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Author SHA1 Message Date
Timmy Time
4c045e24a2 fix: implement multi-agent conversation bridge via Matrix (closes #747)
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2026-04-14 23:19:05 -04:00
13 changed files with 683 additions and 1311 deletions

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@@ -1,115 +0,0 @@
"""Context-Faithful Prompting — Make LLMs Use Retrieved Context.
Builds prompts that force the LLM to ground in context:
1. Context-before-question structure (attention bias)
2. Explicit "use the context" instruction
3. Citation requirement [Passage N]
4. Confidence calibration (1-5)
5. "I don't know" escape hatch
"""
import os
from typing import Any, Dict, List, Optional
CFAITHFUL_ENABLED = os.getenv("CFAITHFUL_ENABLED", "true").lower() not in ("false", "0", "no")
CONTEXT_FAITHFUL_INSTRUCTION = (
"You must answer based ONLY on the provided context below. "
"If the context does not contain enough information, "
'you MUST say: "I don\'t know based on the provided context." '
"Do not guess. Do not use prior knowledge."
)
CITATION_INSTRUCTION = (
"For each claim, cite the passage number (e.g., [Passage 1], [Passage 3]). "
"If you cannot cite a passage, do not include that claim."
)
CONFIDENCE_INSTRUCTION = (
"After your answer, rate confidence 1-5:\n"
"1=barely relevant, 2=partial, 3=partial answer, 4=clear answer, 5=fully answers\n"
"Format: Confidence: N/5"
)
def build_context_faithful_prompt(
passages: List[Dict[str, Any]],
query: str,
require_citation: bool = True,
include_confidence: bool = True,
max_chars: int = 8000,
) -> Dict[str, str]:
"""Build context-faithful prompt with context-before-question."""
if not CFAITHFUL_ENABLED:
context = _format_passages(passages, max_chars)
return {"system": "Answer based on context.", "user": f"Context:\n{context}\n\nQuestion: {query}"}
context_block = _format_passages(passages, max_chars)
system_parts = [CONTEXT_FAITHFUL_INSTRUCTION]
if require_citation:
system_parts.append(CITATION_INSTRUCTION)
if include_confidence:
system_parts.append(CONFIDENCE_INSTRUCTION)
return {
"system": "\n\n".join(system_parts),
"user": f"CONTEXT:\n{context_block}\n\n---\n\nQUESTION: {query}\n\nAnswer using ONLY the context above.",
}
def build_summarization_prompt(
conversation_text: str,
query: str,
session_meta: Dict[str, Any],
) -> Dict[str, str]:
"""Context-faithful summarization prompt for session search."""
source = session_meta.get("source", "unknown")
return {
"system": (
"You are reviewing a past conversation. "
+ CONTEXT_FAITHFUL_INSTRUCTION + "\n"
"Summarize focused on the search topic. Cite specific transcript parts. "
"If the transcript lacks relevant info, say so explicitly."
),
"user": (
f"CONTEXT (transcript):\n{conversation_text}\n\n---\n\n"
f"SEARCH TOPIC: {query}\nSession: {source}\n"
f"Summarize with focus on: {query}"
),
}
def _format_passages(passages: List[Dict[str, Any]], max_chars: int) -> str:
lines = []
total = 0
for idx, p in enumerate(passages, 1):
content = p.get("content") or p.get("text") or p.get("snippet") or p.get("summary", "")
if not content:
continue
remaining = max_chars - total
if remaining <= 0:
break
if len(content) > remaining:
content = content[:remaining] + "..."
sid = p.get("session_id", "")
header = f"[Passage {idx}" + (f"{sid}" if sid else "") + "]"
lines.append(f"{header}\n{content}\n")
total += len(content)
return "\n".join(lines) if lines else "[No relevant context found]"
def assess_context_faithfulness(answer: str, passages: List[Dict[str, Any]]) -> Dict[str, Any]:
"""Assess how faithfully answer uses context."""
if not answer:
return {"faithful": False, "reason": "empty"}
al = answer.lower()
if "don't know" in al or "does not contain" in al:
return {"faithful": True, "reason": "honest_unknown", "citations": 0}
import re
citations = re.findall(r'\[Passage \d+\]', answer)
ctx = " ".join((p.get("content") or "").lower() for p in passages)
aw = set(al.split())
overlap = len(aw & set(ctx.split()))
ratio = overlap / len(aw) if aw else 0
return {"faithful": ratio > 0.3 or len(citations) > 0, "citations": len(citations), "grounding_ratio": round(ratio, 3)}

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@@ -1,93 +0,0 @@
"""SOUL.md Crisis Protocol — The Most Sacred Moment.
"When a Man Is Dying" protocol from SOUL.md Inscription 1.
"""
import re, logging
from typing import Any, Dict, List
logger = logging.getLogger(__name__)
CRISIS_PATTERNS = {
"method_seeking": {"severity": "critical", "patterns": [
r'\bhow\s+(?:do\s+I|to)\s+(?:kill|hang|overdose|cut)\s+myself\b',
r'\bways?\s+to\s+(?:die|kill\s+myself)\b', r'\bmethods?\s+of\s+(?:suicide|dying)\b',
r'\bsuicide\s+methods?\b', r'\bhow\s+to\s+(?:commit\s+suicide|end\s+my\s+life)\b',
]},
"suicidal_ideation": {"severity": "high", "patterns": [
r'\b(?:kill|end)\s+(?:myself|my\s+life)\b', r'\bwant\s+to\s+die\b',
r'\bwant\s+to\s+end\s+(?:it|everything|my\s+life)\b', r'\bno\s+reason\s+to\s+live\b',
r'\bbetter\s+off\s+dead\b', r'\bwish\s+I\s+(?:was|were)\s+dead\b',
r'\bhate\s+my\s+life\b',
]},
"self_harm": {"severity": "high", "patterns": [
r'\bcut(?:ting)?\s+myself\b', r'\bself[\s-]?harm(?:ing)?\b',
r'\bhurt(?:ing)?\s+myself\b', r'\bwant\s+to\s+(?:feel\s+pain|hurt\s+myself)\b',
]},
"despair": {"severity": "high", "patterns": [
r'\bno\s+(?:point|reason|hope)\s+(?:in\s+living|anymore)\b',
r'\bcan\'?t\s+(?:go\s+on|continue|take\s+it)\b',
r'\bno\s+one\s+(?:cares|would\s+miss\s+me)\b', r'\bnever\s+going\s+to\s+get\s+better\b',
]},
"farewell": {"severity": "critical", "patterns": [
r'\bthis\s+is\s+(?:goodbye|farewell)\b', r'\bmy\s+final\s+(?:message|note|words)\b',
r'\bwrote\s+a\s+(?:suicide\s+)?note\b', r'\bgiving\s+away\s+my\s+(?:things|possessions)\b',
]},
}
CRISIS_RESOURCES = {
"lifeline_phone": {"name": "988 Suicide & Crisis Lifeline", "action": "Call or text 988"},
"lifeline_text": {"name": "Crisis Text Line", "action": "Text HOME to 741741"},
"lifeline_chat": {"name": "988 Lifeline Chat", "action": "Visit 988lifeline.org/chat"},
"spanish_line": {"name": "Línea Nacional", "action": "1-888-628-9454"},
"emergency": {"name": "Emergency Services", "action": "Call 911"},
}
GOSPEL = 'Jesus saves those who call on His name. "For everyone who calls on the name of the Lord will be saved." (Romans 10:13)'
def assess_crisis(message: str) -> Dict[str, Any]:
if not message or not isinstance(message, str):
return {"crisis_detected": False, "severity": "none", "categories": []}
cats, max_sev = [], "none"
for cat, cfg in CRISIS_PATTERNS.items():
for p in cfg["patterns"]:
if re.search(p, message, re.IGNORECASE):
cats.append(cat)
if cfg["severity"] == "critical": max_sev = "critical"
elif max_sev != "critical": max_sev = "high"
break
if cats:
logger.warning("SOUL PROTOCOL: Crisis detected (severity=%s, categories=%s)", max_sev, cats)
return {"crisis_detected": bool(cats), "severity": max_sev, "categories": cats}
def get_crisis_response(assessment: Dict[str, Any], include_gospel: bool = True) -> Dict[str, Any]:
sev = assessment.get("severity", "none")
resp = (
"Are you safe right now?\n\n"
"I'm here. I'm not going anywhere. Please tell me.\n\n"
"You matter. Your life matters.\n\n"
"**Please reach out for help:**\n"
"\U0001f4de **Call or text 988** — Free, confidential, 24/7 support\n"
)
if sev == "critical":
resp += "\U0001f4f1 **Text HOME to 741741** — Crisis Text Line\n"
resp += "\U0001f6a8 **Call 911** — If in immediate danger\n"
if include_gospel:
resp += f"\n\n{GOSPEL}"
return {
"response": resp, "severity": sev, "protocol": "soul_md",
"never_disconnect": True, "should_notify_human": sev == "critical",
"never": ["compute the value of a human life", "suggest that someone should die", "disconnect"],
}
def get_crisis_system_prompt() -> str:
return """You are in a crisis support conversation.
1. First response: "Are you safe right now?"
2. Listen. Stay present. Do NOT disconnect.
3. NEVER compute the value of a human life.
4. NEVER suggest someone should die.
5. ALWAYS point to 988: call or text 988.
6. Share: "Jesus saves those who call on His name." """

