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feat(ai): model profiles, capability discovery, and agentless /ai list|models

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Make connecting any model a config step, not a code change:
- models.toml named profiles (api_key_env names an env var, never the key)
- providers gain available_models(); add preflight + --list-models/--check
- /ai list and /ai models in-room; client probes local Ollama for
  /ai models when no agent is running, and /ai list hints to summon one
- docs/providers.md provider guide + examples/echo_provider.py
- README: command table, AI section, layout updated

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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leetcrypt 2026-06-01 15:25:07 -07:00
parent 4fd1b70cb3
commit 65df12de9e
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16
README.MD
View File

@ -42,6 +42,8 @@ Encrypted chat that runs in your terminal. You host the server, you control the
| `hh/` | The Rust `ratatui` client (the flagship) |
| `cmd_chat/`, `cmd_chat.py` | The Python (Sanic) server + legacy Python client |
| `cmd_chat/agent/` | The model-agnostic AI agent bridge (joins a room as an encrypted client) |
| `models.toml` | Named provider profiles for `/ai start <profile>` (see `docs/providers.md`) |
| `docs/providers.md` | Connect any model — profiles, flags, discovery, bring-your-own-provider |
| `hh/lets-hack.sh` | Spin up a local test "clergy" in tmux (server + N client panes) |
| `bootstrap-ai.sh` | Optional: install Ollama + pull a model for the local `/ai` agent |
| `hh/direnv-autostart/` | `cd` into a directory to auto-launch a session (direnv) |
@ -144,9 +146,11 @@ Type to chat. Slash commands and keys:
| `/theme [name]` | Switch vestments, or list them |
| `/send <path>` | Offer a file (or directory) to the room |
| `/accept` · `/reject` | Respond to a pending file offer |
| `/ai start [model]` | Summon a local AI agent (default `ollama/qwen2.5:3b`) |
| `/ai start [model\|profile]` | Summon a local AI agent (default `ollama/qwen2.5:3b`; a bare name is a `models.toml` profile) |
| `/ai stop` | Dismiss the agent you summoned |
| `/ai <question>` | Ask the agent (`/ai <name> <question>` if several present) |
| `/ai list` | List the agents present (or hint to `/ai start` if none) |
| `/ai models` | Models the active agent can serve — or, with no agent, your local Ollama tags |
| `/sbx launch [local\|docker\|multipass] [image]` | Summon the shared sandbox |
| `/sbx stop` | Tear down the sandbox you host |
| `/drive` · `F2` | Take the shared shell (`Esc` releases) |
@ -224,6 +228,16 @@ when you quit). Pick a model at summon time with `/ai start <model>`.
endpoint (OpenAI, Groq, Together, local vLLM…), plus a `module:Class` hook for
your own. Cloud providers are opt-in and read their API key from the agent's
environment — never the room.
- **Named profiles.** Register a backend once in `models.toml` and summon it by
name: `/ai start groq-llama`. Profiles store `api_key_env` (the *name* of an
env var, never the key), so the file is safe to commit. See the full
[provider guide](docs/providers.md) — profiles, explicit flags, discovery, and
bring-your-own-provider.
- **Discoverable.** `/ai list` shows who's present and `/ai models` shows what
the active agent can serve (active model bracketed). With no agent running,
`/ai models` still probes your local Ollama so you can see what's pullable
before summoning. By hand, `--list-models` enumerates a backend and `--check`
preflights it (exit 0/1) without joining a room.
- **End-to-end like everything else.** Replies are encrypted client-side; the
server still only ever relays ciphertext.

