mirror of
https://github.com/FuzzingLabs/fuzzforge_ai.git
synced 2026-05-23 22:54:01 +02:00
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
+213
-5
@@ -5,6 +5,7 @@ A comprehensive Python SDK for the FuzzForge security testing workflow orchestra
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## Features
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- **Complete API Coverage**: All FuzzForge API endpoints supported
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- **File Upload**: Automatic tarball creation and multipart upload for local files
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- **Async & Sync**: Both synchronous and asynchronous client methods
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- **Real-time Monitoring**: WebSocket and Server-Sent Events for live fuzzing updates
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- **Type Safety**: Full Pydantic model validation for all data structures
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@@ -27,9 +28,11 @@ pip install fuzzforge-sdk
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## Quick Start
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### Method 1: File Upload (Recommended)
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```python
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from fuzzforge_sdk import FuzzForgeClient
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from fuzzforge_sdk.utils import create_workflow_submission
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from pathlib import Path
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# Initialize client
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client = FuzzForgeClient(base_url="http://localhost:8000")
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@@ -37,14 +40,20 @@ client = FuzzForgeClient(base_url="http://localhost:8000")
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# List available workflows
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workflows = client.list_workflows()
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# Submit a workflow
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submission = create_workflow_submission(
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target_path="/path/to/your/project",
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# Submit a workflow with automatic file upload
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target_path = Path("/path/to/your/project")
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response = client.submit_workflow_with_upload(
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workflow_name="security_assessment",
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target_path=target_path,
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volume_mode="ro",
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timeout=300
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)
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response = client.submit_workflow("static-analysis", submission)
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# The SDK automatically:
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# - Creates a tarball if target_path is a directory
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# - Uploads the file to the backend via HTTP
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# - Backend stores it in MinIO
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# - Returns the workflow run_id
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# Wait for completion and get results
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final_status = client.wait_for_completion(response.run_id)
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@@ -53,6 +62,27 @@ findings = client.get_run_findings(response.run_id)
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client.close()
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```
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### Method 2: Path-Based Submission (Legacy)
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```python
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from fuzzforge_sdk import FuzzForgeClient
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from fuzzforge_sdk.utils import create_workflow_submission
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# Initialize client
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client = FuzzForgeClient(base_url="http://localhost:8000")
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# Submit a workflow with path (only works if backend can access the path)
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submission = create_workflow_submission(
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target_path="/path/on/backend/filesystem",
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volume_mode="ro",
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timeout=300
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)
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response = client.submit_workflow("security_assessment", submission)
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client.close()
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```
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## Examples
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The `examples/` directory contains complete working examples:
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@@ -61,6 +91,184 @@ The `examples/` directory contains complete working examples:
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- **`fuzzing_monitor.py`**: Real-time fuzzing monitoring with WebSocket/SSE
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- **`batch_analysis.py`**: Batch analysis of multiple projects
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## File Upload API Reference
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### `submit_workflow_with_upload()`
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Submit a workflow with automatic file upload from local filesystem.
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```python
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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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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 workflow with file upload.
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Args:
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workflow_name: Name of the workflow to execute
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target_path: Path to file or directory to upload
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parameters: Optional workflow parameters
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volume_mode: Volume mount mode ('ro' or 'rw')
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timeout: Optional execution timeout in seconds
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progress_callback: Optional callback(bytes_sent, total_bytes)
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Returns:
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RunSubmissionResponse with run_id and status
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Raises:
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FileNotFoundError: If target_path doesn't exist
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ValidationError: If parameters are invalid
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FuzzForgeHTTPError: If upload fails
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"""
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```
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**Example with progress tracking:**
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```python
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from fuzzforge_sdk import FuzzForgeClient
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from pathlib import Path
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def upload_progress(bytes_sent, total_bytes):
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pct = (bytes_sent / total_bytes) * 100
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print(f"Upload progress: {pct:.1f}% ({bytes_sent}/{total_bytes} bytes)")
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client = FuzzForgeClient(base_url="http://localhost:8000")
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response = client.submit_workflow_with_upload(
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workflow_name="security_assessment",
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target_path=Path("./my-project"),
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parameters={"check_secrets": True},
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volume_mode="ro",
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progress_callback=upload_progress
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)
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print(f"Workflow started: {response.run_id}")
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```
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### `asubmit_workflow_with_upload()`
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Async version of `submit_workflow_with_upload()`.
