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Author SHA1 Message Date
Alexander Whitestone
6c849a1157 feat: warm session provisioning v2 — full acceptance criteria (#327)
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Marathon sessions (100+ msgs) have lower per-tool error rates (5.7%)
than mid-length sessions (9.0%). This implements warm session
provisioning addressing all four acceptance criteria:

1. What makes marathon sessions reliable?
   - SessionProfiler analyzes error rates, tool distribution,
     proficiency gain (early vs late error rate delta)

2. Pre-seed sessions with successful tool-call examples?
   - PatternExtractor mines successful tool calls from SessionDB
   - build_warm_conversation() converts to conversation_history
   - Injected via existing run_conversation() parameter

3. Does context compression preserve proficiency?
   - analyze_compression_impact() compares parent vs child session
     error rates after compression events

4. A/B testing: warm vs cold comparison
   - compare_sessions() computes error rate improvement
   - profile action analyzes individual sessions
   - compare action runs A/B between two sessions

agent/warm_session.py (678 lines):
  - SessionProfile, WarmPattern, WarmSessionTemplate dataclasses
  - profile_session() — reliability analysis
  - extract_patterns_from_session() — mines successful patterns
  - extract_from_session_db() — batch extraction from marathon sessions
  - build_warm_conversation() — conversation_history builder
  - analyze_compression_impact() — compression preservation test
  - compare_sessions() — A/B comparison
  - save/load/list templates

tools/warm_session_tool.py (275 lines):
  7 actions: build, list, load, delete, profile, compress-check, compare

25 tests added, all passing.

Closes #327
2026-04-13 20:19:58 -04:00
3 changed files with 1291 additions and 0 deletions

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agent/warm_session.py Normal file
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"""Warm Session Provisioning v2 — pre-proficient agent sessions.
Marathon sessions (100+ msgs) have lower per-tool error rates because
agents accumulate successful patterns and context. This module provides
infrastructure to capture that proficiency and pre-seed new sessions.
Addresses all acceptance criteria from #327:
1. What makes marathon sessions reliable? → pattern extraction + analysis
2. Pre-seed with successful tool-call examples → conversation_history injection
3. Context compression preservation → compressed_session support
4. A/B testing → warm vs cold comparison infrastructure
Architecture:
- SessionProfiler: analyzes session reliability metrics
- PatternExtractor: mines successful tool-call sequences
- WarmSessionTemplate: holds patterns + metadata
- CompressionAnalyzer: tests if compression preserves proficiency
- ABTester: compares warm vs cold session performance
"""
import json
import logging
import time
from collections import defaultdict
from dataclasses import dataclass, field, asdict
from pathlib import Path
from typing import Any, Dict, List, Optional, Tuple
from hermes_constants import get_hermes_home
logger = logging.getLogger(__name__)
TEMPLATES_DIR = get_hermes_home() / "warm_sessions"
# ---------------------------------------------------------------------------
# Data structures
# ---------------------------------------------------------------------------
@dataclass
class ToolCallOutcome:
"""A single tool call with its context and outcome."""
tool_name: str
arguments: Dict[str, Any]
result_success: bool
result_error: Optional[str] = None
result_summary: str = ""
session_position: int = 0 # which turn in the session (0-indexed)
context_tokens: int = 0 # approximate context size at this point
@dataclass
class SessionProfile:
"""Analysis of a single session's reliability patterns."""
session_id: str
message_count: int
tool_call_count: int
successful_calls: int
failed_calls: int
error_rate: float
tool_distribution: Dict[str, int] = field(default_factory=dict)
tool_success_rates: Dict[str, float] = field(default_factory=dict)
early_error_rate: float = 0.0 # first 20% of calls
late_error_rate: float = 0.0 # last 20% of calls
proficiency_gain: float = 0.0 # late_error_rate - early_error_rate (negative = improvement)
dominant_tool_type: str = "" # code, file, research, terminal
@dataclass
class WarmPattern:
"""A successful tool-call pattern with context."""
tool_name: str
arguments: Dict[str, Any]
result_summary: str
preceding_context: str = "" # what the user/agent said before this call
pattern_type: str = "" # "init", "sequence", "retry", "final"
success_count: int = 1
session_types: List[str] = field(default_factory=list) # which session types this appeared in
@dataclass
class WarmSessionTemplate:
"""A template for pre-seeding proficient sessions."""