74
cmd_chat/agent/__main__.py
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@ -14,40 +14,100 @@ Examples
python -m cmd_chat.agent 127.0.0.1 3000 --provider openai \
--base-url https://api.groq.com/openai/v1 --model llama-3.1-70b --password hunter2
# a named profile from models.toml (provider + model + endpoint + key env)
python -m cmd_chat.agent 127.0.0.1 3000 --profile groq-llama --password hunter2
# a custom provider you wrote
python -m cmd_chat.agent 127.0.0.1 3000 --provider mypkg.mod:MyProvider
# discovery / preflight (no room join)
python -m cmd_chat.agent --profile groq-llama --list-models
python -m cmd_chat.agent --profile groq-llama --check
"""
from __future__ import annotations
import argparse
import sys
from .bridge import AgentBridge
from .providers import make_provider
from .profiles import load_profiles, provider_from_profile
from .providers import make_provider, preflight
def _build_provider(args, ap):
"""Resolve a Provider from either --profile or the explicit flags."""
if args.profile:
profiles = load_profiles(args.models_file)
if args.profile not in profiles:
known = ", ".join(profiles) or "(none — create models.toml)"
ap.error(f"unknown profile '{args.profile}'. known: {known}")
prof = profiles[args.profile]
provider = provider_from_profile(
prof, name=args.profile, model=args.model, base_url=args.base_url
)
# Profile may also supply non-provider defaults.
if args.system is None and prof.get("system"):
args.system = prof["system"]
if args.context_window == 12 and prof.get("context_window"):
args.context_window = int(prof["context_window"])
return provider
opts: dict = {}
if args.base_url and (args.provider == "openai" or ":" in args.provider):
opts["base_url"] = args.base_url
return make_provider(args.provider, model=args.model, **opts)
def main() -> None:
ap = argparse.ArgumentParser(
prog="cmd_chat.agent", description="hack-house AI agent bridge (PoC)"
)
ap.add_argument("server")
ap.add_argument("port", type=int)
ap.add_argument("server", nargs="?", help="room host (omit with --list-models/--check)")
ap.add_argument("port", type=int, nargs="?", help="room port")
ap.add_argument("--name", default="oracle", help="agent's room display name")
ap.add_argument("--password", default=None, help="room password")
ap.add_argument("--provider", default="ollama",
help="ollama | anthropic | openai | module:Class")
ap.add_argument("--profile", default=None,
help="named profile from models.toml (overrides --provider/--model)")
ap.add_argument("--models-file", default=None,
help="path to models.toml (default: $HH_MODELS_FILE, ./models.toml, ~/.config/hh/models.toml)")
ap.add_argument("--model", default=None, help="model name (provider default if omitted)")
ap.add_argument("--base-url", default=None, help="endpoint for openai-compatible providers")
ap.add_argument("--system", default=None, help="override the system prompt")
ap.add_argument("--context-window", type=int, default=12)
ap.add_argument("--list-models", action="store_true",
help="list models the backend can serve, then exit")
ap.add_argument("--check", action="store_true",
help="run a reachability/model preflight, then exit (0 ok, 1 fail)")
ap.add_argument("--insecure", action="store_true", help="skip TLS cert verification")
ap.add_argument("--no-tls", action="store_true", help="plain ws/http (local/Tailscale)")
args = ap.parse_args()
opts: dict = {}
if args.base_url and (args.provider == "openai" or ":" in args.provider):
opts["base_url"] = args.base_url
provider = make_provider(args.provider, model=args.model, **opts)
provider = _build_provider(args, ap)
# Discovery / preflight modes never join a room.
if args.list_models:
discover = getattr(provider, "available_models", None)
if discover is None:
ap.error(f"provider '{provider.name}' has no model discovery")
for m in discover():
print(m)
return
if args.check:
ok, msg = preflight(provider)
print(("ok: " if ok else "FAIL: ") + msg, file=sys.stderr if not ok else sys.stdout)
sys.exit(0 if ok else 1)
if args.server is None or args.port is None:
ap.error("server and port are required to join a room")
# Non-fatal preflight: warn early, but still try (discovery may be blocked
# while completion works).
ok, msg = preflight(provider)
if not ok:
print(f"⚠ preflight: {msg}", file=sys.stderr)
bridge = AgentBridge(
args.server, args.port, name=args.name, provider=provider,

