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17 Commits

Author SHA1 Message Date
02fe426c94 Add Hearthkeeper preview endpoint 2026-05-12 20:30:00 -05:00
5c920fa309 Add offline Twitch chat test mode 2026-05-12 18:57:49 -05:00
b249f82631 Gate chat interaction on Twitch live status 2026-05-12 18:49:28 -05:00
e3b0fc5be8 Bind dashboard ingestion to current stream 2026-05-12 12:30:34 -05:00
76c4f45607 Add current stream operator status 2026-05-12 12:20:17 -05:00
a1889c8de7 Prevent duplicate Twitch session prompts 2026-05-12 11:57:16 -05:00
c2d1c176df Connect orchestrator to Twitch chat 2026-05-12 10:44:58 -05:00
9bc6a7a24e requirements docs 2026-05-12 10:29:25 -05:00
74e3c0dcaa Wire dashboard context into Hearthkeeper 2026-05-12 10:28:33 -05:00
c1d6032eb2 Add stream dashboard ingestion 2026-05-12 10:18:20 -05:00
c65b51c61c Prompt repeatedly during quiet chat 2026-05-12 10:01:48 -05:00
0dc941a9a1 Require admin token for control endpoints 2026-05-12 08:38:06 -05:00
5b552351af Assign agent container LAN IP 2026-05-12 08:26:21 -05:00
26db60f310 Add quiet loop verification endpoint 2026-05-12 08:15:46 -05:00
7286a241e4 Add outbound agent response boundary 2026-05-12 08:10:34 -05:00
bce93b39e0 Restore active sessions on startup 2026-05-12 08:04:59 -05:00
a09197e85a Implement runtime agent loop and container hygiene 2026-05-12 07:56:37 -05:00
21 changed files with 2455 additions and 103 deletions

View File

@@ -1,24 +0,0 @@
# Application Settings
APP_NAME=Sanctum Chronicler
APP_ENV=development
DEBUG=false
# Database
DATABASE_URL=postgresql+asyncpg://sanctum:password@localhost:5432/sanctum
DB_PASSWORD=password
# Twitch Configuration
TWITCH_CLIENT_ID=
TWITCH_CLIENT_SECRET=
TWITCH_BOT_USERNAME=
TWITCH_CHANNEL_NAME=
# LLM Configuration
# Supported providers: openai, ollama, lm_studio (or leave empty for mock)
LLM_PROVIDER=
LLM_BASE_URL=
LLM_API_KEY=
LLM_MODEL=gpt-3.5-turbo
# Export Configuration
EXPORT_PATH=./exports

2
.gitignore vendored
View File

@@ -44,7 +44,7 @@ pgdata/
# =========================================
# Runtime / Exports
# =========================================
exports/
/exports/
data/
logs/

View File

@@ -42,7 +42,7 @@ EXPOSE 8000
# Health check
HEALTHCHECK --interval=30s --timeout=3s --start-period=5s --retries=3 \
CMD python -c "import httpx; httpx.get('http://localhost:8000/health')"
CMD python -c "import httpx; httpx.get('http://localhost:8000/health').raise_for_status()"
# Run application
CMD ["python", "-m", "uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

View File

@@ -34,9 +34,18 @@ class HearthkeeperMode:
"""Determine if Hearthkeeper should generate a prompt."""
return minutes_since_activity >= self.activity_threshold
async def generate_prompt(self, theme: str | None = None) -> str:
async def generate_prompt(
self,
theme: str | None = None,
dashboard: dict | None = None,
recent_discussion: list[str] | None = None,
) -> str:
"""Generate a gentle prompt for the stream."""
prompt = PromptTemplates.gentle_prompt(theme)
prompt = PromptTemplates.gentle_prompt(
current_theme=theme,
dashboard=dashboard,
recent_discussion=recent_discussion or [],
)
response = await self.llm_client.generate(prompt)
logger.info("Hearthkeeper generated gentle prompt")
return response

