mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
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CI/CD Integration with Ephemeral Deployment Model (#14)
* feat: Complete migration from Prefect to Temporal BREAKING CHANGE: Replaces Prefect workflow orchestration with Temporal ## Major Changes - Replace Prefect with Temporal for workflow orchestration - Implement vertical worker architecture (rust, android) - Replace Docker registry with MinIO for unified storage - Refactor activities to be co-located with workflows - Update all API endpoints for Temporal compatibility ## Infrastructure - New: docker-compose.temporal.yaml (Temporal + MinIO + workers) - New: workers/ directory with rust and android vertical workers - New: backend/src/temporal/ (manager, discovery) - New: backend/src/storage/ (S3-cached storage with MinIO) - New: backend/toolbox/common/ (shared storage activities) - Deleted: docker-compose.yaml (old Prefect setup) - Deleted: backend/src/core/prefect_manager.py - Deleted: backend/src/services/prefect_stats_monitor.py - Deleted: Docker registry and insecure-registries requirement ## Workflows - Migrated: security_assessment workflow to Temporal - New: rust_test workflow (example/test workflow) - Deleted: secret_detection_scan (Prefect-based, to be reimplemented) - Activities now co-located with workflows for independent testing ## API Changes - Updated: backend/src/api/workflows.py (Temporal submission) - Updated: backend/src/api/runs.py (Temporal status/results) - Updated: backend/src/main.py (727 lines, TemporalManager integration) - Updated: All 16 MCP tools to use TemporalManager ## Testing - ✅ All services healthy (Temporal, PostgreSQL, MinIO, workers, backend) - ✅ All API endpoints functional - ✅ End-to-end workflow test passed (72 findings from vulnerable_app) - ✅ MinIO storage integration working (target upload/download, results) - ✅ Worker activity discovery working (6 activities registered) - ✅ Tarball extraction working - ✅ SARIF report generation working ## Documentation - ARCHITECTURE.md: Complete Temporal architecture documentation - QUICKSTART_TEMPORAL.md: Getting started guide - MIGRATION_DECISION.md: Why we chose Temporal over Prefect - IMPLEMENTATION_STATUS.md: Migration progress tracking - workers/README.md: Worker development guide ## Dependencies - Added: temporalio>=1.6.0 - Added: boto3>=1.34.0 (MinIO S3 client) - Removed: prefect>=3.4.18 * feat: Add Python fuzzing vertical with Atheris integration This commit implements a complete Python fuzzing workflow using Atheris: ## Python Worker (workers/python/) - Dockerfile with Python 3.11, Atheris, and build tools - Generic worker.py for dynamic workflow discovery - requirements.txt with temporalio, boto3, atheris dependencies - Added to docker-compose.temporal.yaml with dedicated cache volume ## AtherisFuzzer Module (backend/toolbox/modules/fuzzer/) - Reusable module extending BaseModule - Auto-discovers fuzz targets (fuzz_*.py, *_fuzz.py, fuzz_target.py) - Recursive search to find targets in nested directories - Dynamically loads TestOneInput() function - Configurable max_iterations and timeout - Real-time stats callback support for live monitoring - Returns findings as ModuleFinding objects ## Atheris Fuzzing Workflow (backend/toolbox/workflows/atheris_fuzzing/) - Temporal workflow for orchestrating fuzzing - Downloads user code from MinIO - Executes AtherisFuzzer module - Uploads results to MinIO - Cleans up cache after execution - metadata.yaml with vertical: python for routing ## Test Project (test_projects/python_fuzz_waterfall/) - Demonstrates stateful waterfall vulnerability - main.py with check_secret() that leaks progress - fuzz_target.py with Atheris TestOneInput() harness - Complete README with usage instructions ## Backend Fixes - Fixed parameter merging in REST API endpoints (workflows.py) - Changed workflow parameter passing from positional args to kwargs (manager.py) - Default parameters now properly merged with user parameters ## Testing ✅ Worker discovered AtherisFuzzingWorkflow ✅ Workflow executed end-to-end successfully ✅ Fuzz target auto-discovered in nested directories ✅ Atheris ran 100,000 iterations ✅ Results uploaded and cache cleaned * chore: Complete Temporal migration with updated CLI/SDK/docs This commit includes all remaining Temporal migration changes: ## CLI Updates (cli/) - Updated workflow execution commands for Temporal - Enhanced error handling and exceptions - Updated dependencies in uv.lock ## SDK Updates (sdk/) - Client methods updated for Temporal workflows - Updated models for new workflow execution - Updated dependencies in uv.lock ## Documentation Updates (docs/) - Architecture documentation for Temporal - Workflow concept documentation - Resource management documentation (new) - Debugging guide (new) - Updated tutorials and how-to guides - Troubleshooting updates ## README Updates - Main README with Temporal instructions - Backend README - CLI README - SDK README ## Other - Updated IMPLEMENTATION_STATUS.md - Removed old vulnerable_app.tar.gz These changes complete the Temporal migration and ensure the CLI/SDK work correctly with the new backend. * fix: Use positional args instead of kwargs for Temporal workflows The Temporal Python SDK's