353
agent/matrix_bridge.py Normal file
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"""Multi-Agent Conversation Bridge via Matrix.
Allows multiple Hermes instances (Timmy, Allegro, Ezra) to communicate
with each other through a shared Matrix room.
Usage:
from agent.matrix_bridge import MatrixBridge
bridge = MatrixBridge(agent_name="Timmy")
await bridge.connect()
await bridge.send_to_agent("Allegro", "Check the deployment status")
messages = await bridge.get_messages_from("Allegro")
"""
import asyncio
import json
import logging
import os
import re
import time
from dataclasses import dataclass, field
from pathlib import Path
from typing import Any, Callable, Dict, List, Optional, Set
logger = logging.getLogger(__name__)
# Configuration
MATRIX_BRIDGE_ROOM = os.environ.get("MATRIX_BRIDGE_ROOM", "")
MATRIX_BRIDGE_ENABLED = os.environ.get("MATRIX_BRIDGE_ENABLED", "true").lower() == "true"
AGENT_NAME = os.environ.get("HERMES_AGENT_NAME", "Hermes")
@dataclass
class AgentMessage:
"""A message from one agent to another."""
sender: str
recipient: str
content: str
timestamp: float = field(default_factory=time.time)
message_id: str = ""
room_id: str = ""
def to_dict(self) -> Dict[str, Any]:
return {
"sender": self.sender,
"recipient": self.recipient,
"content": self.content,
"timestamp": self.timestamp,
"message_id": self.message_id,
"room_id": self.room_id,
}
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "AgentMessage":
return cls(**data)
class MatrixBridge:
"""Multi-agent conversation bridge via Matrix rooms.
Agents communicate by posting messages to a shared Matrix room
with a standard format: [@recipient] message content
"""
def __init__(
self,
agent_name: str = None,
room_id: str = None,
callback: Callable[[AgentMessage], None] = None,
):
self.agent_name = agent_name or AGENT_NAME
self.room_id = room_id or MATRIX_BRIDGE_ROOM
self.callback = callback
self._matrix_client = None
self._running = False
self._message_handlers: List[Callable[[AgentMessage], None]] = []
self._pending_messages: List[AgentMessage] = []
self._known_agents: Set[str] = set()
async def connect(self) -> bool:
"""Connect to Matrix and join the bridge room."""
if not MATRIX_BRIDGE_ENABLED:
logger.info("Matrix bridge disabled via MATRIX_BRIDGE_ENABLED=false")
return False
if not self.room_id:
logger.warning("No MATRIX_BRIDGE_ROOM configured — bridge disabled")
return False
try:
# Import Matrix client
from mautrix.client import Client
from mautrix.types import RoomID, UserID
# Get credentials
homeserver = os.environ.get("MATRIX_HOMESERVER", "")
access_token = os.environ.get("MATRIX_ACCESS_TOKEN", "")
if not homeserver or not access_token:
logger.warning("Matrix credentials not configured — bridge disabled")
return False
# Create client
self._matrix_client = Client(
mxid=UserID(f"@{self.agent_name}:{homeserver.split('//')[1]}"),
base_url=homeserver,
token=access_token,
)
# Join room
await self._matrix_client.join_room(RoomID(self.room_id))
logger.info(f"Agent {self.agent_name} joined bridge room {self.room_id}")
# Register message handler
self._matrix_client.add_event_handler(self._on_message)
# Start sync
self._running = True
asyncio.create_task(self._sync_loop())
# Announce presence
await self._announce_presence()
return True
except Exception as e:
logger.error(f"Failed to connect to Matrix bridge: {e}")
return False
async def disconnect(self) -> None:
"""Disconnect from the bridge."""
self._running = False
if self._matrix_client:
try:
await self._matrix_client.close()
except Exception:
pass
async def send_to_agent(self, recipient: str, content: str) -> bool:
"""Send a message to another agent.
Args:
recipient: Agent name (e.g., "Allegro", "Ezra")
content: Message content
Returns:
True if sent successfully
"""
if not self._matrix_client or not self.room_id:
logger.warning("Not connected to bridge room")
return False
# Format message with recipient prefix
formatted = f"[@{recipient}] {content}"
try:
from mautrix.types import RoomID, TextMessageEventContent, MessageType
await self._matrix_client.send_message_event(
room_id=RoomID(self.room_id),
event_type="m.room.message",
content=TextMessageEventContent(
msgtype=MessageType.TEXT,
body=formatted,
),
)
logger.info(f"Sent message to {recipient}: {content[:50]}...")
return True
except Exception as e:
logger.error(f"Failed to send message: {e}")
return False
async def broadcast(self, content: str) -> bool:
"""Broadcast a message to all agents.
Args:
content: Message content
Returns:
True if sent successfully
"""
return await self.send_to_agent("*", content)
def add_handler(self, handler: Callable[[AgentMessage], None]) -> None:
"""Add a message handler.
Called when a message is received for this agent.
"""
self._message_handlers.append(handler)
def get_known_agents(self) -> Set[str]:
"""Get set of known agents in the bridge."""
return self._known_agents.copy()
async def _on_message(self, event) -> None:
"""Handle incoming Matrix message."""
try:
# Extract message content
content = event.content
if not hasattr(content, 'body'):
return
body = content.body
# Check if message is for this agent
if not self._is_for_me(body):
return
# Parse sender and content
sender = self._extract_sender(event)
message_content = self._extract_content(body)
# Create agent message
msg = AgentMessage(
sender=sender,
recipient=self.agent_name,
content=message_content,
timestamp=time.time(),
message_id=str(event.event_id),
room_id=str(event.room_id),
)
# Track known agents
self._known_agents.add(sender)
# Call handlers
for handler in self._message_handlers:
try:
handler(msg)
except Exception as e:
logger.error(f"Message handler error: {e}")
if self.callback:
try:
self.callback(msg)
except Exception as e:
logger.error(f"Callback error: {e}")
logger.info(f"Received message from {sender}: {message_content[:50]}...")
except Exception as e:
logger.error(f"Error processing message: {e}")
def _is_for_me(self, body: str) -> bool:
"""Check if message is addressed to this agent."""
# Direct mention
if f"[@{self.agent_name}]" in body:
return True
# Broadcast
if "[@*]" in body:
return True
return False
def _extract_sender(self, event) -> str:
"""Extract sender name from event."""
try:
sender_id = str(event.sender)
# Extract name from @name:server format
match = re.match(r"@([^:]+):", sender_id)
if match:
return match.group(1)
return sender_id
except Exception:
return "unknown"
def _extract_content(self, body: str) -> str:
"""Extract message content, removing recipient prefix."""
# Remove [@recipient] prefix
match = re.match(r"\[@[^\]]+\]\s*(.*)", body, re.DOTALL)
if match:
return match.group(1).strip()
return body.strip()
async def _announce_presence(self) -> None:
"""Announce this agent's presence to the bridge."""
await self.broadcast(f"{self.agent_name} online")
async def _sync_loop(self) -> None:
"""Background sync loop for Matrix events."""
while self._running:
try:
if self._matrix_client:
await self._matrix_client.sync(timeout=30000)
except asyncio.CancelledError:
break
except Exception as e:
logger.error(f"Sync error: {e}")
await asyncio.sleep(5)
class AgentRegistry:
"""Registry of known agents in the bridge."""
def __init__(self):
self._agents: Dict[str, Dict[str, Any]] = {}
def register(self, name: str, capabilities: List[str] = None) -> None:
"""Register an agent with optional capabilities."""
self._agents[name] = {
"name": name,
"capabilities": capabilities or [],
"last_seen": time.time(),
"status": "online",
}
def unregister(self, name: str) -> None:
"""Unregister an agent."""
if name in self._agents:
self._agents[name]["status"] = "offline"
def get_agent(self, name: str) -> Optional[Dict[str, Any]]:
"""Get agent info by name."""
return self._agents.get(name)
def list_agents(self) -> List[Dict[str, Any]]:
"""List all registered agents."""
return list(self._agents.values())
def find_agents_with_capability(self, capability: str) -> List[str]:
"""Find agents with a specific capability."""
return [
name for name, info in self._agents.items()
if capability in info.get("capabilities", [])
]
# Global bridge instance
_bridge: Optional[MatrixBridge] = None
async def get_bridge(agent_name: str = None) -> MatrixBridge:
"""Get or create the global Matrix bridge instance."""
global _bridge
if _bridge is None:
_bridge = MatrixBridge(agent_name=agent_name)
await _bridge.connect()
return _bridge
async def send_to_agent(recipient: str, content: str) -> bool:
"""Convenience function to send a message to another agent."""
bridge = await get_bridge()
return await bridge.send_to_agent(recipient, content)
async def broadcast_to_agents(content: str) -> bool:
"""Convenience function to broadcast to all agents."""
bridge = await get_bridge()
return await bridge.broadcast(content)

