diff --git a/.envrc b/.envrc deleted file mode 100644 index f4494d1..0000000 --- a/.envrc +++ /dev/null @@ -1 +0,0 @@ -export PYTHONPATH=src diff --git a/.gitignore b/.gitignore index 58ac441..b10dc5b 100644 --- a/.gitignore +++ b/.gitignore @@ -9,6 +9,7 @@ __pycache__/ # Distribution / packaging .Python build/ +!src/tetra_rp/build/ develop-eggs/ dist/ downloads/ @@ -175,3 +176,7 @@ cython_debug/ .pypirc .tetra_resources.pkl .DS_Store + +# dev only +.envrc +test_app/ diff --git a/.python-version b/.python-version index bd28b9c..2c07333 100644 --- a/.python-version +++ b/.python-version @@ -1 +1 @@ -3.9 +3.11 diff --git a/.vscode/settings.json b/.vscode/settings.json index 1be6a53..d2c3693 100644 --- a/.vscode/settings.json +++ b/.vscode/settings.json @@ -3,5 +3,9 @@ "tests" ], "python.testing.unittestEnabled": false, - "python.testing.pytestEnabled": true + "python.testing.pytestEnabled": true, + "python.envFile": "${workspaceFolder}/.env", + "python.analysis.extraPaths": [ + "${workspaceFolder}/src", + ] } \ No newline at end of file diff --git a/Makefile b/Makefile index de27dc7..11ba839 100644 --- a/Makefile +++ b/Makefile @@ -12,8 +12,9 @@ help: # Show this help menu @awk 'BEGIN {FS = ":.*# "; printf "%-20s %s\n", "Target", "Description"} /^[a-zA-Z_-]+:.*# / {printf "%-20s %s\n", $$1, $$2}' $(MAKEFILE_LIST) @echo "" -dev: # Install development dependencies +dev: # Install development dependencies and package in editable mode uv sync --all-groups + uv pip install -e . update: uv sync --upgrade --all-groups diff --git a/pyproject.toml b/pyproject.toml index 08c4963..b37268f 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -47,6 +47,9 @@ flash = "tetra_rp.cli.main:app" requires = ["setuptools>=42", "wheel"] build-backend = "setuptools.build_meta" +[tool.setuptools.packages.find] +where = ["src"] + [tool.pytest.ini_options] testpaths = ["tests"] python_files = ["test_*.py"] diff --git a/src/tetra_rp/build/__init__.py b/src/tetra_rp/build/__init__.py new file mode 100644 index 0000000..0def1a7 --- /dev/null +++ b/src/tetra_rp/build/__init__.py @@ -0,0 +1,15 @@ +""" +Tetra Build System. + +Flash CLI Build Components: + - TarballStrategy: Tarball-based deployment for GPU workers + - CodeExtractor: Extract and clean source code + - VolumeManager: S3 volume management + +Usage: + from tetra_rp.build.gpu_workers.strategies import TarballStrategyConfig + from tetra_rp.build.gpu_workers.strategies.tarball_strategy import TarballStrategy + from tetra_rp.build.shared.code_extractor import CodeExtractor +""" + +__all__ = [] diff --git a/src/tetra_rp/build/code_extractor.py b/src/tetra_rp/build/code_extractor.py new file mode 100644 index 0000000..1cd3edd --- /dev/null +++ b/src/tetra_rp/build/code_extractor.py @@ -0,0 +1,132 @@ +""" +Code extraction and processing for production builds. + +Handles extracting source code, removing decorators, and generating code hashes. +""" + +import hashlib +import inspect +import logging +from dataclasses import dataclass +from typing import Any + +log = logging.getLogger(__name__) + + +@dataclass +class ExtractedCode: + """Container for extracted code information.""" + + source_code: str + cleaned_code: str + callable_name: str + callable_type: str # "function" or "class" + code_hash: str + + +class CodeExtractor: + """Extract and process source code from callable objects.""" + + def extract(self, func_or_class: Any) -> ExtractedCode: + """ + Extract source code from a function or class. + + Args: + func_or_class: The function or class to extract code from + + Returns: + ExtractedCode object containing source and metadata + + Raises: + ValueError: If source code cannot be extracted + """ + callable_name = func_or_class.__name__ + + try: + source_code = inspect.getsource(func_or_class) + except (OSError, TypeError) as e: + raise ValueError( + f"Failed to extract source code for {callable_name}: {e}" + ) from e + + # Determine callable type + callable_type = "class" if inspect.isclass(func_or_class) else "function" + + # Clean the code (remove decorators) + cleaned_code = self._remove_remote_decorator(source_code) + + # Generate hash for versioning + code_hash = self._generate_code_hash(source_code) + + log.debug( + f"Extracted {callable_type} '{callable_name}' " + f"({len(source_code)} bytes, hash: {code_hash})" + ) + + return ExtractedCode( + source_code=source_code, + cleaned_code=cleaned_code, + callable_name=callable_name, + callable_type=callable_type, + code_hash=code_hash, + ) + + def _remove_remote_decorator(self, source_code: str) -> str: + """ + Remove @remote decorator from source code. + + Uses line-based approach to handle both single-line and multi-line decorators. + + Args: + source_code: Original source code with decorators + + Returns: + Cleaned source code without @remote decorator + """ + lines = source_code.splitlines() + cleaned_lines = [] + in_decorator = False + + for line in lines: + stripped = line.strip() + + # Start of @remote decorator + if stripped.startswith("@remote"): + in_decorator = True + # Check if it's a multi-line decorator + if "(" in stripped and ")" not in stripped: + continue # Multi-line, skip this line + elif "(" in stripped and ")" in stripped: + # Single-line decorator, skip it + continue + else: + # Just @remote without parens + continue + + # Continuation of multi-line decorator + if in_decorator: + if ")" in stripped: + in_decorator = False + continue + + cleaned_lines.append(line) + + cleaned = "\n".join(cleaned_lines) + + # Add header if needed + if "import" not in cleaned[:100]: + cleaned = "# Auto-generated baked code\n" + cleaned + + return cleaned + + def _generate_code_hash(self, source_code: str) -> str: + """ + Generate a short hash from source code for versioning. + + Args: + source_code: Source code to hash + + Returns: + 8-character hex hash + """ + return hashlib.sha256(source_code.encode()).hexdigest()[:8] diff --git a/src/tetra_rp/build/gpu_workers/__init__.py b/src/tetra_rp/build/gpu_workers/__init__.py new file mode 100644 index 0000000..ec84c29 --- /dev/null +++ b/src/tetra_rp/build/gpu_workers/__init__.py @@ -0,0 +1,37 @@ +""" +GPU Worker deployment system - Tarball Strategy. + +Flash CLI uses tarball-based deployment for GPU workers. +""" + +from .strategies import ( + # Base types + DeploymentStrategy, + DeploymentArtifact, + DeploymentConfig, + StrategyType, + # Tarball Strategy + TarballStrategy, + TarballStrategyConfig, +) + +# Shared components +from .code_packager import CodePackager, PackageInfo +from .volume_manager import UploadResult, VolumeConfig, VolumeManager + +__all__ = [ + # Base types + "DeploymentStrategy", + "DeploymentArtifact", + "DeploymentConfig", + "StrategyType", + # Tarball Strategy + "TarballStrategy", + "TarballStrategyConfig", + # Shared Components + "CodePackager", + "PackageInfo", + "VolumeManager", + "VolumeConfig", + "UploadResult", +] diff --git a/src/tetra_rp/build/gpu_workers/code_packager.py b/src/tetra_rp/build/gpu_workers/code_packager.py new file mode 100644 index 0000000..ac6976c --- /dev/null +++ b/src/tetra_rp/build/gpu_workers/code_packager.py @@ -0,0 +1,215 @@ +""" +Code packaging for tarball-based deployment. + +Creates tarball packages of source code for fast deployment to workers. +""" + +import json +import logging +import tarfile +import tempfile +from dataclasses import dataclass +from pathlib import Path +from typing import Optional, List + +from ..shared.code_extractor import ExtractedCode + +log = logging.getLogger(__name__) + + +@dataclass +class PackageInfo: + """Information about a code package.""" + + tarball_path: Path # Path to the created tarball + tarball_name: str # Name of the tarball file + package_name: str + version: str + callable_name: str + callable_type: str + code_hash: str + size_bytes: int + + +class CodePackager: + """ + Package source code into tarballs for deployment. + + Creates tarball packages containing: + - Cleaned source code in baked_code/ directory + - Package metadata (registry.json) + - Dependencies information + """ + + def create_package( + self, + extracted_code: ExtractedCode, + dependencies: Optional[List[str]] = None, + system_dependencies: Optional[List[str]] = None, + output_dir: Optional[Path] = None, + ) -> PackageInfo: + """ + Create a tarball package from extracted code. + + Args: + extracted_code: Extracted code information + dependencies: Python dependencies + system_dependencies: System packages + output_dir: Directory to save tarball (defaults to temp) + + Returns: + PackageInfo with package details + """ + # Use temp directory if no output specified + if output_dir is None: + output_dir = Path(tempfile.gettempdir()) / "tetra_packages" + output_dir.mkdir(exist_ok=True) + + # Generate package name and version + package_name = extracted_code.callable_name.lower().replace("_", "-") + version = extracted_code.code_hash + tarball_name = f"{package_name}_{version}.tar.gz" + package_path = output_dir / tarball_name + + log.info(f"Creating package: {tarball_name}") + + # Create temporary staging directory + with tempfile.TemporaryDirectory() as tmpdir: + staging_dir = Path(tmpdir) / "package" + staging_dir.mkdir() + + # Create baked_code directory structure (same as Docker image layout) + baked_code_dir = staging_dir / "baked_code" + baked_code_dir.mkdir() + + # Write cleaned code to module file + module_file = baked_code_dir / f"{extracted_code.callable_name}.py" + module_file.write_text(extracted_code.cleaned_code) + log.debug(f" Added code: {module_file.name}") + + # Create __init__.py + init_file = baked_code_dir / "__init__.py" + init_file.write_text("") + + # Create registry.json (same format as baked executor expects) + registry = { + extracted_code.callable_name: { + "module": f"baked_code.