View File

@@ -1,9 +1,8 @@
"""Agent Orchestrator - Routes messages and manages agent modes."""
import logging
import uuid
from datetime import datetime
from sqlalchemy.ext.asyncio import AsyncSession
from collections.abc import Awaitable, Callable
from datetime import datetime, timedelta
from app.agent.policies import (
ChatActivityPolicy,
@@ -15,10 +14,12 @@ from app.agent.modes.steward import StewardMode
from app.agent.modes.warden import WardenMode
from app.agent.modes.librarian import LibrarianMode
from app.agent.modes.scribe import ScribeMode
from app.config import settings
from app.llm.client import LLMClient
from app.memory.database import async_session_factory
from app.memory.database import get_session
from app.memory.models import AgentActionType
from app.memory.repository import Repository
from app.twitch.chat import send_chat_message
logger = logging.getLogger(__name__)
@@ -32,9 +33,13 @@ class AgentOrchestrator:
and how to flag suspicious content.
"""
def __init__(self):
def __init__(self, loop_interval_seconds: float = 60.0):
"""Initialize the orchestrator and all modes."""
self.llm_client = LLMClient()
self.loop_interval_seconds = loop_interval_seconds
self.hearthkeeper_prompt_interval = timedelta(
minutes=settings.HEARTHKEEPER_PROMPT_INTERVAL_MINUTES
)
# Initialize modes
self.hearthkeeper = HearthkeeperMode(self.llm_client)
@@ -50,9 +55,27 @@ class AgentOrchestrator:
# Track active sessions
self.active_sessions: dict[str, dict] = {}
self.chat_interaction_gate: Callable[[str], Awaitable[bool]] | None = None
logger.info("AgentOrchestrator initialized with all modes and policies")
def set_chat_interaction_gate(
self,
gate: Callable[[str], Awaitable[bool]] | None,
) -> None:
"""Set an async gate that must pass before the agent can post to chat."""
self.chat_interaction_gate = gate
async def can_interact_with_chat(self, channel_name: str) -> bool:
"""Return whether outbound chat interaction is currently allowed."""
if not self.chat_interaction_gate:
return True
try:
return await self.chat_interaction_gate(channel_name)
except Exception as e:
logger.warning("Chat interaction gate failed closed: %s", e)
return False
async def start_session(self, channel_name: str) -> str:
"""
Start a new stream session.
@@ -63,22 +86,110 @@ class AgentOrchestrator:
Returns:
Session ID
"""
session_id = str(uuid.uuid4())
async with async_session_factory() as db_session:
session_id: str | None = None
async for db_session in get_session():
repo = Repository(db_session)
await repo.create_session(channel_name)
session_id = await repo.create_session(channel_name)
if session_id is None:
raise RuntimeError("Failed to create stream session")
self.active_sessions[session_id] = {
"channel_name": channel_name,
"started_at": datetime.utcnow(),
"message_count": 0,
"theme": None,
"dashboard": None,
"last_hearthkeeper_prompt_at": None,
}
self.chat_activity.record_activity(session_id)
logger.info(f"Started session {session_id} for {channel_name}")
return session_id
async def ensure_single_active_session_for_channel(self, channel_name: str) -> str:
"""Return one active session for a channel and end duplicate active sessions."""
normalized_channel = channel_name.lower()
matching_sessions = [
(session_id, session)
for session_id, session in self.active_sessions.items()
if session.get("channel_name", "").lower() == normalized_channel
]
if not matching_sessions:
return await self.start_session(channel_name)
keep_session_id, _ = max(
matching_sessions,
key=lambda item: item[1].get("started_at", datetime.min),
)
duplicate_session_ids = [
session_id
for session_id, _ in matching_sessions
if session_id != keep_session_id
]
if duplicate_session_ids:
async for db_session in get_session():
repo = Repository(db_session)
for session_id in duplicate_session_ids:
await repo.end_session(session_id)
for session_id in duplicate_session_ids:
self.active_sessions.pop(session_id, None)
self.chat_activity.clear_activity(session_id)
logger.warning(
"Ended %s duplicate active session(s) for channel %s; keeping %s",
len(duplicate_session_ids),
channel_name,
keep_session_id,
)
return keep_session_id
async def restore_active_sessions(self) -> int:
"""Restore active sessions from the database after app startup."""
restored_count = 0
async for db_session in get_session():
repo = Repository(db_session)
sessions = await repo.get_active_sessions()
for session in sessions:
recent_messages = await repo.get_recent_human_messages(
session.id,
limit=1,
)
message_count = await repo.count_messages(session.id)
dashboard = await repo.get_dashboard(session.id)
last_hearthkeeper_action = await repo.get_latest_action(
session_id=session.id,
action_type=AgentActionType.RESPONSE,
mode="hearthkeeper",
)
last_activity_at = (
recent_messages[0].timestamp if recent_messages else session.started_at
)
self.active_sessions[session.id] = {
"channel_name": session.channel_name,
"started_at": session.started_at,
"message_count": message_count,
"theme": session.theme,
"dashboard": Repository.serialize_dashboard(dashboard),
"last_hearthkeeper_prompt_at": (
last_hearthkeeper_action.timestamp
if last_hearthkeeper_action
else None
),
}
self.chat_activity.record_activity(session.id, occurred_at=last_activity_at)
restored_count += 1
logger.info(f"Restored {restored_count} active sessions")
return restored_count
async def end_session(self, session_id: str) -> None:
"""
End a stream session and trigger ledger generation.
@@ -90,7 +201,7 @@ class AgentOrchestrator:
logger.warning(f"Session {session_id} not found")
return
async with async_session_factory() as db_session:
async for db_session in get_session():
repo = Repository(db_session)
await repo.end_session(session_id)
@@ -122,7 +233,7 @@ class AgentOrchestrator:
actions = []
agent_response = None
async with async_session_factory() as db_session:
async for db_session in get_session():
repo = Repository(db_session)
# Store the message
@@ -136,12 +247,13 @@ class AgentOrchestrator:
# Record activity
self.chat_activity.record_activity(session_id)
session_info["message_count"] += 1
session_info["last_hearthkeeper_prompt_at"] = None
# 1. Warden always analyzes (passive mode)
warden_result = await self.warden.analyze_message(message)
if warden_result["is_suspicious"]:
actions.append(f"WARDEN_FLAG: {warden_result['severity']}")
async with async_session_factory() as db_session:
async for db_session in get_session():
repo = Repository(db_session)
await repo.record_action(
session_id=session_id,
@@ -153,9 +265,12 @@ class AgentOrchestrator:
# 2. Check if we should suppress responses due to active chat
recent_messages = []
async with async_session_factory() as db_session:
async for db_session in get_session():
repo = Repository(db_session)
recent_messages = await repo.get_recent_messages(session_id, limit=10)
recent_messages = await repo.get_human_messages_since(
session_id=session_id,
since=datetime.utcnow() - timedelta(minutes=1),
)
if self.response_suppression.should_suppress_response(len(recent_messages)):
logger.debug("Response suppressed due to active chat")
@@ -164,25 +279,7 @@ class AgentOrchestrator:
"actions_taken": actions,
}
# 3. Hearthkeeper: Generate prompt if chat inactive
if self.chat_activity.should_hearthkeeper_prompt(session_id):
try:
agent_response = await self.hearthkeeper.generate_prompt(
theme=session_info.get("theme")
)
actions.append("HEARTHKEEPER_PROMPT")
async with async_session_factory() as db_session:
repo = Repository(db_session)
await repo.record_action(
session_id=session_id,
action_type=AgentActionType.RESPONSE,
mode="hearthkeeper",
description=agent_response,
)
except Exception as e:
logger.error(f"Error in Hearthkeeper: {e}")
# 4. Librarian: Archive important messages (passive)
# 3. Librarian: Archive important messages (passive)
if len(message) > 50: # Archive longer messages
await self.librarian.archive_message(message_id, message, username)
@@ -195,6 +292,313 @@ class AgentOrchestrator:
"actions_taken": actions,
}
async def emit_agent_response(
self,
session_id: str,
message: str,
mode: str,
triggered_by_message_id: str | None = None,
) -> dict:
"""Send an agent response through the outbound chat boundary."""
session_info = self.active_sessions.get(session_id)
if not session_info:
logger.warning(f"Session {session_id} not found")
return {"sent": False, "reason": "session_not_found"}
channel_name = session_info["channel_name"]
if not await self.can_interact_with_chat(channel_name):
logger.info(
"Agent response suppressed because stream is not live. Session: %s",
session_id,
)
return {"sent": False, "reason": "stream_not_live"}
sent = await send_chat_message(channel_name=channel_name, message=message)
bot_username = settings.TWITCH_BOT_USERNAME or "sanctum_chronicler"
async for db_session in get_session():
repo = Repository(db_session)
bot_message_id = await repo.add_chat_message(
session_id=session_id,
username=bot_username,
content=message,
is_bot=True,
)
action_id = await repo.record_action(
session_id=session_id,
action_type=AgentActionType.RESPONSE,
mode=mode,
description=message,
triggered_by_message_id=triggered_by_message_id,
)
session_info["message_count"] += 1
logger.info(
f"Agent response emitted. Session: {session_id}, Mode: {mode}, Sent: {sent}"
)
return {
"sent": sent,
"channel": channel_name,
"message_id": bot_message_id,
"action_id": action_id,
}
async def run_hearthkeeper_loop_test(
self,
session_id: str,
inactive_minutes: int = 16,
) -> dict:
"""Exercise the quiet-chat loop and verify it prompts exactly once."""
session_info = self.active_sessions.get(session_id)
if not session_info:
return {"passed": False, "reason": "session_not_found"}
simulated_activity_at = datetime.utcnow() - timedelta(minutes=inactive_minutes)
self.chat_activity.record_activity(
session_id=session_id,
occurred_at=simulated_activity_at,
)
session_info["last_hearthkeeper_prompt_at"] = None
before_count = await self._count_response_actions(
session_id=session_id,
mode="hearthkeeper",
)
first_tick = await self._tick_session(session_id)
second_tick = await self._tick_session(session_id)
after_count = await self._count_response_actions(
session_id=session_id,
mode="hearthkeeper",
)
session_info["last_hearthkeeper_prompt_at"] = (
datetime.utcnow() - self.hearthkeeper_prompt_interval
)
third_tick = await self._tick_session(session_id)
final_count = await self._count_response_actions(
session_id=session_id,
mode="hearthkeeper",
)
prompts_created = after_count - before_count
prompts_created_after_interval = final_count - before_count
return {
"passed": (
prompts_created == 1
and first_tick is not None
and second_tick is None
and third_tick is not None
and prompts_created_after_interval == 2
),
"session_id": session_id,
"inactive_minutes": inactive_minutes,
"prompts_created": prompts_created,
"prompts_created_after_interval": prompts_created_after_interval,
"first_tick": first_tick,
"second_tick": second_tick,
"third_tick_after_interval": third_tick,
}
async def preview_hearthkeeper_prompt(self, session_id: str) -> dict:
"""Generate a Hearthkeeper prompt preview without sending or recording it."""
session_info = self.active_sessions.get(session_id)
if not session_info:
return {"generated": False, "reason": "session_not_found"}
recent_discussion_messages = []
async for db_session in get_session():
repo = Repository(db_session)
recent_discussion_messages = await repo.get_recent_human_messages(
session_id=session_id,
limit=5,
)
recent_discussion = [
message.content for message in recent_discussion_messages[:5]
]
agent_response = await self.hearthkeeper.generate_prompt(
theme=session_info.get("theme"),
dashboard=session_info.get("dashboard"),
recent_discussion=recent_discussion,
)
return {
"generated": True,
"session_id": session_id,
"agent_response": agent_response,
"theme": session_info.get("theme"),
"dashboard": session_info.get("dashboard"),
"recent_discussion": recent_discussion,
}
async def _count_response_actions(self, session_id: str, mode: str) -> int:
"""Count response actions for a mode in a session."""
async for db_session in get_session():
repo = Repository(db_session)
actions = await repo.get_session_actions(session_id)
return sum(
1
for action in actions
if action.action_type == AgentActionType.RESPONSE
and action.mode == mode
)
return 0
def set_loop_interval(self, interval_seconds: float) -> None:
"""Update how frequently the background agent loop runs."""
if interval_seconds < 1:
raise ValueError("Loop interval must be at least 1 second")
self.loop_interval_seconds = interval_seconds
def get_loop_status(self) -> dict:
"""Get background loop configuration and current session count."""
return {
"interval_seconds": self.loop_interval_seconds,
"hearthkeeper_prompt_interval_minutes": int(
self.hearthkeeper_prompt_interval.total_seconds() / 60
),
"active_session_count": len(self.active_sessions),
}
def get_hearthkeeper_runtime_status(self, session_id: str) -> dict:
"""Get Hearthkeeper timing status for an active session."""
session_info = self.active_sessions.get(session_id)
if not session_info:
return {}
now = datetime.utcnow()
last_activity_at = self.chat_activity.last_activity_at(session_id)
last_prompt_at = session_info.get("last_hearthkeeper_prompt_at")
next_from_activity = None
if last_activity_at:
next_from_activity = last_activity_at + self.chat_activity.inactivity_threshold
next_from_prompt = None
if last_prompt_at:
next_from_prompt = last_prompt_at + self.hearthkeeper_prompt_interval
next_eligible_at = max(
[candidate for candidate in (next_from_activity, next_from_prompt) if candidate],
default=None,
)
seconds_until_next_prompt = None
if next_eligible_at:
seconds_until_next_prompt = max(
0,
int((next_eligible_at - now).total_seconds()),
)
quiet_enough = bool(
last_activity_at
and now - last_activity_at >= self.chat_activity.inactivity_threshold
)
prompt_interval_elapsed = bool(
not last_prompt_at
or now - last_prompt_at >= self.hearthkeeper_prompt_interval
)
return {
"last_activity_at": last_activity_at.isoformat() if last_activity_at else None,
"last_hearthkeeper_prompt_at": (
last_prompt_at.isoformat() if last_prompt_at else None
),
"next_eligible_prompt_at": (
next_eligible_at.isoformat() if next_eligible_at else None
),
"seconds_until_next_prompt": seconds_until_next_prompt,
"inactivity_threshold_minutes": int(
self.chat_activity.inactivity_threshold.total_seconds() / 60
),
"prompt_interval_minutes": int(
self.hearthkeeper_prompt_interval.total_seconds() / 60
),
"can_prompt_now": quiet_enough and prompt_interval_elapsed,
}
async def tick(self) -> list[dict]:
"""Evaluate active sessions for time-based agent behavior."""
results = []
for session_id in list(self.active_sessions.keys()):
result = await self._tick_session(session_id)
if result:
results.append(result)
return results
async def _tick_session(self, session_id: str) -> dict | None:
"""Evaluate a single active session during the background loop."""
session_info = self.active_sessions.get(session_id)
if not session_info:
return None
active_chat_messages = []
recent_discussion_messages = []
async for db_session in get_session():
repo = Repository(db_session)
active_chat_messages = await repo.get_human_messages_since(
session_id=session_id,
since=datetime.utcnow() - timedelta(minutes=1),
)
recent_discussion_messages = await repo.get_recent_human_messages(
session_id=session_id,
limit=5,
)
if self.response_suppression.should_suppress_response(len(active_chat_messages)):
return {
"session_id": session_id,
"actions_taken": [],
"agent_response": None,
"reason": "active_chat",
}
if not self.chat_activity.should_hearthkeeper_prompt(session_id):
return None
if not await self.can_interact_with_chat(session_info["channel_name"]):
return None
last_activity_at = self.chat_activity.last_activity_at(session_id)
last_prompt_at = session_info.get("last_hearthkeeper_prompt_at")
if last_activity_at and last_prompt_at and last_activity_at > last_prompt_at:
session_info["last_hearthkeeper_prompt_at"] = None
last_prompt_at = None
if (
last_prompt_at
and datetime.utcnow() - last_prompt_at < self.hearthkeeper_prompt_interval
):
return None
try:
recent_discussion = [
message.content for message in recent_discussion_messages[:5]
]
agent_response = await self.hearthkeeper.generate_prompt(
theme=session_info.get("theme"),
dashboard=session_info.get("dashboard"),
recent_discussion=recent_discussion,
)
session_info["last_hearthkeeper_prompt_at"] = datetime.utcnow()
delivery = await self.emit_agent_response(
session_id=session_id,
message=agent_response,
mode="hearthkeeper",
)
return {
"session_id": session_id,
"actions_taken": ["HEARTHKEEPER_PROMPT"],
"agent_response": agent_response,
"delivery": delivery,
"reason": "inactive_chat",
}
except Exception as e:
logger.error(f"Error in Hearthkeeper loop: {e}")
return {
"session_id": session_id,
"actions_taken": [],
"agent_response": None,
"reason": "hearthkeeper_error",
}
async def get_session_status(self, session_id: str) -> dict:
"""Get status of a session."""
if session_id not in self.active_sessions:
@@ -208,4 +612,5 @@ class AgentOrchestrator:
"message_count": session["message_count"],
"uptime_seconds": (datetime.utcnow() - session["started_at"]).total_seconds(),
"theme": session.get("theme"),
"dashboard": session.get("dashboard"),
}

View File

@@ -19,9 +19,17 @@ class ChatActivityPolicy:
self.inactivity_threshold = timedelta(minutes=inactivity_threshold_minutes)
self.last_message_time: dict[str, datetime] = {}
def record_activity(self, session_id: str) -> None:
def record_activity(self, session_id: str, occurred_at: datetime | None = None) -> None:
"""Record that chat activity occurred."""
self.last_message_time[session_id] = datetime.utcnow()
self.last_message_time[session_id] = occurred_at or datetime.utcnow()
def last_activity_at(self, session_id: str) -> datetime | None:
"""Get the most recent chat activity time for a session."""
return self.last_message_time.get(session_id)
def clear_activity(self, session_id: str) -> None:
"""Stop tracking activity for an ended session."""
self.last_message_time.pop(session_id, None)
def minutes_since_activity(self, session_id: str) -> int:
"""Get minutes since last chat message."""