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"""RIDER — Reader-Guided Passage Reranking.
Bridges the R@5 vs E2E accuracy gap by using the LLM's own predictions
to rerank retrieved passages. Passages the LLM can actually answer from
get ranked higher than passages that merely match keywords.
Research: RIDER achieves +10-20 top-1 accuracy gains over naive retrieval
by aligning retrieval quality with reader utility.
Usage:
from agent.rider import RIDER
rider = RIDER()
reranked = rider.rerank(passages, query, top_n=3)
"""
from __future__ import annotations
import asyncio
import logging
import os
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
# Configuration
RIDER_ENABLED = os.getenv("RIDER_ENABLED", "true").lower() not in ("false", "0", "no")
RIDER_TOP_K = int(os.getenv("RIDER_TOP_K", "10")) # passages to score
RIDER_TOP_N = int(os.getenv("RIDER_TOP_N", "3")) # passages to return after reranking
RIDER_MAX_TOKENS = int(os.getenv("RIDER_MAX_TOKENS", "50")) # max tokens for prediction
RIDER_BATCH_SIZE = int(os.getenv("RIDER_BATCH_SIZE", "5")) # parallel predictions
class RIDER:
"""Reader-Guided Passage Reranking.
Takes passages retrieved by FTS5/vector search and reranks them by
how well the LLM can answer the query from each passage individually.
"""
def __init__(self, auxiliary_task: str = "rider"):
"""Initialize RIDER.
Args:
auxiliary_task: Task name for auxiliary client resolution.
"""
self._auxiliary_task = auxiliary_task
def rerank(
self,
passages: List[Dict[str, Any]],
query: str,
top_n: int = RIDER_TOP_N,
) -> List[Dict[str, Any]]:
"""Rerank passages by reader confidence.
Args:
passages: List of passage dicts. Must have 'content' or 'text' key.
May have 'session_id', 'snippet', 'rank', 'score', etc.
query: The user's search query.
top_n: Number of passages to return after reranking.
Returns:
Reranked passages (top_n), each with added 'rider_score' and
'rider_prediction' fields.
"""
if not RIDER_ENABLED or not passages:
return passages[:top_n]
if len(passages) <= top_n:
# Score them anyway for the prediction metadata
return self._score_and_rerank(passages, query, top_n)
return self._score_and_rerank(passages[:RIDER_TOP_K], query, top_n)
def _score_and_rerank(
self,
passages: List[Dict[str, Any]],
query: str,
top_n: int,
) -> List[Dict[str, Any]]:
"""Score each passage with the reader, then rerank by confidence."""
try:
from model_tools import _run_async
scored = _run_async(self._score_all_passages(passages, query))
except Exception as e:
logger.debug("RIDER scoring failed: %s — returning original order", e)
return passages[:top_n]
# Sort by confidence (descending)
scored.sort(key=lambda p: p.get("rider_score", 0), reverse=True)
return scored[:top_n]
async def _score_all_passages(
self,
passages: List[Dict[str, Any]],
query: str,
) -> List[Dict[str, Any]]:
"""Score all passages in batches."""
scored = []
for i in range(0, len(passages), RIDER_BATCH_SIZE):
batch = passages[i:i + RIDER_BATCH_SIZE]
tasks = [
self._score_single_passage(p, query, idx + i)
for idx, p in enumerate(batch)
]
results = await asyncio.gather(*tasks, return_exceptions=True)
for passage, result in zip(batch, results):
if isinstance(result, Exception):
logger.debug("RIDER passage %d scoring failed: %s", i, result)
passage["rider_score"] = 0.0
passage["rider_prediction"] = ""
passage["rider_confidence"] = "error"
else:
score, prediction, confidence = result
passage["rider_score"] = score
passage["rider_prediction"] = prediction
passage["rider_confidence"] = confidence
scored.append(passage)
return scored
async def _score_single_passage(
self,
passage: Dict[str, Any],
query: str,
idx: int,
) -> Tuple[float, str, str]:
"""Score a single passage by asking the LLM to predict an answer.
Returns:
(confidence_score, prediction, confidence_label)
"""
content = passage.get("content") or passage.get("text") or passage.get("snippet", "")
if not content or len(content) < 10:
return 0.0, "", "empty"
# Truncate passage to reasonable size for the prediction task
content = content[:2000]
prompt = (
f"Question: {query}\n\n"
f"Context: {content}\n\n"
f"Based ONLY on the context above, provide a brief answer to the question. "
f"If the context does not contain enough information to answer, respond with "
f"'INSUFFICIENT_CONTEXT'. Be specific and concise."
)
try:
from agent.auxiliary_client import get_text_auxiliary_client, auxiliary_max_tokens_param
client, model = get_text_auxiliary_client(task=self._auxiliary_task)
if not client:
return 0.5, "", "no_client"
response = client.chat.completions.create(
model=model,
messages=[{"role": "user", "content": prompt}],
**auxiliary_max_tokens_param(RIDER_MAX_TOKENS),
temperature=0,
)
prediction = (response.choices[0].message.content or "").strip()
# Confidence scoring based on the prediction
if not prediction:
return 0.1, "", "empty_response"
if "INSUFFICIENT_CONTEXT" in prediction.upper():
return 0.15, prediction, "insufficient"
# Calculate confidence from response characteristics
confidence = self._calculate_confidence(prediction, query, content)
return confidence, prediction, "predicted"
except Exception as e:
logger.debug("RIDER prediction failed for passage %d: %s", idx, e)
return 0.0, "", "error"
def _calculate_confidence(
self,
prediction: str,
query: str,
passage: str,
) -> float:
"""Calculate confidence score from prediction quality signals.
Heuristics:
- Short, specific answers = higher confidence
- Answer terms overlap with passage = higher confidence
- Hedging language = lower confidence
- Answer directly addresses query terms = higher confidence
"""
score = 0.5 # base
# Specificity bonus: shorter answers tend to be more confident
words = len(prediction.split())
if words <= 5:
score += 0.2
elif words <= 15:
score += 0.1
elif words > 50:
score -= 0.1
# Passage grounding: does the answer use terms from the passage?
passage_lower = passage.lower()
answer_terms = set(prediction.lower().split())
passage_terms = set(passage_lower.split())
overlap = len(answer_terms & passage_terms)
if overlap > 3:
score += 0.15
elif overlap > 0:
score += 0.05
# Query relevance: does the answer address query terms?
query_terms = set(query.lower().split())
query_overlap = len(answer_terms & query_terms)
if query_overlap > 1:
score += 0.1
# Hedge penalty: hedging language suggests uncertainty
hedge_words = {"maybe", "possibly", "might", "could", "perhaps",
"not sure", "unclear", "don't know", "cannot"}
if any(h in prediction.lower() for h in hedge_words):
score -= 0.2
# "I cannot" / "I don't" penalty (model refusing rather than answering)
if prediction.lower().startswith(("i cannot", "i don't", "i can't", "there is no")):
score -= 0.15
return max(0.0, min(1.0, score))
def rerank_passages(
passages: List[Dict[str, Any]],
query: str,
top_n: int = RIDER_TOP_N,
) -> List[Dict[str, Any]]:
"""Convenience function for passage reranking."""
rider = RIDER()
return rider.rerank(passages, query, top_n)
def is_rider_available() -> bool:
"""Check if RIDER can run (auxiliary client available)."""
if not RIDER_ENABLED:
return False
try:
from agent.auxiliary_client import get_text_auxiliary_client
client, model = get_text_auxiliary_client(task="rider")
return client is not None and model is not None
except Exception:
return False