{extracted_code.callable_name}", + "name": extracted_code.callable_name, + "type": extracted_code.callable_type, + } + } + registry_file = baked_code_dir / "registry.json" + registry_file.write_text(json.dumps(registry, indent=2)) + log.debug(f" Added registry: {registry_file.name}") + + # Create package metadata + metadata = { + "package_name": package_name, + "version": version, + "callable_name": extracted_code.callable_name, + "callable_type": extracted_code.callable_type, + "code_hash": extracted_code.code_hash, + "dependencies": dependencies or [], + "system_dependencies": system_dependencies or [], + } + metadata_file = staging_dir / "package_metadata.json" + metadata_file.write_text(json.dumps(metadata, indent=2)) + log.debug(f" Added metadata: {metadata_file.name}") + + # Create tarball + self._create_tarball(staging_dir, package_path) + + # Get package size + size_bytes = package_path.stat().st_size + size_kb = size_bytes / 1024 + log.info(f"Package created: {package_path.name} ({size_kb:.1f} KB)") + + return PackageInfo( + tarball_path=package_path, + tarball_name=tarball_name, + package_name=package_name, + version=version, + callable_name=extracted_code.callable_name, + callable_type=extracted_code.callable_type, + code_hash=extracted_code.code_hash, + size_bytes=size_bytes, + ) + + def _create_tarball(self, source_dir: Path, output_path: Path) -> None: + """ + Create gzipped tarball from directory. + + Args: + source_dir: Directory to archive + output_path: Output tarball path + """ + with tarfile.open(output_path, "w:gz") as tar: + # Add all files in source directory + for item in source_dir.rglob("*"): + if item.is_file(): + # Add with relative path + arcname = item.relative_to(source_dir) + tar.add(item, arcname=arcname) + log.debug(f" Archived: {arcname}") + + def extract_package(self, package_path: Path, output_dir: Path) -> Path: + """ + Extract tarball package. + + Args: + package_path: Path to tarball + output_dir: Directory to extract to + + Returns: + Path to extracted directory + """ + log.info(f"📂 Extracting package: {package_path.name}") + + output_dir.mkdir(parents=True, exist_ok=True) + + with tarfile.open(package_path, "r:gz") as tar: + tar.extractall(output_dir) + + log.info(f"Extracted to: {output_dir}") + return output_dir + + def verify_package(self, package_path: Path) -> dict: + """ + Verify package integrity and read metadata. + + Args: + package_path: Path to tarball + + Returns: + Package metadata dictionary + + Raises: + ValueError: If package is invalid + """ + if not package_path.exists(): + raise ValueError(f"Package not found: {package_path}") + + try: + with tarfile.open(package_path, "r:gz") as tar: + # Check for required files + members = tar.getnames() + + if "package_metadata.json" not in members: + raise ValueError("Missing package_metadata.json in tarball") + + if "baked_code/registry.json" not in members: + raise ValueError("Missing baked_code/registry.json in tarball") + + # Extract and read metadata + metadata_file = tar.extractfile("package_metadata.json") + if metadata_file is None: + raise ValueError("Could not read package_metadata.json") + + metadata = json.load(metadata_file) + + log.debug(f"Package verified: {metadata.get('package_name')}") + return metadata + + except (tarfile.TarError, json.JSONDecodeError) as e: + raise ValueError(f"Invalid package: {e}") from e diff --git a/src/tetra_rp/build/gpu_workers/strategies/__init__.py b/src/tetra_rp/build/gpu_workers/strategies/__init__.py new file mode 100644 index 0000000..d222915 --- /dev/null +++ b/src/tetra_rp/build/gpu_workers/strategies/__init__.py @@ -0,0 +1,38 @@ +""" +Deployment strategies for GPU workers. + +Flash CLI uses tarball-based deployment strategy. + +Usage: + from tetra_rp.build.gpu_workers.strategies import TarballStrategyConfig + + config = TarballStrategyConfig( + upload_to_storage=True, + storage_endpoint="s3.amazonaws.com", + storage_bucket="my-bucket" + ) + strategy = TarballStrategy(config=config) + artifact = await strategy.prepare_deployment(MyClass, "my-worker") + strategy.apply_to_resource(resource_config, artifact) +""" + +from .base import ( + DeploymentArtifact, + DeploymentConfig, + DeploymentStrategy, + DeployedResource, + StrategyType, +) +from .tarball_strategy import TarballStrategy, TarballStrategyConfig + +__all__ = [ + # Base classes + "DeploymentStrategy", + "DeploymentConfig", + "DeploymentArtifact", + "DeployedResource", + "StrategyType", + # Tarball Strategy + "TarballStrategy", + "TarballStrategyConfig", +] diff --git a/src/tetra_rp/build/gpu_workers/strategies/base.py b/src/tetra_rp/build/gpu_workers/strategies/base.py new file mode 100644 index 0000000..ff3d79b --- /dev/null +++ b/src/tetra_rp/build/gpu_workers/strategies/base.py @@ -0,0 +1,155 @@ +""" +Base deployment strategy interface with Pydantic models. + +Defines the abstract interface that all deployment strategies must implement. +""" + +from abc import ABC, abstractmethod +from enum import Enum +from typing import Any, Dict, List, Optional + +from pydantic import BaseModel, Field, ConfigDict + + +class StrategyType(str, Enum): + """Available deployment strategy types.""" + + IMAGE = "image" # Full Docker image build with baked code + TARBALL = "tarball" # Tarball download at runtime + + +class DeploymentArtifact(BaseModel): + """ + Artifact produced by deployment strategy. + + This represents what gets deployed (image reference, tarball path, etc.) + """ + + model_config = ConfigDict(arbitrary_types_allowed=True) + + strategy_type: StrategyType + artifact_reference: str = Field( + ..., description="Main artifact reference (image name, tarball key, etc.)" + ) + metadata: Dict[str, Any] = Field( + default_factory=dict, description="Strategy-specific metadata" + ) + size_bytes: Optional[int] = Field(None, description="Artifact size in bytes") + code_hash: Optional[str] = Field(None, description="Hash of deployed code") + + +class DeployedResource(BaseModel): + """ + Result of deploying a resource to a platform. + + Contains information about the deployed resource. + """ + + model_config = ConfigDict(arbitrary_types_allowed=True) + + success: bool + resource_id: Optional[str] = None + endpoint_url: Optional[str] = None + artifact: DeploymentArtifact + message: str + metadata: Dict[str, Any] = Field(default_factory=dict) + + +class DeploymentConfig(BaseModel): + """ + Base configuration for deployment strategies. + + Contains common configuration shared across all strategies. + """ + + model_config = ConfigDict(arbitrary_types_allowed=True) + + strategy_type: StrategyType + base_image: str = Field( + default="runpod/worker-v1-tetra:latest", + description="Base Docker image for GPU workers", + ) + dependencies: List[str] = Field( + default_factory=list, description="Python dependencies" + ) + env_vars: Dict[str, str] = Field( + default_factory=dict, description="Environment variables" + ) + platform: str = Field(default="linux/amd64", description="Docker platform") + + +class DeploymentStrategy(ABC): + """ + Abstract base class for deployment strategies. + + All deployment strategies must implement this interface. + + Strategy Pattern: + - ImageBuildStrategy: Bakes code into Docker image + - TarballStrategy: Creates tarball, downloads at runtime + - Future: S3Strategy, GitStrategy, HybridStrategy, etc. + """ + + def __init__(self, config: DeploymentConfig): + """ + Initialize strategy with configuration. + + Args: + config: Deployment configuration + """ + self.config = config + self._validate_config() + + @abstractmethod + def _validate_config(self) -> None: + """ + Validate strategy-specific configuration. + + Raises: + ValueError: If configuration is invalid + """ + pass + + @abstractmethod + async def prepare_deployment( + self, func_or_class: Any, name: str + ) -> DeploymentArtifact: + """ + Prepare deployment artifact (image, tarball, etc.). + + Args: + func_or_class: Python function or class to deploy + name: Name for the deployment + + Returns: + DeploymentArtifact with artifact reference and metadata + + Raises: + RuntimeError: If preparation fails + """ + pass + + @abstractmethod + async def apply_to_resource( + self, resource_config: Any, artifact: DeploymentArtifact + ) -> Any: + """ + Apply deployment artifact to resource configuration. + + Modifies resource_config in place to use the deployment artifact. + + Args: + resource_config: Resource configuration to modify + artifact: Deployment artifact to apply + + Returns: + Modified resource configuration + """ + pass + + def get_strategy_type(self) -> StrategyType: + """Get the strategy type.""" + return self.config.strategy_type + + def __repr__(self) -> str: + return f"{self.__class__.__name__}(strategy={self.config.strategy_type.value})" diff --git a/src/tetra_rp/build/gpu_workers/strategies/tarball_strategy.py b/src/tetra_rp/build/gpu_workers/strategies/tarball_strategy.py new file mode 100644 index 0000000..95c90f1 --- /dev/null +++ b/src/tetra_rp/build/gpu_workers/strategies/tarball_strategy.py @@ -0,0 +1,192 @@ +""" +Tarball Deployment Strategy. + +Creates tarball and downloads at runtime - serverless approach. +Pro: Fast deployments, small artifacts (KBs), like AWS Lambda +Con: Cold start overhead, runtime dependency on storage +""" + +import logging +import tempfile +from pathlib import Path +from typing import Any, Optional + +from pydantic import Field + +from .base import ( + DeploymentArtifact, + DeploymentConfig, + DeploymentStrategy, + StrategyType, +) +from ..code_packager import CodePackager +from ...shared.code_extractor import CodeExtractor +from ..volume_manager import VolumeManager + +log = logging.getLogger(__name__) + + +class TarballStrategyConfig(DeploymentConfig): + """Configuration specific to tarball strategy.""" + + strategy_type: StrategyType = Field(default=StrategyType.TARBALL, frozen=True) + upload_to_storage: bool = Field( + default=False, description="Upload tarball to S3/storage" + ) + storage_endpoint: Optional[str] = Field( + None, description="S3-compatible storage endpoint" + ) + storage_bucket: Optional[str] = Field(None, description="Storage bucket name") + storage_access_key: Optional[str] = Field( + None, description="Storage access key (from env if empty)" + ) + storage_secret_key: Optional[str] = Field( + None, description="Storage secret key (from env if empty)" + ) + + +class TarballStrategy(DeploymentStrategy): + """ + Deployment strategy that creates tarball for runtime download. + + Serverless approach where code is packaged as tarball and downloaded + by workers at startup. Similar to AWS Lambda, Google Cloud Functions. + + Use when: + - Need fast deployments (KBs vs GBs) + - Code changes frequently during development + - Want serverless-style cold start + - Have S3-compatible storage available + """ + + def __init__(self, config: TarballStrategyConfig): + """Initialize tarball strategy.""" + super().__init__(config) + self.config: TarballStrategyConfig = config + self.code_extractor = CodeExtractor() + self.code_packager = CodePackager() + self.volume_manager = VolumeManager() if config.upload_to_storage else None + + def _validate_config(self) -> None: + """Validate tarball strategy configuration.""" + if self.config.upload_to_storage: + if not self.config.storage_endpoint: + raise ValueError( + "storage_endpoint required when upload_to_storage=True" + ) + if not self.config.storage_bucket: + raise ValueError("storage_bucket required when upload_to_storage=True") + + async def prepare_deployment( + self, func_or_class: Any, name: str + ) -> DeploymentArtifact: + """ + Create tarball package for runtime download. + + Args: + func_or_class: Python function or class to deploy + name: Name for the tarball + + Returns: + DeploymentArtifact with tarball reference + """ + log.info(f"Creating tarball package: {name}") + + # Extract code + extracted_code = self.code_extractor.extract(func_or_class) + log.info(f" Code hash: {extracted_code.code_hash}") + + # Create tarball + with tempfile.TemporaryDirectory() as tmpdir: + output_dir = Path(tmpdir) + + package_info = self.code_packager.create_package( + extracted_code=extracted_code, + dependencies=self.config.dependencies, + output_dir=output_dir, + ) + + log.info(f" Tarball: {package_info.tarball_path}") + log.info(f" Size: {package_info.size_bytes / 1024:.2f} KB") + + # Upload to storage if configured + storage_key = None + if self.config.upload_to_storage and self.volume_manager: + storage_key = f"tetra/code/{name}-{extracted_code.code_hash}.tar.gz" + + upload_result = self.volume_manager.upload_tarball( + tarball_path=package_info.tarball_path, + s3_key=storage_key, + ) + + if not upload_result.success: + raise RuntimeError( + f"Tarball upload failed: {upload_result.message}" + ) + + log.info(f"Tarball uploaded: {storage_key}") + + return DeploymentArtifact( + strategy_type=StrategyType.TARBALL, + artifact_reference=storage_key or str(package_info.tarball_path), + code_hash=extracted_code.code_hash, + size_bytes=package_info.size_bytes, + metadata={ + "tarball_name": package_info.tarball_name, + "uploaded": storage_key is not None, + "storage_key": storage_key, + "local_path": str(package_info.tarball_path), + }, + ) + + async def apply_to_resource( + self, resource_config: Any, artifact: DeploymentArtifact + ) -> Any: + """ + Apply tarball configuration to resource. + + Args: + resource_config: Resource configuration to modify + artifact: Deployment artifact with tarball reference + + Returns: + Modified resource configuration + """ + # Use base image (not custom image) + resource_config.imageName = self.config.base_image + + # Set environment variables for tarball loading + if not hasattr(resource_config, "env"): + resource_config.env = {} + + resource_config.env.update(self.config.env_vars) + resource_config.env["TETRA_BAKED_MODE"] = "true" + resource_config.env["TETRA_DEPLOYMENT_STRATEGY"] = "tarball" + + # Set tarball reference + if artifact.metadata.get("uploaded"): + # Downloaded from storage at runtime + resource_config.env["TETRA_CODE_TARBALL"] = artifact.artifact_reference + resource_config.env["RUNPOD_VOLUME_ENDPOINT"] = ( + self.config.storage_endpoint or "" + ) + resource_config.env["RUNPOD_VOLUME_BUCKET"] = ( + self.config.storage_bucket or "" + ) + resource_config.env["RUNPOD_VOLUME_ACCESS_KEY"] = ( + self.config.storage_access_key or "" + ) + resource_config.env["RUNPOD_VOLUME_SECRET_KEY"] = ( + self.config.storage_secret_key or "" + ) + log.info("Applied tarball strategy (storage download)") + log.info(f" Storage key: {artifact.artifact_reference}") + else: + # Local tarball (for testing) + resource_config.env["TETRA_CODE_TARBALL_LOCAL"] = ( + artifact.artifact_reference + ) + log.info("Applied tarball strategy (local)") + log.info(f" Local path: {artifact.artifact_reference}") + + return resource_config diff --git a/src/tetra_rp/build/gpu_workers/volume_manager.py b/src/tetra_rp/build/gpu_workers/volume_manager.py new file mode 100644 index 0000000..53e1e67 --- /dev/null +++ b/src/tetra_rp/build/gpu_workers/volume_manager.py @@ -0,0 +1,256 @@ +""" +RunPod network volume management for S3-compatible storage. + +Handles uploading/downloading tarballs to/from RunPod network volumes. +""" + +import logging +import os +from dataclasses import dataclass +from pathlib import Path +from typing import Optional + +log = logging.getLogger(__name__) + + +@dataclass +class VolumeConfig: + """Configuration for RunPod network volume access.""" + + volume_id: Optional[str] = None + endpoint_url: Optional[str] = None + access_key: Optional[str] = None + secret_key: Optional[str] = None + bucket_name: Optional[str] = None + + @classmethod + def from_environment(cls) -> "VolumeConfig": + """ + Create volume config from environment variables. + + Environment variables: + RUNPOD_VOLUME_ID: Network volume ID + RUNPOD_VOLUME_ENDPOINT: S3-compatible endpoint URL + RUNPOD_VOLUME_ACCESS_KEY: S3 access key + RUNPOD_VOLUME_SECRET_KEY: S3 secret key + RUNPOD_VOLUME_BUCKET: S3 bucket name (defaults to 'tetra-code') + + Returns: + VolumeConfig instance + """ + return cls( + volume_id=os.getenv("RUNPOD_VOLUME_ID"), + endpoint_url=os.getenv("RUNPOD_VOLUME_ENDPOINT"), + access_key=os.getenv("RUNPOD_VOLUME_ACCESS_KEY"), + secret_key=os.getenv("RUNPOD_VOLUME_SECRET_KEY"), + bucket_name=os.getenv("RUNPOD_VOLUME_BUCKET", "tetra-code"), + ) + + def is_configured(self) -> bool: + """Check if volume is properly configured for S3-compatible storage.""" + return all( + [ + self.endpoint_url, + self.access_key, + self.secret_key, + self.bucket_name, + ] + ) + + +@dataclass +class UploadResult: + """Result of tarball upload.""" + + success: bool + s3_key: str + volume_path: str + message: str + size_bytes: int = 0 + + +class VolumeManager: + """ + Manage RunPod network volume operations. + + Uses S3-compatible API (boto3) for fast uploads/downloads. + """ + + def __init__(self, config: Optional[VolumeConfig] = None): + """ + Initialize volume manager. + + Args: + config: Volume configuration (defaults to environment-based) + """ + self.config = config or VolumeConfig.from_environment() + self._s3_client = None + + def _get_s3_client(self): + """Get or create S3 client for volume access.""" + if self._s3_client is not None: + return self._s3_client + + if not self.config.is_configured(): + raise ValueError( + "Volume not configured. Set RUNPOD_VOLUME_* environment variables." + ) + + try: + import boto3 + + self._s3_client = boto3.client( + "s3", + endpoint_url=self.config.endpoint_url, + aws_access_key_id=self.config.access_key, + aws_secret_access_key=self.config.secret_key, + region_name="eu-ro-1", + ) + + log.debug(f"S3 client initialized for volume: {self.config.volume_id}") + return self._s3_client + + except ImportError: + raise ImportError( + "boto3 required for volume management. Install with: pip install boto3" + ) + + def upload_tarball( + self, tarball_path: Path, s3_key: Optional[str] = None + ) -> UploadResult: + """ + Upload tarball to RunPod network volume. + + Args: + tarball_path: Path to tarball file + s3_key: S3 key (defaults to filename) + + Returns: + UploadResult with upload status + """ + if not self.config.is_configured(): + log.warning("Volume not configured - skipping upload") + log.warning(" Set RUNPOD_VOLUME_* env vars to enable volume uploads") + return UploadResult( + success=False, + s3_key="", + volume_path="", + message="Volume not configured", + ) + + if not tarball_path.exists(): + return UploadResult( + success=False, + s3_key="", + volume_path="", + message=f"Tarball not found: {tarball_path}", + ) + + # Use filename as S3 key if not specified + if s3_key is None: + s3_key = tarball_path.name + + # Get file size + size_bytes = tarball_path.stat().st_size + size_kb = size_bytes / 1024 + + log.info(f"Uploading to volume: {s3_key} ({size_kb:.1f} KB)") + + try: + s3 = self._get_s3_client() + + # Upload with progress callback + s3.upload_file( + str(tarball_path), + self.config.bucket_name, + s3_key, + Callback=self._upload_progress_callback(size_bytes), + ) + + volume_path = f"s3://{self.config.bucket_name}/{s3_key}" + + log.info(f"Upload complete: {volume_path}") + + return UploadResult( + success=True, + s3_key=s3_key, + volume_path=volume_path, + message="Upload successful", + size_bytes=size_bytes, + ) + + except Exception as e: + log.error(f"Upload failed: {e}") + return UploadResult( + success=False, + s3_key=s3_key, + volume_path="", + message=f"Upload failed: {e}", + ) + + def download_tarball(self, s3_key: str, output_path: Path) -> bool: + """ + Download tarball from RunPod network volume. + + Args: + s3_key: S3 key of tarball + output_path: Local path to save tarball + + Returns: + True if successful, False otherwise + """ + if not self.config.is_configured(): + log.error("Volume not configured") + return False + + log.info(f"📥 Downloading from volume: {s3_key}") + + try: + s3 = self._get_s3_client() + + # Ensure output directory exists + output_path.parent.mkdir(parents=True, exist_ok=True) + + # Download file + s3.download_file(self.config.bucket_name, s3_key, str(output_path)) + + size_kb = output_path.stat().st_size / 1024 + log.info(f"Downloaded: {output_path.name} ({size_kb:.1f} KB)") + + return True + + except Exception as e: + log.error(f"Download failed: {e}") + return False + + def tarball_exists(self, s3_key: str) -> bool: + """ + Check if tarball exists in volume. + + Args: + s3_key: S3 key to check + + Returns: + True if exists, False otherwise + """ + if not self.config.is_configured(): + return False + + try: + s3 = self._get_s3_client() + s3.head_object(Bucket=self.config.bucket_name, Key=s3_key) + return True + except Exception: + return False + + def _upload_progress_callback(self, total_bytes: int): + """Create callback for upload progress tracking.""" + uploaded = [0] # Use list to allow modification in closure + + def callback(bytes_transferred): + uploaded[0] += bytes_transferred + percent = (uploaded[0] / total_bytes) * 100 + if uploaded[0] == total_bytes or percent % 25 < 1: + log.debug(f" Upload progress: {percent:.0f}%") + + return callback diff --git a/src/tetra_rp/build/shared/__init__.py b/src/tetra_rp/build/shared/__init__.py new file mode 100644 index 0000000..1192931 --- /dev/null +++ b/src/tetra_rp/build/shared/__init__.py @@ -0,0 +1,27 @@ +""" +Shared build utilities. + +Common components used across both CPU and GPU build systems. +""" + +from .code_extractor import CodeExtractor, ExtractedCode +from .image_builder import BuildResult, ImageBuildConfig, ImageBuilder +from .image_cache import CacheEntry, ImageCache +from .registry_manager import PushResult, RegistryConfig, RegistryManager + +__all__ = [ + # Code processing + "CodeExtractor", + "ExtractedCode", + # Docker operations + "ImageBuilder", + "ImageBuildConfig", + "BuildResult", + # Registry operations + "RegistryManager", + "RegistryConfig", + "PushResult", + # Caching + "ImageCache", + "CacheEntry", +] diff --git a/src/tetra_rp/build/shared/code_extractor.py b/src/tetra_rp/build/shared/code_extractor.py new file mode 100644 index 0000000..1cd3edd --- /dev/null +++ b/src/tetra_rp/build/shared/code_extractor.py @@ -0,0 +1,132 @@ +""" +Code extraction and processing for production builds. + +Handles extracting source code, removing decorators, and generating code hashes. +""" + +import hashlib +import inspect +import logging +from dataclasses import dataclass +from typing import Any + +log = logging.getLogger(__name__) + + +@dataclass +class ExtractedCode: + """Container for extracted code information.""" + + source_code: str + cleaned_code: str + callable_name: str + callable_type: str # "function" or "class" + code_hash: str + + +class CodeExtractor: + """Extract and process source code from callable objects.""" + + def extract(self, func_or_class: Any) -> ExtractedCode: + """ + Extract source code from a function or class. + + Args: + func_or_class: The function or class to extract code from + + Returns: + ExtractedCode object containing source and metadata + + Raises: + ValueError: If source code cannot be extracted + """ + callable_name = func_or_class.__name__ + + try: + source_code = inspect.getsource(func_or_class) + except (OSError, TypeError) as e: + raise ValueError( + f"Failed to extract source code for {callable_name}: {e}" + ) from e + + # Determine callable type + callable_type = "class" if inspect.isclass(func_or_class) else "function" + + # Clean the code (remove decorators) + cleaned_code = self._remove_remote_decorator(source_code) + + # Generate hash for versioning + code_hash = self._generate_code_hash(source_code) + + log.debug( + f"Extracted {callable_type} '{callable_name}' " + f"({len(source_code)} bytes, hash: {code_hash})" + ) + + return ExtractedCode( + source_code=source_code, + cleaned_code=cleaned_code, + callable_name=callable_name, + callable_type=callable_type, + code_hash=code_hash, + ) + + def _remove_remote_decorator(self, source_code: str) -> str: + """ + Remove @remote decorator from source code. + + Uses line-based approach to handle both single-line and multi-line decorators. + + Args: + source_code: Original source code with decorators + + Returns: + Cleaned source code without @remote decorator + """ + lines = source_code.splitlines() + cleaned_lines = [] + in_decorator = False + + for line in lines: + stripped = line.strip() + + # Start of @remote decorator + if stripped.startswith("@remote"): + in_decorator = True + # Check if it's a multi-line decorator + if "(" in stripped and ")" not in stripped: + continue # Multi-line, skip this line + elif "(" in stripped and ")" in stripped: + # Single-line decorator, skip it + continue + else: + # Just @remote without parens + continue + + # Continuation of multi-line decorator + if in_decorator: + if ")" in stripped: + in_decorator = False + continue + + cleaned_lines.append(line) + + cleaned = "\n".join(cleaned_lines) + + # Add header if needed + if "import" not in cleaned[:100]: + cleaned = "# Auto-generated baked code\n" + cleaned + + return cleaned + + def _generate_code_hash(self, source_code: str) -> str: + """ + Generate a short hash from source code for versioning. + + Args: + source_code: Source code to hash + + Returns: + 8-character hex hash + """ + return hashlib.sha256(source_code.encode()).hexdigest()[:8] diff --git a/src/tetra_rp/build/shared/image_builder.py b/src/tetra_rp/build/shared/image_builder.py new file mode 100644 index 0000000..ea2c0ad --- /dev/null +++ b/src/tetra_rp/build/shared/image_builder.py @@ -0,0 +1,123 @@ +""" +Docker image building operations. + +Handles building Docker images with platform targeting. +""" + +import logging +import subprocess +from dataclasses import dataclass +from pathlib import Path +from typing import Optional + +log = logging.getLogger(__name__) + + +@dataclass +class ImageBuildConfig: + """Configuration for Docker image build.""" + + build_dir: Path + image_name: str + image_tag: str + platform: str = "linux/amd64" + + +@dataclass +class BuildResult: + """Result of Docker image build.""" + + success: bool + local_image: str + stdout: Optional[str] = None + stderr: Optional[str] = None + + +class ImageBuilder: + """Build Docker images with platform targeting.""" + + def build(self, config: ImageBuildConfig) -> BuildResult: + """ + Build Docker image. + + Args: + config: Build configuration + + Returns: + BuildResult with success status and output + + Raises: + RuntimeError: If Docker build fails + """ + local_image = f"{config.image_name}:{config.image_tag}" + + log.info(f"Building Docker image: {local_image}") + log.info(f" Platform: {config.platform}") + log.info(f" Build dir: {config.build_dir}") + + try: + result = subprocess.run( + [ + "docker", + "build", + "--platform", + config.platform, + "-t", + local_image, + "-f", + "Dockerfile", + ".", + ], + cwd=config.build_dir, + capture_output=True, + text=True, + check=True, + ) + + log.info(f"Image built successfully: {local_image}") + + return BuildResult( + success=True, + local_image=local_image, + stdout=result.stdout, + stderr=result.stderr, + ) + + except subprocess.CalledProcessError as e: + log.error("Docker build failed:") + log.error(e.stderr) + + return BuildResult( + success=False, + local_image=local_image, + stdout=e.stdout, + stderr=e.stderr, + ) + + def tag_image(self, source: str, target: str) -> bool: + """ + Tag a Docker image. + + Args: + source: Source image name + target: Target image name + + Returns: + True if successful, False otherwise + """ + log.debug(f"Tagging image: {source} -> {target}") + + try: + subprocess.run( + ["docker", "tag", source, target], + check=True, + capture_output=True, + ) + log.debug("Tagged successfully") + return True + + except subprocess.CalledProcessError as e: + log.error( + f"Tag failed: {e.stderr.decode() if e.stderr else 'unknown error'}" + ) + return False diff --git a/src/tetra_rp/build/shared/image_cache.py b/src/tetra_rp/build/shared/image_cache.py new file mode 100644 index 0000000..8d51f51 --- /dev/null +++ b/src/tetra_rp/build/shared/image_cache.py @@ -0,0 +1,244 @@ +""" +Image cache management for production builds. + +Provides intelligent caching to avoid unnecessary rebuilds when code hasn't changed. +""" + +import json +import logging +import subprocess +from dataclasses import dataclass +from pathlib import Path +from typing import Optional + +log = logging.getLogger(__name__) + + +@dataclass +class CacheEntry: + """Cached image information.""" + + image_name: str + image_tag: str + full_image: str + code_hash: str + callable_name: str + exists_locally: bool = False + exists_in_registry: bool = False + + +class ImageCache: + """ + Manage build cache to avoid unnecessary rebuilds. + + Checks both local Docker images and remote registry to determine + if an image with the same code hash already exists. + """ + + def __init__(self, cache_file: Optional[Path] = None): + """ + Initialize image cache. + + Args: + cache_file: Path to cache metadata file (defaults to ~/.tetra/build_cache.json) + """ + if cache_file is None: + cache_dir = Path.home() / ".tetra" + cache_dir.mkdir(exist_ok=True) + cache_file = cache_dir / "build_cache.json" + + self.cache_file = cache_file + self._cache_data = self._load_cache() + + def _load_cache(self) -> dict: + """Load cache metadata from disk.""" + if not self.cache_file.exists(): + return {} + + try: + with open(self.cache_file, "r") as f: + return json.load(f) + except (json.JSONDecodeError, IOError) as e: + log.warning(f"Failed to load cache file: {e}") + return {} + + def _save_cache(self) -> None: + """Save cache metadata to disk.""" + try: + self.cache_file.parent.mkdir(parents=True, exist_ok=True) + with open(self.cache_file, "w") as f: + json.dump(self._cache_data, f, indent=2) + except IOError as e: + log.warning(f"Failed to save cache file: {e}") + + def get_cached_image( + self, callable_name: str, code_hash: str + ) -> Optional[CacheEntry]: + """ + Check if cached image exists for given callable and code hash. + + Args: + callable_name: Name of function/class + code_hash: Hash of source code + + Returns: + CacheEntry if found, None otherwise + """ + cache_key = f"{callable_name}:{code_hash}" + + # Check cache metadata + if cache_key not in self._cache_data: + log.debug(f"Cache miss: {cache_key} not in cache metadata") + return None + + cached = self._cache_data[cache_key] + entry = CacheEntry( + image_name=cached["image_name"], + image_tag=cached["image_tag"], + full_image=cached["full_image"], + code_hash=code_hash, + callable_name=callable_name, + ) + + log.debug(f"Cache metadata found for {cache_key}") + + # Verify image still exists + entry.exists_locally = self._check_local_image(entry.full_image) + entry.exists_in_registry = self._check_registry_image(entry.full_image) + + if entry.exists_locally or entry.exists_in_registry: + log.info(f"Cache HIT: {entry.full_image}") + log.info( + f" Local: {entry.exists_locally}, Registry: {entry.exists_in_registry}" + ) + return entry + else: + log.info("Cache metadata exists but image not found, rebuilding") + # Remove stale cache entry + del self._cache_data[cache_key] + self._save_cache() + return None + + def store_image( + self, + callable_name: str, + code_hash: str, + image_name: str, + image_tag: str, + full_image: str, + ) -> None: + """ + Store image information in cache. + + Args: + callable_name: Name of function/class + code_hash: Hash of source code + image_name: Base image name + image_tag: Image tag + full_image: Full image name with registry + """ + cache_key = f"{callable_name}:{code_hash}" + + self._cache_data[cache_key] = { + "callable_name": callable_name, + "code_hash": code_hash, + "image_name": image_name, + "image_tag": image_tag, + "full_image": full_image, + } + + self._save_cache() + log.debug(f"Cached image info: {cache_key} -> {full_image}") + + def invalidate(self, callable_name: str) -> int: + """ + Invalidate all cached images for a callable. + + Args: + callable_name: Name of function/class to invalidate + + Returns: + Number of entries invalidated + """ + keys_to_remove = [ + k for k in self._cache_data.keys() if k.startswith(f"{callable_name}:") + ] + + for key in keys_to_remove: + del self._cache_data[key] + + if keys_to_remove: + self._save_cache() + log.info( + f"Invalidated {len(keys_to_remove)} cache entries for {callable_name}" + ) + + return len(keys_to_remove) + + def clear(self) -> int: + """ + Clear entire cache. + + Returns: + Number of entries cleared + """ + count = len(self._cache_data) + self._cache_data = {} + self._save_cache() + log.info(f"Cleared {count} cache entries") + return count + + def _check_local_image(self, image: str) -> bool: + """ + Check if image exists in local Docker. + + Args: + image: Full image name to check + + Returns: + True if image exists locally + """ + try: + result = subprocess.run( + ["docker", "images", "-q", image], + capture_output=True, + text=True, + check=False, + ) + exists = bool(result.stdout.strip()) + log.debug(f"Local image check for {image}: {exists}") + return exists + except (subprocess.SubprocessError, FileNotFoundError): + log.debug(f"Failed to check local image: {image}") + return False + + def _check_registry_image(self, image: str) -> bool: + """ + Check if image exists in remote registry. + + Uses `docker manifest inspect` which doesn't pull the image. + + Args: + image: Full image name to check + + Returns: + True if image exists in registry + """ + # Only check registry if image has registry prefix + if "/" not in image or image.count("/") < 2: + log.debug(f"Skipping registry check for local-only image: {image}") + return False + + try: + result = subprocess.run( + ["docker", "manifest", "inspect", image], + capture_output=True, + text=True, + check=False, + ) + exists = result.returncode == 0 + log.debug(f"Registry image check for {image}: {exists}") + return exists + except (subprocess.SubprocessError, FileNotFoundError): + log.debug(f"Failed to check registry image: {image}") + return False diff --git a/src/tetra_rp/build/shared/registry_manager.py b/src/tetra_rp/build/shared/registry_manager.py new file mode 100644 index 0000000..9e78a63 --- /dev/null +++ b/src/tetra_rp/build/shared/registry_manager.py @@ -0,0 +1,145 @@ +""" +Docker registry management. + +Handles registry configuration, image pushing, and registry operations. +""" + +import logging +import os +import subprocess +from dataclasses import dataclass +from typing import Optional + +log = logging.getLogger(__name__) + + +@dataclass +class RegistryConfig: + """Docker registry configuration.""" + + registry_url: Optional[str] = None + skip_push: bool = False + + @classmethod + def from_environment(cls) -> "RegistryConfig": + """ + Create registry config from environment variables. + + Environment variables: + TETRA_DOCKER_REGISTRY: Registry URL (e.g., docker.io/myuser) + TETRA_SKIP_PUSH: Skip push for fast local testing (true/false) + + Returns: + RegistryConfig instance + """ + registry = os.getenv("TETRA_DOCKER_REGISTRY") + skip_push = os.getenv("TETRA_SKIP_PUSH", "false").lower() in ( + "true", + "1", + "yes", + ) + + return cls(registry_url=registry, skip_push=skip_push) + + def get_registry_prefix(self) -> Optional[str]: + """ + Get registry prefix for image names. + + Returns: + Registry prefix with trailing slash, or None if not configured + """ + if not self.registry_url: + return None + + # Ensure it ends with / + return ( + self.registry_url + if self.registry_url.endswith("/") + else f"{self.registry_url}/" + ) + + def should_push(self) -> bool: + """Check if images should be pushed to registry.""" + return self.registry_url is not None and not self.skip_push + + +@dataclass +class PushResult: + """Result of Docker image push.""" + + success: bool + image: str + message: Optional[str] = None + + +class RegistryManager: + """Manage Docker registry operations.""" + + def __init__(self, config: Optional[RegistryConfig] = None): + """ + Initialize registry manager. + + Args: + config: Registry configuration (defaults to environment-based) + """ + self.config = config or RegistryConfig.from_environment() + + def get_full_image_name(self, image_name: str, image_tag: str) -> str: + """ + Get full image name with registry prefix. + + Args: + image_name: Base image name + image_tag: Image tag + + Returns: + Full image name (with registry if configured) + """ + local_image = f"{image_name}:{image_tag}" + + if prefix := self.config.get_registry_prefix(): + return f"{prefix}{local_image}" + + return local_image + + def push_image(self, image: str) -> PushResult: + """ + Push image to registry. + + Args: + image: Full image name to push + + Returns: + PushResult with success status + """ + if not self.config.should_push(): + if self.config.skip_push: + log.warning("TETRA_SKIP_PUSH=true - skipping push") + log.warning(f" Image {image} is LOCAL ONLY") + log.warning(" RunPod deployment will fail unless you manually push") + return PushResult( + success=True, image=image, message="Push skipped (TETRA_SKIP_PUSH)" + ) + else: + log.warning("No registry configured - image is local only") + log.warning( + "Set TETRA_DOCKER_REGISTRY env var to enable automatic push" + ) + log.warning("Example: export TETRA_DOCKER_REGISTRY=docker.io/myuser") + return PushResult( + success=True, image=image, message="No registry configured" + ) + + log.info(f"Pushing to registry: {image}") + log.info("This may take several minutes for large base images...") + + try: + # Push to registry (show progress in stdout) + subprocess.run(["docker", "push", image], check=True) + + log.info("Image pushed successfully") + return PushResult(success=True, image=image, message="Push successful") + + except subprocess.CalledProcessError: + log.error("Docker push failed") + return PushResult(success=False, image=image, message="Push failed") diff --git a/src/tetra_rp/cli/commands/build.py b/src/tetra_rp/cli/commands/build.py new file mode 100644 index 0000000..9f3e3aa --- /dev/null +++ b/src/tetra_rp/cli/commands/build.py @@ -0,0 +1,680 @@ +"""Flash build command - Build and package Flash Server and GPU workers for production.""" + +import ast +import asyncio +import importlib.util +import json +import os +import sys +from dataclasses import dataclass, asdict +from datetime import datetime +from pathlib import Path +from typing import List, Optional, Tuple + +import typer +from rich.console import Console +from rich.panel import Panel +from rich.progress import Progress, SpinnerColumn, TextColumn +from rich.table import Table + +from tetra_rp.build.gpu_workers.strategies import TarballStrategyConfig +from tetra_rp.build.gpu_workers.strategies.tarball_strategy import TarballStrategy +from tetra_rp.build.shared.code_extractor import CodeExtractor + +console = Console() + + +# Data classes for clean type safety +@dataclass +class WorkerArtifact: + """Information about a built GPU worker.""" + + name: str + tarball_s3_key: str + code_hash: str + dependencies: List[str] + system_dependencies: List[str] + base_image: str + + +@dataclass +class FlashServerArtifact: + """Information about built Flash Server.""" + + tarball_s3_key: str + base_image: str + port: int + + +@dataclass +class BuildArtifacts: + """Complete build artifacts for a Flash project.""" + + project_name: str + flash_server: FlashServerArtifact + workers: List[WorkerArtifact] + build_time: str + + +def build_command( + project_dir: Optional[Path] = typer.Option( + None, "--dir", "-d", help="Project directory (default: current directory)" + ), + name: Optional[str] = typer.Option( + None, "--name", "-n", help="Project name (auto-detected if not provided)" + ), + upload_to_s3: bool = typer.Option( + True, "--upload/--no-upload", help="Upload tarballs to S3/Network Volume" + ), + flash_server_only: bool = typer.Option( + False, "--flash-server-only", help="Build only Flash Server (skip GPU workers)" + ), + workers_only: bool = typer.Option( + False, "--workers-only", help="Build only GPU workers (skip Flash Server)" + ), +): + """ + Build Flash project for production deployment. + + Packages Flash Server and GPU workers, uploads to S3-compatible storage. + + Examples: + flash build --upload # Build and upload to S3 + flash build --no-upload # Build locally only + flash build --workers-only # Build only GPU workers + """ + # Validate options + if flash_server_only and workers_only: + console.print( + "[red]Error:[/red] Cannot use --flash-server-only and --workers-only together" + ) + raise typer.Exit(1) + + # Validate project structure + project_dir = _resolve_project_dir(project_dir) + name = name or project_dir.name + _validate_project_structure(project_dir, flash_server_only) + + # Display configuration + _display_build_config(name, project_dir, upload_to_s3) + + # Run build + try: + asyncio.run( + _execute_build( + project_dir=project_dir, + name=name, + upload_to_s3=upload_to_s3, + build_flash_server=not workers_only, + build_workers=not flash_server_only, + ) + ) + except KeyboardInterrupt: + console.print("\n[yellow]Build cancelled by user[/yellow]") + raise typer.Exit(1) + except Exception as e: + console.print(f"\n[red]Build failed:[/red] {e}") + import traceback + + console.print(traceback.format_exc()) + raise typer.Exit(1) + + +def _resolve_project_dir(project_dir: Optional[Path]) -> Path: + """Resolve and validate project directory.""" + if project_dir is None: + project_dir = Path.cwd() + else: + project_dir = Path(project_dir).resolve() + + if not project_dir.exists(): + console.print(f"[red]Error:[/red] Directory not found: {project_dir}") + raise typer.Exit(1) + + return project_dir + + +def _validate_project_structure(project_dir: Path, skip_workers: bool = False): + """Validate Flash project structure.""" + main_py = project_dir / "main.py" + workers_dir = project_dir / "workers" + + if not main_py.exists(): + console.print(f"[red]Error:[/red] main.py not found in {project_dir}") + console.print("Run [bold]flash init[/bold] to create a Flash project") + raise typer.Exit(1) + + if not skip_workers and not workers_dir.exists(): + console.print( + f"[red]Error:[/red] workers/ directory not found in {project_dir}" + ) + console.print("Run [bold]flash init[/bold] to create a Flash project") + raise typer.Exit(1) + + +def _display_build_config(name: str, project_dir: Path, upload_to_s3: bool): + """Display build configuration.""" + console.print( + Panel( + f"[bold]Project:[/bold] {name}\n" + f"[bold]Directory:[/bold] {project_dir}\n" + f"[bold]Strategy:[/bold] tarball (Network Volume)\n" + f"[bold]Upload to S3:[/bold] {upload_to_s3}", + title="Flash Build Configuration", + expand=False, + ) + ) + + +async def _execute_build( + project_dir: Path, + name: str, + upload_to_s3: bool, + build_flash_server: bool, + build_workers: bool, +): + """Execute build process with progress tracking.""" + + # Check S3 configuration if upload is requested + if upload_to_s3: + storage_endpoint = os.getenv("RUNPOD_S3_ENDPOINT") + storage_bucket = os.getenv("RUNPOD_S3_BUCKET") + + if not storage_endpoint or not storage_bucket: + console.print( + "[yellow]Warning:[/yellow] S3 not configured (RUNPOD_S3_ENDPOINT, RUNPOD_S3_BUCKET). " + "Building locally..." + ) + upload_to_s3 = False + + with Progress( + SpinnerColumn(), + TextColumn("[progress.description]{task.description}"), + console=console, + ) as progress: + worker_artifacts = [] + flash_server_artifact = None + + # Build GPU Workers + if build_workers: + worker_artifacts = await _build_gpu_workers( + progress, project_dir, name, upload_to_s3 + ) + + # Build Flash Server + if build_flash_server: + flash_server_artifact = await _build_flash_server( + progress, project_dir, name, upload_to_s3 + ) + + # Save build artifacts + if build_flash_server and flash_server_artifact: + await _save_build_artifacts( + project_dir, name, flash_server_artifact, worker_artifacts + ) + + # Display summary + console.print("\n") + _display_build_summary(name, flash_server_artifact, worker_artifacts) + + +async def _build_gpu_workers( + progress: Progress, project_dir: Path, name: str, upload_to_s3: bool +) -> List[WorkerArtifact]: + """Build GPU worker packages.""" + workers_task = progress.add_task("[blue]Preparing GPU workers...") + worker_artifacts = [] + + try: + workers_dir = project_dir / "workers" + + # Find @remote decorated workers + remote_workers = WorkerDiscovery.find_remote_decorated_workers(workers_dir) + + if not remote_workers: + progress.update(workers_task, description="[yellow]No GPU workers found") + progress.stop_task(workers_task) + return [] + + # Create builder + builder = WorkerTarballBuilder( + upload_to_s3=upload_to_s3, + storage_endpoint=os.getenv("RUNPOD_S3_ENDPOINT"), + storage_bucket=os.getenv("RUNPOD_S3_BUCKET", "tetra-code"), + storage_access_key=os.getenv("RUNPOD_VOLUME_ACCESS_KEY", ""), + storage_secret_key=os.getenv("RUNPOD_VOLUME_SECRET_KEY", ""), + ) + + # Build each worker + for worker_file, class_name in remote_workers: + artifact = await builder.build_worker( + workers_dir, worker_file, class_name, name + ) + if artifact: + worker_artifacts.append(artifact) + + if worker_artifacts: + progress.update( + workers_task, + description=f"[green]✓ {len(worker_artifacts)} GPU worker(s) ready", + ) + else: + progress.update( + workers_task, + description="[yellow]No GPU workers built", + ) + progress.stop_task(workers_task) + + except Exception as e: + progress.update(workers_task, description=f"[red]✗ Failed: {e}") + progress.stop_task(workers_task) + raise + + return worker_artifacts + + +async def _build_flash_server( + progress: Progress, project_dir: Path, name: str, upload_to_s3: bool +) -> FlashServerArtifact: + """Build Flash Server package.""" + server_task = progress.add_task("[green]Preparing Flash Server...") + + try: + builder = FlashServerTarballBuilder( + upload_to_s3=upload_to_s3, + storage_endpoint=os.getenv("RUNPOD_S3_ENDPOINT"), + storage_bucket=os.getenv("RUNPOD_S3_BUCKET", "tetra-code"), + ) + + artifact = await builder.build_server(project_dir, name) + + progress.update(server_task, description="[green]✓ Flash Server ready") + progress.stop_task(server_task) + + return artifact + + except Exception as e: + progress.update(server_task, description=f"[red]✗ Flash Server failed: {e}") + progress.stop_task(server_task) + raise + + +async def _save_build_artifacts( + project_dir: Path, + name: str, + flash_server: FlashServerArtifact, + workers: List[WorkerArtifact], +): + """Save build artifacts to .tetra/build_artifacts.json.""" + tetra_dir = project_dir / ".tetra" + tetra_dir.mkdir(exist_ok=True) + + artifacts = BuildArtifacts( + project_name=name, + flash_server=flash_server, + workers=workers, + build_time=datetime.utcnow().isoformat() + "Z", + ) + + artifacts_file = tetra_dir / "build_artifacts.json" + artifacts_file.write_text(json.dumps(asdict(artifacts), indent=2)) + + console.print(f"[dim]Build artifacts saved to {artifacts_file}[/dim]") + + +def _display_build_summary( + project_name: str, + flash_server: Optional[FlashServerArtifact], + workers: List[WorkerArtifact], +): + """Display build results summary.""" + + summary_table = Table(show_header=False, box=None) + summary_table.add_column("Component", style="bold") + summary_table.add_column("Count", style="cyan") + + # GPU Workers + if workers: + worker_names = ", ".join([w.name for w in workers]) + summary_table.add_row("GPU Workers", f"{len(workers)} ({worker_names})") + else: + summary_table.add_row("GPU Workers", "[dim]None[/dim]") + + # Flash Server + if flash_server: + summary_table.add_row("Flash Server", "✓") + + console.print("\n") + console.print(summary_table) + + # Next steps + console.print("\n[bold]Ready to deploy![/bold]") + console.print("[dim]Run:[/dim] [bold cyan]flash deploy[/bold cyan]") + + # Success + console.print( + Panel( + f"Build complete for [bold]{project_name}[/bold]", + title="✓ Success", + expand=False, + border_style="green", + ) + ) + + +# ============================================================================ +# Worker Discovery - Finds @remote decorated classes +# ============================================================================ + + +class WorkerDiscovery: + """Discovers @remote decorated worker classes in project.""" + + @staticmethod + def find_remote_decorated_workers(workers_dir: Path) -> List[Tuple[str, str]]: + """ + Find all @remote decorated classes in workers/ directory. + + Returns: + List of (filename, class_name) tuples + """ + remote_workers = [] + + for py_file in workers_dir.glob("*.py"): + if py_file.name == "__init__.py": + continue + + try: + source = py_file.read_text() + tree = ast.parse(source) + + for node in ast.walk(tree): + if isinstance(node, ast.ClassDef): + if WorkerDiscovery._has_remote_decorator(node): + remote_workers.append((py_file.name, node.name)) + + except Exception as e: + console.print( + f"[yellow]Warning:[/yellow] Failed to parse {py_file.name}: {e}" + ) + + return remote_workers + + @staticmethod + def _has_remote_decorator(class_node: ast.ClassDef) -> bool: + """Check if class has @remote decorator.""" + for decorator in class_node.decorator_list: + # @remote + if isinstance(decorator, ast.Name) and decorator.id == "remote": + return True + # @remote(...) or @remote(config) + elif isinstance(decorator, ast.Call): + if ( + isinstance(decorator.func, ast.Name) + and decorator.func.id == "remote" + ): + return True + return False + + +# ============================================================================ +# Decorator Config Extractor - Extracts deps from @remote() +# ============================================================================ + + +class DecoratorConfigExtractor: + """Extracts configuration from @remote decorator.""" + + @staticmethod + def extract_config( + file_path: Path, class_name: str + ) -> Tuple[Optional[List[str]], Optional[List[str]]]: + """ + Extract dependencies and system_dependencies from @remote decorator. + + Returns: + Tuple of (dependencies, system_dependencies) + """ + try: + source = file_path.read_text() + tree = ast.parse(source) + + for node in ast.walk(tree): + if isinstance(node, ast.ClassDef) and node.name == class_name: + for decorator in node.decorator_list: + if isinstance(decorator, ast.Call): + if ( + isinstance(decorator.func, ast.Name) + and decorator.func.id == "remote" + ): + return DecoratorConfigExtractor._extract_deps(decorator) + + except Exception as e: + console.print( + f"[yellow]Warning:[/yellow] Failed to extract decorator config: {e}" + ) + + return (None, None) + + @staticmethod + def _extract_deps( + call_node: ast.Call, + ) -> Tuple[Optional[List[str]], Optional[List[str]]]: + """Extract dependencies from decorator call node.""" + dependencies = None + system_deps = None + + for keyword in call_node.keywords: + if keyword.arg == "dependencies": + dependencies = DecoratorConfigExtractor._extract_list(keyword.value) + elif keyword.arg == "system_dependencies": + system_deps = DecoratorConfigExtractor._extract_list(keyword.value) + + return (dependencies, system_deps) + + @staticmethod + def _extract_list(node) -> Optional[List[str]]: + """Extract list of strings from AST node.""" + if isinstance(node, ast.List): + items = [] + for elt in node.elts: + if isinstance(elt, ast.Constant): + items.append(elt.value) + elif isinstance(elt, ast.Str): # Older Python versions + items.append(elt.s) + return items + return None + + +# ============================================================================ +# Worker Tarball Builder - Builds GPU worker tarballs +# ============================================================================ + + +class WorkerTarballBuilder: + """Builds tarball packages for GPU workers.""" + + def __init__( + self, + upload_to_s3: bool, + storage_endpoint: str, + storage_bucket: str, + storage_access_key: str, + storage_secret_key: str, + ): + self.upload_to_s3 = upload_to_s3 + self.storage_endpoint = storage_endpoint + self.storage_bucket = storage_bucket + self.storage_access_key = storage_access_key + self.storage_secret_key = storage_secret_key + + async def build_worker( + self, workers_dir: Path, filename: str, class_name: str, project_name: str + ) -> Optional[WorkerArtifact]: + """Build tarball for a single worker.""" + try: + # Import worker class + worker_class = self._import_worker_class(workers_dir, filename, class_name) + if not worker_class: + return None + + # Extract decorator config + file_path = workers_dir / filename + dependencies, system_deps = DecoratorConfigExtractor.extract_config( + file_path, class_name + ) + + # Get GPU image from environment + import os + + gpu_image = os.getenv("TETRA_GPU_IMAGE", "runpod/worker-tetra:latest") + + # Create tarball strategy + strategy_config = TarballStrategyConfig( + base_image=gpu_image, + upload_to_storage=self.upload_to_s3, + storage_endpoint=self.storage_endpoint, + storage_bucket=self.storage_bucket, + storage_access_key=self.storage_access_key, + storage_secret_key=self.storage_secret_key, + dependencies=dependencies or [], + ) + strategy = TarballStrategy(config=strategy_config) + + # Build tarball + artifact = await strategy.prepare_deployment( + func_or_class=worker_class, name=f"{project_name}-{class_name}" + ) + + # Extract code hash + extractor = CodeExtractor() + extracted = extractor.extract(worker_class) + + return WorkerArtifact( + name=class_name, + tarball_s3_key=artifact.artifact_reference, + code_hash=extracted.code_hash, + dependencies=dependencies or [], + system_dependencies=system_deps or [], + base_image=gpu_image, + ) + + except Exception as e: + console.print( + f"[yellow]Warning:[/yellow] Failed to build {class_name}: {e}" + ) + return None + + def _import_worker_class(self, workers_dir: Path, filename: str, class_name: str): + """Dynamically import worker class.""" + try: + sys.path.insert(0, str(workers_dir.parent)) + + module_path = workers_dir / filename + spec = importlib.util.spec_from_file_location( + f"workers.{filename[:-3]}", module_path + ) + module = importlib.util.module_from_spec(spec) + spec.loader.exec_module(module) + + return getattr(module, class_name) + + except Exception as e: + console.print( + f"[yellow]Warning:[/yellow] Failed to import {class_name}: {e}" + ) + return None + + +# ============================================================================ +# Flash Server Tarball Builder - Builds Flash Server tarball +# ============================================================================ + + +class FlashServerTarballBuilder: + """Builds tarball package for Flash Server.""" + + def __init__(self, upload_to_s3: bool, storage_endpoint: str, storage_bucket: str): + self.upload_to_s3 = upload_to_s3 + self.storage_endpoint = storage_endpoint + self.storage_bucket = storage_bucket + + async def build_server( + self, project_dir: Path, project_name: str + ) -> FlashServerArtifact: + """Build Flash Server tarball containing full project.""" + import hashlib + import tarfile + import tempfile + + # Create temporary tarball + with tempfile.TemporaryDirectory() as tmpdir: + tarball_path = Path(tmpdir) / f"{project_name}-flash-server.tar.gz" + + # Create tarball with project contents + with tarfile.open(tarball_path, "w:gz") as tar: + # Add all project files + for item in project_dir.rglob("*"): + if self._should_include(item, project_dir): + arcname = item.relative_to(project_dir) + tar.add(item, arcname=arcname) + + # Calculate hash + with open(tarball_path, "rb") as f: + file_hash = hashlib.sha256(f.read()).hexdigest()[:8] + + # Upload to S3 if configured + if self.upload_to_s3: + from tetra_rp.build.gpu_workers.volume_manager import VolumeManager + + volume_manager = VolumeManager() + storage_key = ( + f"tetra/code/{project_name}-flash-server-{file_hash}.tar.gz" + ) + + upload_result = volume_manager.upload_tarball( + tarball_path=tarball_path, + s3_key=storage_key, + ) + + if upload_result.success: + s3_key = upload_result.s3_key + else: + # Fallback to local if upload fails + console.print( + "[yellow]Warning:[/yellow] S3 upload failed, using local tarball" + ) + s3_key = str(tarball_path) + else: + # Local mode - use file path + s3_key = str(tarball_path) + + return FlashServerArtifact( + tarball_s3_key=s3_key, + base_image="mwiki/flash-server:latest", + port=8888, + ) + + def _should_include(self, path: Path, project_dir: Path) -> bool: + """Determine if file should be included in tarball.""" + # Exclude patterns + exclude_patterns = [ + "__pycache__", + "*.pyc", + ".git", + ".tetra", + "*.egg-info", + ".venv", + "venv", + ".env", + ".DS_Store", + "node_modules", + ] + + # Check if path matches any exclude pattern + path_str = str(path.relative_to(project_dir)) + for pattern in exclude_patterns: + if pattern in path_str or path.name == pattern: + return False + + return path.is_file() diff --git a/src/tetra_rp/cli/commands/deploy.py b/src/tetra_rp/cli/commands/deploy.py deleted file mode 100644 index 5a56b65..0000000 --- a/src/tetra_rp/cli/commands/deploy.py +++ /dev/null @@ -1,336 +0,0 @@ -"""Deployment environment management commands.""" - -import typer -from rich.console import Console -from rich.table import Table -from rich.panel import Panel -import questionary - -from ..utils.deployment import ( - get_deployment_environments, - create_deployment_environment, - remove_deployment_environment, - deploy_to_environment, - rollback_deployment, - get_environment_info, -) - -console = Console() - - -def list_command(): - """Show available deployment environments.""" - - environments = get_deployment_environments() - - if not environments: - console.print( - Panel( - "📦 No deployment environments found\n\n" - "Create one with: [bold]runpod remote deploy new [/bold]", - title="Deployment Environments", - expand=False, - ) - ) - return - - table = Table(title="Deployment Environments") - table.add_column("Environment", style="cyan", no_wrap=True) - table.add_column("Status", justify="center") - table.add_column("Current Version", style="magenta") - table.add_column("Last Deployed", style="yellow") - table.add_column("URL", style="blue") - - active_count = 0 - idle_count = 0 - - for env_name, env_info in environments.items(): - status = env_info.get("status", "Unknown") - if status == "active": - status_display = "🟢 Active" - active_count += 1 - elif status == "idle": - status_display = "🟡 Idle" - idle_count += 1 - else: - status_display = "🔴 Error" - - table.add_row( - env_name, - status_display, - env_info.get("current_version", "N/A"), - env_info.get("last_deployed", "Never"), - env_info.get("url", "N/A"), - ) - - console.print(table) - - # Summary - total = len(environments) - error_count = total - active_count - idle_count - summary = f"Total: {total} environments ({active_count} active" - if idle_count > 0: - summary += f", {idle_count} idle" - if error_count > 0: - summary += f", {error_count} error" - summary += ")" - - console.print(f"\n{summary}") - - -def new_command(name: str): - """Create a new deployment environment.""" - - environments = get_deployment_environments() - - if name in environments: - console.print(f"Environment '{name}' already exists") - raise typer.Exit(1) - - # Interactive configuration - config = {} - - try: - config["region"] = questionary.select( - "Select region:", - choices=["us-east-1", "us-west-2", "eu-west-1", "ap-southeast-1"], - ).ask() - - config["instance_type"] = questionary.select( - "Instance type:", choices=["A40", "A100", "H100", "RTX4090"] - ).ask() - - config["auto_scale"] = questionary.confirm("Enable auto-scaling?").ask() - - if not all([config["region"], config["instance_type"]]): - console.print("Configuration cancelled") - raise typer.Exit(1) - - except KeyboardInterrupt: - console.print("\nEnvironment creation cancelled") - raise typer.Exit(1) - - # