Files
Pyra/src/pyra/setup/wizard.py
T
curo1305 019e8044a9 feat(setup): model re-entry, status indicator, and resumable setup wizard
- _test_connection() now returns the (possibly changed) model name and
  offers a "Change model" option when the error is model-related
- _show_local_model_status() prints which models are currently loaded
  immediately after selecting a local provider
- Draft persistence: each completed wizard step is saved to
  ~/.pyra/setup.draft.json (chmod 600); on the next run a yellow panel
  summarises progress and offers [Resume / Start fresh]; draft is
  deleted on successful completion or Ctrl-C with no completed steps

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
2026-05-19 13:43:49 +02:00

568 lines
20 KiB
Python

import contextlib
import json
import httpx
import questionary
from rich.console import Console
from rich.panel import Panel
from rich.text import Text
from pyra.config.manager import save_config
from pyra.config.schema import GeneralConfig, ProviderConfig, PyraConfig
from pyra.setup.providers import PROVIDERS, Provider, get_provider
from pyra.utils.paths import pyra_home, safe_chmod
console = Console()
_USE_CASE_PLUGINS: dict[str, list[str]] = {
"Research & web": ["websearch", "headless_browser"],
"Development & servers": ["server_manager", "ssh_tool", "docker_tool"],
"File management": ["gdrive", "onedrive", "dropbox_tool"],
"Communication bots": ["matrix_bot", "telegram_bot", "signal_bot"],
"Email": ["email"],
"Productivity & calendars": ["nextcloud"],
}
_DRAFT_FILE = "setup.draft.json"
def _draft_path():
return pyra_home() / _DRAFT_FILE
def _save_draft(state: dict) -> None:
path = _draft_path()
path.write_text(json.dumps(state, indent=2))
safe_chmod(path, 0o600)
def _load_draft() -> dict | None:
path = _draft_path()
if not path.exists():
return None
try:
return json.loads(path.read_text())
except Exception:
return None
def _delete_draft() -> None:
with contextlib.suppress(FileNotFoundError):
_draft_path().unlink()
def _mark_step_done(state: dict, step: str) -> None:
state.setdefault("completed_steps", [])
if step not in state["completed_steps"]:
state["completed_steps"].append(step)
def _offer_resume(draft: dict) -> bool:
"""Show a summary of the incomplete setup and ask Resume / Start fresh."""
completed = draft.get("completed_steps", [])
step_display = {
"profile": f"Profile: {draft.get('user_name', '?')}",
"provider": f"Provider: {draft.get('provider_id', '?')}",
"model": f"Model: {draft.get('model', '?')}",
"api_key": "API key: stored in vault",
"connection": "Connection: test passed",
}
lines = ["[bold]An incomplete setup was found.[/bold]\n"]
for step, label in step_display.items():
if step in completed:
lines.append(f" [green]✓[/green] {label}")
else:
lines.append(f" [dim]○ {label.split(':')[0].strip()}: pending[/dim]")
console.print(Panel("\n".join(lines), title="Incomplete setup", border_style="yellow"))
console.print()
action = questionary.select(
"What would you like to do?",
choices=[
questionary.Choice("Resume from where you left off", value="resume"),
questionary.Choice("Start fresh", value="fresh"),
],
).ask()
if action is None:
raise SystemExit(0)
return action == "resume"
def run_setup() -> None:
console.print(Panel(
Text("Welcome to Pyra Setup", justify="center", style="bold cyan"),
subtitle="Personal AI Assistant",
border_style="cyan",
))
console.print()
state: dict = {}
draft = _load_draft()
if draft:
if _offer_resume(draft):
state = draft
else:
_delete_draft()
try:
# ── Step 1: profile ────────────────────────────────────────────────
if "profile" in state.get("completed_steps", []):
user_name = state["user_name"]
purpose = state["purpose"]
use_cases = state["use_cases"]
console.print(f" [dim]✓ Profile: {user_name}[/dim]")
else:
user_name, purpose, use_cases = _collect_user_profile()
state.update(user_name=user_name, purpose=purpose, use_cases=use_cases)
_mark_step_done(state, "profile")
_save_draft(state)