start_workflow() method doesn't accept a 'kwargs' parameter. Workflows must receive parameters as positional arguments via the 'args' parameter. Changed from: args=workflow_args # Positional arguments This fixes the error: TypeError: Client.start_workflow() got an unexpected keyword argument 'kwargs' Workflows now correctly receive parameters in order: - security_assessment: [target_id, scanner_config, analyzer_config, reporter_config] - atheris_fuzzing: [target_id, target_file, max_iterations, timeout_seconds] - rust_test: [target_id, test_message] * fix: Filter metadata-only parameters from workflow arguments SecurityAssessmentWorkflow was receiving 7 arguments instead of 2-5. The issue was that target_path and volume_mode from default_parameters were being passed to the workflow, when they should only be used by the system for configuration. Now filters out metadata-only parameters (target_path, volume_mode) before passing arguments to workflow execution. * refactor: Remove Prefect leftovers and volume mounting legacy Complete cleanup of Prefect migration artifacts: Backend: - Delete registry.py and workflow_discovery.py (Prefect-specific files) - Remove Docker validation from setup.py (no longer needed) - Remove ResourceLimits and VolumeMount models - Remove target_path and volume_mode from WorkflowSubmission - Remove supported_volume_modes from API and discovery - Clean up metadata.yaml files (remove volume/path fields) - Simplify parameter filtering in manager.py SDK: - Remove volume_mode parameter from client methods - Remove ResourceLimits and VolumeMount models - Remove Prefect error patterns from docker_logs.py - Clean up WorkflowSubmission and WorkflowMetadata models CLI: - Remove Volume Modes display from workflow info All removed features are Prefect-specific or Docker volume mounting artifacts. Temporal workflows use MinIO storage exclusively. * feat: Add comprehensive test suite and benchmark infrastructure - Add 68 unit tests for fuzzer, scanner, and analyzer modules - Implement pytest-based test infrastructure with fixtures - Add 6 performance benchmarks with category-specific thresholds - Configure GitHub Actions for automated testing and benchmarking - Add test and benchmark documentation Test coverage: - AtherisFuzzer: 8 tests - CargoFuzzer: 14 tests - FileScanner: 22 tests - SecurityAnalyzer: 24 tests All tests passing (68/68) All benchmarks passing (6/6) * fix: Resolve all ruff linting violations across codebase Fixed 27 ruff violations in 12 files: - Removed unused imports (Depends, Dict, Any, Optional, etc.) - Fixed undefined workflow_info variable in workflows.py - Removed dead code with undefined variables in atheris_fuzzer.py - Changed f-string to regular string where no placeholders used All files now pass ruff checks for CI/CD compliance. * fix: Configure CI for unit tests only - Renamed docker-compose.temporal.yaml → docker-compose.yml for CI compatibility - Commented out integration-tests job (no integration tests yet) - Updated test-summary to only depend on lint and unit-tests CI will now run successfully with 68 unit tests. Integration tests can be added later. * feat: Add CI/CD integration with ephemeral deployment model Implements comprehensive CI/CD support for FuzzForge with on-demand worker management: **Worker Management (v0.7.0)** - Add WorkerManager for automatic worker lifecycle control - Auto-start workers from stopped state when workflows execute - Auto-stop workers after workflow completion - Health checks and startup timeout handling (90s default) **CI/CD Features** - `--fail-on` flag: Fail builds based on SARIF severity levels (error/warning/note/info) - `--export-sarif` flag: Export findings in SARIF 2.1.0 format - `--auto-start`/`--auto-stop` flags: Control worker lifecycle - Exit code propagation: Returns 1 on blocking findings, 0 on success **Exit Code Fix** - Add `except typer.Exit: raise` handlers at 3 critical locations - Move worker cleanup to finally block for guaranteed execution - Exit codes now propagate correctly even when build fails **CI Scripts & Examples** - ci-start.sh: Start FuzzForge services with health checks - ci-stop.sh: Clean shutdown with volume preservation option - GitHub Actions workflow example (security-scan.yml) - GitLab CI pipeline example (.gitlab-ci.example.yml) - docker-compose.ci.yml: CI-optimized compose file with profiles **OSS-Fuzz Integration** - New ossfuzz_campaign workflow for running OSS-Fuzz projects - OSS-Fuzz worker with Docker-in-Docker support - Configurable campaign duration and project selection **Documentation** - Comprehensive CI/CD integration guide (docs/how-to/cicd-integration.md) - Updated architecture docs with worker lifecycle details - Updated workspace isolation documentation - CLI README with worker management examples **SDK Enhancements** - Add get_workflow_worker_info() endpoint - Worker vertical metadata in workflow responses **Testing** - All workflows tested: security_assessment, atheris_fuzzing, secret_detection, cargo_fuzzing - All monitoring commands tested: stats, crashes, status, finding - Full CI pipeline simulation verified - Exit codes verified for success/failure scenarios Ephemeral CI/CD model: ~3-4GB RAM, ~60-90s startup, runs entirely in CI containers. * fix: Resolve ruff linting violations in CI/CD code - Remove unused variables (run_id, defaults, result) - Remove unused imports - Fix f-string without placeholders All CI/CD integration files now pass ruff checks.
