diff --git a/README.md b/README.md index 5ad2d2c..868e88c 100644 --- a/README.md +++ b/README.md @@ -123,198 +123,6 @@ echo myagent > ~/mnt/ollie/s//agent echo "kill " > ~/mnt/ollie/ctl ``` -## Ideas - -### Automation & Scripting - -**Scripting and automation** — shell scripts that submit prompts, poll `state` until idle, then read `chat` for the result. No SDK, no HTTP client, just file I/O. Works in any language that can write to a file. - -**Multiplexing sessions** — run several agents in parallel, each in their own session directory, and fan work out to them from a shell script. Coordinate by watching their `state` files. - -**Hooks and watchers** — poll `state` in a loop to trigger actions when the agent finishes, or use `tail -f chat` to react to new output. Build lightweight event-driven pipelines with standard shell tools. - -### Tooling & Integration - -**Unix tools** — pipe `chat` into `grep`, `awk`, `sed`. Diff two sessions' outputs. Log conversations with `cp`. Search history across sessions with `grep -r`. - -**Editor integration** — any editor that can read/write files gets agent access for free. In `acme` or `sam`, you write to `prompt` and read back `chat` with no plugin required. Fits naturally into the Plan 9 workflow. - -**Lightweight TUI alternatives** — `watch cat state` as a status bar, `tail -f chat` in one pane, prompt submission in another. Compose a working interface entirely from standard tools. - -### Network & Remote Access - -**Remote access** — 9P is a network protocol. Export the namespace over the network and access agent sessions from another machine using the same file interface, with no additional daemon or API layer. - -### Multi-Agent Workflows - -Each session exposes a `reply` file containing only the assistant text from the most recently completed turn. Writing to `prompt` clears `reply` as a side-effect. Together these make agent-to-agent handoffs expressible as plain file operations — no message queue, no orchestration framework, no shared memory. - -A shell script moves text between sessions. The agents communicate only through what the script explicitly passes between them, so information flow is fully under your control. Each agent can use a different backend, model, or tool configuration. A human can intervene at any point by writing directly to a session's `prompt`. - -#### Example: develop → review → test - -Three sessions with specialized agent configs run a feedback loop. The reviewer ends its response with `LGTM` (proceed) or `PTAL` (revise). The tester ends with `Approved` (done) or `Rejected` (revise). A shell script reads the verdict with `grep` and routes accordingly. - -```sh -#!/bin/sh -workdir=${1:?usage: $0 } -cd ~/mnt/ollie - -# Count existing sessions so we can identify the newly created ones by offset. -n=$(ls s/ | wc -l) - -echo "new agent=developer workdir=$workdir" > ctl -echo "new agent=reviewer workdir=$workdir" > ctl -echo "new agent=tester workdir=$workdir" > ctl - -dev=$(ls s/ | sort | sed -n "$((n+1))p") -rev=$(ls s/ | sort | sed -n "$((n+2))p") -tst=$(ls s/ | sort | sed -n "$((n+3))p") - -wait_reply() { - while [ "$(wc -c < s/$1/reply)" -eq 0 ]; do sleep 1; done -} - -echo "implement a function that parses a JSON config file" > s/$dev/prompt - -while true; do - wait_reply $dev - code=$(cat s/$dev/reply) - - # review phase - printf "Review the following code. End your response with LGTM if it is ready, or PTAL if it needs revision.\n\n%s" "$code" > s/$rev/prompt - wait_reply $rev - - if ! grep -qi "LGTM" s/$rev/reply; then - { echo "revise this code based on the feedback below." - echo "--- code ---"; echo "$code" - echo "--- feedback ---"; cat s/$rev/reply - } > s/$dev/prompt - continue - fi - - # test phase - printf "Test the following code. End your response with Approved if all tests pass, or Rejected if they do not.\n\n%s" "$code" > s/$tst/prompt - wait_reply $tst - - if grep -qi "Approved" s/$tst/reply; then - echo "done." - echo "$code" - break - fi - - { echo "fix the failures reported below." - echo "--- code ---"; echo "$code" - echo "--- test report ---"; cat s/$tst/reply - } > s/$dev/prompt -done -``` - -Each agent only sees what the script explicitly sends it. Each can use a different backend, model, or tool configuration. A human can intervene at any point by writing directly to a session's `prompt`. The boundary between fully automated and human-in-the-loop is just whether the script pauses to ask. - -### Sub-Agents - -A session can spawn ephemeral child sessions to handle a focused