# ── Step 2: provider ───────────────────────────────────────────────
if "provider" in state.get("completed_steps", []):
provider = get_provider(state["provider_id"])
console.print(f" [dim]✓ Provider: {provider.display_name}[/dim]")
else:
provider = _choose_provider()
state.update(provider_id=provider.id)
_mark_step_done(state, "provider")
_save_draft(state)
# ── Step 3: model ──────────────────────────────────────────────────
if "model" in state.get("completed_steps", []):
model = state["model"]
console.print(f" [dim]✓ Model: {model}[/dim]")
else:
model = _choose_model(provider)
state.update(model=model)
_mark_step_done(state, "model")
_save_draft(state)
# ── Step 4: API key ────────────────────────────────────────────────
if "api_key" not in state.get("completed_steps", []) and provider.requires_key:
from pyra.vault.reader import get_key as _get_key
if not _get_key(provider.id):
_collect_api_key(provider)
_mark_step_done(state, "api_key")
_save_draft(state)
# ── Step 5: connection test ────────────────────────────────────────
if "connection" not in state.get("completed_steps", []):
model = _test_connection(provider, model)
state["model"] = model
_mark_step_done(state, "connection")
_save_draft(state)
# ── Finalise ───────────────────────────────────────────────────────
cfg = PyraConfig(
ai=ProviderConfig(
provider_id=provider.id,
model=model,
base_url=provider.base_url,
),
general=GeneralConfig(user_name=user_name, purpose=purpose),
)
save_config(cfg)
_delete_draft()
_suggest_plugins(use_cases)
console.print()
console.print(Panel(
f"[green]Setup complete![/green]\n\n"
f"Provider: [bold]{provider.display_name}[/bold]\n"
f"Model: [bold]{model}[/bold]\n\n"
"Run [bold cyan]pyra chat[/bold cyan] to start talking.",
border_style="green",
))
except SystemExit:
if state.get("completed_steps"):
console.print()
console.print(
" [dim]Setup paused — run [bold]pyra setup[/bold] to resume.[/dim]"
)
raise
def _collect_user_profile() -> tuple[str, str, list[str]]:
console.print("[bold]Let's personalise your setup.[/bold]")
console.print()
name = questionary.text("What should Pyra call you?", default="User").ask()
if name is None:
raise SystemExit(0)
name = name.strip() or "User"
purpose = questionary.text(
"In one sentence, what will you mainly use Pyra for? (optional)",
).ask()
if purpose is None:
raise SystemExit(0)
purpose = purpose.strip()
use_cases = questionary.checkbox(
"Which areas interest you? (Space to select, Enter to confirm)",
choices=list(_USE_CASE_PLUGINS.keys()),
).ask()
if use_cases is None:
raise SystemExit(0)
console.print()
return name, purpose, use_cases or []
def _suggest_plugins(use_cases: list[str]) -> None:
if not use_cases:
return
lines: list[str] = []
for uc in use_cases:
plugins = _USE_CASE_PLUGINS.get(uc, [])
if plugins:
lines.append(f"[bold]{uc}[/bold]")
for p in plugins:
lines.append(f" pyra plugin install {p}")
if not lines:
return
lines.append("")
lines.append("[dim]All listed plugins are in development — install when available.[/dim]")
console.print()
console.print(Panel(
"\n".join(lines),
title="Suggested plugins",
border_style="dim cyan",
))
def _choose_provider() -> Provider:
local = [p for p in PROVIDERS if p.group == "Local"]
cloud = [p for p in PROVIDERS if p.group == "Cloud"]
choices = (
[questionary.Choice("── Local ──────────────────", disabled=True)]
+ [questionary.Choice(p.display_name, value=p.id) for p in local]
+ [questionary.Choice("── Cloud ──────────────────", disabled=True)]
+ [questionary.Choice(p.display_name, value=p.id) for p in cloud]
)
provider_id = questionary.select(
"Choose your AI provider:",
choices=choices,
).ask()
if provider_id is None:
raise SystemExit(0)
provider = get_provider(provider_id)
if provider.connectivity_check:
_check_local_server(provider)
_show_local_model_status(provider)
return provider
def _classify_error(exc: Exception) -> tuple[str, str]:
"""Return (short_label, resolution_hint) for a provider or network error."""