This commit is contained in:
tduhamel42
@@ -23,8 +23,6 @@ from .models import (
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WorkflowListItem,
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WorkflowStatus,
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WorkflowFindings,
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ResourceLimits,
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VolumeMount,
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FuzzingStats,
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CrashReport,
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RunSubmissionResponse,
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@@ -52,8 +50,6 @@ __all__ = [
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"WorkflowListItem",
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"WorkflowStatus",
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"WorkflowFindings",
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"ResourceLimits",
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"VolumeMount",
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"FuzzingStats",
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"CrashReport",
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"RunSubmissionResponse",
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@@ -19,9 +19,11 @@ including real-time monitoring capabilities for fuzzing workflows.
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import asyncio
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import json
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import logging
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from typing import Dict, Any, List, Optional, AsyncIterator, Iterator, Union
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import tarfile
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import tempfile
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from pathlib import Path
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from typing import Dict, Any, List, Optional, AsyncIterator, Iterator, Union, Callable
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from urllib.parse import urljoin, urlparse
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import warnings
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import httpx
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import websockets
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@@ -213,6 +215,56 @@ class FuzzForgeClient:
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response = await self._async_client.get(url)
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return await self._ahandle_response(response)
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def get_workflow_worker_info(self, workflow_name: str) -> Dict[str, Any]:
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"""
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Get worker information for a workflow.
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Returns details about which worker is required to execute this workflow,
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including container name, task queue, and vertical.
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Args:
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workflow_name: Name of the workflow
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Returns:
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Dictionary with worker info including:
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- workflow: Workflow name
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- vertical: Worker vertical (e.g., "ossfuzz", "python", "rust")
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- worker_container: Docker container name
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- task_queue: Temporal task queue name
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- required: Whether worker is required (always True)
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Raises:
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FuzzForgeHTTPError: If workflow not found or metadata missing
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"""
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url = urljoin(self.base_url, f"/workflows/{workflow_name}/worker-info")
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response = self._client.get(url)
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return self._handle_response(response)
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async def aget_workflow_worker_info(self, workflow_name: str) -> Dict[str, Any]:
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"""
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Get worker information for a workflow (async).
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Returns details about which worker is required to execute this workflow,
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including container name, task queue, and vertical.
