Files
hermes-agent/tests/agent/test_context_compressor.py
Teknium 07927f6bf2 feat(stt): add free local whisper transcription via faster-whisper (#1185)
* fix: Home Assistant event filtering now closed by default

Previously, when no watch_domains or watch_entities were configured,
ALL state_changed events passed through to the agent, causing users
to be flooded with notifications for every HA entity change.

Now events are dropped by default unless the user explicitly configures:
- watch_domains: list of domains to monitor (e.g. climate, light)
- watch_entities: list of specific entity IDs to monitor
- watch_all: true (new option — opt-in to receive all events)

A warning is logged at connect time if no filters are configured,
guiding users to set up their HA platform config.

All 49 gateway HA tests + 52 HA tool tests pass.

* docs: update Home Assistant integration documentation

- homeassistant.md: Fix event filtering docs to reflect closed-by-default
  behavior. Add watch_all option. Replace Python dict config example with
  YAML. Fix defaults table (was incorrectly showing 'all'). Add required
  configuration warning admonition.
- environment-variables.md: Add HASS_TOKEN and HASS_URL to Messaging section.
- messaging/index.md: Add Home Assistant to description, architecture
  diagram, platform toolsets table, and Next Steps links.

* fix(terminal): strip provider env vars from background and PTY subprocesses

Extends the env var blocklist from #1157 to also cover the two remaining
leaky paths in process_registry.py:

- spawn_local() PTY path (line 156)
- spawn_local() background Popen path (line 197)

Both were still using raw os.environ, leaking provider vars to background
processes and interactive PTY sessions. Now uses the same dynamic
_HERMES_PROVIDER_ENV_BLOCKLIST from local.py.

Explicit env_vars passed to spawn_local() still override the blocklist,
matching the existing behavior for callers that intentionally need these.

Gap identified by PR #1004 (@PeterFile).

* feat(delegate): add observability metadata to subagent results

Enrich delegate_task results with metadata from the child AIAgent:

- model: which model the child used
- exit_reason: completed | interrupted | max_iterations
- tokens.input / tokens.output: token counts
- tool_trace: per-tool-call trace with byte sizes and ok/error status

Tool trace uses tool_call_id matching to correctly pair parallel tool
calls with their results, with a fallback for messages without IDs.

Cherry-picked from PR #872 by @omerkaz, with fixes:
- Fixed parallel tool call trace pairing (was always updating last entry)
- Removed redundant 'iterations' field (identical to existing 'api_calls')
- Added test for parallel tool call trace correctness

Co-authored-by: omerkaz <omerkaz@users.noreply.github.com>

* feat(stt): add free local whisper transcription via faster-whisper

Replace OpenAI-only STT with a dual-provider system mirroring the TTS
architecture (Edge TTS free / ElevenLabs paid):

  STT: faster-whisper local (free, default) / OpenAI Whisper API (paid)

Changes:
- tools/transcription_tools.py: Full rewrite with provider dispatch,
  config loading, local faster-whisper backend, and OpenAI API backend.
  Auto-downloads model (~150MB for 'base') on first voice message.
  Singleton model instance reused across calls.
- pyproject.toml: Add faster-whisper>=1.0.0 as core dependency
- hermes_cli/config.py: Expand stt config to match TTS pattern with
  provider selection and per-provider model settings
- agent/context_compressor.py: Fix .strip() crash when LLM returns
  non-string content (dict from llama.cpp, None). Fixes #1100 partially.
- tests/: 23 new tests for STT providers + 2 for compressor fix
- docs/: Updated Voice & TTS page with STT provider table, model sizes,
  config examples, and fallback behavior

Fallback behavior:
- Local not installed → OpenAI API (if key set)
- OpenAI key not set → local whisper (if installed)
- Neither → graceful error message to user

Co-authored-by: Jah-yee <Jah-yee@users.noreply.github.com>

---------

Co-authored-by: omerkaz <omerkaz@users.noreply.github.com>
Co-authored-by: Jah-yee <Jah-yee@users.noreply.github.com>
2026-03-13 11:11:05 -07:00