task, then tear them down when done. The parent uses `execute_code` to write `new` to `ctl`, send an initial context and task to the child's `prompt`, poll until `reply` is ready, read the result, and write `kill ` to `ctl`. From the child's perspective it is just a normal session; it has no knowledge of its own ephemerality. - -**Sub-agents as function calls** — the parent primes the child with exactly the context it needs (excerpts from its own `chat`, relevant beads, local file contents) and receives a single focused reply. Failures are isolated; a child that errors or stalls can be killed and retried without affecting the parent. The pattern composes naturally: a sub-agent can itself spawn sub-agents, building a call tree bounded only by the number of sessions open at once. - -`spawn_subagents.py` reads a JSON spec from stdin, fans out the work concurrently, and returns a JSON array of results — a single `execute_tool` call from the parent's perspective. Note: this requires adding Python language support to `execute_code`, `execute_tool`, and `execute_pipe`, which is low effort. - -```python -#!/usr/bin/env python3 -"""spawn_subagents.py — fan out tasks to ephemeral olliesrv sub-agents. - -Input (stdin): JSON array of {"task": str, "agent": str, "context": str} -Output (stdout): JSON array of {"agent": str, "reply": str} - -Install in ~/.local/share/ollie/tools/ to make available via execute_tool. -""" - -import json, os, sys, threading, time -from concurrent.futures import ThreadPoolExecutor, as_completed -from pathlib import Path - -BASE = Path.home() / "mnt" / "ollie" -POLL = 0.5 -_spawn_lock = threading.Lock() - - -def session_ids(): - return {e.name for e in (BASE / "s").iterdir() if e.is_dir()} - -def spawn_session(agent="default", workdir=""): - with _spawn_lock: - before = session_ids() - (BASE / "ctl").write_text(f"new agent={agent} workdir={workdir}\n") - while True: - new = session_ids() - before - if new: - return new.pop() - time.sleep(0.1) - -def kill_session(sid): - (BASE / "ctl").write_text(f"kill {sid}\n") - -def wait_reply(sid): - path = BASE / "s" / sid / "reply" - while True: - if path.stat().st_size > 0: - return path.read_text().strip() - time.sleep(POLL) - -def run_subagent(spec): - agent = spec.get("agent", "default") - workdir = spec.get("workdir", "") - context = spec.get("context", "") - task = spec.get("task", "") - sid = spawn_session(agent, workdir) - try: - prompt = f"{context}\n\n{task}".strip() if context else task - (BASE / "s" / sid / "prompt").write_text(prompt) - return {"agent": agent, "reply": wait_reply(sid)} - finally: - kill_session(sid) - -def main(): - specs = json.load(sys.stdin) - results = [None] * len(specs) - with ThreadPoolExecutor(max_workers=len(specs)) as pool: - futures = {pool.submit(run_subagent, s): i for i, s in enumerate(specs)} - for f in as_completed(futures): - results[futures[f]] = f.result() - json.dump(results, sys.stdout, indent=2) - print() - -if __name__ == "__main__": - main() -``` - -The parent agent constructs the spec and makes a single tool call: - -```json -[ - { "task": "review this code for correctness", "agent": "reviewer", "context": "..." }, - { "task": "check this code for security issues", "agent": "security", "context": "..." } -] -``` - -Results come back as: - -```json -[ - { "agent": "reviewer", "reply": "..." }, - { "agent": "security", "reply": "..." } -] -``` - -### Self-Generating Workflows - -Since agents have access to `execute_code`, a session can write and execute a workflow script without any human involvement. Given a task and knowledge of the filesystem layout, an agent can decompose the work, spawn sessions, write the coordination script, and run it — all in a single turn. The README you are reading is essentially its system prompt. Conductor functionality, for free. - -### Persistent Memory - -**Task tracking** — Agent sessions are ephemeral by nature: context windows fill, processes crash, work gets lost. [9beads](https://github.com/lneely/9beads) addresses this by exposing a structured, version-controlled task database as a 9P filesystem. Any session can read the task list, claim work, track dependencies, and mark completion through ordinary file operations. If a session is interrupted, another can pick up exactly where it left off. Task lists are scoped per-project, keeping them focused and bounded. Combined with olliesrv, agents get both a communication surface and a memory layer, with no special integration required between them. - ## Example shell session ```sh