name: str
description: str
patterns: List[WarmPattern] = field(default_factory=list)
system_prompt_addendum: str = ""
tags: List[str] = field(default_factory=list)
source_session_ids: List[str] = field(default_factory=list)
created_at: float = 0
version: int = 2
metrics: Dict[str, Any] = field(default_factory=dict) # extraction metrics
def __post_init__(self):
if not self.created_at:
self.created_at = time.time()
def to_dict(self) -> Dict[str, Any]:
return asdict(self)
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "WarmSessionTemplate":
patterns = [
WarmPattern(**p) if isinstance(p, dict) else p
for p in data.get("patterns", [])
]
return cls(
name=data["name"],
description=data.get("description", ""),
patterns=patterns,
system_prompt_addendum=data.get("system_prompt_addendum", ""),
tags=data.get("tags", []),
source_session_ids=data.get("source_session_ids", []),
created_at=data.get("created_at", 0),
version=data.get("version", 2),
metrics=data.get("metrics", {}),
)
# ---------------------------------------------------------------------------
# Session Profiler — analyzes why marathon sessions are more reliable
# ---------------------------------------------------------------------------
# Tools that are "trivial" and shouldn't be included in patterns
_TRIVIAL_TOOLS = frozenset({
"clarify", "memory", "fact_store", "fact_feedback",
"session_search", "skill_view", "skills_list",
})
# Tool type classification
_TOOL_TYPES = {
"terminal": "terminal",
"execute_code": "code",
"read_file": "file",
"write_file": "file",
"patch": "file",
"search_files": "file",
"web_search": "research",
"web_extract": "research",
"browser": "research",
"skill_manage": "code",
"warm_session": "meta",
}
def classify_tool_type(tool_name: str) -> str:
"""Classify a tool into a broad category."""
return _TOOL_TYPES.get(tool_name, "general")
def profile_session(messages: List[Dict[str, Any]], session_id: str = "") -> SessionProfile:
"""Analyze a session's reliability patterns.
Examines tool call outcomes across the session to determine if
the agent improved with experience (lower error rate later).
"""
tool_outcomes: List[ToolCallOutcome] = []
for i, msg in enumerate(messages):
if msg.get("role") != "assistant":
continue
tool_calls_raw = msg.get("tool_calls")
if not tool_calls_raw:
continue
try:
tool_calls = json.loads(tool_calls_raw) if isinstance(tool_calls_raw, str) else tool_calls_raw
except (json.JSONDecodeError, TypeError):
continue
if not isinstance(tool_calls, list):
continue
for tc in tool_calls:
if not isinstance(tc, dict):
continue
func = tc.get("function", {})
tool_name = func.get("name", "")
if not tool_name or tool_name in _TRIVIAL_TOOLS:
continue
try:
arguments = json.loads(func.get("arguments", "{}"))
except (json.JSONDecodeError, TypeError):
arguments = {}
# Find the corresponding tool result
tc_id = tc.get("id", "")
result_msg = None
for subsequent in messages[i+1:i+5]: # look ahead a few messages
if subsequent.get("role") == "tool" and subsequent.get("tool_call_id") == tc_id:
result_msg = subsequent
break
result_content = result_msg.get("content", "") if result_msg else ""
# Heuristic: if result contains error indicators, it failed
result_success = not any(err in str(result_content).lower() for err in [
"error", "failed", "exception", "traceback", "denied", "not found",
])
tool_outcomes.append(ToolCallOutcome(
tool_name=tool_name,
arguments=arguments,
result_success=result_success,
result_summary=str(result_content)[:500] if result_content else "",
session_position=i,
))
if not tool_outcomes:
return SessionProfile(
session_id=session_id,
message_count=len(messages),
tool_call_count=0,
successful_calls=0,
failed_calls=0,
error_rate=0.0,
)
# Calculate metrics
total = len(tool_outcomes)
successful = sum(1 for o in tool_outcomes if o.result_success)
failed = total - successful
error_rate = failed / total if total > 0 else 0.0
# Tool distribution
tool_dist: Dict[str, int] = defaultdict(int)
tool_success: Dict[str, List[bool]] = defaultdict(list)
for outcome in tool_outcomes:
tool_dist[outcome.tool_name] += 1
tool_success[outcome.tool_name].append(outcome.result_success)
tool_success_rates = {
name: sum(outcomes) / len(outcomes) if outcomes else 0.0
for name, outcomes in tool_success.items()
}
# Early vs late error rates (proficiency gain)
split_point = max(1, total // 5) # first 20%
early = tool_outcomes[:split_point]
late = tool_outcomes[-split_point:]
early_errors = sum(1 for o in early if not o.result_success) / len(early) if early else 0
late_errors = sum(1 for o in late if not o.result_success) / len(late) if late else 0
proficiency_gain = late_errors - early_errors # negative = improvement
# Dominant tool type
type_counts: Dict[str, int] = defaultdict(int)
for outcome in tool_outcomes:
type_counts[classify_tool_type(outcome.tool_name)] += 1
dominant = max(type_counts.items(), key=lambda x: x[1])[0] if type_counts else "general"
return SessionProfile(
session_id=session_id,
message_count=len(messages),
tool_call_count=total,
successful_calls=successful,
failed_calls=failed,
error_rate=error_rate,
tool_distribution=dict(tool_dist),
tool_success_rates=tool_success_rates,
early_error_rate=early_errors,
late_error_rate=late_errors,
proficiency_gain=proficiency_gain,
dominant_tool_type=dominant,
)
# ---------------------------------------------------------------------------
# Pattern Extractor — mines successful tool-call sequences
# ---------------------------------------------------------------------------
def extract_patterns_from_session(
messages: List[Dict[str, Any]],
min_success_rate: float = 0.8,
) -> List[WarmPattern]:
"""Extract successful patterns from a single session.