358 lines
15 KiB
Python

"""Tests for agent/context_compressor.py — compression logic, thresholds, truncation fallback."""
import pytest
from unittest.mock import patch, MagicMock
from agent.context_compressor import ContextCompressor
@pytest.fixture()
def compressor():
"""Create a ContextCompressor with mocked dependencies."""
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(
model="test/model",
threshold_percent=0.85,
protect_first_n=2,
protect_last_n=2,
quiet_mode=True,
)
return c
class TestShouldCompress:
def test_below_threshold(self, compressor):
compressor.last_prompt_tokens = 50000
assert compressor.should_compress() is False
def test_above_threshold(self, compressor):
compressor.last_prompt_tokens = 90000
assert compressor.should_compress() is True
def test_exact_threshold(self, compressor):
compressor.last_prompt_tokens = 85000
assert compressor.should_compress() is True
def test_explicit_tokens(self, compressor):
assert compressor.should_compress(prompt_tokens=90000) is True
assert compressor.should_compress(prompt_tokens=50000) is False
class TestShouldCompressPreflight:
def test_short_messages(self, compressor):
msgs = [{"role": "user", "content": "short"}]
assert compressor.should_compress_preflight(msgs) is False
def test_long_messages(self, compressor):
# Each message ~100k chars / 4 = 25k tokens, need >85k threshold
msgs = [{"role": "user", "content": "x" * 400000}]
assert compressor.should_compress_preflight(msgs) is True
class TestUpdateFromResponse:
def test_updates_fields(self, compressor):
compressor.update_from_response({
"prompt_tokens": 5000,
"completion_tokens": 1000,
"total_tokens": 6000,
})
assert compressor.last_prompt_tokens == 5000
assert compressor.last_completion_tokens == 1000
assert compressor.last_total_tokens == 6000
def test_missing_fields_default_zero(self, compressor):
compressor.update_from_response({})
assert compressor.last_prompt_tokens == 0
class TestGetStatus:
def test_returns_expected_keys(self, compressor):
status = compressor.get_status()
assert "last_prompt_tokens" in status
assert "threshold_tokens" in status
assert "context_length" in status
assert "usage_percent" in status
assert "compression_count" in status
def test_usage_percent_calculation(self, compressor):
compressor.last_prompt_tokens = 50000
status = compressor.get_status()
assert status["usage_percent"] == 50.0
class TestCompress:
def _make_messages(self, n):
return [{"role": "user" if i % 2 == 0 else "assistant", "content": f"msg {i}"} for i in range(n)]
def test_too_few_messages_returns_unchanged(self, compressor):
msgs = self._make_messages(4) # protect_first=2 + protect_last=2 + 1 = 5 needed
result = compressor.compress(msgs)
assert result == msgs
def test_truncation_fallback_no_client(self, compressor):
# compressor has client=None, so should use truncation fallback
msgs = [{"role": "system", "content": "System prompt"}] + self._make_messages(10)
result = compressor.compress(msgs)
assert len(result) < len(msgs)
# Should keep system message and last N
assert result[0]["role"] == "system"
assert compressor.compression_count == 1
def test_compression_increments_count(self, compressor):
msgs = self._make_messages(10)
compressor.compress(msgs)
assert compressor.compression_count == 1
compressor.compress(msgs)
assert compressor.compression_count == 2
def test_protects_first_and_last(self, compressor):
msgs = self._make_messages(10)
result = compressor.compress(msgs)
# First 2 messages should be preserved (protect_first_n=2)
# Last 2 messages should be preserved (protect_last_n=2)
assert result[-1]["content"] == msgs[-1]["content"]
assert result[-2]["content"] == msgs[-2]["content"]
class TestGenerateSummaryNoneContent:
"""Regression: content=None (from tool-call-only assistant messages) must not crash."""
def test_none_content_does_not_crash(self):
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "[CONTEXT SUMMARY]: tool calls happened"
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True)
messages = [
{"role": "user", "content": "do something"},
{"role": "assistant", "content": None, "tool_calls": [
{"function": {"name": "search"}}
]},
{"role": "tool", "content": "result"},
{"role": "assistant", "content": None},
{"role": "user", "content": "thanks"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
summary = c._generate_summary(messages)
assert isinstance(summary, str)
assert "CONTEXT SUMMARY" in summary
def test_none_content_in_system_message_compress(self):
"""System message with content=None should not crash during compress."""
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True, protect_first_n=2, protect_last_n=2)
msgs = [{"role": "system", "content": None}] + [
{"role": "user" if i % 2 == 0 else "assistant", "content": f"msg {i}"}
for i in range(10)
]
result = c.compress(msgs)
assert len(result) < len(msgs)
class TestNonStringContent:
"""Regression: content as dict (e.g., llama.cpp tool calls) must not crash."""
def test_dict_content_coerced_to_string(self):
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = {"text": "some summary"}
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True)
messages = [
{"role": "user", "content": "do something"},
{"role": "assistant", "content": "ok"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
summary = c._generate_summary(messages)
assert isinstance(summary, str)
assert "CONTEXT SUMMARY" in summary
def test_none_content_coerced_to_empty(self):
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = None