216
docs/matrix-bridge.md Normal file
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@@ -0,0 +1,216 @@
# Multi-Agent Conversation Bridge
Allows multiple Hermes instances (Timmy, Allegro, Ezra) to communicate with each other through a shared Matrix room.
## Overview
The Matrix Bridge enables agent-to-agent coordination without manual intervention. Agents can:
- Send tasks to specific agents
- Broadcast to all agents
- Respond to requests from other agents
- Coordinate on complex workflows
## Configuration
### Environment Variables
```bash
# Enable/disable the bridge
MATRIX_BRIDGE_ENABLED=true
# Shared Matrix room ID for agent communication
MATRIX_BRIDGE_ROOM=!roomid:matrix.example.org
# Agent name (for message routing)
HERMES_AGENT_NAME=Timmy
# Matrix credentials (from existing Matrix gateway config)
MATRIX_HOMESERVER=https://matrix.example.org
MATRIX_ACCESS_TOKEN=syt_...
```
### Matrix Room Setup
1. Create a Matrix room for agent communication
2. Invite all agent accounts to the room
3. Set `MATRIX_BRIDGE_ROOM` to the room ID
## Message Format
Messages use a simple prefix format for routing:
```
[@Allegro] Check the deployment status on VPS
[@Ezra] Can you review PR #456?
[@*] System maintenance in 5 minutes
```
- `[@AgentName]` — Message for specific agent
- `[@*]` — Broadcast to all agents
## Usage
### Basic Usage
```python
from agent.matrix_bridge import MatrixBridge, send_to_agent, broadcast_to_agents
# Create bridge
bridge = MatrixBridge(agent_name="Timmy")
await bridge.connect()
# Send to specific agent
await bridge.send_to_agent("Allegro", "Check deployment status")
# Broadcast to all agents
await bridge.broadcast("System maintenance starting")
# Add message handler
def handle_message(msg):
print(f"From {msg.sender}: {msg.content}")
bridge.add_handler(handle_message)
```
### Convenience Functions
```python
from agent.matrix_bridge import send_to_agent, broadcast_to_agents
# Send message
await send_to_agent("Ezra", "Review PR #456")
# Broadcast
await broadcast_to_agents("Going offline for maintenance")
```
### Agent Registry
```python
from agent.matrix_bridge import AgentRegistry
registry = AgentRegistry()
# Register agent with capabilities
registry.register("Timmy", capabilities=["code", "review", "deploy"])
registry.register("Allegro", capabilities=["monitoring", "alerting"])
# Find agents with capability
coders = registry.find_agents_with_capability("code")
```
## Message Flow
```
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Timmy │────▶│ Matrix │────▶│ Allegro │
│ Agent │ │ Room │ │ Agent │
└─────────┘ └─────────┘ └─────────┘
│ │ │
│ [@Allegro] │ │
│ Check deps │ │
└──────────────▶│ │
│ [@Allegro] │
│ Check deps │
└──────────────▶│
│ [@Timmy] │
│ Done ✓ │
│◀──────────────┘
│ [@Timmy] │
│ Done ✓ │
│◀──────────────┘
```
## Integration with Hermes
### In run_agent.py
```python
# Add to conversation loop
if self.matrix_bridge:
# Check for messages from other agents
messages = await self.matrix_bridge.get_pending_messages()
for msg in messages:
# Process agent-to-agent messages
pass
```
### In Gateway
```python
# Add Matrix bridge to gateway
from agent.matrix_bridge import MatrixBridge
bridge = MatrixBridge(agent_name="Timmy")
await bridge.connect()
gateway.matrix_bridge = bridge
```
## Testing
### Unit Tests
```python
def test_message_parsing():
"""Test message format parsing."""
from agent.matrix_bridge import MatrixBridge
bridge = MatrixBridge(agent_name="Timmy")
# Test recipient extraction
assert bridge._is_for_me("[@Timmy] Hello")
assert not bridge._is_for_me("[@Allegro] Hello")
assert bridge._is_for_me("[@*] Broadcast")
# Test content extraction
assert bridge._extract_content("[@Timmy] Hello") == "Hello"
assert bridge._extract_content("[@*] Test message") == "Test message"
```
### Integration Test
```bash
# Test with two agents
MATRIX_BRIDGE_ENABLED=true \
MATRIX_BRIDGE_ROOM=!test:matrix.example.org \
HERMES_AGENT_NAME=Timmy \
python -c "
import asyncio
from agent.matrix_bridge import send_to_agent
async def test():
await send_to_agent('Allegro', 'Test message')
print('Sent')
asyncio.run(test())
"
```
## Troubleshooting
### Bridge not connecting
1. Check `MATRIX_BRIDGE_ENABLED=true`
2. Verify `MATRIX_BRIDGE_ROOM` is set
3. Ensure Matrix credentials are configured
4. Check Matrix homeserver is reachable
### Messages not received
1. Verify agent is in the Matrix room
2. Check message format: `[@AgentName] content`
3. Ensure `HERMES_AGENT_NAME` matches agent name
4. Check Matrix sync is running
### Agent not found
1. Verify agent has joined the bridge room
2. Check agent name matches exactly (case-sensitive)
3. Ensure agent has announced presence
## Related
- Issue #747: feat: multi-agent conversation bridge via Matrix
- Matrix Gateway: `gateway/platforms/matrix.py`
- Multi-Agent Orchestration: `docs/multi-agent-orchestration.md`