Only includes tools that succeeded, with their arguments and
result summaries as reusable patterns.
"""
patterns: List[WarmPattern] = []
for i, msg in enumerate(messages):
if msg.get("role") != "assistant":
continue
tool_calls_raw = msg.get("tool_calls")
if not tool_calls_raw:
continue
try:
tool_calls = json.loads(tool_calls_raw) if isinstance(tool_calls_raw, str) else tool_calls_raw
except (json.JSONDecodeError, TypeError):
continue
if not isinstance(tool_calls, list):
continue
for tc in tool_calls:
if not isinstance(tc, dict):
continue
func = tc.get("function", {})
tool_name = func.get("name", "")
if not tool_name or tool_name in _TRIVIAL_TOOLS:
continue
try:
arguments = json.loads(func.get("arguments", "{}"))
except (json.JSONDecodeError, TypeError):
continue
# Find the result
tc_id = tc.get("id", "")
result_content = ""
result_success = False
for subsequent in messages[i+1:i+5]:
if subsequent.get("role") == "tool" and subsequent.get("tool_call_id") == tc_id:
result_content = str(subsequent.get("content", ""))
result_success = not any(err in result_content.lower() for err in [
"error", "failed", "exception", "traceback", "denied",
])
break
if not result_success:
continue # only capture successful patterns
# Get preceding context
preceding = ""
if i > 0:
prev = messages[i-1]
if prev.get("role") == "user":
preceding = str(prev.get("content", ""))[:200]
patterns.append(WarmPattern(
tool_name=tool_name,
arguments=arguments,
result_summary=result_content[:500],
preceding_context=preceding,
pattern_type="sequence",
))
return patterns
def extract_from_session_db(
session_db,
min_messages: int = 30,
max_sessions: int = 50,
source_filter: str = None,
) -> Tuple[List[WarmPattern], Dict[str, Any]]:
"""Mine patterns from marathon sessions in the SessionDB.
Returns (patterns, metrics) where metrics tracks extraction stats.
"""
all_patterns: List[WarmPattern] = []
metrics = {
"sessions_scanned": 0,
"sessions_qualified": 0,
"total_patterns": 0,
"tool_distribution": defaultdict(int),
"avg_proficiency_gain": 0.0,
}
try:
sessions = session_db.list_sessions(
limit=max_sessions,
source=source_filter,
)
except Exception as e:
logger.warning("Failed to list sessions: %s", e)
return all_patterns, metrics
proficiency_gains: List[float] = []
for session_meta in sessions:
session_id = session_meta.get("id") or session_meta.get("session_id")
if not session_id:
continue
msg_count = session_meta.get("message_count", 0)
if msg_count < min_messages:
continue
end_reason = session_meta.get("end_reason", "")
if end_reason and end_reason not in ("completed", "user_exit", "compression"):
continue
metrics["sessions_scanned"] += 1
try:
messages = session_db.get_messages(session_id)
except Exception:
continue
# Profile the session
profile = profile_session(messages, session_id)
if profile.error_rate > 0.5: # skip very error-prone sessions
continue
metrics["sessions_qualified"] += 1
proficiency_gains.append(profile.proficiency_gain)
# Extract patterns
patterns = extract_patterns_from_session(messages)
for p in patterns:
p.session_types.append(profile.dominant_tool_type)
all_patterns.extend(patterns)
for p in patterns:
metrics["tool_distribution"][p.tool_name] += 1
metrics["total_patterns"] = len(all_patterns)
metrics["avg_proficiency_gain"] = (
sum(proficiency_gains) / len(proficiency_gains) if proficiency_gains else 0.0
)
return all_patterns, dict(metrics)
# ---------------------------------------------------------------------------
# Conversation Builder — converts patterns to conversation_history
# ---------------------------------------------------------------------------
def build_warm_conversation(
template: WarmSessionTemplate,
max_patterns: int = 15,
) -> List[Dict[str, Any]]:
"""Convert template patterns into conversation_history messages.
Produces a synthetic conversation that demonstrates successful
tool-calling patterns, priming the agent with experience.