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```python
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import asyncio
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from fuzzforge_sdk import FuzzForgeClient
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async def main():
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client = FuzzForgeClient(base_url="http://localhost:8000")
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response = await client.asubmit_workflow_with_upload(
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workflow_name="security_assessment",
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target_path="/path/to/project",
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parameters={"timeout": 3600}
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)
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print(f"Workflow started: {response.run_id}")
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await client.aclose()
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asyncio.run(main())
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```
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### Internal: `_create_tarball()`
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Creates a compressed tarball from a file or directory.
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```python
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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 compressed tarball (.tar.gz) from source.
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Args:
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source_path: Path to file or directory
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progress_callback: Optional callback(files_added)
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Returns:
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Path to created tarball in temp directory
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Note:
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Caller is responsible for cleaning up the tarball
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"""
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```
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**How it works:**
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1. **Directory**: Creates tarball with all files, preserving structure
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```python
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# For directory: /path/to/project/
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# Creates: /tmp/tmpXXXXXX.tar.gz containing:
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# project/file1.py
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# project/subdir/file2.py
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```
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2. **Single file**: Creates tarball with just that file
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```python
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# For file: /path/to/binary.elf
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# Creates: /tmp/tmpXXXXXX.tar.gz containing:
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# binary.elf
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```
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### Upload Flow Diagram
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```
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User Code
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↓
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submit_workflow_with_upload()
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↓
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_create_tarball() ───→ Compress files
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↓
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HTTP POST multipart/form-data
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↓
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Backend API (/workflows/{name}/upload-and-submit)
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↓
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MinIO Storage (S3) ───→ Store with target_id
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↓
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Temporal Workflow
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↓
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Worker downloads from MinIO
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↓
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Workflow execution
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```
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### Error Handling
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The SDK provides detailed error context:
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```python
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from fuzzforge_sdk import FuzzForgeClient
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from fuzzforge_sdk.exceptions import (
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FuzzForgeHTTPError,
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ValidationError,
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ConnectionError
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)
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client = FuzzForgeClient(base_url="http://localhost:8000")
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try:
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response = client.submit_workflow_with_upload(
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workflow_name="security_assessment",
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target_path="./nonexistent",
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)
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except FileNotFoundError as e:
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print(f"Target not found: {e}")
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except ValidationError as e:
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print(f"Invalid parameters: {e}")
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except FuzzForgeHTTPError as e:
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print(f"Upload failed (HTTP {e.status_code}): {e.message}")
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if e.context.response_data:
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print(f"Server response: {e.context.response_data}")
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except ConnectionError as e:
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print(f"Cannot connect to backend: {e}")
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```
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## Development
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Install with development dependencies:
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@@ -25,7 +25,7 @@ import asyncio
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import time
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from pathlib import Path
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from fuzzforge_sdk import FuzzForgeClient, WorkflowSubmission
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from fuzzforge_sdk import FuzzForgeClient
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from fuzzforge_sdk.utils import create_workflow_submission, format_sarif_summary, format_duration
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@@ -61,7 +61,7 @@ def main():
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# Get workflow metadata
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metadata = client.get_workflow_metadata(selected_workflow.name)
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print(f"📝 Workflow metadata:")
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print("📝 Workflow metadata:")
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print(f" Author: {metadata.author}")
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print(f" Required modules: {metadata.required_modules}")
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print(f" Supported volume modes: {metadata.supported_volume_modes}")
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@@ -81,7 +81,7 @@ def main():
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# Submit the workflow
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print(f"🚀 Submitting workflow '{selected_workflow.name}'...")
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response = client.submit_workflow(selected_workflow.name, submission)
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print(f"✅ Workflow submitted!")
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print("✅ Workflow submitted!")
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print(f" Run ID: {response.run_id}")
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print(f" Status: {response.status}")
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print()
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@@ -124,7 +124,7 @@ def main():
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# Display metadata
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if findings.metadata:
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print(f"🔍 Metadata:")
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print("🔍 Metadata:")
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for key, value in findings.metadata.items():
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print(f" {key}: {value}")
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@@ -180,7 +180,7 @@ def main():
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# Additional properties
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properties = result.get('properties', {})
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if properties:
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print(f" Properties:")
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print(" Properties:")
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for prop_key, prop_value in properties.items():
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print(f" {prop_key}: {prop_value}")
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@@ -27,18 +27,14 @@ from typing import List, Dict, Any
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import time
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from fuzzforge_sdk import (
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FuzzForgeClient,
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WorkflowSubmission,
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WorkflowFindings,
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RunSubmissionResponse
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FuzzForgeClient
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)
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from fuzzforge_sdk.utils import (
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create_workflow_submission,
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format_sarif_summary,
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count_sarif_severity_levels,
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save_sarif_to_file,
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get_project_files,
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estimate_analysis_time
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get_project_files
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)
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@@ -308,7 +304,7 @@ async def main():
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batch_duration = batch_end_time - batch_start_time
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# Generate batch summary report
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print(f"\n📊 Batch Analysis Complete!")