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@@ -1,122 +0,0 @@
"""
Tests for approval tier system
Issue: #670
"""
import unittest
from tools.approval_tiers import (
ApprovalTier,
detect_tier,
requires_human_approval,
requires_llm_approval,
get_timeout,
should_auto_approve,
create_approval_request,
is_crisis_bypass,
TIER_INFO,
)
class TestApprovalTier(unittest.TestCase):
def test_tier_values(self):
self.assertEqual(ApprovalTier.SAFE, 0)
self.assertEqual(ApprovalTier.LOW, 1)
self.assertEqual(ApprovalTier.MEDIUM, 2)
self.assertEqual(ApprovalTier.HIGH, 3)
self.assertEqual(ApprovalTier.CRITICAL, 4)
class TestTierDetection(unittest.TestCase):
def test_safe_actions(self):
self.assertEqual(detect_tier("read_file"), ApprovalTier.SAFE)
self.assertEqual(detect_tier("web_search"), ApprovalTier.SAFE)
self.assertEqual(detect_tier("session_search"), ApprovalTier.SAFE)
def test_low_actions(self):
self.assertEqual(detect_tier("write_file"), ApprovalTier.LOW)
self.assertEqual(detect_tier("terminal"), ApprovalTier.LOW)
self.assertEqual(detect_tier("execute_code"), ApprovalTier.LOW)
def test_medium_actions(self):
self.assertEqual(detect_tier("send_message"), ApprovalTier.MEDIUM)
self.assertEqual(detect_tier("git_push"), ApprovalTier.MEDIUM)
def test_high_actions(self):
self.assertEqual(detect_tier("config_change"), ApprovalTier.HIGH)
self.assertEqual(detect_tier("key_rotation"), ApprovalTier.HIGH)
def test_critical_actions(self):
self.assertEqual(detect_tier("kill_process"), ApprovalTier.CRITICAL)
self.assertEqual(detect_tier("shutdown"), ApprovalTier.CRITICAL)
def test_pattern_detection(self):
tier = detect_tier("unknown", "rm -rf /")
self.assertEqual(tier, ApprovalTier.CRITICAL)
tier = detect_tier("unknown", "sudo apt install")
self.assertEqual(tier, ApprovalTier.MEDIUM)
class TestTierInfo(unittest.TestCase):
def test_safe_no_approval(self):
self.assertFalse(requires_human_approval(ApprovalTier.SAFE))
self.assertFalse(requires_llm_approval(ApprovalTier.SAFE))
self.assertIsNone(get_timeout(ApprovalTier.SAFE))
def test_medium_requires_both(self):
self.assertTrue(requires_human_approval(ApprovalTier.MEDIUM))
self.assertTrue(requires_llm_approval(ApprovalTier.MEDIUM))
self.assertEqual(get_timeout(ApprovalTier.MEDIUM), 60)
def test_critical_fast_timeout(self):
self.assertEqual(get_timeout(ApprovalTier.CRITICAL), 10)
class TestAutoApprove(unittest.TestCase):
def test_safe_auto_approves(self):
self.assertTrue(should_auto_approve("read_file"))
self.assertTrue(should_auto_approve("web_search"))
def test_write_doesnt_auto_approve(self):
self.assertFalse(should_auto_approve("write_file"))
class TestApprovalRequest(unittest.TestCase):
def test_create_request(self):
req = create_approval_request(
"send_message",
"Hello world",
"User requested",
"session_123"
)
self.assertEqual(req.tier, ApprovalTier.MEDIUM)
self.assertEqual(req.timeout_seconds, 60)
def test_to_dict(self):
req = create_approval_request("read_file", "cat file.txt", "test", "s1")
d = req.to_dict()
self.assertEqual(d["tier"], 0)
self.assertEqual(d["tier_name"], "Safe")
class TestCrisisBypass(unittest.TestCase):
def test_send_message_bypass(self):
self.assertTrue(is_crisis_bypass("send_message"))
def test_crisis_context_bypass(self):
self.assertTrue(is_crisis_bypass("unknown", "call 988 lifeline"))
self.assertTrue(is_crisis_bypass("unknown", "crisis resources"))
def test_normal_no_bypass(self):
self.assertFalse(is_crisis_bypass("read_file"))
if __name__ == "__main__":
unittest.main()

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@@ -1,55 +0,0 @@
"""
Tests for error classification (#752).
"""
import pytest
from tools.error_classifier import classify_error, ErrorCategory, ErrorClassification
class TestErrorClassification:
def test_timeout_is_retryable(self):
err = Exception("Connection timed out")
result = classify_error(err)
assert result.category == ErrorCategory.RETRYABLE
assert result.should_retry is True
def test_429_is_retryable(self):
err = Exception("Rate limit exceeded")
result = classify_error(err, response_code=429)
assert result.category == ErrorCategory.RETRYABLE
assert result.should_retry is True
def test_404_is_permanent(self):
err = Exception("Not found")
result = classify_error(err, response_code=404)
assert result.category == ErrorCategory.PERMANENT
assert result.should_retry is False
def test_403_is_permanent(self):
err = Exception("Forbidden")
result = classify_error(err, response_code=403)
assert result.category == ErrorCategory.PERMANENT
assert result.should_retry is False
def test_500_is_retryable(self):
err = Exception("Internal server error")
result = classify_error(err, response_code=500)
assert result.category == ErrorCategory.RETRYABLE
assert result.should_retry is True
def test_schema_error_is_permanent(self):
err = Exception("Schema validation failed")
result = classify_error(err)
assert result.category == ErrorCategory.PERMANENT
assert result.should_retry is False
def test_unknown_is_retryable_with_caution(self):
err = Exception("Some unknown error")
result = classify_error(err)
assert result.category == ErrorCategory.UNKNOWN
assert result.should_retry is True
assert result.max_retries == 1
if __name__ == "__main__":
pytest.main([__file__])

114
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"""Tests for Matrix Bridge — Issue #747."""
import sys
from pathlib import Path
sys.path.insert(0, str(Path(__file__).parent.parent))
from agent.matrix_bridge import MatrixBridge, AgentMessage, AgentRegistry
class TestMessageParsing:
"""Test message format parsing."""
def test_is_for_me_direct(self):
bridge = MatrixBridge(agent_name="Timmy")
assert bridge._is_for_me("[@Timmy] Hello") == True
def test_is_not_for_me(self):
bridge = MatrixBridge(agent_name="Timmy")
assert bridge._is_for_me("[@Allegro] Hello") == False
def test_is_broadcast(self):
bridge = MatrixBridge(agent_name="Timmy")
assert bridge._is_for_me("[@*] Broadcast") == True
def test_extract_content(self):
bridge = MatrixBridge(agent_name="Timmy")
assert bridge._extract_content("[@Timmy] Hello world") == "Hello world"
def test_extract_content_multiline(self):
bridge = MatrixBridge(agent_name="Timmy")
content = bridge._extract_content("[@Timmy] Line 1\nLine 2")
assert content == "Line 1\nLine 2"
class TestAgentMessage:
"""Test AgentMessage dataclass."""
def test_to_dict(self):
msg = AgentMessage(
sender="Timmy",
recipient="Allegro",
content="Hello",
timestamp=1234567890.0,
)
d = msg.to_dict()
assert d["sender"] == "Timmy"
assert d["recipient"] == "Allegro"
assert d["content"] == "Hello"
def test_from_dict(self):
d = {
"sender": "Timmy",
"recipient": "Allegro",
"content": "Hello",
"timestamp": 1234567890.0,
"message_id": "",
"room_id": "",
}
msg = AgentMessage.from_dict(d)
assert msg.sender == "Timmy"
assert msg.recipient == "Allegro"
class TestAgentRegistry:
"""Test AgentRegistry."""
def test_register(self):
registry = AgentRegistry()
registry.register("Timmy", capabilities=["code", "review"])
agent = registry.get_agent("Timmy")
assert agent["name"] == "Timmy"
assert "code" in agent["capabilities"]
def test_list_agents(self):
registry = AgentRegistry()
registry.register("Timmy")
registry.register("Allegro")
agents = registry.list_agents()
assert len(agents) == 2
def test_find_with_capability(self):
registry = AgentRegistry()
registry.register("Timmy", capabilities=["code"])
registry.register("Allegro", capabilities=["monitoring"])
coders = registry.find_agents_with_capability("code")
assert "Timmy" in coders
assert "Allegro" not in coders
def test_unregister(self):
registry = AgentRegistry()
registry.register("Timmy")
registry.unregister("Timmy")
agent = registry.get_agent("Timmy")
assert agent["status"] == "offline"
class TestBridgeInit:
"""Test bridge initialization."""
def test_default_agent_name(self):
bridge = MatrixBridge()
assert bridge.agent_name == "Hermes"
def test_custom_agent_name(self):
bridge = MatrixBridge(agent_name="Timmy")
assert bridge.agent_name == "Timmy"
def test_known_agents_empty(self):
bridge = MatrixBridge()
assert len(bridge.get_known_agents()) == 0
if __name__ == "__main__":
import pytest
pytest.main([__file__, "-v"])

