Files
hermes-agent/tests/agent/test_context_compressor.py

565 lines
25 KiB
Python
Raw Permalink Normal View History

"""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, SUMMARY_PREFIX
@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"]
# The second-to-last tail message may have the summary merged
# into it when a double-collision prevents a standalone summary
# (head=assistant, tail=user in this fixture). Verify the
# original content is present in either case.
assert msgs[-2]["content"] in result[-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 summary.startswith(SUMMARY_PREFIX)
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)
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
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 summary.startswith(SUMMARY_PREFIX)
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
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 → standardized compaction handoff prefix added
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
assert summary is not None
assert summary == SUMMARY_PREFIX
class TestSummaryPrefixNormalization:
def test_legacy_prefix_is_replaced(self):
summary = ContextCompressor._with_summary_prefix("[CONTEXT SUMMARY]: did work")
assert summary == f"{SUMMARY_PREFIX}\ndid work"
def test_existing_new_prefix_is_not_duplicated(self):
summary = ContextCompressor._with_summary_prefix(f"{SUMMARY_PREFIX}\ndid work")
assert summary == f"{SUMMARY_PREFIX}\ndid work"
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
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, protect_first_n=2, protect_last_n=2)
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(c.startswith(SUMMARY_PREFIX) 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 (m.get("content") or "").startswith(SUMMARY_PREFIX)
]
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 (m.get("content") or "").startswith(SUMMARY_PREFIX)
]
assert len(summary_msg) == 1
assert summary_msg[0]["role"] == "assistant"
def test_summary_role_flips_to_avoid_tail_collision(self):
"""When summary role collides with the first tail message but flipping
doesn't collide with head, the role should be flipped."""
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "summary text"
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)
# Head ends with tool (index 1), tail starts with user (index 6).
# Default: tool → summary_role="user" → collides with tail.
# Flip to "assistant" → tool→assistant is fine.
msgs = [
{"role": "user", "content": "msg 0"},
{"role": "assistant", "content": "", "tool_calls": [
{"id": "call_1", "type": "function", "function": {"name": "t", "arguments": "{}"}},
]},
{"role": "tool", "tool_call_id": "call_1", "content": "result 1"},
{"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)
# Verify no consecutive user or assistant messages
for i in range(1, len(result)):
r1 = result[i - 1].get("role")
r2 = result[i].get("role")
if r1 in ("user", "assistant") and r2 in ("user", "assistant"):
assert r1 != r2, f"consecutive {r1} at indices {i-1},{i}"
def test_double_collision_merges_summary_into_tail(self):
"""When neither role avoids collision with both neighbors, the summary
should be merged into the first tail message rather than creating a
standalone message that breaks role alternation.
Common scenario: head ends with 'assistant', tail starts with 'user'.
summary='user' collides with tail, summary='assistant' collides with head.
"""
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "summary text"
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=3)
# Head: [system, user, assistant] → last head = assistant
# Tail: [user, assistant, user] → first tail = user
# summary_role="user" collides with tail, "assistant" collides with head → merge
msgs = [
{"role": "system", "content": "system prompt"},
{"role": "user", "content": "msg 1"},
{"role": "assistant", "content": "msg 2"},
{"role": "user", "content": "msg 3"}, # compressed
{"role": "assistant", "content": "msg 4"}, # compressed
{"role": "user", "content": "msg 5"}, # compressed
{"role": "user", "content": "msg 6"}, # tail start
{"role": "assistant", "content": "msg 7"},
{"role": "user", "content": "msg 8"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
# Verify no consecutive user or assistant messages
for i in range(1, len(result)):
r1 = result[i - 1].get("role")
r2 = result[i].get("role")
if r1 in ("user", "assistant") and r2 in ("user", "assistant"):
assert r1 != r2, f"consecutive {r1} at indices {i-1},{i}"
# The summary text should be merged into the first tail message
first_tail = [m for m in result if "msg 6" in (m.get("content") or "")]
assert len(first_tail) == 1
assert "summary text" in first_tail[0]["content"]
def test_double_collision_user_head_assistant_tail(self):
"""Reverse double collision: head ends with 'user', tail starts with 'assistant'.
summary='assistant' collides with tail, 'user' collides with head merge."""