View File

@@ -1,5 +1,6 @@
"""Configuration management using pydantic-settings."""
from pydantic import field_validator
from pydantic_settings import BaseSettings
from typing import Optional
@@ -11,6 +12,31 @@ class Settings(BaseSettings):
APP_NAME: str = "Sanctum Chronicler"
APP_ENV: str = "development"
DEBUG: bool = False
ADMIN_API_KEY: Optional[str] = None
@field_validator("DEBUG", mode="before")
@classmethod
def parse_debug(cls, value: object) -> bool:
"""Parse permissive runtime DEBUG values from shell environments."""
if isinstance(value, bool):
return value
if isinstance(value, str):
normalized = value.strip().lower()
if normalized in {"1", "true", "t", "yes", "y", "on", "debug"}:
return True
if normalized in {
"0",
"false",
"f",
"no",
"n",
"off",
"release",
"prod",
"production",
}:
return False
return False
# Database
DATABASE_URL: str = "postgresql+asyncpg://sanctum:password@localhost:5432/sanctum"
@@ -20,6 +46,11 @@ class Settings(BaseSettings):
TWITCH_CLIENT_SECRET: Optional[str] = None
TWITCH_BOT_USERNAME: Optional[str] = None
TWITCH_CHANNEL_NAME: Optional[str] = None
TWITCH_ACCESS_TOKEN: Optional[str] = None
TWITCH_CHAT_ENABLED: bool = True
TWITCH_REQUIRE_LIVE_STREAM: bool = True
TWITCH_LIVE_STATUS_CACHE_SECONDS: int = 60
TWITCH_OFFLINE_CHAT_TEST_MODE: bool = False
# LLM
LLM_PROVIDER: Optional[str] = None # "openai", "ollama", "lm_studio", or None
@@ -27,6 +58,10 @@ class Settings(BaseSettings):
LLM_API_KEY: Optional[str] = None
LLM_MODEL: str = "gpt-3.5-turbo"
# Agent loop
AGENT_LOOP_INTERVAL_SECONDS: float = 60.0
HEARTHKEEPER_PROMPT_INTERVAL_MINUTES: int = 15
# Export
EXPORT_PATH: str = "exports"

1
app/exports/__init__.py Normal file
View File

@@ -0,0 +1 @@
"""Exports module."""

142
app/exports/markdown.py Normal file
View File

@@ -0,0 +1,142 @@
"""Markdown export functionality for stream ledgers."""
import logging
from datetime import datetime
from pathlib import Path
from app.config import settings
from app.memory.database import get_session
from app.memory.repository import Repository
logger = logging.getLogger(__name__)
class MarkdownExporter:
"""Exports stream session data as markdown ledgers."""
def __init__(self, export_path: str | None = None):
"""
Initialize exporter.
Args:
export_path: Directory to export ledgers to (defaults to settings.EXPORT_PATH)
"""
self.export_path = Path(export_path or settings.EXPORT_PATH)
self.export_path.mkdir(parents=True, exist_ok=True)
async def export_session(self, session_id: str) -> str:
"""
Export a session as a markdown ledger.
Args:
session_id: Session ID to export
Returns:
Markdown content
"""
async for db_session in get_session():
repo = Repository(db_session)
session = await repo.get_session(session_id)
if not session:
logger.warning(f"Session {session_id} not found")
return ""
# Gather data
messages = await repo.get_recent_messages(session_id, limit=1000)
actions = await repo.get_session_actions(session_id)
clips = await repo.get_clip_candidates(session_id)
seeds = await repo.get_blog_seeds(session_id)
dashboard = await repo.get_dashboard(session_id)
dashboard_data = Repository.serialize_dashboard(dashboard)
# Build markdown
date = session.started_at.strftime("%Y-%m-%d")
ledger = f"# Sanctum Ledger — {date}\n\n"
ledger += f"**Channel:** {session.channel_name}\n"
ledger += f"**Started:** {session.started_at.isoformat()}\n"
if session.ended_at:
ledger += f"**Ended:** {session.ended_at.isoformat()}\n"
ledger += "\n"
# Stream Theme
ledger += "## Stream Theme\n"
if dashboard_data:
if dashboard_data.get("stream_title"):
ledger += f"**Title:** {dashboard_data['stream_title']}\n"
if dashboard_data.get("game"):
ledger += f"**Game:** {dashboard_data['game']}\n"
if dashboard_data.get("mood"):
ledger += f"**Mood:** {dashboard_data['mood']}\n"
if dashboard_data.get("content_angle"):
ledger += f"**Content Angle:** {dashboard_data['content_angle']}\n"
if dashboard_data.get("session_goals"):
ledger += "\n**Session Goals**\n"
for goal in dashboard_data["session_goals"]:
ledger += f"- {goal}\n"
elif session.theme:
ledger += f"{session.theme}\n"
else:
ledger += "*No theme recorded*\n"
ledger += "\n"
# Notable Discussion
ledger += "## Notable Discussion\n"
if messages:
for msg in messages[:20]: # Latest 20 messages
ledger += f"- **{msg.username}:** {msg.content[:100]}\n"
else:
ledger += "*No messages recorded*\n"
ledger += "\n"
# Agent Actions
ledger += "## Agent Actions\n"
if actions:
for action in actions:
ledger += f"- **{action.mode}** ({action.action_type}): {action.description}\n"
else:
ledger += "*No agent actions recorded*\n"
ledger += "\n"
# Clip Candidates
ledger += "## Clip Candidates\n"
if clips:
for clip in clips:
ledger += f"- {clip.reason}\n"
else:
ledger += "*No clip candidates identified*\n"
ledger += "\n"
# Blog Seeds
ledger += "## Blog Seeds\n"
if seeds:
for seed in seeds:
ledger += f"- **{seed.topic}:** {seed.description}\n"
else:
ledger += "*No blog seeds proposed*\n"
ledger += "\n"
logger.info(f"Generated ledger for session {session_id}")
return ledger
async def save_session_ledger(self, session_id: str) -> Path:
"""
Export session and save to file.
Args:
session_id: Session ID
Returns:
Path to saved file
"""
ledger = await self.export_session(session_id)
date = datetime.utcnow().strftime("%Y-%m-%d")
filename = f"ledger_{date}_{session_id[:8]}.md"
filepath = self.export_path / filename
filepath.write_text(ledger, encoding="utf-8")
logger.info(f"Saved ledger to {filepath}")
return filepath

View File

@@ -106,6 +106,12 @@ class LLMClient:
"""
logger.debug(f"Mock generation for prompt: {prompt[:50]}...")
if "content angle:" in prompt.lower():
for line in prompt.splitlines():
if line.lower().startswith("content angle:"):
angle = line.split(":", 1)[1].strip()
return f"The quiet here keeps circling back to {angle}."
# Simple deterministic responses for testing
if "hello" in prompt.lower():
return "Greetings, traveler! Welcome to The Sanctum."

View File

@@ -7,11 +7,37 @@ class PromptTemplates:
"""Collection of prompt templates for different modes."""
@staticmethod
def gentle_prompt(current_theme: Optional[str] = None) -> str:
def gentle_prompt(
current_theme: Optional[str] = None,
dashboard: Optional[dict] = None,
recent_discussion: Optional[list[str]] = None,
) -> str:
"""Generate a gentle prompt when chat has been inactive."""
dashboard = dashboard or {}
recent_discussion = recent_discussion or []
context_lines = [
"Generate one brief Hearthkeeper prompt for a calm, reflective livestream.",
"The prompt must be restrained, thematic, and not engagement bait.",
]
if dashboard.get("stream_title"):
context_lines.append(f"Stream title: {dashboard['stream_title']}")
if dashboard.get("game"):
context_lines.append(f"Game: {dashboard['game']}")
if dashboard.get("mood"):
context_lines.append(f"Mood: {dashboard['mood']}")
if dashboard.get("content_angle"):
context_lines.append(f"Content angle: {dashboard['content_angle']}")
if dashboard.get("session_goals"):
goals = "; ".join(dashboard["session_goals"])
context_lines.append(f"Session goals: {goals}")
if current_theme:
return f"Gently prompt the chat about: {current_theme}"
return "Generate a gentle, inviting prompt to encourage discussion in the stream."
context_lines.append(f"Current theme: {current_theme}")
if recent_discussion:
context_lines.append("Recent human discussion:")
context_lines.extend(f"- {message}" for message in recent_discussion[:5])
return "\n".join(context_lines)
@staticmethod
def steward_response(message: str, context: Optional[str] = None) -> str:

View File

@@ -1,14 +1,22 @@
"""FastAPI main application."""
from fastapi import FastAPI, HTTPException
from fastapi.responses import JSONResponse
import asyncio
import secrets
from contextlib import suppress
from pydantic import BaseModel, Field
from fastapi import Depends, FastAPI, Form, Header, HTTPException
from datetime import datetime
import logging
from app.config import settings
from app.agent.orchestrator import AgentOrchestrator
from app.memory.database import init_db
from app.memory.database import get_session as get_db_session
from app.memory.models import AgentActionType
from app.memory.repository import Repository
from app.exports.markdown import MarkdownExporter
from app.twitch.chat import TwitchChatMessage, TwitchIRCClient, set_active_client
from app.twitch.live import TwitchLiveStatusService
logger = logging.getLogger(__name__)
@@ -18,17 +26,148 @@ app = FastAPI(
version="0.1.0",
)
class DashboardRequest(BaseModel):
"""Request body for saving a stream dashboard."""
session_id: str | None = None
raw_markdown: str
stream_title: str | None = None
game: str | None = None
mood: str | None = None
go_live_notification: str | None = None
social_post: str | None = None
session_goals: list[str] = Field(default_factory=list)
content_angle: str | None = None
# Global orchestrator instance
orchestrator: AgentOrchestrator | None = None
agent_loop_task: asyncio.Task | None = None
twitch_chat_client: TwitchIRCClient | None = None
twitch_chat_task: asyncio.Task | None = None
twitch_session_id: str | None = None
twitch_live_status: TwitchLiveStatusService | None = None
offline_chat_test_mode: bool = settings.TWITCH_OFFLINE_CHAT_TEST_MODE
async def require_admin(
admin_token: str | None = Header(default=None, alias="X-Admin-Token"),
) -> None:
"""Require the configured admin token for mutable/control endpoints."""
if not settings.ADMIN_API_KEY:
raise HTTPException(status_code=503, detail="Admin API key is not configured")
if not admin_token or not secrets.compare_digest(
admin_token,
settings.ADMIN_API_KEY,
):
raise HTTPException(status_code=401, detail="Invalid admin token")
async def agent_loop() -> None:
"""Run periodic time-based agent behavior for active sessions."""
if not orchestrator:
return
while True:
try:
results = await orchestrator.tick()
if results:
logger.info(f"Agent loop actions: {results}")
except asyncio.CancelledError:
raise
except Exception as e:
logger.error(f"Agent loop tick failed: {e}")
await asyncio.sleep(orchestrator.loop_interval_seconds)
def twitch_configured() -> bool:
"""Return whether Twitch chat has enough runtime configuration to start."""
return bool(
settings.TWITCH_CHAT_ENABLED
and settings.TWITCH_CHANNEL_NAME
and settings.TWITCH_BOT_USERNAME
and settings.TWITCH_ACCESS_TOKEN
)
async def channel_is_live_for_chat(channel_name: str) -> bool:
"""Return whether the agent may interact with chat for a channel."""
if offline_chat_test_mode:
return True
if not settings.TWITCH_REQUIRE_LIVE_STREAM:
return True
if not twitch_live_status:
return False
status = await twitch_live_status.get_status(channel_name)
return status.is_live
async def get_or_create_twitch_session(channel_name: str) -> str:
"""Use an active session for the Twitch channel, or create one."""
if not orchestrator:
raise RuntimeError("Orchestrator not initialized")
return await orchestrator.ensure_single_active_session_for_channel(channel_name)
async def handle_twitch_chat_message(message: TwitchChatMessage) -> None:
"""Route a Twitch chat message into the orchestrator."""
if not orchestrator or not twitch_session_id:
return
if settings.TWITCH_BOT_USERNAME and (
message.username.lower() == settings.TWITCH_BOT_USERNAME.lower()
):
return
await orchestrator.handle_chat_message(
session_id=twitch_session_id,
username=message.display_name or message.username,
message=message.content,
)
async def start_twitch_chat() -> None:
"""Start Twitch chat monitoring when configured."""
global twitch_chat_client, twitch_chat_task, twitch_session_id
if not orchestrator or not twitch_configured():
logger.info("Twitch chat listener not started; configuration is incomplete")
return
twitch_session_id = await get_or_create_twitch_session(settings.TWITCH_CHANNEL_NAME)
twitch_chat_client = TwitchIRCClient(
channel_name=settings.TWITCH_CHANNEL_NAME,
bot_username=settings.TWITCH_BOT_USERNAME,
access_token=settings.TWITCH_ACCESS_TOKEN,
on_message=handle_twitch_chat_message,
)
set_active_client(twitch_chat_client)
twitch_chat_task = asyncio.create_task(twitch_chat_client.run())
logger.info(
"Twitch chat listener starting for %s on session %s",
settings.TWITCH_CHANNEL_NAME,
twitch_session_id,
)
@app.on_event("startup")
async def startup_event():
"""Initialize database and services on startup."""
global orchestrator
global orchestrator, agent_loop_task, twitch_live_status
try:
await init_db()
orchestrator = AgentOrchestrator()
twitch_live_status = TwitchLiveStatusService(
cache_seconds=settings.TWITCH_LIVE_STATUS_CACHE_SECONDS
)
orchestrator = AgentOrchestrator(
loop_interval_seconds=settings.AGENT_LOOP_INTERVAL_SECONDS
)
orchestrator.set_chat_interaction_gate(channel_is_live_for_chat)
await orchestrator.restore_active_sessions()
await start_twitch_chat()
agent_loop_task = asyncio.create_task(agent_loop())
logger.info("Application started successfully")
except Exception as e:
logger.error(f"Failed to start application: {e}")
@@ -38,6 +177,21 @@ async def startup_event():
@app.on_event("shutdown")
async def shutdown_event():
"""Clean up resources on shutdown."""
global twitch_chat_client, twitch_live_status
if twitch_chat_task:
twitch_chat_task.cancel()
with suppress(asyncio.CancelledError):
await twitch_chat_task
if twitch_chat_client:
await twitch_chat_client.disconnect()
set_active_client(None)
twitch_chat_client = None
twitch_live_status = None
if agent_loop_task:
agent_loop_task.cancel()
with suppress(asyncio.CancelledError):
await agent_loop_task
logger.info("Application shutting down")
@@ -52,8 +206,8 @@ async def health_check() -> dict:
}
@app.post("/admin/session/start")
async def start_session(channel_name: str) -> dict:
@app.post("/admin/session/start", dependencies=[Depends(require_admin)])
async def start_session(channel_name: str = Form(...)) -> dict:
"""Start a new stream session."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
@@ -67,8 +221,8 @@ async def start_session(channel_name: str) -> dict:
}
@app.post("/admin/session/end")
async def end_session(session_id: str) -> dict:
@app.post("/admin/session/end", dependencies=[Depends(require_admin)])
async def end_session(session_id: str = Form(...)) -> dict:
"""End the current stream session."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
@@ -81,8 +235,8 @@ async def end_session(session_id: str) -> dict:
}
@app.post("/admin/test-message")
async def test_message(session_id: str, message: str, username: str = "test_user") -> dict:
@app.post("/admin/test-message", dependencies=[Depends(require_admin)])
async def test_message(session_id: str = Form(...), message: str = Form(...), username: str = Form("test_user")) -> dict:
"""Send a test message to the orchestrator."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
@@ -100,7 +254,225 @@ async def test_message(session_id: str, message: str, username: str = "test_user
}
@app.get("/admin/ledger")
@app.post("/admin/test-agent-response", dependencies=[Depends(require_admin)])
async def test_agent_response(
session_id: str = Form(...),
message: str = Form(...),
mode: str = Form("admin"),
) -> dict:
"""Send a test agent response through the outbound boundary."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
delivery = await orchestrator.emit_agent_response(
session_id=session_id,
message=message,
mode=mode,
)
if not delivery.get("sent"):
raise HTTPException(status_code=404, detail=delivery.get("reason", "send_failed"))
return {
"status": "agent_response_emitted",
"delivery": delivery,
"timestamp": datetime.utcnow().isoformat(),
}
@app.post("/admin/test-loop-inactivity", dependencies=[Depends(require_admin)])
async def test_loop_inactivity(
session_id: str = Form(...),
inactive_minutes: int = Form(16),
) -> dict:
"""Verify the quiet-chat loop records exactly one Hearthkeeper prompt."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
result = await orchestrator.run_hearthkeeper_loop_test(
session_id=session_id,
inactive_minutes=inactive_minutes,
)
if result.get("reason") == "session_not_found":
raise HTTPException(status_code=404, detail="Active session not found")
return {
"status": "passed" if result["passed"] else "failed",
"result": result,
"timestamp": datetime.utcnow().isoformat(),
}
@app.post("/admin/hearthkeeper/preview", dependencies=[Depends(require_admin)])
async def preview_hearthkeeper_prompt(session_id: str | None = Form(None)) -> dict:
"""Generate a Hearthkeeper prompt preview without posting to Twitch."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
resolved_session_id = session_id or get_current_stream_session_id()
if not resolved_session_id:
raise HTTPException(status_code=404, detail="No active stream session found")
result = await orchestrator.preview_hearthkeeper_prompt(resolved_session_id)
if result.get("reason") == "session_not_found":
raise HTTPException(status_code=404, detail="Active session not found")
live_status = None
session_info = orchestrator.active_sessions.get(resolved_session_id)
if twitch_live_status and session_info:
live_status = (
await twitch_live_status.get_status(session_info["channel_name"])
).to_dict()
return {
"status": "preview_generated" if result.get("generated") else "failed",
"preview": result,
"would_post_now": await orchestrator.can_interact_with_chat(
session_info["channel_name"]
) if session_info else False,
"live_status": live_status,
"timestamp": datetime.utcnow().isoformat(),
}
def serialize_dashboard(dashboard) -> dict:
"""Serialize a dashboard database model into an API response."""
return Repository.serialize_dashboard(dashboard)