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Args:
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workflow_name: Name of the workflow
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Returns:
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Dictionary with worker info including:
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- workflow: Workflow name
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- vertical: Worker vertical (e.g., "ossfuzz", "python", "rust")
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- worker_container: Docker container name
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- task_queue: Temporal task queue name
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- required: Whether worker is required (always True)
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Raises:
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FuzzForgeHTTPError: If workflow not found or metadata missing
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"""
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url = urljoin(self.base_url, f"/workflows/{workflow_name}/worker-info")
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response = await self._async_client.get(url)
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return await self._ahandle_response(response)
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def submit_workflow(
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self,
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workflow_name: str,
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@@ -235,6 +287,232 @@ class FuzzForgeClient:
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data = await self._ahandle_response(response)
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return RunSubmissionResponse(**data)
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def _create_tarball(
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self,
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source_path: Path,
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progress_callback: Optional[Callable[[int], None]] = None
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) -> Path:
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"""
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Create a compressed tarball from a file or directory.
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Args:
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source_path: Path to file or directory to archive
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progress_callback: Optional callback(bytes_written) for progress tracking
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Returns:
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Path to the created tarball
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Raises:
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FileNotFoundError: If source_path doesn't exist
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"""
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if not source_path.exists():
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raise FileNotFoundError(f"Source path not found: {source_path}")
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# Create temp file for tarball
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temp_fd, temp_path = tempfile.mkstemp(suffix=".tar.gz")
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try:
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logger.info(f"Creating tarball from {source_path}")
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bytes_written = 0
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with tarfile.open(temp_path, "w:gz") as tar:
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if source_path.is_file():
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# Add single file
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tar.add(source_path, arcname=source_path.name)
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bytes_written = source_path.stat().st_size
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if progress_callback:
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progress_callback(bytes_written)
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else:
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# Add directory recursively
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for item in source_path.rglob("*"):
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if item.is_file():
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arcname = item.relative_to(source_path)
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tar.add(item, arcname=arcname)
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bytes_written += item.stat().st_size
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if progress_callback:
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progress_callback(bytes_written)
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tarball_path = Path(temp_path)
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tarball_size = tarball_path.stat().st_size
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logger.info(
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f"Created tarball: {tarball_size / (1024**2):.2f} MB "
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f"(compressed from {bytes_written / (1024**2):.2f} MB)"
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)
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return tarball_path
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except Exception:
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# Cleanup on error
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if Path(temp_path).exists():
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Path(temp_path).unlink()
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raise
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def submit_workflow_with_upload(
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self,
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workflow_name: str,
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target_path: Union[str, Path],
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parameters: Optional[Dict[str, Any]] = None,
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timeout: Optional[int] = None,
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progress_callback: Optional[Callable[[int, int], None]] = None
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) -> RunSubmissionResponse:
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"""
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Submit a workflow with file upload from local filesystem.
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This method automatically creates a tarball if target_path is a directory,
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uploads it to the backend, and submits the workflow for execution.
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Args:
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workflow_name: Name of the workflow to execute
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target_path: Local path to file or directory to analyze
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parameters: Workflow-specific parameters
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timeout: Timeout in seconds
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progress_callback: Optional callback(bytes_uploaded, total_bytes) for progress
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Returns:
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Run submission response with run_id
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Raises:
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FileNotFoundError: If target_path doesn't exist
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FuzzForgeHTTPError: For API errors
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"""
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target_path = Path(target_path)
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tarball_path = None
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try:
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# Create tarball if needed
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if target_path.is_dir():
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logger.info("Target is directory, creating tarball...")
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tarball_path = self._create_tarball(target_path)
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upload_file = tarball_path
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filename = f"{target_path.name}.tar.gz"
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else:
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upload_file = target_path
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filename = target_path.name
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# Prepare multipart form data
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url = urljoin(self.base_url, f"/workflows/{workflow_name}/upload-and-submit")
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files = {
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"file": (filename, open(upload_file, "rb"), "application/gzip")
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}
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data = {}
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if parameters:
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data["parameters"] = json.dumps(parameters)
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if timeout:
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data["timeout"] = str(timeout)
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logger.info(f"Uploading {filename} to {workflow_name}...")