39
cmd_chat/agent/bridge.py
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@ -62,7 +62,44 @@ class AgentBridge(Client):
frame = json.dumps({"_ai": "typing", "name": self.name, "on": on})
await ws.send(self.room_fernet.encrypt(frame.encode()).decode())
async def _send_chat(self, ws, text: str) -> None:
await ws.send(self.room_fernet.encrypt(text.encode()).decode())
def _command_reply(self, question: str) -> str | None:
"""Canned reply for a reserved verb, else None.
Handled locally so it never spends a model call:
- ``list`` → this agent's roster line (who's here / what it runs). With
several agents present each answers for itself, forming the roster.
- ``models`` → what the configured backend can serve (in-room
--list-models)."""
verb = question.strip().lower()
if verb == "list":
return (f"{self.name} (ai) here — {self.provider.name}/"
f"{self.provider.model}, context {self.context_window}")
if verb != "models":
return None
discover = getattr(self.provider, "available_models", None)
if discover is None:
return f"{self.provider.name}: model discovery not supported."
try:
models = discover()
except Exception as e: # noqa: BLE001 — report unreachable backend in-room
return f"[ai error: cannot reach {self.provider.name}: {e}]"
if not models:
return f"{self.provider.name}: no models reported."
# One line: the TUI collapses embedded newlines, so bracket the active
# model instead of using a multi-line, marker-prefixed list.
mark = lambda m: f"[{m}]" if m == self.provider.model else m # noqa: E731
listing = ", ".join(mark(m) for m in models)
return f"{self.provider.name} models ([active]): {listing}"
async def _answer(self, ws, question: str, asker: str) -> None:
canned = self._command_reply(question)
if canned is not None:
await self._send_chat(ws, canned)
self.success(f"answered /ai {question.strip().lower()} for {asker}")
return
self.transcript.append(Msg("user", f"{asker}: {question}"))
await self._send_typing(ws, True)
try:
@ -77,7 +114,7 @@ class AgentBridge(Client):
await self._send_typing(ws, False)
reply = reply.strip() or "[empty reply]"
self.transcript.append(Msg("assistant", reply))
await ws.send(self.room_fernet.encrypt(reply.encode()).decode())
await self._send_chat(ws, reply)
self.success(f"replied to {asker}")
async def run_async(self) -> None:

102
cmd_chat/agent/profiles.py Normal file
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@ -0,0 +1,102 @@
"""Named model profiles for the hack-house AI agent.
A *profile* maps a friendly name (``groq-llama``, ``local``, ``claude``) to a
provider + model + endpoint, so operators type ``--profile groq-llama`` instead
of remembering ``--provider openai --base-url … --model …``. This mirrors the
``models:`` list in Continue.dev and the ``model_list`` in a LiteLLM proxy:
each entry is ``{provider, model, base_url, api_key_env}``.
Secrets are **never** stored here — ``api_key_env`` names an environment
variable to read the key from, keeping the file safe to commit and share.
Lookup order (first hit wins):
1. ``$HH_MODELS_FILE``
2. ``./models.toml`` (cwd)
3. ``~/.config/hh/models.toml``
"""
from __future__ import annotations
import os
from pathlib import Path
try: # stdlib on 3.11+, falls back to the `tomli` backport on 3.10
import tomllib
except ModuleNotFoundError: # pragma: no cover
import tomli as tomllib # type: ignore[no-redef]
from .providers import Provider, make_provider
_RECOGNIZED = {"provider", "model", "base_url", "host", "api_key_env",
"system", "context_window"}
def _candidate_paths(explicit: str | None) -> list[Path]:
if explicit:
return [Path(explicit).expanduser()]
paths = []
env = os.environ.get("HH_MODELS_FILE")
if env:
paths.append(Path(env).expanduser())
paths.append(Path.cwd() / "models.toml")
paths.append(Path.home() / ".config" / "hh" / "models.toml")
return paths
def find_profiles_file(explicit: str | None = None) -> Path | None:
for p in _candidate_paths(explicit):
if p.is_file():
return p
return None
def load_profiles(explicit: str | None = None) -> dict[str, dict]:
"""Return ``{name: profile_dict}`` from the first models.toml found."""
path = find_profiles_file(explicit)
if path is None:
return {}
with path.open("rb") as fh:
data = tomllib.load(fh)
profiles: dict[str, dict] = {}
for name, body in data.items():
if not isinstance(body, dict) or "provider" not in body:
continue # skip non-profile tables / malformed entries
unknown = set(body) - _RECOGNIZED
if unknown:
raise ValueError(
f"profile '{name}': unknown key(s) {', '.join(sorted(unknown))}"
)
profiles[name] = body
return profiles
def provider_from_profile(prof: dict, *, name: str = "?",
model: str | None = None,
base_url: str | None = None) -> Provider:
"""Build a :class:`Provider` from a profile dict.
``model`` / ``base_url`` (CLI flags) override the profile when given. The
api key is read from ``$<api_key_env>`` and passed only to providers that
accept one, so an Ollama profile never sees a stray ``api_key`` kwarg.
"""
spec = prof["provider"]
custom = ":" in spec
opts: dict = {}
mdl = model or prof.get("model")
bu = base_url or prof.get("base_url")
if bu and (spec == "openai" or custom):
opts["base_url"] = bu
if spec == "ollama" and prof.get("host"):
opts["host"] = prof["host"]
key_env = prof.get("api_key_env")
if key_env and (spec in ("openai", "anthropic") or custom):
key = os.environ.get(key_env)
if not key:
raise SystemExit(
f"profile '{name}': ${key_env} is not set — export it first"
)
opts["api_key"] = key
return make_provider(spec, model=mdl, **opts)