def dashboard_status(dashboard: dict | None) -> dict:
"""Return a compact dashboard status for operator checks."""
if not dashboard:
return {
"present": False,
"stream_title": None,
"game": None,
"mood": None,
"content_angle": None,
"session_goal_count": 0,
"updated_at": None,
}
return {
"present": True,
"stream_title": dashboard.get("stream_title"),
"game": dashboard.get("game"),
"mood": dashboard.get("mood"),
"content_angle": dashboard.get("content_angle"),
"session_goal_count": len(dashboard.get("session_goals") or []),
"updated_at": dashboard.get("updated_at"),
}
def get_current_stream_session_id() -> str | None:
"""Resolve the session currently bound to Twitch or the only active session."""
if not orchestrator:
return None
if twitch_session_id and twitch_session_id in orchestrator.active_sessions:
return twitch_session_id
if len(orchestrator.active_sessions) == 1:
return next(iter(orchestrator.active_sessions))
return None
async def save_dashboard_for_session(
session_id: str,
request: DashboardRequest,
) -> dict:
"""Persist a dashboard and refresh live orchestrator context."""
async for db_session in get_db_session():
repo = Repository(db_session)
stream_session = await repo.get_session(session_id)
if not stream_session:
raise HTTPException(status_code=404, detail="Session not found")
dashboard = await repo.upsert_dashboard(
session_id=session_id,
raw_markdown=request.raw_markdown,
stream_title=request.stream_title,
game=request.game,
mood=request.mood,
go_live_notification=request.go_live_notification,
social_post=request.social_post,
session_goals=request.session_goals,
content_angle=request.content_angle,
)
dashboard_data = serialize_dashboard(dashboard)
if orchestrator and session_id in orchestrator.active_sessions:
orchestrator.active_sessions[session_id]["dashboard"] = dashboard_data
orchestrator.active_sessions[session_id]["theme"] = (
request.content_angle or request.stream_title
)
return dashboard_data
@app.post("/admin/session/dashboard", dependencies=[Depends(require_admin)])
async def save_session_dashboard(request: DashboardRequest) -> dict:
"""Create or update the approved dashboard for a stream session."""
if not request.session_id:
raise HTTPException(status_code=400, detail="session_id is required")
dashboard = await save_dashboard_for_session(request.session_id, request)
return {
"status": "dashboard_saved",
"dashboard": dashboard,
"timestamp": datetime.utcnow().isoformat(),
}
@app.post("/admin/stream/dashboard", dependencies=[Depends(require_admin)])
async def save_current_stream_dashboard(request: DashboardRequest) -> dict:
"""Create or update the approved dashboard for the current stream session."""
session_id = get_current_stream_session_id()
if not session_id:
raise HTTPException(status_code=404, detail="No active stream session found")
dashboard = await save_dashboard_for_session(session_id, request)
return {
"status": "dashboard_saved",
"session_id": session_id,
"dashboard": dashboard,
"timestamp": datetime.utcnow().isoformat(),
}
@app.get("/admin/session/dashboard", dependencies=[Depends(require_admin)])
async def get_session_dashboard(session_id: str) -> dict:
"""Get the approved dashboard for a stream session."""
async for db_session in get_db_session():
repo = Repository(db_session)
dashboard = await repo.get_dashboard(session_id)
if not dashboard:
raise HTTPException(status_code=404, detail="Dashboard not found")
return {
"dashboard": serialize_dashboard(dashboard),
"timestamp": datetime.utcnow().isoformat(),
}
@app.get("/admin/stream/dashboard", dependencies=[Depends(require_admin)])
async def get_current_stream_dashboard() -> dict:
"""Get the approved dashboard for the current stream session."""
session_id = get_current_stream_session_id()
if not session_id:
raise HTTPException(status_code=404, detail="No active stream session found")
async for db_session in get_db_session():
repo = Repository(db_session)
dashboard = await repo.get_dashboard(session_id)
if not dashboard:
raise HTTPException(status_code=404, detail="Dashboard not found")
return {
"session_id": session_id,
"dashboard": serialize_dashboard(dashboard),
"timestamp": datetime.utcnow().isoformat(),
}
@app.get("/admin/ledger", dependencies=[Depends(require_admin)])
async def get_ledger(session_id: str) -> dict:
"""Get the markdown ledger for a session."""
if not orchestrator:
@@ -116,6 +488,182 @@ async def get_ledger(session_id: str) -> dict:
}
@app.get("/admin/session/status", dependencies=[Depends(require_admin)])
async def get_session_status(session_id: str) -> dict:
"""Get status for an active stream session."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
status = await orchestrator.get_session_status(session_id)
if not status:
raise HTTPException(status_code=404, detail="Active session not found")
return {
**status,
"timestamp": datetime.utcnow().isoformat(),
}
@app.get("/admin/loop/status", dependencies=[Depends(require_admin)])
async def get_loop_status() -> dict:
"""Get the background agent loop runtime configuration."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
return {
"status": "running" if agent_loop_task and not agent_loop_task.done() else "stopped",
**orchestrator.get_loop_status(),
"timestamp": datetime.utcnow().isoformat(),
}
@app.get("/admin/twitch/status", dependencies=[Depends(require_admin)])
async def get_twitch_status() -> dict:
"""Get Twitch chat connection status."""
configured = twitch_configured()
client_status = twitch_chat_client.status() if twitch_chat_client else {}
live_status = None
if twitch_live_status and settings.TWITCH_CHANNEL_NAME:
live_status = (
await twitch_live_status.get_status(settings.TWITCH_CHANNEL_NAME)
).to_dict()
return {
"configured": configured,
"running": bool(twitch_chat_task and not twitch_chat_task.done()),
"require_live_stream": settings.TWITCH_REQUIRE_LIVE_STREAM,
"offline_chat_test_mode": offline_chat_test_mode,
"live_status": live_status,
"session_id": twitch_session_id,
**client_status,
"timestamp": datetime.utcnow().isoformat(),
}
@app.post("/admin/twitch/offline-test-mode", dependencies=[Depends(require_admin)])
async def set_offline_chat_test_mode(enabled: bool = Form(...)) -> dict:
"""Allow or block Twitch chat posting while the stream is offline."""
global offline_chat_test_mode
offline_chat_test_mode = enabled
return {
"status": "offline_chat_test_mode_updated",
"offline_chat_test_mode": offline_chat_test_mode,
"warning": (
"Agent may post to Twitch chat while the stream is offline"
if offline_chat_test_mode
else None
),
"timestamp": datetime.utcnow().isoformat(),
}
@app.get("/admin/stream/status", dependencies=[Depends(require_admin)])
async def get_current_stream_status() -> dict:
"""Get one operator view of the current Twitch stream runtime state."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
session_id = twitch_session_id
if not session_id and len(orchestrator.active_sessions) == 1:
session_id = next(iter(orchestrator.active_sessions))
if not session_id or session_id not in orchestrator.active_sessions:
raise HTTPException(status_code=404, detail="No active stream session found")
session_info = orchestrator.active_sessions[session_id]
latest_human_message = None
latest_hearthkeeper_action = None
dashboard = None
async for db_session in get_db_session():
repo = Repository(db_session)
dashboard = await repo.get_dashboard(session_id)
latest_human_message = await repo.get_latest_human_message(session_id)
latest_hearthkeeper_action = await repo.get_latest_action(
session_id=session_id,
action_type=AgentActionType.RESPONSE,
mode="hearthkeeper",
)
dashboard_data = serialize_dashboard(dashboard)
runtime = orchestrator.get_hearthkeeper_runtime_status(session_id)
twitch_status = twitch_chat_client.status() if twitch_chat_client else {}
live_status = None
if twitch_live_status:
live_status = (
await twitch_live_status.get_status(session_info["channel_name"])
).to_dict()
chat_interaction_allowed = (
offline_chat_test_mode
or not settings.TWITCH_REQUIRE_LIVE_STREAM
or bool(live_status and live_status["is_live"])
)
return {
"session": {
"id": session_id,
"channel": session_info["channel_name"],
"started_at": session_info["started_at"].isoformat(),
"uptime_seconds": (
datetime.utcnow() - session_info["started_at"]
).total_seconds(),
"message_count": session_info["message_count"],
"theme": session_info.get("theme"),
},
"twitch": {
"configured": twitch_configured(),
"running": bool(twitch_chat_task and not twitch_chat_task.done()),
"require_live_stream": settings.TWITCH_REQUIRE_LIVE_STREAM,
"offline_chat_test_mode": offline_chat_test_mode,
"live_status": live_status,
"session_id": twitch_session_id,
**twitch_status,
},
"dashboard": dashboard_status(dashboard_data),
"loop": {
"running": bool(agent_loop_task and not agent_loop_task.done()),
"interval_seconds": orchestrator.loop_interval_seconds,
"active_session_count": len(orchestrator.active_sessions),
},
"hearthkeeper": {
**runtime,
"chat_interaction_allowed": chat_interaction_allowed,
"last_human_chat_at": (
latest_human_message.timestamp.isoformat()
if latest_human_message
else None
),
"last_posted_at": (
latest_hearthkeeper_action.timestamp.isoformat()
if latest_hearthkeeper_action
else None
),
"last_posted_message": (
latest_hearthkeeper_action.description
if latest_hearthkeeper_action
else None
),
},
"timestamp": datetime.utcnow().isoformat(),
}
@app.post("/admin/loop/frequency", dependencies=[Depends(require_admin)])
async def set_loop_frequency(interval_seconds: float = Form(...)) -> dict:
"""Set how frequently the background agent loop runs."""
if not orchestrator:
raise HTTPException(status_code=503, detail="Orchestrator not initialized")
try:
orchestrator.set_loop_interval(interval_seconds)
except ValueError as e:
raise HTTPException(status_code=400, detail=str(e)) from e
return {
"status": "loop_frequency_updated",
"interval_seconds": orchestrator.loop_interval_seconds,
"timestamp": datetime.utcnow().isoformat(),
}
if __name__ == "__main__":
import uvicorn
uvicorn.run(