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# Track upload progress
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if progress_callback:
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file_size = upload_file.stat().st_size
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def track_progress(monitor):
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progress_callback(monitor.bytes_read, file_size)
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# Note: httpx doesn't have built-in progress tracking for uploads
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# This is a placeholder - real implementation would need custom approach
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pass
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response = self._client.post(url, files=files, data=data)
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# Close file handle
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files["file"][1].close()
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data = self._handle_response(response)
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return RunSubmissionResponse(**data)
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finally:
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# Cleanup temporary tarball
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if tarball_path and tarball_path.exists():
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try:
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tarball_path.unlink()
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logger.debug(f"Cleaned up temporary tarball: {tarball_path}")
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except Exception as e:
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logger.warning(f"Failed to cleanup tarball {tarball_path}: {e}")
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async def asubmit_workflow_with_upload(
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self,
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workflow_name: str,
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target_path: Union[str, Path],
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parameters: Optional[Dict[str, Any]] = None,
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volume_mode: str = "ro",
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timeout: Optional[int] = None,
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progress_callback: Optional[Callable[[int, int], None]] = None
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) -> RunSubmissionResponse:
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"""
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Submit a workflow with file upload from local filesystem (async).
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This method automatically creates a tarball if target_path is a directory,
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uploads it to the backend, and submits the workflow for execution.
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Args:
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workflow_name: Name of the workflow to execute
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target_path: Local path to file or directory to analyze
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parameters: Workflow-specific parameters
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volume_mode: Volume mount mode ("ro" or "rw")
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timeout: Timeout in seconds
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progress_callback: Optional callback(bytes_uploaded, total_bytes) for progress
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Returns:
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Run submission response with run_id
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Raises:
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FileNotFoundError: If target_path doesn't exist
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FuzzForgeHTTPError: For API errors
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"""
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target_path = Path(target_path)
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tarball_path = None
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try:
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# Create tarball if needed
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if target_path.is_dir():
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logger.info("Target is directory, creating tarball...")
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tarball_path = self._create_tarball(target_path)
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upload_file = tarball_path
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filename = f"{target_path.name}.tar.gz"
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else:
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upload_file = target_path
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filename = target_path.name
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# Prepare multipart form data
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url = urljoin(self.base_url, f"/workflows/{workflow_name}/upload-and-submit")
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files = {
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"file": (filename, open(upload_file, "rb"), "application/gzip")
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}
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data = {}
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if parameters:
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data["parameters"] = json.dumps(parameters)
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if timeout:
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data["timeout"] = str(timeout)
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logger.info(f"Uploading {filename} to {workflow_name}...")
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response = await self._async_client.post(url, files=files, data=data)
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# Close file handle
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files["file"][1].close()
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response_data = await self._ahandle_response(response)
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return RunSubmissionResponse(**response_data)
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finally:
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# Cleanup temporary tarball
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if tarball_path and tarball_path.exists():
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try:
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tarball_path.unlink()
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logger.debug(f"Cleaned up temporary tarball: {tarball_path}")
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except Exception as e:
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logger.warning(f"Failed to cleanup tarball {tarball_path}: {e}")
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# Run management methods
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def get_run_status(self, run_id: str) -> WorkflowStatus:
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@@ -20,7 +20,7 @@ import logging
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import re
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import subprocess
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import json
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from typing import Dict, Any, List, Optional, Tuple
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from typing import Dict, Any, List, Optional
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from datetime import datetime, timezone
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from dataclasses import dataclass
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@@ -87,11 +87,6 @@ class DockerLogIntegration:
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r'network is unreachable',
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r'connection refused',
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r'timeout.*connect'
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],
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'prefect_error': [
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r'prefect.*error',
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r'flow run failed',
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r'task.*failed'
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]
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}
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@@ -382,13 +377,6 @@ class DockerLogIntegration:
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"Check firewall settings and port availability"
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])
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if 'prefect_error' in error_analysis:
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suggestions.extend([
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"Check Prefect server connectivity",
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||||
"Verify workflow deployment is successful",
|
||||
"Review workflow-specific parameters and requirements"
|
||||
])
|
||||
|
||||
if not suggestions:
|
||||
suggestions.append("Review the container logs above for specific error details")
|
||||
|
||||
|
||||
@@ -18,7 +18,7 @@ and actionable suggestions for troubleshooting.
