GlyphRunner System
1a0b45df9c
New subsystem fully self-contained: Components: - LLMCompress/llm_adapter.py: LLMAdapter + LLMResponse (abstract over LLM backends) - LLMCompress/compression_report.py: CompressionReport (symbolic analysis results) - LLMCompress/llm_compressor.py: compress_interaction() and compress_session() - LLMCompress/tests/test_llm_compress.py: 5 comprehensive tests Integration: - Uses GlyphOS Cognitive Kernel for symbolic analysis - Integrates with GlyphOS Event System - Emits cognition.started and cognition.completed events - Supports in-memory GX execution via execute_symbolic() Test Coverage: - LLMCompress tests: 5/5 PASS - All existing tests still pass (52/52) - Total: 57 tests passing Bug fixes in cognitive_kernel.py: - Fixed execute_symbolic() method calls to use correct function signatures - normalize_segments(manifest, segments, payload) - map_lanes(segments) - build_envelope(manifest, lanes, payload, context) - execute_with_lain(envelope) Constraints: - No modifications to gx_compiler/* - No modifications to glyphs/super_registry.py - Self-contained subsystem with proper isolation - Full backward compatibility maintained
134 lines
3.8 KiB
Python
134 lines
3.8 KiB
Python
"""Tests for LLMCompress subsystem.
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These tests verify:
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- LLMAdapter normalization
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- compress_interaction() end-to-end flow
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- compress_session() multi-turn flow
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- Integration with GlyphOS Cognitive Kernel
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- Event emission during compression
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This uses a fake LLM backend so tests run without external dependencies.
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"""
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from typing import Any, Dict
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from LLMCompress import (
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LLMAdapter,
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compress_interaction,
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compress_session,
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CompressionReport,
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)
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from glyphos.events import get_event_bus
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from glyphos.cognitive_kernel import get_kernel # noqa: F401 # imported to ensure availability
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# ---------------------------------------------------------------------------
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# Fake LLM backend
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# ---------------------------------------------------------------------------
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def fake_llm_backend(prompt: str, **kwargs: Any) -> Dict[str, Any]:
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"""A deterministic fake LLM backend for testing."""
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return {
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"response": f"FAKE_RESPONSE({prompt})",
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"tokens_prompt": len(prompt.split()),
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"tokens_response": 3,
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"model_name": "fake-llm-test",
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"extra_info": "ok",
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}
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# ---------------------------------------------------------------------------
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# Tests
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# ---------------------------------------------------------------------------
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def test_adapter_normalization():
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adapter = LLMAdapter(fake_llm_backend, model_name="fake-llm-test")
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out = adapter.run("hello world")
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assert out.prompt == "hello world"
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assert out.response.startswith("FAKE_RESPONSE")
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assert out.tokens_prompt == 2
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assert out.tokens_response == 3
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assert out.model_name == "fake-llm-test"
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assert isinstance(out.metadata, dict)
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def test_compress_interaction_basic():
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adapter = LLMAdapter(fake_llm_backend, model_name="fake-llm-test")
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bus = get_event_bus()
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bus.clear_history()
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report = compress_interaction(adapter, "hello test")
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# Report structure
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assert isinstance(report, CompressionReport)
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assert len(report.interactions) == 1
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assert "prompt" in report.interactions[0]
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assert "response" in report.interactions[0]
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# Kernel output
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assert isinstance(report.fused_symbol, dict)
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assert isinstance(report.diagnostics, dict)
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# Events fired
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history = bus.get_history(limit=10)
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types = [e["type"] for e in history]
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assert "cognition.started" in types
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assert "cognition.completed" in types
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def test_compress_session_multi_turn():
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adapter = LLMAdapter(fake_llm_backend, model_name="fake-llm-test")
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bus = get_event_bus()
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bus.clear_history()
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prompts = ["turn one", "turn two", "turn three"]
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report = compress_session(adapter, prompts)
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assert isinstance(report, CompressionReport)
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assert len(report.interactions) == 3
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# Kernel output
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assert isinstance(report.fused_symbol, dict)
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assert isinstance(report.diagnostics, dict)
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# Events fired
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history = bus.get_history(limit=10)
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types = [e["type"] for e in history]
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assert "cognition.started" in types
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assert "cognition.completed" in types
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def test_payload_encoding_is_valid_json():
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adapter = LLMAdapter(fake_llm_backend)
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report = compress_interaction(adapter, "encode me")
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# Ensure payload was JSON-serializable and processed by kernel
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assert isinstance(report.fused_symbol, dict)
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assert isinstance(report.diagnostics, dict)
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def test_event_metadata_includes_source():
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adapter = LLMAdapter(fake_llm_backend)
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bus = get_event_bus()
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bus.clear_history()
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compress_interaction(adapter, "metadata test")
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events = bus.get_history(limit=10)
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found = False
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for e in events:
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if e["type"] == "cognition.started":
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assert e["payload"]["source"] == "LLMCompress"
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found = True
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break
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assert found, "Expected cognition.started event with source=LLMCompress"
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