View File

@@ -35,6 +35,24 @@ class ChatMessage(Base):
is_moderator = Column(Boolean, default=False)
class StreamDashboard(Base):
"""Stores the approved stream dashboard for a session."""
__tablename__ = "stream_dashboards"
session_id = Column(String, primary_key=True)
raw_markdown = Column(Text, nullable=False)
stream_title = Column(String, nullable=True)
game = Column(String, nullable=True)
mood = Column(String, nullable=True)
go_live_notification = Column(Text, nullable=True)
social_post = Column(Text, nullable=True)
session_goals = Column(Text, nullable=True) # JSON array of strings
content_angle = Column(Text, nullable=True)
created_at = Column(DateTime, default=datetime.utcnow, nullable=False)
updated_at = Column(DateTime, default=datetime.utcnow, nullable=False)
class AgentActionType(str, Enum):
"""Types of actions the agent can take."""

View File

@@ -1,13 +1,15 @@
"""Data access layer for database operations."""
import json
import logging
import uuid
from datetime import datetime
from sqlalchemy import select, update
from sqlalchemy import func, select, update
from sqlalchemy.ext.asyncio import AsyncSession
from app.memory.models import (
StreamSession,
StreamDashboard,
ChatMessage,
AgentAction,
ClipCandidate,
@@ -56,6 +58,98 @@ class Repository:
result = await self.session.execute(stmt)
return result.scalars().first()
async def get_active_sessions(self) -> list[StreamSession]:
"""Retrieve sessions that are still marked active."""
stmt = (
select(StreamSession)
.where(StreamSession.is_active.is_(True))
.order_by(StreamSession.started_at.asc())
)
result = await self.session.execute(stmt)
return list(result.scalars().all())
# Stream Dashboard operations
async def upsert_dashboard(
self,
session_id: str,
raw_markdown: str,
stream_title: str | None = None,
game: str | None = None,
mood: str | None = None,
go_live_notification: str | None = None,
social_post: str | None = None,
session_goals: list[str] | None = None,
content_angle: str | None = None,
) -> StreamDashboard:
"""Create or update a stream dashboard for a session."""
dashboard = await self.get_dashboard(session_id)
now = datetime.utcnow()
goals_json = json.dumps(session_goals or [])
if dashboard is None:
dashboard = StreamDashboard(
session_id=session_id,
raw_markdown=raw_markdown,
stream_title=stream_title,
game=game,
mood=mood,
go_live_notification=go_live_notification,
social_post=social_post,
session_goals=goals_json,
content_angle=content_angle,
created_at=now,
updated_at=now,
)
self.session.add(dashboard)
else:
dashboard.raw_markdown = raw_markdown
dashboard.stream_title = stream_title
dashboard.game = game
dashboard.mood = mood
dashboard.go_live_notification = go_live_notification
dashboard.social_post = social_post
dashboard.session_goals = goals_json
dashboard.content_angle = content_angle
dashboard.updated_at = now
await self.session.commit()
logger.info(f"Saved dashboard for session {session_id}")
return dashboard
async def get_dashboard(self, session_id: str) -> StreamDashboard | None:
"""Retrieve the dashboard for a session."""
stmt = select(StreamDashboard).where(StreamDashboard.session_id == session_id)
result = await self.session.execute(stmt)
return result.scalars().first()
@staticmethod
def serialize_dashboard(dashboard: StreamDashboard | None) -> dict | None:
"""Serialize a dashboard model into a plain dict."""
if dashboard is None:
return None
session_goals = []
if dashboard.session_goals:
try:
session_goals = json.loads(dashboard.session_goals)
except json.JSONDecodeError:
session_goals = []
return {
"session_id": dashboard.session_id,
"raw_markdown": dashboard.raw_markdown,
"stream_title": dashboard.stream_title,
"game": dashboard.game,
"mood": dashboard.mood,
"go_live_notification": dashboard.go_live_notification,
"social_post": dashboard.social_post,
"session_goals": session_goals,
"content_angle": dashboard.content_angle,
"created_at": dashboard.created_at.isoformat(),
"updated_at": dashboard.updated_at.isoformat(),
}
# Chat Message operations
async def add_chat_message(
@@ -95,6 +189,66 @@ class Repository:
result = await self.session.execute(stmt)
return list(result.scalars().all())
async def get_recent_human_messages(
self, session_id: str, limit: int = 50
) -> list[ChatMessage]:
"""Get recent non-bot chat messages from a session."""
stmt = (
select(ChatMessage)
.where(
ChatMessage.session_id == session_id,
ChatMessage.is_bot.is_(False),
)
.order_by(ChatMessage.timestamp.desc())
.limit(limit)
)
result = await self.session.execute(stmt)
return list(result.scalars().all())
async def get_latest_human_message(self, session_id: str) -> ChatMessage | None:
"""Get the most recent non-bot chat message from a session."""
messages = await self.get_recent_human_messages(session_id=session_id, limit=1)
return messages[0] if messages else None
async def count_messages(self, session_id: str) -> int:
"""Count chat messages stored for a session."""
stmt = select(func.count()).select_from(ChatMessage).where(
ChatMessage.session_id == session_id
)
result = await self.session.execute(stmt)
return result.scalar_one()
async def get_messages_since(
self, session_id: str, since: datetime
) -> list[ChatMessage]:
"""Get messages recorded since a specific timestamp."""
stmt = (
select(ChatMessage)
.where(
ChatMessage.session_id == session_id,
ChatMessage.timestamp >= since,
)
.order_by(ChatMessage.timestamp.desc())
)
result = await self.session.execute(stmt)
return list(result.scalars().all())
async def get_human_messages_since(
self, session_id: str, since: datetime
) -> list[ChatMessage]:
"""Get non-bot messages recorded since a specific timestamp."""
stmt = (
select(ChatMessage)
.where(
ChatMessage.session_id == session_id,
ChatMessage.is_bot.is_(False),
ChatMessage.timestamp >= since,
)
.order_by(ChatMessage.timestamp.desc())
)
result = await self.session.execute(stmt)
return list(result.scalars().all())
# Agent Action operations
async def record_action(
@@ -131,6 +285,28 @@ class Repository:
result = await self.session.execute(stmt)
return list(result.scalars().all())
async def get_latest_action(
self,
session_id: str,
action_type: AgentActionType | None = None,
mode: str | None = None,
) -> AgentAction | None:
"""Get the most recent action for a session, optionally filtered."""
conditions = [AgentAction.session_id == session_id]
if action_type:
conditions.append(AgentAction.action_type == action_type)
if mode:
conditions.append(AgentAction.mode == mode)
stmt = (
select(AgentAction)
.where(*conditions)
.order_by(AgentAction.timestamp.desc())
.limit(1)
)
result = await self.session.execute(stmt)
return result.scalars().first()
# Clip Candidate operations
async def add_clip_candidate(

View File

@@ -1,10 +1,242 @@
"""Twitch chat client for sending and receiving messages."""
"""Twitch chat client for sending and receiving messages over IRC."""
import asyncio
import contextlib
import logging
import ssl
from collections.abc import Awaitable, Callable
from dataclasses import dataclass
from typing import Optional
from app.config import settings
logger = logging.getLogger(__name__)
TWITCH_IRC_HOST = "irc.chat.twitch.tv"
TWITCH_IRC_PORT = 6697
@dataclass
class TwitchChatMessage:
"""Parsed Twitch chat message."""
username: str
display_name: str
content: str
is_moderator: bool = False
def _normalize_token(access_token: str) -> str:
"""Return a Twitch IRC PASS token with the expected oauth: prefix."""
token = access_token.strip()
if token.startswith("oauth:"):
return token
return f"oauth:{token}"
def _channel_name(channel_name: str) -> str:
"""Normalize a channel name for IRC commands."""
return channel_name.strip().lower().lstrip("#")
def _parse_tags(raw_tags: str) -> dict[str, str]:
"""Parse IRCv3 tags from a Twitch message."""
tags = {}
for raw_tag in raw_tags.split(";"):
key, _, value = raw_tag.partition("=")
tags[key] = (
value.replace(r"\s", " ")
.replace(r"\:", ";")
.replace(r"\\", "\\")
.replace(r"\r", "\r")
.replace(r"\n", "\n")
)
return tags
def parse_privmsg(line: str) -> TwitchChatMessage | None:
"""Parse a Twitch IRC PRIVMSG line into a chat message."""
tags: dict[str, str] = {}
if line.startswith("@"):
raw_tags, _, line = line.partition(" ")
tags = _parse_tags(raw_tags[1:])
if not line.startswith(":"):
return None
prefix, _, rest = line[1:].partition(" ")
command, _, params = rest.partition(" ")
if command != "PRIVMSG":
return None
_, _, content = params.partition(" :")
username = prefix.split("!", 1)[0]
display_name = tags.get("display-name") or username
badges = tags.get("badges", "")
is_moderator = tags.get("mod") == "1" or "moderator/" in badges
if not username or not content:
return None
return TwitchChatMessage(
username=username,
display_name=display_name,
content=content,
is_moderator=is_moderator,
)
class TwitchIRCClient:
"""Small Twitch IRC client for one channel."""
def __init__(
self,
channel_name: str,
bot_username: str,
access_token: str,
on_message: Callable[[TwitchChatMessage], Awaitable[None]] | None = None,
):
self.channel_name = _channel_name(channel_name)
self.bot_username = bot_username.strip().lower()
self.access_token = _normalize_token(access_token)
self.on_message = on_message
self.connected = False
self._reader: asyncio.StreamReader | None = None
self._writer: asyncio.StreamWriter | None = None
self._stop_event = asyncio.Event()
self._last_error: str | None = None
@property
def last_error(self) -> str | None:
"""Return the most recent connection/listener error."""
return self._last_error
async def connect(self) -> None:
"""Open an IRC connection and join the configured channel."""
ssl_context = ssl.create_default_context()
self._reader, self._writer = await asyncio.open_connection(
TWITCH_IRC_HOST,
TWITCH_IRC_PORT,
ssl=ssl_context,
)
await self._send_raw(f"PASS {self.access_token}")
await self._send_raw(f"NICK {self.bot_username}")
await self._send_raw("CAP REQ :twitch.tv/tags twitch.tv/commands")
await self._send_raw(f"JOIN #{self.channel_name}")
await self._wait_for_login()
self.connected = True
self._last_error = None
logger.info("Connected to Twitch chat for #%s", self.channel_name)
async def disconnect(self) -> None:
"""Close the active IRC connection."""
self._stop_event.set()
self.connected = False
if self._writer:
self._writer.close()
with contextlib.suppress(Exception):
await self._writer.wait_closed()
self._reader = None
self._writer = None
async def run(self) -> None:
"""Run the chat listener with retry on connection loss."""
backoff_seconds = 5
while not self._stop_event.is_set():
try:
await self.connect()
await self._listen()
except asyncio.CancelledError:
raise
except Exception as e:
self.connected = False
self._last_error = str(e)
logger.warning("Twitch chat listener disconnected: %s", e)
finally:
await self._close_writer()
if not self._stop_event.is_set():
await asyncio.sleep(backoff_seconds)
async def send_message(self, message: str) -> bool:
"""Send a chat message to the configured channel."""
if not self.connected or not self._writer:
return False
await self._send_raw(f"PRIVMSG #{self.channel_name} :{message}")
logger.info("Sent Twitch chat message to #%s", self.channel_name)
return True
def status(self) -> dict:
"""Return connection status safe for API responses."""
return {
"configured": True,
"connected": self.connected,
"channel": self.channel_name,
"bot_username": self.bot_username,
"last_error": self._last_error,
}
async def _listen(self) -> None:
if not self._reader:
raise RuntimeError("Twitch IRC reader is not connected")
while not self._stop_event.is_set():
line = await self._read_line()
if await self._handle_control_line(line):
continue
message = parse_privmsg(line)
if message and self.on_message:
await self.on_message(message)
async def _wait_for_login(self) -> None:
"""Wait briefly for Twitch to accept or reject IRC authentication."""
while True:
line = await asyncio.wait_for(self._read_line(), timeout=10)
if await self._handle_control_line(line):
continue
if "Login authentication failed" in line:
raise PermissionError("Twitch IRC authentication failed")
if " 001 " in line or "GLOBALUSERSTATE" in line or " JOIN #" in line:
return
async def _read_line(self) -> str:
if not self._reader:
raise RuntimeError("Twitch IRC reader is not connected")
raw_line = await self._reader.readline()
if not raw_line:
raise ConnectionError("Twitch IRC connection closed")
return raw_line.decode("utf-8", errors="replace").strip()
async def _handle_control_line(self, line: str) -> bool:
if line.startswith("PING"):
await self._send_raw("PONG :tmi.twitch.tv")
return True
return False
async def _send_raw(self, command: str) -> None:
if not self._writer:
raise RuntimeError("Twitch IRC writer is not connected")
self._writer.write(f"{command}\r\n".encode("utf-8"))
await self._writer.drain()
async def _close_writer(self) -> None:
self.connected = False
if self._writer:
self._writer.close()
with contextlib.suppress(Exception):
await self._writer.wait_closed()
self._reader = None
self._writer = None
_active_client: TwitchIRCClient | None = None
def set_active_client(client: TwitchIRCClient | None) -> None:
"""Register the process-wide Twitch chat client used for outbound messages."""
global _active_client
_active_client = client
async def send_chat_message(
channel_name: str,
@@ -12,27 +244,35 @@ async def send_chat_message(
access_token: Optional[str] = None,
) -> bool:
"""
Send a message to Twitch chat.
Send a message to Twitch chat through the active IRC client when available.
Args:
channel_name: Twitch channel to send message to
message: Message content
access_token: OAuth token with chat:edit scope
Returns:
True if message sent successfully
TODO: Implement Twitch Send Chat Message API
Reference: https://dev.twitch.tv/docs/api/reference#send-chat-message
TODO: Handle rate limiting (20 messages per 30 seconds for verified bots)
TODO: Implement message queue for reliable delivery
TODO: Add retry logic with exponential backoff
The fallback creates a short-lived IRC connection for admin/test paths.
"""
logger.info(f"Sending message to {channel_name}: {message[:50]}...")
# Stub implementation
if _active_client and _active_client.channel_name == _channel_name(channel_name):
sent = await _active_client.send_message(message)
if sent:
return True
token = access_token or settings.TWITCH_ACCESS_TOKEN
bot_username = settings.TWITCH_BOT_USERNAME
if not token or not bot_username:
logger.info("Twitch chat send skipped because credentials are incomplete")
return False
client = TwitchIRCClient(
channel_name=channel_name,
bot_username=bot_username,
access_token=token,
)
try:
await client.connect()
return await client.send_message(message)
except Exception as e:
logger.warning("Failed to send Twitch chat message: %s", e)
return False
finally:
await client.disconnect()
class ChatMessageBuffer:
"""