name = type(exc).__name__
module = type(exc).__module__ or ""
is_llm = "litellm" in module or "openai" in module
if is_llm:
if "AuthenticationError" in name:
return (
"Invalid API key",
"The provider rejected your API key.\n"
"Double-check it on the provider dashboard and re-enter it.",
)
if "NotFoundError" in name:
return (
"Model not found",
"The model name doesn't exist for this provider.\n"
"Check the exact model identifier on the provider's model list.",
)
if "RateLimitError" in name:
return (
"Rate limit reached",
"You've exceeded the provider's request rate.\n"
"Wait a few seconds and retry.",
)
if "ServiceUnavailable" in name:
return (
"Service temporarily unavailable",
"The provider's servers returned a 5xx error.\n"
"This is usually transient — wait a minute and retry.",
)
if "APIConnectionError" in name or "ConnectError" in name:
return (
"Cannot reach provider",
"A network error prevented the connection.\n"
"Check your internet connection and firewall settings.",
)
if "Timeout" in name:
return (
"Request timed out",
"The provider did not respond in time.\n"
"The service may be overloaded — retry in a moment.",
)
if "BadRequestError" in name or "InvalidRequest" in name:
return (
"Bad request",
"The request was rejected — the model name or parameters may be wrong.\n"
"Verify the exact model identifier.",
)
return ("Provider error", str(exc)[:300])
if "httpx" in module:
if "ConnectError" in name or "ConnectTimeout" in name:
return (
"Server not reachable",
"Could not connect to the local server.\n"
"Make sure it is running and listening on the expected address.",
)
if "Timeout" in name:
return (
"Connection timed out",
"The local server did not respond in time.\n"
"It may still be starting up — wait a moment and retry.",
)
if "HTTPStatusError" in name:
code = getattr(getattr(exc, "response", None), "status_code", 0)
if code == 401:
return ("Unauthorized (401)", "The server requires credentials that were not provided.")
if code == 404:
return ("Endpoint not found (404)", "The API endpoint was not found — check the server version.")
return (f"HTTP {code}", f"The server returned an unexpected error (HTTP {code}).")
return ("Unexpected error", str(exc)[:300])
def _check_local_server(provider: Provider) -> None:
while True:
console.print(
f" Checking connection to [bold]{provider.display_name}[/bold]...", end=" "
)
try:
resp = httpx.get(provider.connectivity_check, timeout=3.0)
resp.raise_for_status()
console.print("[green]✓[/green]")
return
except Exception as exc:
label, hint = _classify_error(exc)
console.print("[yellow]✗[/yellow]")
console.print()
console.print(Panel(
f"[bold yellow]{label}[/bold yellow]\n\n{hint}",
title="Connection problem",
border_style="yellow",
))
action = questionary.select(
"How would you like to proceed?",
choices=[
questionary.Choice("Retry", value="retry"),
questionary.Choice(
"Continue anyway (model list may be unavailable)", value="continue"
),
questionary.Choice("Abort setup", value="abort"),
],
).ask()
if action is None or action == "abort":
raise SystemExit(0)
if action == "continue":
return
# "retry" → loop
def _show_local_model_status(provider: Provider) -> None:
"""Print a one-line status showing which models are currently loaded."""
models = _fetch_local_models(provider)
if not models:
console.print(" [yellow]No model currently loaded[/yellow]")
elif len(models) == 1:
console.print(f" [green]Loaded model:[/green] {models[0]}")
else:
names = ", ".join(models)
console.print(f" [green]{len(models)} models loaded:[/green] {names}")
def _fetch_local_models(provider: Provider) -> list[str]:
"""Return currently loaded/available models from a local provider's API."""
if not provider.base_url:
return []
try:
if provider.id == "ollama":
resp = httpx.get(f"{provider.base_url}/api/tags", timeout=3.0)
resp.raise_for_status()
return [m["name"] for m in resp.json().get("models", [])]
else:
resp = httpx.get(f"{provider.base_url}/models", timeout=3.0)
resp.raise_for_status()
return [m["id"] for m in resp.json().get("data", [])]
except Exception:
return []
def _fetch_lmstudio_available_models() -> list[str]:
"""Return all downloaded (not necessarily loaded) models from LM Studio's beta API."""
try:
resp = httpx.get("http://localhost:1234/api/v0/models", timeout=3.0)
resp.raise_for_status()
return [m["id"] for m in resp.json().get("data", [])]
except Exception:
return []
def _load_lmstudio_model(model_id: str) -> bool:
"""Attempt to load a model via LM Studio's beta API. Returns True on success."""
try:
resp = httpx.post(
"http://localhost:1234/api/v0/models/load",
json={"identifier": model_id},
timeout=60.0,
)
return resp.is_success
except Exception:
return False
def _choose_model(provider: Provider) -> str:
if provider.group != "Local":
model = questionary.text("Model name:", default=provider.default_model).ask()
if model is None:
raise SystemExit(0)
return model.strip()
_MANUAL = "__manual__"
loaded = _fetch_local_models(provider)
if loaded:
choices = loaded + [questionary.Choice("── Enter manually ──", value=_MANUAL)]
selected = questionary.select("Select model:", choices=choices).ask()
if selected is None:
raise SystemExit(0)
if selected != _MANUAL:
return selected
elif provider.id == "lmstudio":
console.print(" [yellow]No model currently loaded in LM Studio.[/yellow]")
available = _fetch_lmstudio_available_models()
if available:
choices = available + [questionary.Choice("── Enter manually ──", value=_MANUAL)]
selected = questionary.select(
"Select a downloaded model to load:", choices=choices
).ask()
if selected is None:
raise SystemExit(0)
if selected != _MANUAL:
console.print(f" Loading [bold]{selected}[/bold]...", end=" ")
if _load_lmstudio_model(selected):
console.print("[green]✓ Loaded[/green]")
else:
console.print(
"[yellow]Could not load via API — "
"please load the model manually in LM Studio.[/yellow]"
)
return selected
else:
console.print(Panel(
"No models are loaded or downloaded in LM Studio.\n"
"Open LM Studio → Local Server tab → load a model, then re-run setup.",
border_style="yellow",
))
else:
console.print(f" [yellow]No models found at {provider.base_url}.[/yellow]")
model = questionary.text("Model name:", default=provider.default_model).ask()
if model is None:
raise SystemExit(0)
return model.strip()
def _collect_api_key(provider: Provider) -> None:
from pyra.vault.writer import set_key
console.print(
f"\n [dim]API key will be stored in the encrypted vault — never in config.yaml[/dim]"
)
key = questionary.password(f"Enter your {provider.display_name} API key:").ask()
if key is None:
raise SystemExit(0)
key = key.strip()
if not key:
console.print("[red]No key entered — skipping.[/red]")
return
set_key(provider.id, key)
console.print(" [green]✓ Key stored in vault[/green]")
def _test_connection(provider: Provider, model: str) -> str:
from pyra.vault.reader import get_key
while True:
console.print("\n Running connection test...", end=" ")
try:
import litellm
api_key = get_key(provider.id) if provider.requires_key else "local"
kwargs: dict = {
"model": f"{provider.litellm_prefix}{model}",
"messages": [{"role": "user", "content": "Reply with exactly: OK"}],
"max_tokens": 10,
"api_key": api_key,
}
if provider.base_url:
kwargs["api_base"] = provider.base_url
litellm.completion(**kwargs)
console.print("[green]✓ Connection OK[/green]")
return model
except Exception as exc:
label, hint = _classify_error(exc)
console.print("[red]✗[/red]")
console.print()
console.print(Panel(
f"[bold red]{label}[/bold red]\n\n{hint}",
title="Test call failed",
border_style="red",
))
exc_name = type(exc).__name__
is_auth_error = "AuthenticationError" in exc_name
is_model_error = any(
kw in exc_name for kw in ("NotFoundError", "BadRequestError", "InvalidRequest")
)
choices = [questionary.Choice("Retry", value="retry")]
if is_model_error:
choices.append(questionary.Choice("Change model", value="change_model"))
if provider.requires_key and is_auth_error:
choices.append(questionary.Choice("Re-enter API key", value="rekey"))
choices += [
questionary.Choice("Skip test and continue setup", value="skip"),
questionary.Choice("Abort setup", value="abort"),
]
action = questionary.select(
"How would you like to proceed?",
choices=choices,
).ask()
if action is None or action == "abort":
raise SystemExit(0)
if action == "skip":
console.print(
" [dim]Test skipped — run [bold]pyra setup[/bold] again if chat doesn't work.[/dim]"
)
return model
if action == "change_model":
model = _choose_model(provider)
elif action == "rekey":
_collect_api_key(provider)
# loop → retry (with possibly new model or key)