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print("\n📊 Batch Analysis Complete!")
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print(f" Total time: {batch_duration:.1f}s")
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print(f" Projects analyzed: {len(analyzer.results)}")
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@@ -345,7 +341,7 @@ async def main():
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print(f" Batch summary: {batch_summary_file}")
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# Display project summaries
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print(f"\n📈 Project Summaries:")
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print("\n📈 Project Summaries:")
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for result in analyzer.results:
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print(f" {result['project_name']}: " +
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f"{result['summary']['successful_workflows']}/{result['summary']['total_workflows']} workflows successful, " +
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@@ -23,11 +23,10 @@ This example demonstrates how to:
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import asyncio
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import signal
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import sys
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import time
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from pathlib import Path
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from datetime import datetime
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|
||||
from fuzzforge_sdk import FuzzForgeClient, WorkflowSubmission
|
||||
from fuzzforge_sdk import FuzzForgeClient
|
||||
from fuzzforge_sdk.utils import (
|
||||
create_workflow_submission,
|
||||
create_resource_limits,
|
||||
@@ -113,7 +112,7 @@ class FuzzingMonitor:
|
||||
corpus_size = stats_data.get('corpus_size', 0)
|
||||
elapsed_time = stats_data.get('elapsed_time', 0)
|
||||
|
||||
print(f"📊 Statistics:")
|
||||
print("📊 Statistics:")
|
||||
print(f" Executions: {executions:,}")
|
||||
print(f" Rate: {format_execution_rate(exec_per_sec)}")
|
||||
print(f" Runtime: {format_duration(elapsed_time)}")
|
||||
@@ -123,7 +122,7 @@ class FuzzingMonitor:
|
||||
print(f" Coverage: {coverage:.1f}%")
|
||||
|
||||
print()
|
||||
print(f"💥 Crashes:")
|
||||
print("💥 Crashes:")
|
||||
print(f" Total crashes: {crashes}")
|
||||
print(f" Unique crashes: {unique_crashes}")
|
||||
|
||||
@@ -204,11 +203,11 @@ async def main():
|
||||
}
|
||||
)
|
||||
|
||||
print(f"🚀 Submitting fuzzing workflow...")
|
||||
print("🚀 Submitting fuzzing workflow...")
|
||||
response = await client.asubmit_workflow(selected_workflow.name, submission)
|
||||
monitor.run_id = response.run_id
|
||||
|
||||
print(f"✅ Fuzzing started!")
|
||||
print("✅ Fuzzing started!")
|
||||
print(f" Run ID: {response.run_id}")
|
||||
print(f" Initial status: {response.status}")
|
||||
print()
|
||||
|
||||
@@ -23,8 +23,6 @@ from .models import (
|
||||
WorkflowListItem,
|
||||
WorkflowStatus,
|
||||
WorkflowFindings,
|
||||
ResourceLimits,
|
||||
VolumeMount,
|
||||
FuzzingStats,
|
||||
CrashReport,
|
||||
RunSubmissionResponse,
|
||||
@@ -52,8 +50,6 @@ __all__ = [
|
||||
"WorkflowListItem",
|
||||
"WorkflowStatus",
|
||||
"WorkflowFindings",
|
||||
"ResourceLimits",
|
||||
"VolumeMount",
|
||||
"FuzzingStats",
|
||||
"CrashReport",
|
||||
"RunSubmissionResponse",
|
||||
|
||||
@@ -19,9 +19,11 @@ including real-time monitoring capabilities for fuzzing workflows.