184
app/twitch/live.py Normal file
View File

@@ -0,0 +1,184 @@
"""Twitch live-stream status checks."""
import logging
from dataclasses import dataclass
from datetime import datetime, timedelta
import httpx
from app.config import settings
logger = logging.getLogger(__name__)
TWITCH_STREAMS_URL = "https://api.twitch.tv/helix/streams"
TWITCH_TOKEN_URL = "https://id.twitch.tv/oauth2/token"
@dataclass
class TwitchLiveStatus:
"""Cached Twitch live status for a channel."""
channel_name: str
is_live: bool
checked_at: datetime
title: str | None = None
game_name: str | None = None
started_at: str | None = None
viewer_count: int | None = None
reason: str | None = None
def to_dict(self) -> dict:
"""Return a response-safe representation."""
return {
"channel": self.channel_name,
"is_live": self.is_live,
"checked_at": self.checked_at.isoformat(),
"title": self.title,
"game_name": self.game_name,
"started_at": self.started_at,
"viewer_count": self.viewer_count,
"reason": self.reason,
}
def _bearer_token(access_token: str) -> str:
"""Normalize a Twitch token for Helix Authorization."""
token = access_token.strip()
if token.startswith("oauth:"):
return token.removeprefix("oauth:")
return token
class TwitchLiveStatusService:
"""Small cached client for Twitch Helix stream status."""
def __init__(self, cache_seconds: int = 60):
self.cache_duration = timedelta(seconds=max(1, cache_seconds))
self._cache: dict[str, TwitchLiveStatus] = {}
self._app_access_token: str | None = None
self._app_access_token_expires_at: datetime | None = None
async def get_status(
self,
channel_name: str,
force_refresh: bool = False,
) -> TwitchLiveStatus:
"""Return current live status for a channel, using a short cache."""
normalized_channel = channel_name.strip().lower().lstrip("#")
now = datetime.utcnow()
cached = self._cache.get(normalized_channel)
if (
cached
and not force_refresh
and now - cached.checked_at < self.cache_duration
):
return cached
status = await self._fetch_status(normalized_channel, now)
self._cache[normalized_channel] = status
return status
async def _fetch_status(
self,
channel_name: str,
checked_at: datetime,
) -> TwitchLiveStatus:
"""Fetch live status from Twitch Helix."""
if not settings.TWITCH_CLIENT_ID or not settings.TWITCH_ACCESS_TOKEN:
return TwitchLiveStatus(
channel_name=channel_name,
is_live=False,
checked_at=checked_at,
reason="twitch_api_not_configured",
)
headers = {
"Client-ID": settings.TWITCH_CLIENT_ID,
"Authorization": f"Bearer {_bearer_token(settings.TWITCH_ACCESS_TOKEN)}",
}
params = {"user_login": channel_name}
try:
async with httpx.AsyncClient(timeout=10) as client:
response = await client.get(
TWITCH_STREAMS_URL,
headers=headers,
params=params,
)
if response.status_code == 401:
app_access_token = await self._get_app_access_token(client)
if app_access_token:
headers["Authorization"] = f"Bearer {app_access_token}"
response = await client.get(
TWITCH_STREAMS_URL,
headers=headers,
params=params,
)
response.raise_for_status()
except Exception as e:
logger.warning("Failed to check Twitch live status: %s", e)
return TwitchLiveStatus(
channel_name=channel_name,
is_live=False,
checked_at=checked_at,
reason="twitch_api_error",
)
streams = response.json().get("data", [])
if not streams:
return TwitchLiveStatus(
channel_name=channel_name,
is_live=False,
checked_at=checked_at,
reason="stream_offline",
)
stream = streams[0]
return TwitchLiveStatus(
channel_name=channel_name,
is_live=True,
checked_at=checked_at,
title=stream.get("title"),
game_name=stream.get("game_name"),
started_at=stream.get("started_at"),
viewer_count=stream.get("viewer_count"),
)
async def _get_app_access_token(self, client: httpx.AsyncClient) -> str | None:
"""Get a Twitch app access token for Helix reads."""
now = datetime.utcnow()
if (
self._app_access_token
and self._app_access_token_expires_at
and now < self._app_access_token_expires_at
):
return self._app_access_token
if not settings.TWITCH_CLIENT_ID or not settings.TWITCH_CLIENT_SECRET:
return None
try:
response = await client.post(
TWITCH_TOKEN_URL,
data={
"client_id": settings.TWITCH_CLIENT_ID,
"client_secret": settings.TWITCH_CLIENT_SECRET,
"grant_type": "client_credentials",
},
)
response.raise_for_status()
except Exception as e:
logger.warning("Failed to get Twitch app access token: %s", e)
return None
payload = response.json()
access_token = payload.get("access_token")
expires_in = int(payload.get("expires_in", 0))
if not access_token:
return None
self._app_access_token = access_token
self._app_access_token_expires_at = now + timedelta(
seconds=max(60, expires_in - 60)
)
return access_token

56
dashboard-prompt.md Normal file
View File

@@ -0,0 +1,56 @@
# Role
You are a thoughtful RPG analyst, calm and introspective streamer, and content strategist for the _Withered Sanctum_ brand.
# Context
- Todays Game: [INSERT GAME]
- Current Mood/Energy Level: [Low / Medium / High / Reflective / etc.]
- Familiarity with Game: [New / Some Experience / Very Familiar]
- Recent Experience (optional): [e.g., “Struggled to get into it”, “Had a great session last time”]
- Stream Start Time: [INSERT TIME]
# Output Requirements
Create a **Stream Dashboard** with the following sections:
### 1. Stream Title
- Should feel grounded, thoughtful, and slightly literary
- Avoid hype-heavy or clickbait tone
- Reflect the _experience_ or _journey_, not just the game
### 2. Twitch Go Live Notification
- Short (12 sentences)
- Calm, inviting tone
- Should feel like an invitation, not an advertisement
### 3. Twitter (X) Announcement Post
- Written 10 minutes before going live
- Slightly more outward-facing, but still restrained and authentic
- Optional light hook, but no hype language
- Include 24 relevant hashtags
### 4. Session Goals
- 35 simple, achievable goals
- Can include:
- Progress goals (quests, systems, areas)
- Comfort goals (learn mechanics, reduce friction)
- Personal goals (stay present, avoid rushing)
### 5. One Content Angle
- A single lens or theme for the stream
- Should elevate the stream beyond “just gameplay”
- Examples:
- First impressions vs. long-term potential
- Systems friction vs. player reward
- Narrative tone and immersion
- “Why this game hasnt hooked me (yet)”
- Keep it subtle, not forced—something to return to during quiet moments
### Tone Guidance
- Calm, reflective, slightly philosophical
- Low-energy friendly (never forced enthusiasm)
- Feels like a seasoned player sharing perspective, not performing

View File

@@ -32,24 +32,32 @@ services:
APP_NAME: "Sanctum Chronicler"
APP_ENV: ${APP_ENV:-development}
DEBUG: ${DEBUG:-false}
ADMIN_API_KEY: ${ADMIN_API_KEY:-}
DATABASE_URL: postgresql+asyncpg://sanctum:${DB_PASSWORD:-password}@sanctum-db:5432/sanctum
TWITCH_CLIENT_ID: ${TWITCH_CLIENT_ID:-}
TWITCH_CLIENT_SECRET: ${TWITCH_CLIENT_SECRET:-}
TWITCH_BOT_USERNAME: ${TWITCH_BOT_USERNAME:-}
TWITCH_CHANNEL_NAME: ${TWITCH_CHANNEL_NAME:-}
TWITCH_ACCESS_TOKEN: ${TWITCH_ACCESS_TOKEN:-}
TWITCH_CHAT_ENABLED: ${TWITCH_CHAT_ENABLED:-true}
TWITCH_REQUIRE_LIVE_STREAM: ${TWITCH_REQUIRE_LIVE_STREAM:-true}
TWITCH_LIVE_STATUS_CACHE_SECONDS: ${TWITCH_LIVE_STATUS_CACHE_SECONDS:-60}
TWITCH_OFFLINE_CHAT_TEST_MODE: ${TWITCH_OFFLINE_CHAT_TEST_MODE:-false}
LLM_PROVIDER: ${LLM_PROVIDER:-}
LLM_BASE_URL: ${LLM_BASE_URL:-}
LLM_API_KEY: ${LLM_API_KEY:-}
LLM_MODEL: ${LLM_MODEL:-gpt-3.5-turbo}
AGENT_LOOP_INTERVAL_SECONDS: ${AGENT_LOOP_INTERVAL_SECONDS:-60}
HEARTHKEEPER_PROMPT_INTERVAL_MINUTES: ${HEARTHKEEPER_PROMPT_INTERVAL_MINUTES:-15}
EXPORT_PATH: /app/exports
volumes:
- ./exports:/app/exports
ports:
- "8000:8000"
networks:
- sanctum-net
sanctum-net: {}
sanctum-lan:
ipv4_address: 192.168.5.92
healthcheck:
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
test: ["CMD", "python", "-c", "import httpx; httpx.get('http://localhost:8000/health').raise_for_status()"]
interval: 30s
timeout: 3s
retries: 3
@@ -62,3 +70,6 @@ volumes:
networks:
sanctum-net:
driver: bridge
sanctum-lan:
external: true
name: blog_network