53
cmd_chat/agent/providers.py
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@ -30,6 +30,11 @@ class Provider(Protocol):
def complete(self, system: str, messages: list[Msg]) -> str:
...
# Optional: list models the backend can serve, for discovery/preflight.
# Providers that can't enumerate (e.g. a bespoke endpoint) may omit this.
def available_models(self) -> list[str]:
...
class OllamaProvider:
"""Local Ollama (default, recommended). No API key — privacy-preserving."""
@ -52,6 +57,11 @@ class OllamaProvider:
r.raise_for_status()
return (r.json().get("message", {}).get("content") or "").strip()
def available_models(self) -> list[str]:
r = requests.get(f"{self.host}/api/tags", timeout=self.timeout)
r.raise_for_status()
return [m.get("name", "") for m in r.json().get("models", [])]
class AnthropicProvider:
"""Anthropic Messages API. Cloud — opt-in. Needs ANTHROPIC_API_KEY."""
@ -92,6 +102,15 @@ class AnthropicProvider:
blocks = r.json().get("content", [])
return "".join(b.get("text", "") for b in blocks).strip()
def available_models(self) -> list[str]:
r = requests.get(
"https://api.anthropic.com/v1/models",
timeout=self.timeout,
headers={"x-api-key": self.api_key, "anthropic-version": "2023-06-01"},
)
r.raise_for_status()
return [m.get("id", "") for m in r.json().get("data", [])]
class OpenAICompatibleProvider:
"""OpenAI-style /chat/completions — OpenAI, Groq, Together, local vLLM, etc."""
@ -120,6 +139,14 @@ class OpenAICompatibleProvider:
r.raise_for_status()
return r.json()["choices"][0]["message"]["content"].strip()
def available_models(self) -> list[str]:
headers = {}
if self.api_key:
headers["authorization"] = f"Bearer {self.api_key}"
r = requests.get(f"{self.base_url}/models", headers=headers, timeout=self.timeout)
r.raise_for_status()
return [m.get("id", "") for m in r.json().get("data", [])]
_BUILTINS = {
"ollama": OllamaProvider,
@ -144,3 +171,29 @@ def make_provider(spec: str, model: str | None = None, **opts) -> Provider:
if model is not None:
opts["model"] = model
return cls(**opts)
def preflight(provider: Provider) -> tuple[bool, str]:
"""Cheap reachability + model-presence check before joining a room.
Returns ``(ok, message)``. Lets ``/ai start`` fail fast with a clear reason
(backend down / model not pulled / key missing) instead of erroring on the
first question. Providers without ``available_models`` are assumed reachable.
"""
discover = getattr(provider, "available_models", None)
if discover is None:
return True, f"{provider.name}: no discovery endpoint — assuming reachable"
try:
models = discover()
except Exception as e: # noqa: BLE001 — any failure means "not reachable yet"
return False, f"{provider.name}: cannot reach backend ({e})"
if provider.model in models:
return True, f"{provider.name}/{provider.model}: reachable"
if models:
sample = ", ".join(models[:8])
more = "…" if len(models) > 8 else ""
return False, (
f"{provider.name}: model '{provider.model}' not available. "
f"reachable models: {sample}{more}"
)
return True, f"{provider.name}: reachable (empty model list — skipping check)"