"""
messages: List[Dict[str, Any]] = []
if template.system_prompt_addendum:
messages.append({
"role": "system",
"content": (
f"[WARM SESSION] The following patterns come from experienced, "
f"successful sessions. They demonstrate effective tool usage. "
f"Use them as reference for structuring your own tool calls.\n\n"
f"{template.system_prompt_addendum}"
),
})
patterns = template.patterns[:max_patterns]
for i, pattern in enumerate(patterns):
# User turn describing intent
user_content = pattern.preceding_context or f"[Pattern {i+1}] Demonstrate {pattern.tool_name} usage."
messages.append({"role": "user", "content": user_content})
# Assistant turn with the tool call
tool_call_id = f"warm_{i}_{pattern.tool_name}"
messages.append({
"role": "assistant",
"content": None,
"tool_calls": [{
"id": tool_call_id,
"type": "function",
"function": {
"name": pattern.tool_name,
"arguments": json.dumps(pattern.arguments, ensure_ascii=False),
},
}],
})
# Tool result
messages.append({
"role": "tool",
"tool_call_id": tool_call_id,
"content": pattern.result_summary or f"Tool {pattern.tool_name} executed successfully.",
})
return messages
# ---------------------------------------------------------------------------
# Compression Analyzer — tests if compression preserves proficiency
# ---------------------------------------------------------------------------
def analyze_compression_impact(
session_db,
session_id: str,
) -> Dict[str, Any]:
"""Analyze whether context compression preserves agent proficiency.
Compares the error rates before and after compression events in a session.
Compression creates a new session_id (parent → child chain).
"""
result = {
"session_id": session_id,
"has_compression": False,
"pre_compression_profile": None,
"post_compression_profile": None,
"proficiency_preserved": None,
}
try:
messages = session_db.get_messages(session_id)
except Exception:
return result
# Check if this session was the result of compression
try:
session_meta = session_db.get_session(session_id)
parent_id = session_meta.get("parent_session_id") if session_meta else None
except Exception:
parent_id = None
if not parent_id:
return result
result["has_compression"] = True
# Profile parent (pre-compression)
try:
parent_messages = session_db.get_messages(parent_id)
pre_profile = profile_session(parent_messages, parent_id)
result["pre_compression_profile"] = {
"error_rate": pre_profile.error_rate,
"tool_call_count": pre_profile.tool_call_count,
"proficiency_gain": pre_profile.proficiency_gain,
}
except Exception:
pass
# Profile current (post-compression)
post_profile = profile_session(messages, session_id)
result["post_compression_profile"] = {
"error_rate": post_profile.error_rate,
"tool_call_count": post_profile.tool_call_count,
"proficiency_gain": post_profile.proficiency_gain,
}
# Determine if proficiency was preserved
if result["pre_compression_profile"]:
pre_rate = result["pre_compression_profile"]["error_rate"]
post_rate = result["post_compression_profile"]["error_rate"]
# Proficiency preserved if post-compression error rate isn't significantly worse
result["proficiency_preserved"] = post_rate <= pre_rate * 1.2 # 20% tolerance
return result
# ---------------------------------------------------------------------------
# A/B Testing — warm vs cold session comparison
# ---------------------------------------------------------------------------
@dataclass
class ABTestResult:
"""Result of comparing warm vs cold session performance."""
test_name: str
warm_session_errors: int
warm_session_total: int
cold_session_errors: int
cold_session_total: int
warm_error_rate: float
cold_error_rate: float
improvement: float # positive = warm is better
warm_session_id: str = ""
cold_session_id: str = ""
def compare_sessions(
warm_profile: SessionProfile,
cold_profile: SessionProfile,
test_name: str = "",
) -> ABTestResult:
"""Compare warm vs cold session performance."""
warm_rate = warm_profile.error_rate
cold_rate = cold_profile.error_rate
improvement = cold_rate - warm_rate # positive means warm is better
return ABTestResult(
test_name=test_name,
warm_session_errors=warm_profile.failed_calls,
warm_session_total=warm_profile.tool_call_count,
cold_session_errors=cold_profile.failed_calls,
cold_session_total=cold_profile.tool_call_count,
warm_error_rate=warm_rate,
cold_error_rate=cold_rate,
improvement=improvement,
warm_session_id=warm_profile.session_id,
cold_session_id=cold_profile.session_id,
)
# ---------------------------------------------------------------------------
# Persistence
# ---------------------------------------------------------------------------
def save_template(template: WarmSessionTemplate) -> Path:
"""Save a warm session template to disk."""
TEMPLATES_DIR.mkdir(parents=True, exist_ok=True)
path = TEMPLATES_DIR / f"{template.name}.json"
path.write_text(json.dumps(template.to_dict(), indent=2, ensure_ascii=False))
logger.info("Warm session template saved: %s", path)
return path
def load_template(name: str) -> Optional[WarmSessionTemplate]:
"""Load a warm session template by name."""
path = TEMPLATES_DIR / f"{name}.json"
if not path.exists():
return None
try:
data = json.loads(path.read_text())
return WarmSessionTemplate.from_dict(data)
except Exception as e:
logger.warning("Failed to load warm session template '%s': %s", name, e)
return None
def list_templates() -> List[Dict[str, Any]]:
"""List all saved warm session templates."""
if not TEMPLATES_DIR.exists():
return []
templates = []
for path in sorted(TEMPLATES_DIR.glob("*.json")):
try:
data = json.loads(path.read_text())
templates.append({
"name": data.get("name", path.stem),
"description": data.get("description", ""),
"tags": data.get("tags", []),
"pattern_count": len(data.get("patterns", [])),
"created_at": data.get("created_at", 0),
"version": data.get("version", 1),
})
except Exception:
continue
return templates
def build_and_save(
session_db,
name: str,
description: str = "",
min_messages: int = 30,
max_sessions: int = 30,
source_filter: str = None,
tags: List[str] = None,
) -> Tuple[WarmSessionTemplate, Dict[str, Any]]:
"""One-shot: mine sessions, build template, save it.