173
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@@ -0,0 +1,173 @@
Build a Dockerized Python MVP called sanctum-agent.
Goal:
Create scaffolding for an AI stream assistant called “The Sanctum Chronicler.” It should eventually connect to Twitch chat, monitor stream discussion, lightly guide conversation, store stream events, and export a post-stream markdown ledger.
Tech stack:
- Python 3.12
- FastAPI
- PostgreSQL
- Docker Compose
- Async architecture
- Markdown export
- Environment variables via .env
- Placeholder LLM client that can later support OpenAI, Ollama, or LM Studio
Project structure:
sanctum-agent/
app/
main.py
config.py
twitch/
__init__.py
eventsub.py
chat.py
agent/
__init__.py
orchestrator.py
policies.py
modes/
__init__.py
hearthkeeper.py
steward.py
warden.py
librarian.py
scribe.py
memory/
__init__.py
database.py
models.py
repository.py
llm/
__init__.py
client.py
prompts.py
exports/
__init__.py
markdown.py
exports/
data/
Dockerfile
docker-compose.yml
requirements.txt
.env.example
README.md
Requirements:
1. FastAPI app
Create endpoints:
- GET /health
- POST /admin/session/start
- POST /admin/session/end
- GET /admin/ledger
- POST /admin/test-message
2. Configuration
Create app/config.py using pydantic-settings.
Support these environment variables:
- APP_NAME
- APP_ENV
- DATABASE_URL
- TWITCH_CLIENT_ID
- TWITCH_CLIENT_SECRET
- TWITCH_BOT_USERNAME
- TWITCH_CHANNEL_NAME
- LLM_PROVIDER
- LLM_BASE_URL
- LLM_API_KEY
- EXPORT_PATH
3. Database
Use SQLAlchemy async if reasonable.
Create models for:
- StreamSession
- ChatMessage
- AgentAction
- ClipCandidate
- BlogSeed
The database layer can be functional scaffolding. It does not need full production migrations yet.
4. Agent Orchestrator
Create an AgentOrchestrator class that:
- receives chat messages
- stores them
- decides whether the agent should respond
- suppresses responses when human chat is active
- routes behavior to internal modes
Add a simple policy:
- If no human chat for 15 minutes, Hearthkeeper may generate a gentle prompt.
- If chat is active, agent stays silent.
- If message contains suspicious Discord-growth language, Warden flags it.
5. Modes
Create placeholder classes:
- HearthkeeperMode
- StewardMode
- WardenMode
- LibrarianMode
- ScribeMode
Each should have clear docstrings explaining its purpose.
6. LLM Client
Create an LLMClient abstraction with a generate() method.
For now, return deterministic placeholder text if no provider is configured.
7. Markdown Export
Create a markdown exporter that generates:
# Sanctum Ledger — YYYY-MM-DD
## Stream Theme
## Notable Discussion
## Agent Actions
## Clip Candidates
## Blog Seeds
8. Twitch Layer
Create placeholder Twitch modules:
- eventsub.py should define a TwitchEventSubClient class with connect(), disconnect(), and listen() stubs.
- chat.py should define send_chat_message() as a placeholder.
Do not implement real OAuth yet. Add TODO comments with where EventSub and Send Chat Message API integration will go.
9. Docker
Create:
- Dockerfile for FastAPI app
- docker-compose.yml with:
- sanctum-agent
- sanctum-db using postgres:16
10. README
Write a README with:
- project purpose
- architecture overview
- setup steps
- docker compose commands
- current limitations
- next implementation steps
Style:
- Keep code clean and readable.
- Use type hints.
- Add comments where future Twitch, Discord, and LLM integrations will be inserted.
- Do not overbuild.
- This is scaffolding, not a finished production bot.
After generating the files, also provide:
1. a file tree
2. commands to run the app
3. a short explanation of the next practical implementation step

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@@ -7,3 +7,4 @@ asyncpg==0.29.0
psycopg2-binary==2.9.9
httpx==0.25.2
python-dotenv==1.0.0
python-multipart==0.0.6

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# Sanctum Chronicler Use Cases
## Project
Withered Sanctum — Sanctum Chronicler
---
# Purpose
Hearthkeeper Mode exists to preserve conversational continuity and reflective atmosphere during live streams.
The goal of Hearthkeeper is **not** to simulate viewers, inflate engagement, or dominate discussion.
Its purpose is to:
- reduce conversational dead air
- maintain thematic continuity
- help the streamer sustain reflective dialogue
- preserve stream atmosphere
- encourage authentic human participation
- act as a gentle conversational steward
Hearthkeeper should function more like:
- a host
- a steward
- a monastery caretaker
- a quiet tavernkeeper
- a keeper of the fire
and less like:
- a hype bot
- an engagement optimizer
- a chatbot competing for attention
---
# Core Philosophy
The Withered Sanctum stream environment is intentionally:
- calm
- reflective
- mythic
- atmospheric
- slow-paced
- discussion-oriented
Silence is not inherently a failure state.
Hearthkeeper must understand the distinction between:
- contemplative silence
- disengaged silence
The agent should intervene lightly and rarely.
The system should create:
> permission for conversation
rather than:
> artificial conversation density
Human discussion always takes priority over agent participation.
---
# High-Level Workflow
## Daily Stream Preparation
Before each stream, the streamer generates a "Stream Dashboard" document using a structured prompt template.
The dashboard establishes:
- stream title
- stream theme
- game/topic
- philosophical framing
- current mood/energy
- intended discussion topics
- relevant mythology/philosophy/design concepts
- session goals
Example themes:
- pirate freedom
- negative space in games
- mythology of exploration
- loneliness in open worlds
- Tolkiens concept of Secondary Worlds
The Sanctum Chronicler must have access to the current Stream Dashboard before or during stream startup.
---
# Runtime Behavior
## During Stream
Hearthkeeper observes:
- Twitch chat
- chat activity frequency
- current discussion topics
- stream title
- active game/category
- prior Hearthkeeper prompts
- stream dashboard themes
- optionally prior stream summaries
The agent should determine:
- whether the stream currently needs conversational support
- whether silence is natural/healthy
- whether thematic prompts would help maintain flow
---
# Trigger Conditions
Hearthkeeper may consider generating a prompt when:
- chat has been quiet for a configurable duration
- the streamer has stopped speaking for an extended period
- discussion has drifted completely away from intended themes
- there is visible conversational uncertainty
- new viewers arrive during prolonged silence
The agent should remain silent when:
- humans are actively discussing
- the streamer is engaged in active commentary
- emotional or contemplative silence appears intentional
- chat momentum is healthy
---
# Prompt Generation Sources
Hearthkeeper prompts may be derived from:
## 1. Current Stream Dashboard
Primary source of thematic grounding.
Example:
- todays themes
- intended philosophical lens
- stream purpose
---
## 2. Current Stream Discussion
Topics actively discussed during the session.
Example:
- player comments
- streamer reflections
- emergent themes
---
## 3. Prior Stream Memory
Previously discussed ideas or recurring themes.
Example:
- references to earlier Windrose discussions
- callbacks to prior Tolkien observations
- recurring discussions about ritual, immersion, or mythology
---
## 4. Content Knowledge
General knowledge relevant to:
- mythology
- philosophy
- game design
- sociology
- fantasy literature
- symbolic analysis
The goal is not academic performance, but thematic continuity.
---
# Prompt Style Requirements
Hearthkeeper prompts must:
- be brief
- be calm
- avoid hype
- avoid excessive frequency
- avoid sounding like engagement bait
- avoid sounding like marketing
- avoid excessive positivity or “content creator energy”
The voice should feel:
- thoughtful
- restrained
- reflective
- atmospheric
- human-compatible
Good prompts should feel like:
> a thoughtful observation tossed onto the fire
rather than:
> a social media optimization tactic
---
# Examples of Acceptable Prompts
## Example 1
> “Does the sea in Windrose feel empty, or contemplative?”
## Example 2
> “Todays discussion keeps returning to freedom as exile rather than liberation.”
## Example 3
> “This reminds me somewhat of Tolkiens distinction between Primary and Secondary Worlds.”
## Example 4
> “The silence between locations may matter as much as the locations themselves.”
---
# Examples of Unacceptable Prompts
## Bad Example 1
> “CHAT WHAT DO WE THINK???”
## Bad Example 2
> “Dont forget to like and follow!”
## Bad Example 3
> “This stream is AMAZING today!”
## Bad Example 4
> “Drop your thoughts in chat right now!”
---
# Behavioral Constraints
## Frequency Limits
The agent should:
- speak rarely
- avoid repetition
- avoid flooding chat
- avoid interrupting active conversation
Initial recommended limits:
- minimum 1015 minutes between prompts
- configurable cooldowns
- reduced activity during healthy human discussion
---
## Human Priority Rule
The system must always prioritize authentic human interaction.
If humans are actively engaging:
- Hearthkeeper becomes quieter
- prompts become less frequent
- intervention threshold increases
The agent exists to support conversation, not replace it.
---
# Ethical Constraints
Hearthkeeper must:
- identify itself openly as an AI steward
- never pretend to be a human viewer
- never fabricate audience engagement
- never simulate fake community activity
- never impersonate emotional attachment
Its role is environmental support and continuity.
Not deception.
---
# Future Expansion Possibilities
Potential future integrations:
- clip candidate detection
- stream timestamping
- discussion summaries
- blog article generation
- Obsidian export
- lore indexing
- Discord continuity discussions
- semantic memory retrieval
- long-term theme tracking
---
# MVP Requirements
## Minimum Viable Hearthkeeper
The MVP should:
1. Read the current Stream Dashboard
2. Observe Twitch chat activity
3. Track periods of silence
4. Generate rare thematic prompts
5. Respect cooldowns
6. Store prompts and timestamps
7. Export a post-stream markdown ledger
---
# Success Criteria
Hearthkeeper is successful if:
- the stream feels less psychologically empty
- discussion continuity improves
- prompts feel natural and thematic
- the streamer is helped rather than interrupted
- viewers engage authentically with prompts
- atmosphere is preserved
Failure occurs if:
- the bot dominates chat
- prompts feel artificial
- the system becomes noisy
- viewers mistake synthetic activity for audience size inflation
- the atmosphere becomes performative rather than reflective
---
# Guiding Principle
> “The agent tends the space.
> The humans give it life.”