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True)
messages = [
{"role": "user", "content": "do something"},
{"role": "assistant", "content": "ok"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
summary = c._generate_summary(messages)
# None content → empty string → "[CONTEXT SUMMARY]: " prefix added
assert summary is not None
assert "CONTEXT SUMMARY" in summary
class TestCompressWithClient:
def test_summarization_path(self):
mock_client = MagicMock()
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "[CONTEXT SUMMARY]: stuff happened"
mock_client.chat.completions.create.return_value = mock_response
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True)
msgs = [{"role": "user" if i % 2 == 0 else "assistant", "content": f"msg {i}"} for i in range(10)]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
# Should have summary message in the middle
contents = [m.get("content", "") for m in result]
assert any("CONTEXT SUMMARY" in c for c in contents)
assert len(result) < len(msgs)
def test_summarization_does_not_split_tool_call_pairs(self):
mock_client = MagicMock()
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "[CONTEXT SUMMARY]: compressed middle"
mock_client.chat.completions.create.return_value = mock_response
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(
model="test",
quiet_mode=True,
protect_first_n=3,
protect_last_n=4,
)
msgs = [
{"role": "user", "content": "Could you address the reviewer comments in PR#71"},
{
"role": "assistant",
"content": "",
"tool_calls": [
{"id": "call_a", "type": "function", "function": {"name": "skill_view", "arguments": "{}"}},
{"id": "call_b", "type": "function", "function": {"name": "skill_view", "arguments": "{}"}},
],
},
{"role": "tool", "tool_call_id": "call_a", "content": "output a"},
{"role": "tool", "tool_call_id": "call_b", "content": "output b"},
{"role": "user", "content": "later 1"},
{"role": "assistant", "content": "later 2"},
{"role": "tool", "tool_call_id": "call_x", "content": "later output"},
{"role": "assistant", "content": "later 3"},
{"role": "user", "content": "later 4"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
answered_ids = {
msg.get("tool_call_id")
for msg in result
if msg.get("role") == "tool" and msg.get("tool_call_id")
}
for msg in result:
if msg.get("role") == "assistant" and msg.get("tool_calls"):
for tc in msg["tool_calls"]:
assert tc["id"] in answered_ids
def test_summary_role_avoids_consecutive_user_messages(self):
"""Summary role should alternate with the last head message to avoid consecutive same-role messages."""
mock_client = MagicMock()
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "[CONTEXT SUMMARY]: stuff happened"
mock_client.chat.completions.create.return_value = mock_response
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True, protect_first_n=2, protect_last_n=2)
# Last head message (index 1) is "assistant" → summary should be "user"
msgs = [
{"role": "user", "content": "msg 0"},
{"role": "assistant", "content": "msg 1"},
{"role": "user", "content": "msg 2"},
{"role": "assistant", "content": "msg 3"},
{"role": "user", "content": "msg 4"},
{"role": "assistant", "content": "msg 5"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
summary_msg = [m for m in result if "CONTEXT SUMMARY" in (m.get("content") or "")]
assert len(summary_msg) == 1
assert summary_msg[0]["role"] == "user"
def test_summary_role_avoids_consecutive_user_when_head_ends_with_user(self):
"""When last head message is 'user', summary must be 'assistant' to avoid two consecutive user messages."""
mock_client = MagicMock()
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "[CONTEXT SUMMARY]: stuff happened"
mock_client.chat.completions.create.return_value = mock_response
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(model="test", quiet_mode=True, protect_first_n=3, protect_last_n=2)
# Last head message (index 2) is "user" → summary should be "assistant"
msgs = [
{"role": "system", "content": "system prompt"},
{"role": "user", "content": "msg 1"},
{"role": "user", "content": "msg 2"}, # last head — user
{"role": "assistant", "content": "msg 3"},
{"role": "user", "content": "msg 4"},
{"role": "assistant", "content": "msg 5"},
{"role": "user", "content": "msg 6"},
{"role": "assistant", "content": "msg 7"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
summary_msg = [m for m in result if "CONTEXT SUMMARY" in (m.get("content") or "")]
assert len(summary_msg) == 1
assert summary_msg[0]["role"] == "assistant"
def test_summarization_does_not_start_tail_with_tool_outputs(self):
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "[CONTEXT SUMMARY]: compressed middle"
with patch("agent.context_compressor.get_model_context_length", return_value=100000):
c = ContextCompressor(
model="test",
quiet_mode=True,
protect_first_n=2,
protect_last_n=3,
)
msgs = [
{"role": "user", "content": "earlier 1"},
{"role": "assistant", "content": "earlier 2"},
{"role": "user", "content": "earlier 3"},
{
"role": "assistant",
"content": "",
"tool_calls": [
{"id": "call_c", "type": "function", "function": {"name": "search_files", "arguments": "{}"}},
],
},
{"role": "tool", "tool_call_id": "call_c", "content": "output c"},
{"role": "user", "content": "latest user"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
called_ids = {
tc["id"]
for msg in result
if msg.get("role") == "assistant" and msg.get("tool_calls")
for tc in msg["tool_calls"]
}
for msg in result:
if msg.get("role") == "tool" and msg.get("tool_call_id"):
assert msg["tool_call_id"] in called_ids