|
||||
import asyncio
|
||||
import json
|
||||
import logging
|
||||
from typing import Dict, Any, List, Optional, AsyncIterator, Iterator, Union
|
||||
import tarfile
|
||||
import tempfile
|
||||
from pathlib import Path
|
||||
from typing import Dict, Any, List, Optional, AsyncIterator, Iterator, Union, Callable
|
||||
from urllib.parse import urljoin, urlparse
|
||||
import warnings
|
||||
|
||||
import httpx
|
||||
import websockets
|
||||
@@ -213,6 +215,56 @@ class FuzzForgeClient:
|
||||
response = await self._async_client.get(url)
|
||||
return await self._ahandle_response(response)
|
||||
|
||||
def get_workflow_worker_info(self, workflow_name: str) -> Dict[str, Any]:
|
||||
"""
|
||||
Get worker information for a workflow.
|
||||
|
||||
Returns details about which worker is required to execute this workflow,
|
||||
including container name, task queue, and vertical.
|
||||
|
||||
Args:
|
||||
workflow_name: Name of the workflow
|
||||
|
||||
Returns:
|
||||
Dictionary with worker info including:
|
||||
- workflow: Workflow name
|
||||
- vertical: Worker vertical (e.g., "ossfuzz", "python", "rust")
|
||||
- worker_container: Docker container name
|
||||
- task_queue: Temporal task queue name
|
||||
- required: Whether worker is required (always True)
|
||||
|
||||
Raises:
|
||||
FuzzForgeHTTPError: If workflow not found or metadata missing
|
||||
"""
|
||||
url = urljoin(self.base_url, f"/workflows/{workflow_name}/worker-info")
|
||||
response = self._client.get(url)
|
||||
return self._handle_response(response)
|
||||
|
||||
async def aget_workflow_worker_info(self, workflow_name: str) -> Dict[str, Any]:
|
||||
"""
|
||||
Get worker information for a workflow (async).
|
||||
|
||||
Returns details about which worker is required to execute this workflow,
|
||||
including container name, task queue, and vertical.
|
||||
|
||||
Args:
|
||||
workflow_name: Name of the workflow
|
||||
|
||||
Returns:
|
||||
Dictionary with worker info including:
|
||||
- workflow: Workflow name
|
||||
- vertical: Worker vertical (e.g., "ossfuzz", "python", "rust")
|
||||
- worker_container: Docker container name
|
||||
- task_queue: Temporal task queue name
|
||||
- required: Whether worker is required (always True)
|
||||
|
||||
Raises:
|
||||
FuzzForgeHTTPError: If workflow not found or metadata missing
|
||||
"""
|
||||
url = urljoin(self.base_url, f"/workflows/{workflow_name}/worker-info")
|
||||
response = await self._async_client.get(url)
|
||||
return await self._ahandle_response(response)
|
||||
|
||||
def submit_workflow(
|
||||
self,
|
||||
workflow_name: str,
|
||||
@@ -235,6 +287,232 @@ class FuzzForgeClient:
|
||||
data = await self._ahandle_response(response)
|
||||
return RunSubmissionResponse(**data)
|
||||
|
||||
def _create_tarball(
|
||||
self,
|
||||
source_path: Path,
|
||||
progress_callback: Optional[Callable[[int], None]] = None
|
||||
) -> Path:
|
||||
"""
|
||||
Create a compressed tarball from a file or directory.
|
||||
|
||||
Args:
|
||||
source_path: Path to file or directory to archive
|
||||
progress_callback: Optional callback(bytes_written) for progress tracking
|
||||
|
||||
Returns:
|
||||
Path to the created tarball
|
||||
|
||||
Raises:
|
||||
FileNotFoundError: If source_path doesn't exist
|
||||
"""
|
||||
if not source_path.exists():
|
||||
raise FileNotFoundError(f"Source path not found: {source_path}")
|
||||
|
||||
# Create temp file for tarball
|
||||
temp_fd, temp_path = tempfile.mkstemp(suffix=".tar.gz")
|
||||
|
||||
try:
|
||||
logger.info(f"Creating tarball from {source_path}")
|
||||
|
||||
bytes_written = 0
|
||||
|
||||
with tarfile.open(temp_path, "w:gz") as tar:
|
||||
if source_path.is_file():
|
||||
# Add single file
|
||||
tar.add(source_path, arcname=source_path.name)
|
||||
bytes_written = source_path.stat().st_size
|
||||
if progress_callback:
|
||||
progress_callback(bytes_written)
|
||||
else:
|
||||
# Add directory recursively
|
||||
for item in source_path.rglob("*"):
|
||||
if item.is_file():
|
||||
arcname = item.relative_to(source_path)
|
||||
tar.add(item, arcname=arcname)
|
||||
bytes_written += item.stat().st_size
|
||||
if progress_callback:
|
||||
progress_callback(bytes_written)
|
||||
|
||||
tarball_path = Path(temp_path)
|
||||
tarball_size = tarball_path.stat().st_size
|
||||
logger.info(
|
||||
f"Created tarball: {tarball_size / (1024**2):.2f} MB "
|
||||
f"(compressed from {bytes_written / (1024**2):.2f} MB)"
|
||||
)
|
||||
|
||||
return tarball_path
|
||||
|
||||
except Exception:
|
||||
# Cleanup on error
|
||||
if Path(temp_path).exists():
|
||||
Path(temp_path).unlink()
|
||||
raise
|
||||
|
||||
def submit_workflow_with_upload(
|
||||
self,
|
||||
workflow_name: str,
|
||||
target_path: Union[str, Path],
|
||||
parameters: Optional[Dict[str, Any]] = None,
|
||||
timeout: Optional[int] = None,
|
||||
progress_callback: Optional[Callable[[int, int], None]] = None
|
||||
) -> RunSubmissionResponse:
|
||||
"""
|
||||
Submit a workflow with file upload from local filesystem.