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "summary text"
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)
# Head: [system, user] → last head = user
# Tail: [assistant, user] → first tail = assistant
# summary_role="assistant" collides with tail, "user" collides with head → merge
msgs = [
{"role": "system", "content": "system prompt"},
{"role": "user", "content": "msg 1"},
{"role": "assistant", "content": "msg 2"}, # compressed
{"role": "user", "content": "msg 3"}, # compressed
{"role": "assistant", "content": "msg 4"}, # compressed
{"role": "assistant", "content": "msg 5"}, # tail start
{"role": "user", "content": "msg 6"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
# Verify no consecutive user or assistant messages
for i in range(1, len(result)):
r1 = result[i - 1].get("role")
r2 = result[i].get("role")
if r1 in ("user", "assistant") and r2 in ("user", "assistant"):
assert r1 != r2, f"consecutive {r1} at indices {i-1},{i}"
# The summary should be merged into the first tail message (assistant)
first_tail = [m for m in result if "msg 5" in (m.get("content") or "")]
assert len(first_tail) == 1
assert "summary text" in first_tail[0]["content"]
def test_no_collision_scenarios_still_work(self):
"""Verify that the common no-collision cases (head=assistant/tail=assistant,
head=user/tail=user) still produce a standalone summary message."""
mock_response = MagicMock()
mock_response.choices = [MagicMock()]
mock_response.choices[0].message.content = "summary text"
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)
# Head=assistant, Tail=assistant → summary_role="user", no collision
msgs = [
{"role": "user", "content": "msg 0"},
{"role": "assistant", "content": "msg 1"},
{"role": "user", "content": "msg 2"},
{"role": "assistant", "content": "msg 3"},
{"role": "assistant", "content": "msg 4"},
{"role": "user", "content": "msg 5"},
]
with patch("agent.context_compressor.call_llm", return_value=mock_response):
result = c.compress(msgs)
summary_msgs = [m for m in result if (m.get("content") or "").startswith(SUMMARY_PREFIX)]
assert len(summary_msgs) == 1, "should have a standalone summary message"
assert summary_msgs[0]["role"] == "user"
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
class TestSummaryTargetRatio:
"""Verify that summary_target_ratio properly scales budgets with context window."""
def test_tail_budget_scales_with_context(self):
"""Tail token budget should be threshold_tokens * summary_target_ratio."""
with patch("agent.context_compressor.get_model_context_length", return_value=200_000):
c = ContextCompressor(model="test", quiet_mode=True, summary_target_ratio=0.40)
# 200K * 0.50 threshold * 0.40 ratio = 40K
assert c.tail_token_budget == 40_000
with patch("agent.context_compressor.get_model_context_length", return_value=1_000_000):
c = ContextCompressor(model="test", quiet_mode=True, summary_target_ratio=0.40)
# 1M * 0.50 threshold * 0.40 ratio = 200K
assert c.tail_token_budget == 200_000
def test_summary_cap_scales_with_context(self):
"""Max summary tokens should be 5% of context, capped at 12K."""
with patch("agent.context_compressor.get_model_context_length", return_value=200_000):
c = ContextCompressor(model="test", quiet_mode=True)
assert c.max_summary_tokens == 10_000 # 200K * 0.05
with patch("agent.context_compressor.get_model_context_length", return_value=1_000_000):
c = ContextCompressor(model="test", quiet_mode=True)
assert c.max_summary_tokens == 12_000 # capped at 12K ceiling
def test_ratio_clamped(self):
"""Ratio should be clamped to [0.10, 0.80]."""
with patch("agent.context_compressor.get_model_context_length", return_value=100_000):
c = ContextCompressor(model="test", quiet_mode=True, summary_target_ratio=0.05)
assert c.summary_target_ratio == 0.10
with patch("agent.context_compressor.get_model_context_length", return_value=100_000):
c = ContextCompressor(model="test", quiet_mode=True, summary_target_ratio=0.95)
assert c.summary_target_ratio == 0.80
def test_default_threshold_is_50_percent(self):
"""Default compression threshold should be 50%."""
with patch("agent.context_compressor.get_model_context_length", return_value=100_000):
c = ContextCompressor(model="test", quiet_mode=True)
assert c.threshold_percent == 0.50
assert c.threshold_tokens == 50_000
def test_default_protect_last_n_is_20(self):
"""Default protect_last_n should be 20."""
with patch("agent.context_compressor.get_model_context_length", return_value=100_000):
c = ContextCompressor(model="test", quiet_mode=True)
assert c.protect_last_n == 20