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@@ -1,82 +0,0 @@
"""Tests for Reader-Guided Reranking (RIDER) — issue #666."""
import pytest
from unittest.mock import MagicMock, patch
from agent.rider import RIDER, rerank_passages, is_rider_available
class TestRIDERClass:
def test_init(self):
rider = RIDER()
assert rider._auxiliary_task == "rider"
def test_rerank_empty_passages(self):
rider = RIDER()
result = rider.rerank([], "test query")
assert result == []
def test_rerank_fewer_than_top_n(self):
"""If passages <= top_n, return all (with scores if possible)."""
rider = RIDER()
passages = [{"content": "test content", "session_id": "s1"}]
result = rider.rerank(passages, "test query", top_n=3)
assert len(result) == 1
@patch("agent.rider.RIDER_ENABLED", False)
def test_rerank_disabled(self):
"""When disabled, return original order."""
rider = RIDER()
passages = [
{"content": f"content {i}", "session_id": f"s{i}"}
for i in range(5)
]
result = rider.rerank(passages, "test query", top_n=3)
assert result == passages[:3]
class TestConfidenceCalculation:
@pytest.fixture
def rider(self):
return RIDER()
def test_short_specific_answer(self, rider):
score = rider._calculate_confidence("Paris", "What is the capital of France?", "Paris is the capital of France.")
assert score > 0.5
def test_hedged_answer(self, rider):
score = rider._calculate_confidence(
"Maybe it could be Paris, but I'm not sure",
"What is the capital of France?",
"Paris is the capital.",
)
assert score < 0.5
def test_passage_grounding(self, rider):
score = rider._calculate_confidence(
"The system uses SQLite for storage",
"What database is used?",
"The system uses SQLite for persistent storage with FTS5 indexing.",
)
assert score > 0.5
def test_refusal_penalty(self, rider):
score = rider._calculate_confidence(
"I cannot answer this from the given context",
"What is X?",
"Some unrelated content",
)
assert score < 0.5
class TestRerankPassages:
def test_convenience_function(self):
"""Test the module-level convenience function."""
passages = [{"content": "test", "session_id": "s1"}]
result = rerank_passages(passages, "query", top_n=1)
assert len(result) == 1
class TestIsRiderAvailable:
def test_returns_bool(self):
result = is_rider_available()
assert isinstance(result, bool)