|
||||
|
||||
This method automatically creates a tarball if target_path is a directory,
|
||||
uploads it to the backend, and submits the workflow for execution.
|
||||
|
||||
Args:
|
||||
workflow_name: Name of the workflow to execute
|
||||
target_path: Local path to file or directory to analyze
|
||||
parameters: Workflow-specific parameters
|
||||
timeout: Timeout in seconds
|
||||
progress_callback: Optional callback(bytes_uploaded, total_bytes) for progress
|
||||
|
||||
Returns:
|
||||
Run submission response with run_id
|
||||
|
||||
Raises:
|
||||
FileNotFoundError: If target_path doesn't exist
|
||||
FuzzForgeHTTPError: For API errors
|
||||
"""
|
||||
target_path = Path(target_path)
|
||||
tarball_path = None
|
||||
|
||||
try:
|
||||
# Create tarball if needed
|
||||
if target_path.is_dir():
|
||||
logger.info("Target is directory, creating tarball...")
|
||||
tarball_path = self._create_tarball(target_path)
|
||||
upload_file = tarball_path
|
||||
filename = f"{target_path.name}.tar.gz"
|
||||
else:
|
||||
upload_file = target_path
|
||||
filename = target_path.name
|
||||
|
||||
# Prepare multipart form data
|
||||
url = urljoin(self.base_url, f"/workflows/{workflow_name}/upload-and-submit")
|
||||
|
||||
files = {
|
||||
"file": (filename, open(upload_file, "rb"), "application/gzip")
|
||||
}
|
||||
|
||||
data = {}
|
||||
|
||||
if parameters:
|
||||
data["parameters"] = json.dumps(parameters)
|
||||
|
||||
if timeout:
|
||||
data["timeout"] = str(timeout)
|
||||
|
||||
logger.info(f"Uploading {filename} to {workflow_name}...")
|
||||
|
||||
# Track upload progress
|
||||
if progress_callback:
|
||||
file_size = upload_file.stat().st_size
|
||||
|
||||
def track_progress(monitor):
|
||||
progress_callback(monitor.bytes_read, file_size)
|
||||
|
||||
# Note: httpx doesn't have built-in progress tracking for uploads
|
||||
# This is a placeholder - real implementation would need custom approach
|
||||
pass
|
||||
|
||||
response = self._client.post(url, files=files, data=data)
|
||||
|
||||
# Close file handle
|
||||
files["file"][1].close()
|
||||
|
||||
data = self._handle_response(response)
|
||||
return RunSubmissionResponse(**data)
|
||||
|
||||
finally:
|
||||
# Cleanup temporary tarball
|
||||
if tarball_path and tarball_path.exists():
|
||||
try:
|
||||
tarball_path.unlink()
|
||||
logger.debug(f"Cleaned up temporary tarball: {tarball_path}")
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to cleanup tarball {tarball_path}: {e}")
|
||||
|
||||
async def asubmit_workflow_with_upload(
|
||||
self,
|
||||
workflow_name: str,
|
||||
target_path: Union[str, Path],
|
||||
parameters: Optional[Dict[str, Any]] = None,
|
||||
volume_mode: str = "ro",
|
||||
timeout: Optional[int] = None,
|
||||
progress_callback: Optional[Callable[[int, int], None]] = None
|
||||
) -> RunSubmissionResponse:
|
||||
"""
|
||||
Submit a workflow with file upload from local filesystem (async).
|
||||
|
||||
This method automatically creates a tarball if target_path is a directory,
|
||||
uploads it to the backend, and submits the workflow for execution.
|
||||
|
||||
Args:
|
||||
workflow_name: Name of the workflow to execute
|
||||
target_path: Local path to file or directory to analyze
|
||||
parameters: Workflow-specific parameters
|
||||
volume_mode: Volume mount mode ("ro" or "rw")
|
||||
timeout: Timeout in seconds
|
||||
progress_callback: Optional callback(bytes_uploaded, total_bytes) for progress
|
||||
|
||||
Returns:
|
||||
Run submission response with run_id
|
||||
|
||||
Raises:
|
||||
FileNotFoundError: If target_path doesn't exist
|
||||
FuzzForgeHTTPError: For API errors
|
||||
"""
|
||||
target_path = Path(target_path)
|
||||
tarball_path = None
|
||||
|
||||
try:
|
||||
# Create tarball if needed
|
||||
if target_path.is_dir():
|
||||
logger.info("Target is directory, creating tarball...")
|
||||
tarball_path = self._create_tarball(target_path)
|
||||
upload_file = tarball_path
|
||||
filename = f"{target_path.name}.tar.gz"
|
||||
else:
|
||||
upload_file = target_path
|
||||
filename = target_path.name
|
||||
|
||||
# Prepare multipart form data
|
||||
url = urljoin(self.base_url, f"/workflows/{workflow_name}/upload-and-submit")
|
||||
|
||||
files = {
|
||||
"file": (filename, open(upload_file, "rb"), "application/gzip")
|
||||
}
|
||||
|
||||
data = {}
|
||||
|
||||
if parameters:
|
||||
data["parameters"] = json.dumps(parameters)
|
||||
|
||||
if timeout:
|
||||
data["timeout"] = str(timeout)
|
||||
|
||||
logger.info(f"Uploading {filename} to {workflow_name}...")
|
||||
|
||||
response = await self._async_client.post(url, files=files, data=data)
|
||||
|
||||
# Close file handle
|
||||
files["file"][1].close()
|
||||
|
||||
response_data = await self._ahandle_response(response)
|
||||
return RunSubmissionResponse(**response_data)
|
||||
|
||||
finally:
|
||||
# Cleanup temporary tarball
|
||||
if tarball_path and tarball_path.exists():
|
||||
try:
|
||||
tarball_path.unlink()
|
||||
logger.debug(f"Cleaned up temporary tarball: {tarball_path}")
|
||||
except Exception as e:
|
||||
logger.warning(f"Failed to cleanup tarball {tarball_path}: {e}")
|
||||
|
||||
# Run management methods
|
||||
|
||||
def get_run_status(self, run_id: str) -> WorkflowStatus:
|
||||
|
||||
@@ -20,7 +20,7 @@ import logging
|
||||
import re
|
||||
import subprocess
|
||||
import json
|
||||
from typing import Dict, Any, List, Optional, Tuple
|
||||
from typing import Dict, Any, List, Optional
|
||||
from datetime import datetime, timezone
|
||||
from dataclasses import dataclass
|
||||
|
||||
@@ -87,11 +87,6 @@ class DockerLogIntegration:
|
||||
r'network is unreachable',
|
||||
r'connection refused',
|
||||
r'timeout.*connect'
|
||||
],
|
||||
'prefect_error': [
|
||||
r'prefect.*error',
|
||||
r'flow run failed',
|
||||
r'task.*failed'
|
||||
]
|
||||
}
|
||||
|
||||
@@ -382,13 +377,6 @@ class DockerLogIntegration:
|
||||
"Check firewall settings and port availability"
|
||||
])
|
||||
|
||||
if 'prefect_error' in error_analysis:
|
||||
suggestions.extend([
|
||||
"Check Prefect server connectivity",
|
||||
"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
|
||||
)
|
||||
|
||||
|
||||
|
||||
Generated
+1
-1
@@ -85,7 +85,7 @@ wheels = [
|
||||
|
||||
[[package]]
|
||||
name = "fuzzforge-sdk"
|
||||
version = "0.1.0"
|
||||
version = "0.6.0"
|
||||
source = { editable = "." }
|
||||
dependencies = [
|
||||
{ name = "httpx" },
|
||||
|
||||
Reference in New Issue
Block a user