Returns (template, extraction_metrics).
"""
patterns, metrics = extract_from_session_db(
session_db,
min_messages=min_messages,
max_sessions=max_sessions,
source_filter=source_filter,
)
# Deduplicate patterns by (tool_name, arguments)
seen = set()
unique_patterns = []
for p in patterns:
key = (p.tool_name, json.dumps(p.arguments, sort_keys=True))
if key not in seen:
seen.add(key)
unique_patterns.append(p)
template = WarmSessionTemplate(
name=name,
description=description or f"Auto-generated from {metrics['sessions_qualified']} sessions",
patterns=unique_patterns,
tags=tags or [],
source_session_ids=[],
metrics=metrics,
)
if unique_patterns:
save_template(template)
return template, metrics

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"""Tests for warm session provisioning v2 (#327)."""
import json
import time
from collections import defaultdict
from unittest.mock import MagicMock, patch
import pytest
from agent.warm_session import (
SessionProfile,
WarmPattern,
WarmSessionTemplate,
ToolCallOutcome,
classify_tool_type,
profile_session,
extract_patterns_from_session,
build_warm_conversation,
analyze_compression_impact,
compare_sessions,
save_template,
load_template,
list_templates,
_TRIVIAL_TOOLS,
)
@pytest.fixture()
def isolated_templates_dir(tmp_path, monkeypatch):
"""Point TEMPLATES_DIR at a temp directory."""
tdir = tmp_path / "warm_sessions"
tdir.mkdir()
monkeypatch.setattr("agent.warm_session.TEMPLATES_DIR", tdir)
return tdir
def _make_messages(tool_calls_and_results):
"""Helper to build message list from (tool_name, args, result, success) tuples."""
messages = []
for i, (tool_name, args, result, success) in enumerate(tool_calls_and_results):
tc_id = f"tc_{i}"
messages.append({
"role": "assistant",
"content": None,
"tool_calls": json.dumps([{
"id": tc_id,
"type": "function",
"function": {"name": tool_name, "arguments": json.dumps(args)},
}]),
})
error_words = "error failed" if not success else ""
messages.append({
"role": "tool",
"tool_call_id": tc_id,
"content": f"{result} {error_words}".strip(),
})
return messages
# ---------------------------------------------------------------------------
# Tool classification
# ---------------------------------------------------------------------------
class TestClassifyToolType:
def test_terminal(self):
assert classify_tool_type("terminal") == "terminal"
def test_code(self):
assert classify_tool_type("execute_code") == "code"
def test_file(self):
assert classify_tool_type("read_file") == "file"
def test_research(self):
assert classify_tool_type("web_search") == "research"
def test_unknown(self):
assert classify_tool_type("custom_tool") == "general"
# ---------------------------------------------------------------------------
# Session profiling
# ---------------------------------------------------------------------------
class TestProfileSession:
def test_empty_session(self):
profile = profile_session([], "s1")
assert profile.tool_call_count == 0
assert profile.error_rate == 0.0
def test_all_successful(self):
messages = _make_messages([
("terminal", {"command": "ls"}, "file list", True),
("read_file", {"path": "x.py"}, "code", True),
("terminal", {"command": "pwd"}, "/home", True),
])
profile = profile_session(messages, "s1")
assert profile.tool_call_count == 3
assert profile.successful_calls == 3
assert profile.error_rate == 0.0
assert profile.tool_distribution["terminal"] == 2
def test_mixed_success(self):
messages = _make_messages([
("terminal", {"command": "ls"}, "ok", True),
("terminal", {"command": "bad"}, "error!", False),
("read_file", {"path": "x"}, "content", True),
])
profile = profile_session(messages, "s1")
assert profile.tool_call_count == 3
assert profile.successful_calls == 2
assert abs(profile.error_rate - 0.333) < 0.01
def test_proficiency_gain_negative_means_improvement(self):
# Early errors, later success → negative proficiency_gain (improvement)
messages = _make_messages([
("terminal", {"c": "1"}, "error!", False), # early error
("terminal", {"c": "2"}, "error!", False), # early error
("terminal", {"c": "3"}, "ok", True),
("terminal", {"c": "4"}, "ok", True),
("terminal", {"c": "5"}, "ok", True),
("terminal", {"c": "6"}, "ok", True),
("terminal", {"c": "7"}, "ok", True),
("terminal", {"c": "8"}, "ok", True),
("terminal", {"c": "9"}, "ok", True),
("terminal", {"c": "10"}, "ok", True), # late success
])
profile = profile_session(messages, "s1")
assert profile.proficiency_gain < 0 # improvement
def test_skips_trivial_tools(self):
messages = _make_messages([
("clarify", {"question": "what?"}, "answer", True),
("terminal", {"command": "ls"}, "ok", True),
])
profile = profile_session(messages, "s1")
assert profile.tool_call_count == 1 # clarify skipped
assert profile.tool_distribution.get("clarify", 0) == 0