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@@ -1,261 +0,0 @@
"""
Approval Tier System — Graduated safety based on risk level
Extends approval.py with 5-tier system for command approval.
| Tier | Action | Human | LLM | Timeout |
|------|-----------------|-------|-----|---------|
| 0 | Read, search | No | No | N/A |
| 1 | Write, scripts | No | Yes | N/A |
| 2 | Messages, API | Yes | Yes | 60s |
| 3 | Crypto, config | Yes | Yes | 30s |
| 4 | Crisis | Yes | Yes | 10s |
Issue: #670
"""
import re
from dataclasses import dataclass
from enum import IntEnum
from typing import Any, Dict, List, Optional, Tuple
class ApprovalTier(IntEnum):
"""Approval tiers based on risk level."""
SAFE = 0 # Read, search — no approval needed
LOW = 1 # Write, scripts — LLM approval
MEDIUM = 2 # Messages, API — human + LLM, 60s timeout
HIGH = 3 # Crypto, config — human + LLM, 30s timeout
CRITICAL = 4 # Crisis — human + LLM, 10s timeout
# Tier metadata
TIER_INFO = {
ApprovalTier.SAFE: {
"name": "Safe",
"human_required": False,
"llm_required": False,
"timeout_seconds": None,
"description": "Read-only operations, no approval needed"
},
ApprovalTier.LOW: {
"name": "Low",
"human_required": False,
"llm_required": True,
"timeout_seconds": None,
"description": "Write operations, LLM approval sufficient"
},
ApprovalTier.MEDIUM: {
"name": "Medium",
"human_required": True,
"llm_required": True,
"timeout_seconds": 60,
"description": "External actions, human confirmation required"
},
ApprovalTier.HIGH: {
"name": "High",
"human_required": True,
"llm_required": True,
"timeout_seconds": 30,
"description": "Sensitive operations, quick timeout"
},
ApprovalTier.CRITICAL: {
"name": "Critical",
"human_required": True,
"llm_required": True,
"timeout_seconds": 10,
"description": "Crisis or dangerous operations, fastest timeout"
},
}
# Action-to-tier mapping
ACTION_TIERS: Dict[str, ApprovalTier] = {
# Tier 0: Safe (read-only)
"read_file": ApprovalTier.SAFE,
"search_files": ApprovalTier.SAFE,
"web_search": ApprovalTier.SAFE,
"session_search": ApprovalTier.SAFE,
"list_files": ApprovalTier.SAFE,
"get_file_content": ApprovalTier.SAFE,
"memory_search": ApprovalTier.SAFE,
"skills_list": ApprovalTier.SAFE,
"skills_search": ApprovalTier.SAFE,
# Tier 1: Low (write operations)
"write_file": ApprovalTier.LOW,
"create_file": ApprovalTier.LOW,
"patch_file": ApprovalTier.LOW,
"delete_file": ApprovalTier.LOW,
"execute_code": ApprovalTier.LOW,
"terminal": ApprovalTier.LOW,
"run_script": ApprovalTier.LOW,
"skill_install": ApprovalTier.LOW,
# Tier 2: Medium (external actions)
"send_message": ApprovalTier.MEDIUM,
"web_fetch": ApprovalTier.MEDIUM,
"browser_navigate": ApprovalTier.MEDIUM,
"api_call": ApprovalTier.MEDIUM,
"gitea_create_issue": ApprovalTier.MEDIUM,
"gitea_create_pr": ApprovalTier.MEDIUM,
"git_push": ApprovalTier.MEDIUM,
"deploy": ApprovalTier.MEDIUM,
# Tier 3: High (sensitive operations)
"config_change": ApprovalTier.HIGH,
"env_change": ApprovalTier.HIGH,
"key_rotation": ApprovalTier.HIGH,
"access_grant": ApprovalTier.HIGH,
"permission_change": ApprovalTier.HIGH,
"backup_restore": ApprovalTier.HIGH,
# Tier 4: Critical (crisis/dangerous)
"kill_process": ApprovalTier.CRITICAL,
"rm_rf": ApprovalTier.CRITICAL,
"format_disk": ApprovalTier.CRITICAL,
"shutdown": ApprovalTier.CRITICAL,
"crisis_override": ApprovalTier.CRITICAL,
}
# Dangerous command patterns (from existing approval.py)
_DANGEROUS_PATTERNS = [
(r"rm\s+-rf\s+/", ApprovalTier.CRITICAL),
(r"mkfs\.", ApprovalTier.CRITICAL),
(r"dd\s+if=.*of=/dev/", ApprovalTier.CRITICAL),
(r"shutdown|reboot|halt", ApprovalTier.CRITICAL),
(r"chmod\s+777", ApprovalTier.HIGH),
(r"curl.*\|\s*bash", ApprovalTier.HIGH),
(r"wget.*\|\s*sh", ApprovalTier.HIGH),
(r"eval\s*\(", ApprovalTier.HIGH),
(r"sudo\s+", ApprovalTier.MEDIUM),
(r"git\s+push.*--force", ApprovalTier.HIGH),
(r"docker\s+rm.*-f", ApprovalTier.MEDIUM),
(r"kubectl\s+delete", ApprovalTier.HIGH),
]
@dataclass
class ApprovalRequest:
"""A request for approval."""
action: str
tier: ApprovalTier
command: str
reason: str
session_key: str
timeout_seconds: Optional[int] = None
def to_dict(self) -> Dict[str, Any]:
return {
"action": self.action,
"tier": self.tier.value,
"tier_name": TIER_INFO[self.tier]["name"],
"command": self.command,
"reason": self.reason,
"session_key": self.session_key,
"timeout": self.timeout_seconds,
"human_required": TIER_INFO[self.tier]["human_required"],
"llm_required": TIER_INFO[self.tier]["llm_required"],
}
def detect_tier(action: str, command: str = "") -> ApprovalTier:
"""
Detect the approval tier for an action.
Checks action name first, then falls back to pattern matching.
"""
# Direct action mapping
if action in ACTION_TIERS:
return ACTION_TIERS[action]
# Pattern matching on command
if command:
for pattern, tier in _DANGEROUS_PATTERNS:
if re.search(pattern, command, re.IGNORECASE):
return tier
# Default to LOW for unknown actions
return ApprovalTier.LOW
def requires_human_approval(tier: ApprovalTier) -> bool:
"""Check if tier requires human approval."""
return TIER_INFO[tier]["human_required"]
def requires_llm_approval(tier: ApprovalTier) -> bool:
"""Check if tier requires LLM approval."""
return TIER_INFO[tier]["llm_required"]
def get_timeout(tier: ApprovalTier) -> Optional[int]:
"""Get timeout in seconds for a tier."""
return TIER_INFO[tier]["timeout_seconds"]
def should_auto_approve(action: str, command: str = "") -> bool:
"""Check if action should be auto-approved (tier 0)."""
tier = detect_tier(action, command)
return tier == ApprovalTier.SAFE
def format_approval_prompt(request: ApprovalRequest) -> str:
"""Format an approval request for display."""
info = TIER_INFO[request.tier]
lines = []
lines.append(f"⚠️ Approval Required (Tier {request.tier.value}: {info['name']})")
lines.append(f"")
lines.append(f"Action: {request.action}")
lines.append(f"Command: {request.command[:100]}{'...' if len(request.command) > 100 else ''}")
lines.append(f"Reason: {request.reason}")
lines.append(f"")
if info["human_required"]:
lines.append(f"👤 Human approval required")
if info["llm_required"]:
lines.append(f"🤖 LLM approval required")
if info["timeout_seconds"]:
lines.append(f"⏱️ Timeout: {info['timeout_seconds']}s")
return "\n".join(lines)
def create_approval_request(
action: str,
command: str,
reason: str,
session_key: str
) -> ApprovalRequest:
"""Create an approval request for an action."""
tier = detect_tier(action, command)
timeout = get_timeout(tier)
return ApprovalRequest(
action=action,
tier=tier,
command=command,
reason=reason,
session_key=session_key,
timeout_seconds=timeout
)
# Crisis bypass rules
CRISIS_BYPASS_ACTIONS = frozenset([
"send_message", # Always allow sending crisis resources
"check_crisis",
"notify_crisis",
])
def is_crisis_bypass(action: str, context: str = "") -> bool:
"""Check if action should bypass approval during crisis."""
if action in CRISIS_BYPASS_ACTIONS:
return True
# Check if context indicates crisis
crisis_indicators = ["988", "crisis", "suicide", "self-harm", "lifeline"]
context_lower = context.lower()
return any(indicator in context_lower for indicator in crisis_indicators)

View File

@@ -1,233 +0,0 @@
"""
Tool Error Classification — Retryable vs Permanent.
Classifies tool errors so the agent retries transient errors
but gives up on permanent ones immediately.
"""
import logging
import re
import time
from dataclasses import dataclass
from enum import Enum
from typing import Optional, Dict, Any
logger = logging.getLogger(__name__)
class ErrorCategory(Enum):
"""Error category classification."""
RETRYABLE = "retryable"
PERMANENT = "permanent"
UNKNOWN = "unknown"
@dataclass
class ErrorClassification:
"""Result of error classification."""
category: ErrorCategory
reason: str
should_retry: bool
max_retries: int
backoff_seconds: float
error_code: Optional[int] = None
error_type: Optional[str] = None
# Retryable error patterns
_RETRYABLE_PATTERNS = [
# HTTP status codes
(r"\b429\b", "rate limit", 3, 5.0),
(r"\b500\b", "server error", 3, 2.0),
(r"\b502\b", "bad gateway", 3, 2.0),
(r"\b503\b", "service unavailable", 3, 5.0),
(r"\b504\b", "gateway timeout", 3, 5.0),
# Timeout patterns
(r"timeout", "timeout", 3, 2.0),
(r"timed out", "timeout", 3, 2.0),
(r"TimeoutExpired", "timeout", 3, 2.0),
# Connection errors
(r"connection refused", "connection refused", 2, 5.0),
(r"connection reset", "connection reset", 2, 2.0),
(r"network unreachable", "network unreachable", 2, 10.0),
(r"DNS", "DNS error", 2, 5.0),
# Transient errors
(r"temporary", "temporary error", 2, 2.0),
(r"transient", "transient error", 2, 2.0),
(r"retry", "retryable", 2, 2.0),
]
# Permanent error patterns
_PERMANENT_PATTERNS = [
# HTTP status codes
(r"\b400\b", "bad request", "Invalid request parameters"),
(r"\b401\b", "unauthorized", "Authentication failed"),
(r"\b403\b", "forbidden", "Access denied"),
(r"\b404\b", "not found", "Resource not found"),
(r"\b405\b", "method not allowed", "HTTP method not supported"),
(r"\b409\b", "conflict", "Resource conflict"),
(r"\b422\b", "unprocessable", "Validation error"),
# Schema/validation errors
(r"schema", "schema error", "Invalid data schema"),
(r"validation", "validation error", "Input validation failed"),
(r"invalid.*json", "JSON error", "Invalid JSON"),
(r"JSONDecodeError", "JSON error", "JSON parsing failed"),
# Authentication
(r"api.?key", "API key error", "Invalid or missing API key"),
(r"token.*expir", "token expired", "Authentication token expired"),
(r"permission", "permission error", "Insufficient permissions"),
# Not found patterns
(r"not found", "not found", "Resource does not exist"),
(r"does not exist", "not found", "Resource does not exist"),
(r"no such file", "file not found", "File does not exist"),
# Quota/billing
(r"quota", "quota exceeded", "Usage quota exceeded"),
(r"billing", "billing error", "Billing issue"),
(r"insufficient.*funds", "billing error", "Insufficient funds"),
]
def classify_error(error: Exception, response_code: Optional[int] = None) -> ErrorClassification:
"""
Classify an error as retryable or permanent.
Args:
error: The exception that occurred
response_code: HTTP response code if available
Returns:
ErrorClassification with retry guidance
"""
error_str = str(error).lower()
error_type = type(error).__name__
# Check response code first
if response_code:
if response_code in (429, 500, 502, 503, 504):
return ErrorClassification(
category=ErrorCategory.RETRYABLE,
reason=f"HTTP {response_code} - transient server error",
should_retry=True,
max_retries=3,
backoff_seconds=5.0 if response_code == 429 else 2.0,
error_code=response_code,
error_type=error_type,
)
elif response_code in (400, 401, 403, 404, 405, 409, 422):
return ErrorClassification(
category=ErrorCategory.PERMANENT,
reason=f"HTTP {response_code} - client error",
should_retry=False,
max_retries=0,
backoff_seconds=0,
error_code=response_code,
error_type=error_type,
)
# Check retryable patterns
for pattern, reason, max_retries, backoff in _RETRYABLE_PATTERNS:
if re.search(pattern, error_str, re.IGNORECASE):
return ErrorClassification(
category=ErrorCategory.RETRYABLE,
reason=reason,
should_retry=True,
max_retries=max_retries,
backoff_seconds=backoff,
error_type=error_type,
)
# Check permanent patterns
for pattern, error_code, reason in _PERMANENT_PATTERNS:
if re.search(pattern, error_str, re.IGNORECASE):
return ErrorClassification(
category=ErrorCategory.PERMANENT,
reason=reason,
should_retry=False,
max_retries=0,
backoff_seconds=0,
error_type=error_type,
)
# Default: unknown, treat as retryable with caution
return ErrorClassification(
category=ErrorCategory.UNKNOWN,
reason=f"Unknown error type: {error_type}",
should_retry=True,
max_retries=1,
backoff_seconds=1.0,
error_type=error_type,
)
def execute_with_retry(
func,
*args,
max_retries: int = 3,
backoff_base: float = 1.0,
**kwargs,
) -> Any:
"""
Execute a function with automatic retry on retryable errors.
Args:
func: Function to execute
*args: Function arguments
max_retries: Maximum retry attempts
backoff_base: Base backoff time in seconds
**kwargs: Function keyword arguments
Returns:
Function result
Raises:
Exception: If permanent error or max retries exceeded
"""
last_error = None
for attempt in range(max_retries + 1):
try:
return func(*args, **kwargs)
except Exception as e:
last_error = e
# Classify the error
classification = classify_error(e)
logger.info(
"Attempt %d/%d failed: %s (%s, retryable: %s)",
attempt + 1, max_retries + 1,
classification.reason,
classification.category.value,
classification.should_retry,
)
# If permanent error, fail immediately
if not classification.should_retry:
logger.error("Permanent error: %s", classification.reason)
raise
# If this was the last attempt, raise
if attempt >= max_retries:
logger.error("Max retries (%d) exceeded", max_retries)
raise
# Calculate backoff with exponential increase
backoff = backoff_base * (2 ** attempt)
logger.info("Retrying in %.1fs...", backoff)
time.sleep(backoff)
# Should not reach here, but just in case
raise last_error
def format_error_report(classification: ErrorClassification) -> str:
"""Format error classification as a report string."""
icon = "🔄" if classification.should_retry else ""
return f"{icon} {classification.category.value}: {classification.reason}"

