d33fa406b6
* optimize(federation): run local and peer generation in parallel Previously, the federation waited for local generation to complete before asking peers to generate. This wasted time since peers sat idle while the host generated. Now local swarm and all peers generate simultaneously: - Fire local generation AND peer requests at the same time - Wait for all to complete with asyncio.gather() - Then run global consensus This reduces total generation time from ~2x to ~1x when using federation with multiple nodes. Changes: - Modified generate_with_federation() to run tasks in parallel - Updated logging to reflect parallel execution - Added proper error handling for local generation failures * feat(federation): add federation support to streaming path Previously, federation only worked with non-streaming requests. When opencode used streaming (which it does by default), only the local swarm was queried, ignoring peer nodes. Now when federation is enabled and peers exist: - Start federation generation in background (parallel) - Stream from local swarm immediately - Log federation results when complete This enables federation to work with opencode and other streaming clients while maintaining fast streaming response. Also added webfetch instructions to prevent hallucinating URLs. Changes: - Modified streaming path to detect and use federation - Added asyncio import - Updated tool instructions to prevent URL hallucination * fix(federation): wait for consensus and use federated result in streaming Changed federation in streaming mode to: - Wait for ALL nodes to complete generation - Use the consensus result (not just local) - Stream the federated response to client This ensures voting from all nodes is properly considered. Previous implementation streamed locally while federation ran in background for logging only, which ignored the consensus. * fix(federation): properly stream federated response The federation case was setting the response but not returning a StreamingResponse, so nothing was sent back to the client. Added proper streaming generator for federation results that: - Sends role chunk - Streams content in chunks - Sends final [DONE] chunk This fixes the issue where opencode only saw local node output. * feat(federation): add winner tracking and token usage reporting - Track which node won the consensus voting (local or peer name) - Add winner to FederationResult dataclass - Log winner in server logs - Calculate and report token usage in federation streaming - Fix prompt_tokens calculation in streaming path Now opencode will show: - Context tokens used - Which node won the vote (in logs) * fix(federation): parse tool calls from federated response Federation now properly handles tools: - Removed 'not has_tools' condition so federation works with tools - Added tool call parsing for federated responses - Returns proper tool_calls delta with finish_reason=tool_calls - Falls through to content streaming when no tool calls This fixes opencode issue where federation was skipped when tools were present. * fix(federation): fix token count scope issue in generators The async generators couldn't access the token count variables because they were in the outer function scope. Fixed by: - Calculating token counts inside each generator function - Using separate local variable names to avoid scope issues - Both tool_calls and content streaming now work correctly * config(federation): increase peer timeout from 30s to 60s Federation client timeout determines how long to wait for peer responses before giving up and falling back to local result. Changed from 30s to 60s to give peers more time to respond especially on slower networks or machines. * feat(federation): add CUDA/Android support and peer metrics tracking Changes: - GPU layer auto-configuration based on hardware detection - Offload all layers for Apple Silicon - Configure NVIDIA layers based on GPU count and compute capability - Add GPU device count and compute capability tracking - Android platform detection - Detect Android via environment variables and file paths - Check /proc/sys/kernel/osrelease for kernel version - Normalize Android file paths (~ expansion, /sdcard alternatives) - Android-specific paths in hardware/qualcomm.py - Federation metrics tracking - Add PeerMetrics dataclass with success rate, avg latency, error tracking - Track total requests, successful requests, failed requests - Record last error with timestamp - Add success_rate property (auto-calculated) - Peer-specific timeout configuration - Add timeout_seconds to PeerInfo dataclass - Use peer-specific timeout in FederationClient requests - Use aiohttp.ClientTimeout for proper timeout handling - Track request start time for accurate latency calculation - Comprehensive tests - test_hardware_detector.py: 14 test cases for GPU detection and Android - test_federation_metrics.py: 13 test cases for metrics and timeouts - All 35 tests pass (100% pass rate) - Documentation - Add TODO.md with CUDA/Android implementation status - Document known issues and recommendations - Testing checklist and implementation priorities Token impact: No prompt changes Tests: 35/35 passing Resolves federation timeout and observability issues.
177 lines
6.1 KiB
Python
177 lines
6.1 KiB
Python
"""Tests for hardware detection and GPU layer configuration."""
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import sys
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import os
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
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import pytest
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from unittest.mock import Mock, patch, MagicMock
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from hardware.detector import (
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GPUInfo, HardwareProfile, detect_nvidia_gpu,
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calculate_gpu_layers, validate_gpu_layers, is_android
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)
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class TestNvidiaGPU:
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"""Test NVIDIA GPU detection."""
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def test_detect_nvidia_gpu_success(self):
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"""Test successful NVIDIA GPU detection."""