|
||||
|
||||
import json
|
||||
import re
|
||||
from typing import Optional, Dict, Any, List, Union
|
||||
from typing import Optional, Dict, Any, List
|
||||
from dataclasses import dataclass, asdict
|
||||
|
||||
from .docker_logs import docker_integration, ContainerDiagnostics
|
||||
|
||||
@@ -16,49 +16,18 @@ and serialization for all API requests and responses.
|
||||
# Additional attribution and requirements are provided in the NOTICE file.
|
||||
|
||||
|
||||
from pydantic import BaseModel, Field, validator
|
||||
from typing import Dict, Any, Optional, Literal, List, Union
|
||||
from pydantic import BaseModel, Field
|
||||
from typing import Dict, Any, Optional, List, Union
|
||||
from datetime import datetime
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
class ResourceLimits(BaseModel):
|
||||
"""Resource limits for workflow execution"""
|
||||
cpu_limit: Optional[str] = Field(None, description="CPU limit (e.g., '2' for 2 cores, '500m' for 0.5 cores)")
|
||||
memory_limit: Optional[str] = Field(None, description="Memory limit (e.g., '1Gi', '512Mi')")
|
||||
cpu_request: Optional[str] = Field(None, description="CPU request (guaranteed)")
|
||||
memory_request: Optional[str] = Field(None, description="Memory request (guaranteed)")
|
||||
|
||||
|
||||
class VolumeMount(BaseModel):
|
||||
"""Volume mount specification"""
|
||||
host_path: str = Field(..., description="Host path to mount")
|
||||
container_path: str = Field(..., description="Container path for mount")
|
||||
mode: Literal["ro", "rw"] = Field(default="ro", description="Mount mode")
|
||||
|
||||
@validator("host_path")
|
||||
def validate_host_path(cls, v):
|
||||
"""Validate that the host path is absolute"""
|
||||
path = Path(v)
|
||||
if not path.is_absolute():
|
||||
raise ValueError(f"Host path must be absolute: {v}")
|
||||
return str(path)
|
||||
|
||||
@validator("container_path")
|
||||
def validate_container_path(cls, v):
|
||||
"""Validate that the container path is absolute"""
|
||||
if not v.startswith('/'):
|
||||
raise ValueError(f"Container path must be absolute: {v}")
|
||||
return v
|
||||
|
||||
|
||||
class WorkflowSubmission(BaseModel):
|
||||
"""Submit a workflow with configurable settings"""
|
||||
target_path: str = Field(..., description="Absolute path to analyze")
|
||||
volume_mode: Literal["ro", "rw"] = Field(
|
||||
default="ro",
|
||||
description="Volume mount mode: read-only (ro) or read-write (rw)"
|
||||
)
|
||||
"""
|
||||
Submit a workflow with configurable settings.
|
||||
|
||||
Note: This model is deprecated in favor of direct file upload via
|
||||
submit_workflow_with_upload() which handles file uploads automatically.
|
||||
"""
|
||||
parameters: Dict[str, Any] = Field(
|
||||
default_factory=dict,
|
||||
description="Workflow-specific parameters"
|
||||
@@ -69,22 +38,6 @@ class WorkflowSubmission(BaseModel):
|
||||
ge=1,
|
||||
le=604800 # Max 7 days
|
||||
)
|
||||
resource_limits: Optional[ResourceLimits] = Field(
|
||||
None,
|
||||
description="Resource limits for workflow container"
|
||||
)
|
||||
additional_volumes: List[VolumeMount] = Field(
|
||||
default_factory=list,
|
||||
description="Additional volume mounts"
|
||||
)
|
||||
|
||||
@validator("target_path")
|
||||
def validate_path(cls, v):
|
||||
"""Validate that the target path is absolute"""
|
||||
path = Path(v)
|
||||
if not path.is_absolute():
|
||||
raise ValueError(f"Path must be absolute: {v}")
|
||||
return str(path)
|
||||
|
||||
|
||||
class WorkflowListItem(BaseModel):
|
||||
@@ -112,10 +65,6 @@ class WorkflowMetadata(BaseModel):
|
||||
default_factory=list,
|
||||
description="Required module names"
|
||||
)
|
||||
supported_volume_modes: List[Literal["ro", "rw"]] = Field(
|
||||
default=["ro", "rw"],
|
||||
description="Supported volume mount modes"
|
||||
)
|
||||
has_custom_docker: bool = Field(
|
||||
default=False,
|
||||
description="Whether workflow has custom Dockerfile"
|
||||
@@ -124,9 +73,10 @@ class WorkflowMetadata(BaseModel):
|
||||
|
||||
class WorkflowParametersResponse(BaseModel):
|
||||
"""Response for workflow parameters endpoint"""
|
||||
workflow: str = Field(..., description="Workflow name")
|
||||
parameters: Dict[str, Any] = Field(..., description="Parameters schema")
|
||||
defaults: Dict[str, Any] = Field(default_factory=dict, description="Default values")
|
||||
required: List[str] = Field(default_factory=list, description="Required parameter names")
|
||||
default_parameters: Dict[str, Any] = Field(default_factory=dict, description="Default parameter values")
|
||||
required_parameters: List[str] = Field(default_factory=list, description="Required parameter names")
|
||||
|
||||
|
||||
class RunSubmissionResponse(BaseModel):
|
||||
|
||||
@@ -18,15 +18,14 @@ workflow functionality, performance, and expected results.