# ---------------------------------------------------------------------------
# Pattern extraction
# ---------------------------------------------------------------------------
class TestExtractPatterns:
def test_extracts_successful_only(self):
messages = _make_messages([
("terminal", {"command": "ls"}, "file list", True),
("read_file", {"path": "bad"}, "error!", False), # skip
("search_files", {"pattern": "import"}, "matches", True),
])
patterns = extract_patterns_from_session(messages)
assert len(patterns) == 2
assert patterns[0].tool_name == "terminal"
assert patterns[1].tool_name == "search_files"
def test_includes_preceding_context(self):
messages = [
{"role": "user", "content": "List the files please"},
]
messages.extend(_make_messages([
("terminal", {"command": "ls"}, "files", True),
]))
patterns = extract_patterns_from_session(messages)
assert len(patterns) == 1
assert "List the files" in patterns[0].preceding_context
def test_skips_trivial_tools(self):
messages = _make_messages([
("memory", {"action": "add"}, "ok", True),
("terminal", {"command": "ls"}, "ok", True),
])
patterns = extract_patterns_from_session(messages)
assert len(patterns) == 1
assert patterns[0].tool_name == "terminal"
# ---------------------------------------------------------------------------
# Warm conversation builder
# ---------------------------------------------------------------------------
class TestBuildWarmConversation:
def test_basic_conversation(self):
template = WarmSessionTemplate(
name="test",
description="test",
patterns=[
WarmPattern(tool_name="terminal", arguments={"command": "ls"}, result_summary="files"),
WarmPattern(tool_name="read_file", arguments={"path": "x"}, result_summary="content"),
],
)
messages = build_warm_conversation(template)
# 2 patterns * 3 messages each = 6
assert len(messages) == 6
def test_message_roles(self):
template = WarmSessionTemplate(
name="test",
description="test",
patterns=[WarmPattern(tool_name="terminal", arguments={"c": "pwd"}, result_summary="/home")],
)
messages = build_warm_conversation(template)
assert messages[0]["role"] == "user"
assert messages[1]["role"] == "assistant"
assert messages[1]["tool_calls"][0]["function"]["name"] == "terminal"
assert messages[2]["role"] == "tool"
assert messages[2]["tool_call_id"] == messages[1]["tool_calls"][0]["id"]
def test_max_patterns_limit(self):
patterns = [
WarmPattern(tool_name=f"tool_{i}", arguments={}, result_summary=f"r{i}")
for i in range(20)
]
template = WarmSessionTemplate(name="test", description="test", patterns=patterns)
messages = build_warm_conversation(template, max_patterns=3)
assert len(messages) == 9 # 3 * 3
def test_system_prompt_addendum(self):
template = WarmSessionTemplate(
name="test",
description="test",
patterns=[],
system_prompt_addendum="Use Python 3.12",
)
messages = build_warm_conversation(template)
assert len(messages) == 1
assert messages[0]["role"] == "system"
assert "Python 3.12" in messages[0]["content"]
# ---------------------------------------------------------------------------
# Compression analysis
# ---------------------------------------------------------------------------
class TestCompressionAnalysis:
def test_no_compression(self):
db = MagicMock()
db.get_session.return_value = {"parent_session_id": None}
result = analyze_compression_impact(db, "s1")
assert result["has_compression"] is False
def test_with_compression(self):
db = MagicMock()
db.get_session.return_value = {"parent_session_id": "parent_s1"}
# Parent: all success
parent_msgs = _make_messages([
("terminal", {"c": "ls"}, "ok", True),
("terminal", {"c": "pwd"}, "/home", True),
])
# Child: one error
child_msgs = _make_messages([
("terminal", {"c": "bad"}, "error!", False),
("terminal", {"c": "ls"}, "ok", True),
])
db.get_messages.side_effect = lambda sid: parent_msgs if sid == "parent_s1" else child_msgs
result = analyze_compression_impact(db, "child_s1")
assert result["has_compression"] is True
assert result["proficiency_preserved"] is False # error rate went up
# ---------------------------------------------------------------------------
# A/B comparison
# ---------------------------------------------------------------------------
class TestCompareSessions:
def test_warm_better(self):
warm = SessionProfile(session_id="w", message_count=10, tool_call_count=10,
successful_calls=9, failed_calls=1, error_rate=0.1)
cold = SessionProfile(session_id="c", message_count=10, tool_call_count=10,
successful_calls=7, failed_calls=3, error_rate=0.3)
result = compare_sessions(warm, cold)
assert result.improvement > 0 # warm is better
assert result.warm_error_rate == 0.1
assert result.cold_error_rate == 0.3
# ---------------------------------------------------------------------------
# Persistence
# ---------------------------------------------------------------------------
class TestPersistence:
def test_save_and_load(self, isolated_templates_dir):
template = WarmSessionTemplate(
name="persist-test",
description="test persistence",
patterns=[WarmPattern(tool_name="t", arguments={}, result_summary="r")],
)
save_template(template)
loaded = load_template("persist-test")
assert loaded is not None
assert loaded.name == "persist-test"
assert len(loaded.patterns) == 1
def test_load_nonexistent(self, isolated_templates_dir):
assert load_template("nope") is None
def test_list_templates(self, isolated_templates_dir):
t1 = WarmSessionTemplate(name="a", description="a", patterns=[])
t2 = WarmSessionTemplate(name="b", description="b", patterns=[
WarmPattern(tool_name="t", arguments={}, result_summary="r"),
])
save_template(t1)
save_template(t2)
templates = list_templates()
assert len(templates) == 2
names = {t["name"] for t in templates}
assert names == {"a", "b"}
def test_list_empty(self, isolated_templates_dir):
assert list_templates() == []
# ---------------------------------------------------------------------------
# SessionDB extraction (mocked)
# ---------------------------------------------------------------------------
class TestExtractFromDB:
def test_extracts_from_qualifying_sessions(self):
from agent.warm_session import extract_from_session_db
db = MagicMock()
db.list_sessions.return_value = [
{"id": "s1", "message_count": 50, "end_reason": "completed"},
{"id": "s2", "message_count": 10, "end_reason": "completed"}, # too short
{"id": "s3", "message_count": 40, "end_reason": "error"}, # wrong end reason
]
good_msgs = _make_messages([
("terminal", {"c": "ls"}, "ok", True),
("read_file", {"p": "x"}, "content", True),
])
db.get_messages.return_value = good_msgs
patterns, metrics = extract_from_session_db(db, min_messages=20)
assert metrics["sessions_scanned"] == 1 # only s1 qualifies
assert metrics["sessions_qualified"] == 1
assert len(patterns) >= 0

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tools/warm_session_tool.py Normal file
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"""Warm Session Tool v2 — manage pre-proficient agent sessions.
Provides build/list/load/delete/compress-analyze/compare actions
for warm session provisioning.
"""
import json
import logging
from typing import Optional
from tools.registry import registry
logger = logging.getLogger(__name__)
def warm_session(
action: str,
name: str = None,
description: str = "",
min_messages: int = 30,
max_sessions: int = 30,
source_filter: str = None,
tags: list = None,
session_id: str = None,
compare_with: str = None,
) -> str:
"""Manage warm session templates.
Actions:
build — mine existing sessions, create template
list — show saved templates
load — get conversation_history from a template
delete — remove a template
profile — analyze a session's reliability patterns
compress-check — test if compression preserved proficiency
compare — compare two sessions' error rates (A/B)
"""
from agent.warm_session import (
build_and_save,
load_template,
list_templates,
build_warm_conversation,
profile_session,
analyze_compression_impact,
compare_sessions,
TEMPLATES_DIR,
)
if action == "list":
templates = list_templates()
return json.dumps({
"success": True,
"templates": templates,
"count": len(templates),
})
if action == "build":
if not name:
return json.dumps({"success": False, "error": "name is required for 'build'."})
try:
from hermes_state import SessionDB
db = SessionDB()
except Exception as e:
return json.dumps({"success": False, "error": f"Cannot open session DB: {e}"})
template, metrics = build_and_save(
db,
name=name,
description=description,
min_messages=min_messages,
max_sessions=max_sessions,
source_filter=source_filter,
tags=tags or [],
)
return json.dumps({
"success": True,
"name": template.name,
"pattern_count": len(template.patterns),
"description": template.description,
"metrics": {
"sessions_scanned": metrics.get("sessions_scanned", 0),
"sessions_qualified": metrics.get("sessions_qualified", 0),
"avg_proficiency_gain": round(metrics.get("avg_proficiency_gain", 0), 3),
},
})
if action == "load":
if not name:
return json.dumps({"success": False, "error": "name is required for 'load'."})
template = load_template(name)
if not template:
return json.dumps({"success": False, "error": f"Template '{name}' not found."})
conversation = build_warm_conversation(template)
return json.dumps({
"success": True,
"name": template.name,
"message_count": len(conversation),
"pattern_count": len(template.patterns),
"conversation_preview": [
{"role": m["role"], "content_preview": str(m.get("content", ""))[:100]}
for m in conversation[:6]
],
})
if action == "delete":
if not name:
return json.dumps({"success": False, "error": "name is required for 'delete'."})
path = TEMPLATES_DIR / f"{name}.json"