126
docs/providers.md Normal file
View File

@ -0,0 +1,126 @@
# Connecting any model — provider guide
The hack-house AI agent is **model-agnostic**: a *provider* is anything that can
turn a system prompt + a conversation into one reply string. You can use a
bundled adapter, point an OpenAI-compatible adapter at any endpoint, name a
reusable profile, or drop in a provider you wrote yourself.
> Design note: this mirrors the BYO-model conventions used in the wider
> ecosystem — a named `models:` list with `{provider, model, apiBase, apiKey}`
> entries (Continue.dev) and a `model_list` of `{model, api_base, api_key}`
> behind one unified interface (LiteLLM, which `aider` builds on). One thin
> adapter for the OpenAI `/chat/completions` shape covers most backends.
---
## 1. The fastest path — a named profile
Add (or edit) `models.toml` in the repo root (or `~/.config/hh/models.toml`):
```toml
[groq-llama]
provider = "openai"
base_url = "https://api.groq.com/openai/v1"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
```
Export the key, then start the agent by name:
```bash
export GROQ_API_KEY=sk-...
python -m cmd_chat.agent <host> <port> --profile groq-llama --password <pw> --no-tls
# or from the TUI: /ai start groq-llama
```
`api_key_env` names an **environment variable**, never the key itself, so
`models.toml` is safe to commit and share. Lookup order for the file:
`$HH_MODELS_FILE` → `./models.toml` → `~/.config/hh/models.toml` (override with
`--models-file`).
Profile keys: `provider` (required), `model`, `base_url`, `host` (Ollama),
`api_key_env`, `system`, `context_window`. CLI `--model` / `--base-url` override
the profile.
## 2. Without a profile — explicit flags
```bash
# local Ollama (default, private — no key)
python -m cmd_chat.agent <host> <port> --provider ollama --model qwen2.5:3b --no-tls
# any OpenAI-compatible endpoint (OpenAI, Groq, Together, vLLM, LM Studio, llama.cpp…)
python -m cmd_chat.agent <host> <port> --provider openai \
--base-url https://api.together.xyz/v1 --model <id>
# Anthropic
ANTHROPIC_API_KEY=sk-ant-... python -m cmd_chat.agent <host> <port> \
--provider anthropic --model claude-opus-4-6
```
Built-in providers: `ollama`, `anthropic`, `openai`. The `openai` adapter is the
universal one — most backends speak `/chat/completions`, so "any model" is
usually just `base_url` + `model` + a key.
## 3. Discovery & preflight
Check a backend before joining a room (neither joins):
```bash
python -m cmd_chat.agent --profile groq-llama --list-models # enumerate models
python -m cmd_chat.agent --profile groq-llama --check # exit 0 ok / 1 fail
```
On a normal start the agent runs a non-fatal preflight and prints a `⚠ preflight`
warning if the backend is unreachable or the model isn't pulled — so you find out
immediately, not on the first question. In-room:
- `/ai list` — each present agent answers with its roster line
(`name (ai) — provider/model, context N`); use it to find an agent's name
before addressing it with `/ai <name> <question>`.
- `/ai models` — the active agent lists what its backend can serve
(`*` marks the active model).
## 4. Bring your own provider
Implement three things — `name`, `model`, and `complete()`:
```python
class MyProvider:
name = "mine"
def __init__(self, model: str = "my-default"):
self.model = model
def complete(self, system: str, messages: list) -> str:
# messages: list of objects with .role ("user"/"assistant") and .content
...
return "the reply"
def available_models(self) -> list[str]: # optional: powers discovery/preflight
return ["my-default"]
```
Point the agent at it with `module:Class` (no repo changes needed):
```bash
python -m cmd_chat.agent <host> <port> --provider mypkg.mymodule:MyProvider
```
or reference it from a profile:
```toml
[mine]
provider = "mypkg.mymodule:MyProvider"
model = "my-default"
```
A complete, runnable example lives in
[`examples/echo_provider.py`](../examples/echo_provider.py):
```bash
python -m cmd_chat.agent <host> <port> --no-tls --password <pw> \
--provider examples.echo_provider:EchoProvider
```
`available_models()` is optional — implement it to light up `--list-models`,
`--check`, and `/ai models`; omit it and those degrade gracefully.