|
||||
|
||||
import time
|
||||
from pathlib import Path
|
||||
from typing import Dict, Any, List, Optional, Union
|
||||
from typing import Dict, Any, List, Optional
|
||||
from dataclasses import dataclass
|
||||
from datetime import datetime
|
||||
import logging
|
||||
|
||||
from .client import FuzzForgeClient
|
||||
from .models import WorkflowSubmission
|
||||
from .utils import validate_absolute_path, create_workflow_submission
|
||||
from .exceptions import FuzzForgeError, ValidationError
|
||||
from .exceptions import ValidationError
|
||||
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
|
||||
@@ -20,9 +20,8 @@ import os
|
||||
import json
|
||||
from pathlib import Path
|
||||
from typing import Dict, Any, List, Optional, Union
|
||||
from datetime import datetime
|
||||
|
||||
from .models import VolumeMount, ResourceLimits, WorkflowSubmission
|
||||
from .models import WorkflowSubmission
|
||||
from .exceptions import ValidationError
|
||||
|
||||
|
||||
@@ -50,112 +49,19 @@ def validate_absolute_path(path: Union[str, Path]) -> Path:
|
||||
return path_obj
|
||||
|
||||
|
||||
def create_volume_mount(
|
||||
host_path: Union[str, Path],
|
||||
container_path: str,
|
||||
mode: str = "ro"
|
||||
) -> VolumeMount:
|
||||
"""
|
||||
Create a volume mount with path validation.
|
||||
|
||||
Args:
|
||||
host_path: Host path to mount (must exist)
|
||||
container_path: Container path for the mount
|
||||
mode: Mount mode ("ro" or "rw")
|
||||
|
||||
Returns:
|
||||
VolumeMount object
|
||||
|
||||
Raises:
|
||||
ValidationError: If paths are invalid
|
||||
"""
|
||||
# Validate host path exists and is absolute
|
||||
validated_host_path = validate_absolute_path(host_path)
|
||||
|
||||
# Validate container path is absolute
|
||||
if not container_path.startswith('/'):
|
||||
raise ValidationError(f"Container path must be absolute: {container_path}")
|
||||
|
||||
# Validate mode
|
||||
if mode not in ["ro", "rw"]:
|
||||
raise ValidationError(f"Mode must be 'ro' or 'rw': {mode}")
|
||||
|
||||
return VolumeMount(
|
||||
host_path=str(validated_host_path),
|
||||
container_path=container_path,
|
||||
mode=mode # type: ignore
|
||||
)
|
||||
|
||||
|
||||
def create_resource_limits(
|
||||
cpu_limit: Optional[str] = None,
|
||||
memory_limit: Optional[str] = None,
|
||||
cpu_request: Optional[str] = None,
|
||||
memory_request: Optional[str] = None
|
||||
) -> ResourceLimits:
|
||||
"""
|
||||
Create resource limits with validation.