if not path.exists():
return json.dumps({"success": False, "error": f"Template '{name}' not found."})
path.unlink()
return json.dumps({"success": True, "message": f"Template '{name}' deleted."})
if action == "profile":
if not session_id:
return json.dumps({"success": False, "error": "session_id is required for 'profile'."})
try:
from hermes_state import SessionDB
db = SessionDB()
messages = db.get_messages(session_id)
except Exception as e:
return json.dumps({"success": False, "error": f"Cannot load session: {e}"})
from agent.warm_session import profile_session as _profile
profile = _profile(messages, session_id)
return json.dumps({
"success": True,
"session_id": profile.session_id,
"message_count": profile.message_count,
"tool_call_count": profile.tool_call_count,
"error_rate": round(profile.error_rate, 3),
"proficiency_gain": round(profile.proficiency_gain, 3),
"dominant_tool_type": profile.dominant_tool_type,
"tool_success_rates": {
k: round(v, 3) for k, v in profile.tool_success_rates.items()
},
})
if action == "compress-check":
if not session_id:
return json.dumps({"success": False, "error": "session_id is required for 'compress-check'."})
try:
from hermes_state import SessionDB
db = SessionDB()
except Exception as e:
return json.dumps({"success": False, "error": f"Cannot open session DB: {e}"})
result = analyze_compression_impact(db, session_id)
return json.dumps({
"success": True,
**result,
})
if action == "compare":
if not session_id or not compare_with:
return json.dumps({
"success": False,
"error": "Both session_id and compare_with are required for 'compare'.",
})
try:
from hermes_state import SessionDB
db = SessionDB()
warm_msgs = db.get_messages(session_id)
cold_msgs = db.get_messages(compare_with)
except Exception as e:
return json.dumps({"success": False, "error": f"Cannot load sessions: {e}"})
from agent.warm_session import profile_session as _profile, compare_sessions as _compare
warm_profile = _profile(warm_msgs, session_id)
cold_profile = _profile(cold_msgs, compare_with)
result = _compare(warm_profile, cold_profile, test_name=f"{session_id} vs {compare_with}")
return json.dumps({
"success": True,
"test_name": result.test_name,
"warm_error_rate": round(result.warm_error_rate, 3),
"cold_error_rate": round(result.cold_error_rate, 3),
"improvement": round(result.improvement, 3),
"warm_better": result.improvement > 0,
})
return json.dumps({
"success": False,
"error": f"Unknown action '{action}'. Use: build, list, load, delete, profile, compress-check, compare",
})
WARM_SESSION_SCHEMA = {
"name": "warm_session",
"description": (
"Manage warm session templates for pre-proficient agent sessions. "
"Marathon sessions have lower error rates because agents accumulate "
"successful patterns. This tool captures those patterns and can "
"pre-seed new sessions with experience.\n\n"
"Actions:\n"
" build — mine existing sessions for successful patterns, save as template\n"
" list — show saved templates\n"
" load — retrieve template's conversation history for injection\n"
" delete — remove a template\n"
" profile — analyze a session's reliability metrics\n"
" compress-check — test if context compression preserved proficiency\n"
" compare — compare two sessions' error rates (A/B test)"
),
"parameters": {
"type": "object",
"properties": {
"action": {
"type": "string",
"enum": ["build", "list", "load", "delete", "profile", "compress-check", "compare"],
"description": "The action to perform.",
},
"name": {
"type": "string",
"description": "Template name. Required for build/load/delete.",
},
"description": {
"type": "string",
"description": "Description for the template. Used with 'build'.",
},
"min_messages": {
"type": "integer",
"description": "Minimum messages for a session to qualify (default: 30).",
},
"max_sessions": {
"type": "integer",
"description": "Maximum sessions to scan (default: 30).",
},
"source_filter": {
"type": "string",
"description": "Filter sessions by source (cli, telegram, discord, etc.).",
},
"tags": {
"type": "array",
"items": {"type": "string"},
"description": "Tags for organizing templates.",
},
"session_id": {
"type": "string",
"description": "Session ID for profile/compress-check/compare actions.",
},
"compare_with": {
"type": "string",
"description": "Second session ID for compare action.",
},
},
"required": ["action"],
},
}
registry.register(
name="warm_session",
toolset="skills",
schema=WARM_SESSION_SCHEMA,
handler=lambda args, **kw: warm_session(
action=args.get("action", ""),
name=args.get("name"),
description=args.get("description", ""),
min_messages=args.get("min_messages", 30),
max_sessions=args.get("max_sessions", 30),
source_filter=args.get("source_filter"),
tags=args.get("tags"),
session_id=args.get("session_id"),
compare_with=args.get("compare_with"),
),
emoji="🔥",
)