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import argparse
import os
import sys
from pathlib import Path
from typing import List, Optional
from rich.console import Console
from rich.panel import Panel
from rich.prompt import Prompt, Confirm
from rich.rule import Rule
from rooms.config import SessionConfig, AgentConfig, SessionType, ModelType
from rooms.agent import Agent
from rooms.session import Session
from rooms.storage import save_transcript
from rooms.skills_cli import list_skills, inspect_skill, suggest_skills
from rooms.env import bootstrap_environment
from rooms.settings import (
RoomsSettings,
SettingsError,
load_settings,
get_default_personas,
init_settings_file,
reset_settings_file,
find_settings_file,
EXAMPLE_SETTINGS_FILENAME,
USER_SETTINGS_FILENAME,
)
console = Console()
def _set_session_env_key(tracked_keys: List[str], key_name: str, value: str) -> None:
"""Set a wizard-provided secret and track it for cleanup. Skips if the key already exists."""
if not key_name or key_name in os.environ:
return
os.environ[key_name] = value
tracked_keys.append(key_name)
def _prompt_api_key_if_needed(tracked_keys: List[str], key_prompt: str = "Enter the environment variable name (e.g. OPENAI_API_KEY, ANTHROPIC_API_KEY)") -> None:
"""Prompt for an API key env var when the model needs one; track keys set during this session."""
if not Confirm.ask("Does this model require an API Key?"):
return
key_name = Prompt.ask(key_prompt)
if key_name and key_name not in os.environ:
_set_session_env_key(tracked_keys, key_name, Prompt.ask(f"Enter your {key_name}", password=True))
def _cleanup_session_env(tracked_keys: List[str]) -> None:
"""Remove environment variables that were added by the wizard for this session."""
for key in tracked_keys:
os.environ.pop(key, None)
def create_custom_agent_wizard(settings: RoomsSettings, tracked_env_keys: Optional[List[str]] = None) -> AgentConfig:
"""Guided wizard to create a brand new agent."""
defaults = settings.defaults
console.print(Panel("[bold yellow]Create Custom Agent[/bold yellow]"))
name = Prompt.ask("Agent Name")
sys_prompt = Prompt.ask("System Prompt (Background, personality, rules)")
exp = Prompt.ask("Expertise keywords (comma separated, e.g., 'trading, data')")
expertise = [x.strip() for x in exp.split(',')] if exp else []
mtype_str = Prompt.ask(
"Model Type",
choices=["litellm", "custom_function"],
default="litellm"
)
config = AgentConfig(
name=name,
system_prompt=sys_prompt,
expertise=expertise,
timeout=defaults.timeout,
)
if mtype_str == "custom_function":
config.model_type = ModelType.CUSTOM_FUNCTION
config.custom_function_path = Prompt.ask("Enter full path to the .py file (e.g. ./my_model.py)")
config.custom_function_name = Prompt.ask("Enter the exact function name to call (e.g. process_inference)")
else:
config.model_type = ModelType.LITELLM
default_model = defaults.litellm_model
console.print(
"[dim]Hint: For local Ollama use your tag from `ollama list` (e.g. "
f"'{default_model}'). For OpenAI use 'gpt-4o'.[/dim]"
)
model_str = Prompt.ask("Enter LiteLLM model string", default=default_model)
config.model = model_str
if not model_str.startswith("ollama/"):
_prompt_api_key_if_needed(tracked_env_keys or [])
config.color = Prompt.ask("CLI output color (e.g. red, green, blue, cyan, magenta, yellow)", default="blue")
config.temperature = float(Prompt.ask("Generation Temperature", default=str(defaults.temperature)))
_assign_skills_in_wizard(config)
return config
def _assign_skills_in_wizard(config: AgentConfig) -> None:
"""Optional skill assignment step for custom agents."""
if not Confirm.ask("Assign Skillware skills to this agent?", default=False):
return
skills, err = list_skills()
if err:
console.print(f"[yellow]{err}[/yellow]")
if not Confirm.ask("Continue with manual skill IDs anyway?", default=False):
return
if skills:
console.print("\n[bold green]Available Skills[/bold green]")
for item in skills:
desc = item.get("description", "").strip()
suffix = f" - {desc}" if desc else ""
console.print(f"- {item['id']}{suffix}")
raw = Prompt.ask(
"Skill IDs to assign (comma separated, leave blank to skip)",
default="",
).strip()
if not raw:
return
config.skills = [item.strip() for item in raw.split(",") if item.strip()]
for skill_id in config.skills:
if Confirm.ask(f"Add runtime config overrides for {skill_id}?", default=False):
cfg_raw = Prompt.ask(
f"Enter {skill_id} overrides as key=value pairs (comma separated)",
default="",
).strip()
overrides = {}
if cfg_raw:
for pair in [p.strip() for p in cfg_raw.split(",") if p.strip()]:
if "=" in pair:
key, value = pair.split("=", 1)
overrides[key.strip()] = value.strip()
if overrides:
config.skill_settings[skill_id] = overrides
def main_menu(settings: RoomsSettings):
console.print(Panel.fit("[bold magenta]Multi-Agent Room Framework[/bold magenta]", subtitle="Advanced Scenario Wizard"))
default_personas = get_default_personas(settings)
defaults = settings.defaults
# 0. User Profile
console.print("\n[bold cyan]--- 0. Your Profile ---[/bold cyan]")
console.print("[dim]This helps agents treat you as an equal participant in the room.[/dim]")
user_name = Prompt.ask("Your name (or alias)", default=settings.user.name)
user_background = Prompt.ask(
"Brief background or role (e.g. 'CTO with 15 years in cloud infrastructure')",
default=set
10BC8
tings.user.background,
)
user_profile = {"name": user_name, "background": user_background}
tracked_env_keys: List[str] = []
# 1. Session Basics
console.print("\n[bold cyan]--- 1. Session Setup ---[/bold cyan]")
topic = Prompt.ask("Enter the Topic or Problem statement for this room")
turns = int(Prompt.ask("Max total turns for the entire session before exiting", default="20"))
session_type_str = Prompt.ask(
"Select session type (round_robin/dynamic/argumentative)",
choices=["round_robin", "dynamic", "argumentative"],
default="dynamic"
)
console.print("[dim]Agents can talk freely, but when do you want to step in?[/dim]")
hitl_turns = int(Prompt.ask("Max interactions between agents before requiring human input (0 for fully autonomous)", default="5"))
# 2. Agent Selection
console.print("\n[bold cyan]--- 2. Participant Setup ---[/bold cyan]")
active_agent_configs = []
console.print("\n[bold green]Available Default Personas:[/bold green]")
for i, a in enumerate(default_personas):
console.print(f"{i+1}. {a.name} - {a.expertise}")
for a in default_personas:
if Confirm.ask(f"Include {a.name} in this room?", default=False):
custom_instr = Prompt.ask(f"Any specific instructions for {a.name} just for this session? (Enter to skip)", default="")
temp = float(Prompt.ask(f"Temperature for {a.name}?", default=str(a.temperature)))
new_config = a.model_copy()
new_config.temperature = temp
if custom_instr.strip():
new_config.custom_instructions = custom_instr.strip()
active_agent_configs.append(new_config)
while True:
if Confirm.ask("Would you like to build and invite a Custom Agent?", default=False):
custom_agent = create_custom_agent_wizard(settings, tracked_env_keys)
active_agent_configs.append(custom_agent)
else:
break
if len(active_agent_configs) < 1:
console.print("[red]You must have at least 1 agent![/red]")
sys.exit(1)
# 3. Optional Orchestrator
console.print("\n[bold cyan]--- 3. Orchestration Setup ---[/bold cyan]")
orchestrator_config = None
if Confirm.ask("Do you want a Global Orchestrator to monitor the room and interject occasionally?", default=False):
sys_prompt = Prompt.ask(
"Orchestrator System Prompt",
default="You are the room moderator. Summarize progress or steer the agents if they go off topic. Say exactly 'PASS' if you have nothing to add."
)
model = Prompt.ask("Orchestrator Model", default=defaults.resolved_orchestrator_model)
if not model.startswith("ollama/"):
_prompt_api_key_if_needed(
tracked_env_keys,
key_prompt="Enter the environment variable name (e.g. OPENAI_API_KEY)",
)
orchestrator_config = AgentConfig(
name="System Moderator",
system_prompt=sys_prompt,
model=model,
temperature=0.3,
timeout=defaults.timeout,
color="bright_black"
)
agents = [Agent(config=ac) for ac in active_agent_configs]
session_config = SessionConfig(
topic=topic,
agents=active_agent_configs,
orchestrator=orchestrator_config,
session_type=SessionType(session_type_str),
max_turns=turns,
human_in_the_loop_turns=hitl_turns
)
console.print("\n[bold yellow]Starting Room Session...[/bold yellow]")
run_session(session_config, agents, user_profile, tracked_env_keys)
def run_session(
config: SessionConfig,
agents: list[Agent],
user_profile: dict = None,
tracked_env_keys: Optional[List[str]] = None,
):
session = Session(config, agents, user_profile=user_profile)
env_keys = tracked_env_keys if tracked_env_keys is not None else []
console.print(Panel(session.global_intro, title="System Introduction", border_style="bold grey53"))
try:
while session.turn_count < config.max_turns:
if session.needs_human_input():
console.print("")
console.rule("[bold white on dark_orange] Your Turn [/bold white on dark_orange]")
user_display_name = user_profile.get("name", "User") if user_profile else "User"
console.print("[dim]Tip: type @AgentName to force a specific agent to respond next.[/dim]")
user_msg = Prompt.ask(f"[bold white]{user_display_name}[/bold white]")
if user_msg.lower() in ['exit', 'quit']:
console.print("[yellow]Session interrupted by user.[/yellow]")
break
session.add_user_message(user_display_name, user_msg)
console.print(Panel(user_msg, title=f"[bold white]{user_display_name}[/bold white]", border_style="white", padding=(0, 1)))
console.print("[dim]Thinking...[/dim]", end="\r")
next_turn = session.generate_next_turn()
if not next_turn:
break
if next_turn.get("skipped"):
console.print(f"[dim]{next_turn['role']} passed.[/dim]", end="\r")
continue
color = next_turn.get("color", "blue")
console.print(f"\n[bold {color}]{next_turn['role']}:[/bold {color}]")
console.print(next_turn["content"])
except KeyboardInterrupt:
console.print("\n[yellow]Session interrupted via keyboard.[/yellow]")
finally:
_cleanup_session_env(env_keys)
console.print("\n[bold green]Session ended.[/bold green]")
prompt_save(session)
def prompt_save(session: Session):
console.print("\n[bold red]WARNING: Memory is ephemeral and private. If you exit, this conversation is lost.[/bold red]")
save = Confirm.ask("Do you want to save this conversation transcript locally?", default=False)
if save:
fmt = Prompt.ask("Save format", choices=["markdown", "csv"], default="markdown")
ext = "md" if fmt == "markdown" else "csv"
path = Prompt.ask("Enter directory path to save to", default="./outputs")
from rooms.storage import slugify_topic
slug = slugify_topic(session.config.topic)
default_name = f"{slug}.{ext}"
filename = Prompt.ask("Enter filename", default=default_name)
full_path = os.path.join(path, filename)
save_transcript(session.history, full_path, format=fmt)
console.print(f"[bold green]Saved securely to {full_path}[/bold green]")
else:
console.print("[bold yellow]Conversation discarded. Privacy maintained.[/bold yellow]")
def cmd_config_init(_args: argparse.Namespace) -> int:
try:
dest = init_settings_file()
console.print(f"[green]Created {dest}[/green]")
console.print(f"[dim]Edit {USER_SETTINGS_FILENAME} (see {EXAMPLE_SETTINGS_FILENAME}).[/dim]")
return 0
except SettingsError as e:
console.print(f"[red]{e}[/red]")
return 1
def cmd_config_reset(args: argparse.Namespace) -> int:
target = Path(args.path) if getattr(args, "path", None) else None
if not args.yes:
if not Confirm.ask("Remove user settings and revert to shipped defaults?", default=False):
console.print("[yellow]Cancelled.[/yellow]")
return 0
removed = reset_settings_file(target)
if removed:
console.print("[green]Settings removed. Next run uses shipped personas and built-in defaults.[/green]")
else:
console.print(f"[yellow]No {USER_SETTINGS_FILENAME} found to remove.[/yellow]")
return 0
def cmd_skills_list(_args: argparse.Namespace) -> int:
skills, err = list_skills()
if err:
console.print(f"[yellow]{err}[/yellow]")
return 0
if not skills:
console.print("[yellow]No skills discovered.[/yellow]")
return 0
console.print("[bold green]Available Skills[/bold green]")
for item in skills:
desc = item.get("description", "").strip()
suffix = f" - {desc}" if desc else ""
console.print(f"- {item['id']}{suffix}")
return 0
def cmd_skills_inspect(args: argparse.Namespace) -> int:
payload, err = inspect_skill(args.skill_id)
if err:
console.print(f"[yellow]{err}[/yellow]")
return 1
console.print(Panel.fit(f"[bold]{payload['id']}[/bold]", title="Skill"))
if payload.get("version"):
console.print(f"[cyan]Version:[/cyan] {payload['version']}")
if payload.get("description"):
console.print(f"[cyan]Description:[/cyan] {payload['description']}")
if payload.get("inputs"):
console.print(f"[cyan]Inputs:[/cyan] {payload['inputs']}")
if payload.get("instructions"):
console.print(Rule("Skill Instructions"))
console.print(payload["instructions"])
return 0
def cmd_skills_suggest(args: argparse.Namespace) -> int:
expertise = [item.strip() for item in args.expertise.split(",") if item.strip()]
if not expertise:
console.print("[yellow]No expertise keywords provided.[/yellow]")
return 1
skills, err = list_skills()
if err:
console.print(f"[yellow]{err}[/yellow]")
return 0
suggested = suggest_skills(skills, expertise)
if not suggested:
console.print("[yellow]No suggested skills matched your expertise keywords.[/yellow]")
return 0
console.print("[bold green]Suggested Skills[/bold green]")
for item in suggested:
desc = item.get("description", "").strip()
suffix = f" - {desc}" if desc else ""
console.print(f"- {item['id']}{suffix}")
return 0
def build_parser() -> argparse.ArgumentParser:
parser = argparse.ArgumentParser(description="Multi-Agent Room Framework")
parser.add_argument(
"--config",
metavar="PATH",
help=f"Path to settings YAML (default: search {USER_SETTINGS_FILENAME})",
)
sub = parser.add_subparsers(dest="command")
config_parser = sub.add_parser("config", help="Manage rooms.settings.yaml")
config_sub = config_parser.add_subparsers(dest="config_cmd", required=True)
config_sub.add_parser("init", help=f"Copy {EXAMPLE_SETTINGS_FILENAME} to {USER_SETTINGS_FILENAME}")
reset_p = config_sub.add_parser("reset", help="Remove user settings file")
reset_p.add_argument("--path", help="Specific settings file to remove")
reset_p.add_argument("-y", "--yes", action="store_true", help="Skip confirmation")
skills_parser = sub.add_parser("skills", help="Rooms-native Skillware discovery and inspection")
skills_sub = skills_parser.add_subparsers(dest="skills_cmd", required=True)
skills_sub.add_parser("list", help="List available skills")
inspect_p = skills_sub.add_parser("inspect", help="Inspect a specific skill")
inspect_p.add_argument("skill_id", help="Skill ID, e.g. finance/wallet_screening")
suggest_p = skills_sub.add_parser("suggest", help="Suggest skills from expertise keywords")
suggest_p.add_argument(
"--expertise",
required=True,
help="Comma-separated keywords, e.g. finance,risk,compliance",
)
parser.add_argument(
"--skip-preflight",
action="store_true",
help="Skip Ollama preflight connectivity and model validation checks"
)
return parser
def check_ollama_preflight(settings) -> bool:
"""
Runs an optional preflight check for Ollama reachability and model availability
if the default configured model relies on a local Ollama instance.
"""
from rooms import ollama_preflight
return ollama_preflight.run_ollama_preflight(settings)
def main(argv: Optional[List[str]] = None) -> int:
bootstrap_environment()
parser = build_parser()
args = parser.parse_args(argv)
if args.command == "config":
if args.config_cmd == "init":
return cmd_config_init(args)
if args.config_cmd == "reset":
return cmd_config_reset(args)
return 1
if args.command == "skills":
if args.skills_cmd == "list":
return cmd_skills_list(args)
if args.skills_cmd == "inspect":
return cmd_skills_inspect(args)
if args.skills_cmd == "suggest":
return cmd_skills_suggest(args)
return 1
try:
settings = load_settings(args.config, required=bool(args.config))
except SettingsError as e:
console.print(f"[red]{e}[/red]")
return 1
if args.config:
console.print(f"[dim]Using settings: {args.config}[/dim]")
else:
found = find_settings_file()
if found:
console.print(f"[dim]Using settings: {found}[/dim]")
# Run the Ollama preflight check unless --skip-preflight is passed.
if not args.skip_preflight:
if not check_ollama_preflight(settings):
return 1
main_menu(settings)
return 0
if __name__ == "__main__":
sys.exit(main())