencies. It runs anywhere a Go binary runs: containers, cloud VMs, CI runners, embedded systems.

The embedded D-Bus adapter is automatically disabled when using -tcp (remote listen mode). You can also disable it explicitly with -nodbus:

olliesrv start -tcp :5640          # TCP listener, no D-Bus (implied)
olliesrv start -nodbus             # Unix socket only, no D-Bus

Shell composability

Because operations are file I/O, they compose with the entire Unix toolkit:

# Fan out a prompt to all sessions
for s in /mnt/ollie/s/*/prompt; do echo "run tests" > "$s"; done

# Wait for all agents to finish
for s in /mnt/ollie/s/*/statewait; do cat "$s" > /dev/null; done

# Grep all agent plans
grep -r "TODO" /mnt/ollie/s/*/plan

# Monitor costs
paste /mnt/ollie/s/*/cost

Pipe agents into awk. Filter with grep. Schedule with cron. Orchestrate with a 10-line shell script instead of a framework.

Multiplexing

Multiple clients — terminals, editors, scripts, other agents — can mount the same server simultaneously. Each gets an independent view through 9P’s per-fid state model. No connection pools, no session affinity, no WebSocket juggling.

Plan 9 patterns

The design follows Plan 9 conventions directly:

  • /net/dns pattern — /complete, /generate, and /route are stateless per-fid: write a request, read back the result, like a DNS lookup
  • ctl files — control operations (stop, kill, rename, compact) are writes to a control file, not method calls
  • Blocking reads — statewait blocks until state changes, replacing event subscriptions with a simple cat

D-Bus: desktop integration

The D-Bus interface (org.ollie.SessionManager) is available two ways: embedded in olliesrv (recommended) or as the standalone ollied daemon. Both expose the same methods and signals. The KDE frontends connect to whichever is running.

Typed method calls

D-Bus gives you introspectable, typed interfaces with proper error returns. No string parsing, no exit codes to check:

# Create a session
dbus-send --session --dest=de.lneely.ollie --print-reply \
  /de/lneely/ollie de.lneely.ollie.Manager.CreateSession \
  string:"worker" string:"" string:""

# Submit a prompt
dbus-send --session --dest=de.lneely.ollie --print-reply \
  /de/lneely/ollie/sessions/worker de.lneely.ollie.Session.SubmitPrompt \
  string:"fix the bug in main.go"

# Read state
dbus-send --session --dest=de.lneely.ollie --print-reply \
  /de/lneely/ollie/sessions/worker de.lneely.ollie.Session.GetState

Real-time signals

D-Bus signals push events to subscribers without polling:

  • ChatDelta — stream tokens as they arrive
  • StateChanged — transition notifications (idle → thinking → calling: grep → idle)
  • SessionCreated / SessionRemoved — lifecycle events for UIs that display session lists

GUI frontends subscribe once and react to changes — no timers, no file watches, no busy loops.

KDE integration

The D-Bus interface is what makes native desktop integration possible:

  • Plasmoid — embed an agent chat widget directly in the Plasma panel
  • Kate plugin — inline AI assistance in the text editor
  • KRunner — launch prompts from the desktop search bar
  • System tray — status indicator and quick actions
  • Standalone GUI — full-featured Qt6 chat application

All of these talk to org.ollie.SessionManager over D-Bus using Qt's native bindings — no IPC glue code, no subprocess management. They work with either olliesrv or ollied.

Activation and lifecycle

D-Bus supports socket activation: ollied can start on first use and exit when idle. The desktop session manages its lifecycle automatically through a .service file — no init scripts, no manual daemon management.

Getting started

Clone with submodules:

git clone --recurse-submodules https://git.lneely.de/lkn/ollie.git

Or after cloning:

git submodule update --init --recursive

Build and install everything from the monorepo root:

mk

Or build specific components:

mk core    # Core library
mk 9p      # 9P filesystem server
mk httpgw  # HTTP gateway
mk webui   # Web UI (requires Node.js + npm)
mk dbus    # D-Bus daemon
mk data    # Install agents/prompts/tools/skills to ~/.config/ollie/
mk scripts # Install CLI scripts

For KDE, build from kde/ with CMake. For Emacs, copy el/ellie.el into your config and (require 'ellie).

See doc/USAGE.md for usage instructions.

Configuration

Environment: ~/.config/ollie/env

OLLIE_BACKEND=openai           # ollama | openai | anthropic | copilot | kiro (default: ollama)
OLLIE_OLLAMA_URL=              # base URL for Ollama (default: http://localhost:11434)
OLLIE_OPENAI_URL=https://openrouter.ai/api
OLLIE_OPENAI_KEY=sk-or-...
OLLIE_ANTHROPIC_KEY=sk-ant-...
OLLIE_COPILOT_TOKEN=...
OLLIE_KIRO_TOKEN=...           # bearer token or sqlite:// path (auto-detected from Kiro CLI if unset)
OLLIE_MODEL=qwen/qwen3-235b-a22b
OLLIE_TOOLS_PATH=~/.config/ollie/tools    # directory for tool scripts ({tool} steps)
OLLIE_MEMORY_PATH=~/.config/ollie/memory  # directory for memory files (ollie/m)
OLLIE_ELEVATE_SOCKET=${XDG_RUNTIME_DIR}/ollie/elevate.sock  # socket path for x/elevate adapter
OLLIE_COMPLETE_BACKEND=ollama             # backend for u/complete (required)
OLLIE_COMPLETE_MODEL=qwen3:latest         # model for u/complete (required)
OLLIE_ENABLED_BACKENDS=openrouter,kiro  # backends available for routing (comma-separated)

# /route file configuration
OLLIE_ROUTE_BACKEND=ollama               # backend for the classifier model
OLLIE_ROUTE_MODEL=qwen3:8b               # model that classifies task complexity

Shell environment variables take precedence over the env file.

Development

Update all submodules to latest:

git submodule update --remote

Each submodule has its own Go module with independent tests (go test ./...). See individual submodule READMEs for component-specific build and test instructions.

Credits

Many sources of inspiration:

  • Plan 9 from Bell Labs — for an interesting system
  • @9fans — for the Plan 9 port
  • Suckless — for articulating good software development principles
  • @simonfxr — for a solid agent baseline to "borrow" from, and other nifty ideas
  • @aws — for a solid open-source agent implementation

License

GPLv3