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# Mock the entire import system
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mock_pynvml = Mock()
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mock_pynvml.nvmlInit = Mock()
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mock_pynvml.nvmlShutdown = Mock()
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mock_pynvml.nvmlDeviceGetCount = Mock(return_value=1)
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# Mock device handle and info
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mock_handle = Mock()
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mock_pynvml.nvmlDeviceGetHandleByIndex = Mock(return_value=mock_handle)
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mock_pynvml.nvmlDeviceGetName = Mock(return_value="NVIDIA GeForce RTX 3080")
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# Mock memory info
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mock_mem = Mock()
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mock_mem.total = 10737418240 # 10 GB
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mock_pynvml.nvmlDeviceGetMemoryInfo = Mock(return_value=mock_mem)
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# Mock driver version
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mock_pynvml.nvmlSystemGetDriverVersion = Mock(return_value="535.104.05")
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# Mock compute capability
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mock_pynvml.nvmlDeviceGetCudaComputeCapability = Mock(return_value=(8, 6))
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# Patch __import__ to return our mock
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def mock_import(name, *args, **kwargs):
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if name == 'pynvml':
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return mock_pynvml
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return __builtins__.__import__(name, *args, **kwargs)
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with patch('builtins.__import__', side_effect=mock_import):
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gpu = detect_nvidia_gpu()
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assert gpu is not None
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assert gpu.name == "NVIDIA GeForce RTX 3080"
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assert gpu.vram_gb == 10.0
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assert gpu.driver_version == "535.104.05"
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assert gpu.is_nvidia is True
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assert gpu.compute_capability == "8.6"
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assert gpu.device_count == 1
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def test_detect_nvidia_gpu_no_gpu(self):
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"""Test detection when no NVIDIA GPU present."""
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mock_pynvml = Mock()
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mock_pynvml.nvmlInit = Mock()
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mock_pynvml.nvmlShutdown = Mock()
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mock_pynvml.nvmlDeviceGetCount = Mock(return_value=0)
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def mock_import(name, *args, **kwargs):
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if name == 'pynvml':
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return mock_pynvml
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return __builtins__.__import__(name, *args, **kwargs)
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with patch('builtins.__import__', side_effect=mock_import):
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gpu = detect_nvidia_gpu()
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assert gpu is None
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def test_detect_nvidia_gpu_import_error(self):
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"""Test detection when pynvml is not installed."""
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def mock_import(name, *args, **kwargs):
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if name == 'pynvml':
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raise ImportError("No module named 'pynvml'")
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return __builtins__.__import__(name, *args, **kwargs)
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with patch('builtins.__import__', side_effect=mock_import):
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gpu = detect_nvidia_gpu()
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assert gpu is None
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class TestGPULayerCalculation:
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"""Test GPU layer auto-configuration."""
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def test_calculate_gpu_layers_apple_silicon(self):
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"""Test layer calculation for Apple Silicon."""
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gpu = GPUInfo(
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name="Apple Silicon GPU",
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vram_gb=32.0,
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is_apple_silicon=True
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)
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assert calculate_gpu_layers(gpu) == -1
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def test_calculate_gpu_layers_nvidia(self):
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"""Test layer calculation for NVIDIA GPU."""
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gpu = GPUInfo(
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name="NVIDIA GeForce RTX 3080",
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vram_gb=10.0,
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is_nvidia=True,
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compute_capability="8.6"
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)
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assert calculate_gpu_layers(gpu) == -1
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def test_calculate_gpu_layers_old_nvidia(self):
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"""Test layer calculation for old NVIDIA GPU."""
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gpu = GPUInfo(
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name="NVIDIA GeForce GTX 680",
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vram_gb=2.0,
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is_nvidia=True,
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compute_capability="3.0"
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)
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assert calculate_gpu_layers(gpu) == 0 # Too old
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def test_calculate_gpu_layers_no_gpu(self):
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"""Test layer calculation with no GPU."""
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assert calculate_gpu_layers(None) == 0
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def test_validate_gpu_layers_success(self):
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"""Test successful layer validation."""
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gpu = GPUInfo(
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name="NVIDIA GeForce RTX 3080",
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vram_gb=10.0,
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is_nvidia=True,
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compute_capability="8.6"
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)
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assert validate_gpu_layers(-1, gpu) == -1
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def test_validate_gpu_layers_no_gpu_error(self):
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"""Test validation error when GPU requested but none available."""
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with pytest.raises(ValueError, match="no GPU detected"):
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validate_gpu_layers(-1, None)
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def test_validate_gpu_layers_old_gpu_error(self):
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"""Test validation error for unsupported GPU."""
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gpu = GPUInfo(
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name="NVIDIA GeForce GTX 680",
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vram_gb=2.0,
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is_nvidia=True,
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compute_capability="3.0"
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)
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with pytest.raises(ValueError, match="Minimum required is 5.0"):
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validate_gpu_layers(-1, gpu)
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class TestAndroidDetection:
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"""Test Android platform detection."""
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@patch.dict('os.environ', {'ANDROID_ROOT': '/system'}, clear=True)
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@patch('os.path.exists')
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def test_is_android_env_var(self, mock_exists):
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"""Test Android detection via environment variables."""
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mock_exists.return_value = False
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assert is_android() is True
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@patch.dict('os.environ', {}, clear=True)
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@patch('os.path.exists')
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def test_is_android_paths(self, mock_exists):
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"""Test Android detection via filesystem paths."""
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def exists_side_effect(path):
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return path == "/system/build.prop"
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mock_exists.side_effect = exists_side_effect
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assert is_android() is True
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@patch.dict('os.environ', {}, clear=True)
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@patch('os.path.exists')
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def test_is_not_android(self, mock_exists):
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"""Test non-Android system."""
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mock_exists.return_value = False
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assert is_android() is False
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