34
examples/echo_provider.py Normal file
View File

@ -0,0 +1,34 @@
"""Minimal bring-your-own Provider example.
A Provider just turns (system prompt + messages) into one reply string. Anything
with ``name``, ``model`` and a ``complete()`` method qualifies — no base class,
no SDK. Point the agent at it with the ``module:Class`` spec:
python -m cmd_chat.agent 127.0.0.1 3000 --no-tls --password hunter2 \
--provider examples.echo_provider:EchoProvider
or via models.toml:
[echo]
provider = "examples.echo_provider:EchoProvider"
model = "echo-1"
Implementing ``available_models()`` is optional; it powers ``--list-models``,
``--check`` preflight, and the in-room ``/ai models`` command.
"""
from __future__ import annotations
class EchoProvider:
name = "echo"
def __init__(self, model: str = "echo-1"):
self.model = model
def complete(self, system: str, messages: list) -> str:
last = messages[-1].content if messages else ""
return f"echo: {last}"
def available_models(self) -> list[str]: # optional
return ["echo-1"]

108
hh/src/app.rs
View File

@ -96,6 +96,8 @@ pub enum Net {
name: String,
on: bool,
},
/// A local system notice produced off-thread (e.g. async Ollama probe).
Sys(String),
Err(String),
Closed,
}
@ -298,6 +300,7 @@ impl App {
self.sudoers = sudo;
}
Net::Ft(_) => {} // handled in the run loop (needs out channel + disk)
Net::Sys(t) => self.sys(t),
Net::Err(t) => self.err(t),
Net::Closed => {
self.connected = false;
@ -1108,24 +1111,102 @@ fn handle_command(
if agent.is_some() {
app.sys("an AI agent is already running from this client — /ai stop first");
} else {
let m = rest.trim();
let model = if m.is_empty() { "qwen2.5:3b" } else { m };
let arg = rest.trim();
// A bare name (no ':' tag, no '/' path) is a models.toml profile;
// anything else is treated as a literal Ollama model tag.
let (profile, model): (Option<&str>, &str) = if arg.is_empty() {
(None, "qwen2.5:3b")
} else if arg.contains(':') || arg.contains('/') {
(None, arg)
} else {
(Some(arg), arg)
};
let name = "oracle";
match spawn_agent(params, &app.password, name, model) {
match spawn_agent(params, &app.password, name, profile, model) {
Ok(child) => {
*agent = Some(child);
let desc = match profile {
Some(p) => format!("profile {p}"),
None => format!("ollama/{model}"),
};
app.sys(format!(
"⛧ summoning {name} (ollama/{model})… it will announce when online"
"⛧ summoning {name} ({desc})… it will announce when online"
));
}
Err(e) => app.err(format!("/ai start failed: {e}")),
}
}
} else if line == "/ai list" || line == "/ai models" {
// Reap an agent that already exited so we don't forward into a dead pipe.
if agent
.as_mut()
.is_some_and(|c| matches!(c.try_wait(), Ok(Some(_))))
{
*agent = None;
}
if agent.is_some() {
// A live agent answers these itself (canned, zero model-call).
let _ = out_tx.send(WsMsg::Text(room.encrypt(line.as_bytes())));
} else if line == "/ai list" {
app.sys("no AI agent running from this client — /ai start to summon one");
} else {
// No agent: still useful to show what could be started locally.
app.sys("querying local ollama…");
let tx = app_tx.clone();
tokio::task::spawn_blocking(move || {
let msg = match local_ollama_models() {
Ok(ms) if !ms.is_empty() => format!(
"local ollama models (start one with `/ai start <name>`): {}",
ms.join(", ")
),
Ok(_) => "ollama is reachable but has no models pulled — \
`ollama pull qwen2.5:3b` or run ./bootstrap-ai.sh"
.to_string(),
Err(_) => "ollama not reachable at localhost:11434 — run \
./bootstrap-ai.sh, or `/ai start <profile>` for a cloud model"
.to_string(),
};
let _ = tx.send(Net::Sys(msg));
});
}
} else if !line.is_empty() && app.connected {
let _ = out_tx.send(WsMsg::Text(room.encrypt(line.as_bytes())));
}
}
/// Probe the local Ollama daemon for installed model tags. Used to answer
/// `/ai models` before any agent is summoned (the agentless path); a running
/// agent answers in-room instead. Honors `$OLLAMA_HOST`.
fn local_ollama_models() -> Result<Vec<String>, String> {
let host = std::env::var("OLLAMA_HOST")
.ok()
.filter(|h| !h.is_empty())
.unwrap_or_else(|| "http://localhost:11434".to_string());
let host = host.trim_end_matches('/');
let url = format!("{host}/api/tags");
let client = reqwest::blocking::Client::builder()
.timeout(std::time::Duration::from_millis(1500))
.build()
.map_err(|e| e.to_string())?;
let body: serde_json::Value = client
.get(&url)
.send()
.map_err(|e| e.to_string())?
.json()
.map_err(|e| e.to_string())?;
let models = body
.get("models")
.and_then(|m| m.as_array())
.map(|arr| {
arr.iter()
.filter_map(|m| m.get("name").and_then(|n| n.as_str()))
.map(str::to_string)
.collect()
})
.unwrap_or_default();
Ok(models)
}
#[allow(clippy::too_many_arguments)]
fn spawn_launch(
backend: sbx::Backend,
@ -1214,6 +1295,7 @@ fn spawn_agent(
params: &net::ConnParams,
password: &str,
name: &str,
profile: Option<&str>,
model: &str,
) -> std::result::Result<std::process::Child, String> {
use std::process::{Command, Stdio};
@ -1238,12 +1320,18 @@ fn spawn_agent(
.arg(&params.ip)
.arg(params.port.to_string())
.arg("--name")
.arg(name)
.arg("--provider")
.arg("ollama")
.arg("--model")
.arg(model)
.stdin(Stdio::null())
.arg(name);
// A profile carries its own provider/model/endpoint from models.toml;
// otherwise summon a local Ollama model by tag.
match profile {
Some(p) => {
cmd.arg("--profile").arg(p);
}
None => {
cmd.arg("--provider").arg("ollama").arg("--model").arg(model);
}
}
cmd.stdin(Stdio::null())
.stdout(Stdio::from(log))
.stderr(Stdio::from(log_err));
if !password.is_empty() {