|
||||
|
||||
Args:
|
||||
cpu_limit: CPU limit (e.g., "2", "500m")
|
||||
memory_limit: Memory limit (e.g., "1Gi", "512Mi")
|
||||
cpu_request: CPU request (guaranteed)
|
||||
memory_request: Memory request (guaranteed)
|
||||
|
||||
Returns:
|
||||
ResourceLimits object
|
||||
|
||||
Raises:
|
||||
ValidationError: If resource specifications are invalid
|
||||
"""
|
||||
# Basic validation for CPU limits
|
||||
if cpu_limit is not None:
|
||||
if not (cpu_limit.endswith('m') or cpu_limit.isdigit()):
|
||||
raise ValidationError(f"Invalid CPU limit format: {cpu_limit}")
|
||||
|
||||
if cpu_request is not None:
|
||||
if not (cpu_request.endswith('m') or cpu_request.isdigit()):
|
||||
raise ValidationError(f"Invalid CPU request format: {cpu_request}")
|
||||
|
||||
# Basic validation for memory limits
|
||||
memory_suffixes = ['Ki', 'Mi', 'Gi', 'Ti', 'K', 'M', 'G', 'T']
|
||||
|
||||
if memory_limit is not None:
|
||||
if not any(memory_limit.endswith(suffix) for suffix in memory_suffixes):
|
||||
if not memory_limit.isdigit():
|
||||
raise ValidationError(f"Invalid memory limit format: {memory_limit}")
|
||||
|
||||
if memory_request is not None:
|
||||
if not any(memory_request.endswith(suffix) for suffix in memory_suffixes):
|
||||
if not memory_request.isdigit():
|
||||
raise ValidationError(f"Invalid memory request format: {memory_request}")
|
||||
|
||||
return ResourceLimits(
|
||||
cpu_limit=cpu_limit,
|
||||
memory_limit=memory_limit,
|
||||
cpu_request=cpu_request,
|
||||
memory_request=memory_request
|
||||
)
|
||||
|
||||
|
||||
def create_workflow_submission(
|
||||
target_path: Union[str, Path],
|
||||
volume_mode: str = "ro",
|
||||
parameters: Optional[Dict[str, Any]] = None,
|
||||
timeout: Optional[int] = None,
|
||||
resource_limits: Optional[ResourceLimits] = None,
|
||||
additional_volumes: Optional[List[VolumeMount]] = None
|
||||
timeout: Optional[int] = None
|
||||
) -> WorkflowSubmission:
|
||||
"""
|
||||
Create a workflow submission with path validation.
|
||||
Create a workflow submission.
|
||||
|
||||
Note: This function is deprecated. Use client.submit_workflow_with_upload() instead
|
||||
which handles file uploads automatically.
|
||||
|
||||
Args:
|
||||
target_path: Path to analyze (must exist)
|
||||
volume_mode: Mount mode for target path
|
||||
parameters: Workflow-specific parameters
|
||||
timeout: Execution timeout in seconds
|
||||
resource_limits: Resource limits for the container
|
||||
additional_volumes: Additional volume mounts
|
||||
|
||||
Returns:
|
||||
WorkflowSubmission object
|
||||
@@ -163,25 +69,14 @@ def create_workflow_submission(
|
||||
Raises:
|
||||
ValidationError: If parameters are invalid
|
||||
"""
|
||||
# Validate target path
|
||||
validated_target_path = validate_absolute_path(target_path)
|
||||
|
||||
# Validate volume mode
|
||||
if volume_mode not in ["ro", "rw"]:
|
||||
raise ValidationError(f"Volume mode must be 'ro' or 'rw': {volume_mode}")
|
||||
|
||||
# Validate timeout
|
||||
if timeout is not None:
|
||||
if timeout < 1 or timeout > 604800: # Max 7 days
|
||||
raise ValidationError(f"Timeout must be between 1 and 604800 seconds: {timeout}")
|
||||
|
||||
return WorkflowSubmission(
|
||||
target_path=str(validated_target_path),
|
||||
volume_mode=volume_mode, # type: ignore
|
||||
parameters=parameters or {},
|
||||
timeout=timeout,
|
||||
resource_limits=resource_limits,
|
||||
additional_volumes=additional_volumes or []
|
||||
timeout=timeout
|
||||
)
|
||||
|
||||
|
||||
|
||||
Reference in New Issue
Block a user