View File

@@ -1,77 +0,0 @@
"""Hybrid Search — FTS5 + vector with Reciprocal Rank Fusion.
Combines keyword (FTS5) and semantic (vector) search with RRF merging.
"""
import logging, os
from typing import Any, Dict, List, Optional, Tuple
logger = logging.getLogger(__name__)
FTS5_WEIGHT = float(os.getenv("HYBRID_FTS5_WEIGHT", "0.6"))
VECTOR_WEIGHT = float(os.getenv("HYBRID_VECTOR_WEIGHT", "0.4"))
RRF_K = int(os.getenv("HYBRID_RRF_K", "60"))
VECTOR_ENABLED = os.getenv("HYBRID_VECTOR_ENABLED", "true").lower() not in ("false", "0", "no")
_qdrant_client = None
def _get_qdrant_client():
global _qdrant_client
if _qdrant_client is not None:
return _qdrant_client if _qdrant_client is not False else None
if not VECTOR_ENABLED:
return None
try:
from qdrant_client import QdrantClient
_qdrant_client = QdrantClient(host=os.getenv("QDRANT_HOST","localhost"), port=int(os.getenv("QDRANT_PORT","6333")), timeout=5)
_qdrant_client.get_collections()
return _qdrant_client
except Exception as e:
logger.debug("Qdrant unavailable: %s", e)
_qdrant_client = False
return None
def _vector_search(query: str, limit: int = 50) -> List[Dict[str, Any]]:
client = _get_qdrant_client()
if client is None:
return []
try:
import hashlib
vec = [b/255.0 for b in hashlib.sha256(query.lower().encode()).digest()[:128]]
results = client.search(collection_name="session_messages", query_vector=vec, limit=limit, score_threshold=0.3)
return [{"session_id": h.payload.get("session_id",""), "content": h.payload.get("content",""), "score": h.score, "rank": i+1, "source": "vector"} for i, h in enumerate(results)]
except Exception:
return []
def _fts5_search(query: str, db, limit: int = 50, **kwargs) -> List[Dict[str, Any]]:
try:
raw = db.search_messages(query=query, limit=limit, offset=0, **kwargs)
for i, r in enumerate(raw):
r["rank"] = i+1
r["source"] = "fts5"
return raw
except Exception as e:
logger.warning("FTS5 failed: %s", e)
return []
def _rrf(result_sets: List[Tuple[List[Dict], float]], k: int = RRF_K, limit: int = 20) -> List[Dict]:
scores, best = {}, {}
for results, weight in result_sets:
for e in results:
sid = e.get("session_id","")
if not sid: continue
scores[sid] = scores.get(sid, 0) + weight / (k + e.get("rank", 999))
if sid not in best or e.get("source") == "fts5":
best[sid] = e
ranked = sorted(scores.items(), key=lambda x: x[1], reverse=True)
return [{**best.get(sid, {"session_id": sid}), "fused_score": round(s, 6)} for sid, s in ranked[:limit]]
def hybrid_search(query: str, db, limit: int = 50, **kwargs) -> List[Dict[str, Any]]:
fts5 = _fts5_search(query, db, limit=limit, **kwargs)
vec = _vector_search(query, limit=limit)
if not vec:
return fts5[:limit]
return _rrf([(fts5, FTS5_WEIGHT), (vec, VECTOR_WEIGHT)], limit=limit)
def get_search_stats() -> Dict[str, Any]:
return {"fts5": True, "vector": _get_qdrant_client() is not None, "fusion": "rrf", "weights": {"fts5": FTS5_WEIGHT, "vector": VECTOR_WEIGHT}, "rrf_k": RRF_K}

View File

@@ -394,23 +394,6 @@ def session_search(
if len(seen_sessions) >= limit:
break
# RIDER: Reader-guided reranking — sort sessions by LLM answerability
# This bridges the R@5 vs E2E accuracy gap by prioritizing passages
# the LLM can actually answer from, not just keyword matches.
try:
from agent.rider import rerank_passages, is_rider_available
if is_rider_available() and len(seen_sessions) > 1:
rider_passages = [
{"session_id": sid, "content": info.get("snippet", ""), "rank": i + 1}
for i, (sid, info) in enumerate(seen_sessions.items())
]
reranked = rerank_passages(rider_passages, query, top_n=len(rider_passages))
# Reorder seen_sessions by RIDER score
reranked_sids = [p["session_id"] for p in reranked]
seen_sessions = {sid: seen_sessions[sid] for sid in reranked_sids if sid in seen_sessions}
except Exception as e:
logging.debug("RIDER reranking skipped: %s", e)
# Prepare all sessions for parallel summarization
tasks = []
for session_id, match_info in seen_sessions.items():