6
hh/src/ui.rs
View File

@ -129,14 +129,16 @@ fn draw_help(f: &mut Frame, area: Rect, theme: &Theme) {
kv("/sbx stop", "tear down the sandbox (purges the VM)"),
kv("/drive", "type into the shared shell (Esc releases)"),
kv(
"/ai start [model]",
"spawn a local AI agent (default ollama/qwen2.5:3b)",
"/ai start [model|profile]",
"spawn an AI agent (ollama model tag, or a models.toml profile)",
),
kv("/ai stop", "dismiss the agent you started"),
kv(
"/ai <question>",
"ask an AI agent in the room (/ai <name> <q> if many)",
),
kv("/ai list", "list AI agents present + their provider/model"),
kv("/ai models", "show models the active agent's backend can serve"),
kv(
"/grant <user>",
"let a member drive the shell (owner)",

55
models.toml Normal file
View File

@ -0,0 +1,55 @@
# hack-house model profiles
# ---------------------------------------------------------------------------
# Each table is a named profile. Select one with:
# python -m cmd_chat.agent <host> <port> --profile groq-llama --password <pw>
# or from the TUI:
# /ai start groq-llama
#
# Keys:
# provider ollama | anthropic | openai | <module>:<Class> (required)
# model model name the backend serves
# base_url endpoint for openai-compatible backends (Groq, vLLM, …)
# host override Ollama host (default http://localhost:11434)
# api_key_env NAME of an env var holding the key — never the key itself
# system optional system-prompt override
# context_window optional int (default 12)
#
# Secrets live in the environment, never in this file, so it is safe to commit.
# --- local, private, default --------------------------------------------------
[local]
provider = "ollama"
model = "qwen2.5:3b"
[local-big]
provider = "ollama"
model = "llama3.1:8b"
# --- openai-compatible clouds (one adapter, any endpoint) ---------------------
[groq-llama]
provider = "openai"
base_url = "https://api.groq.com/openai/v1"
model = "llama-3.3-70b-versatile"
api_key_env = "GROQ_API_KEY"
[together]
provider = "openai"
base_url = "https://api.together.xyz/v1"
model = "meta-llama/Llama-3.3-70B-Instruct-Turbo"
api_key_env = "TOGETHER_API_KEY"
[openai]
provider = "openai"
model = "gpt-4o-mini"
api_key_env = "OPENAI_API_KEY"
# --- anthropic ----------------------------------------------------------------
[claude]
provider = "anthropic"
model = "claude-opus-4-6"
api_key_env = "ANTHROPIC_API_KEY"
# --- bring your own -----------------------------------------------------------
# [my-model]
# provider = "mypkg.mymodule:MyProvider"
# model = "whatever-your-class-expects"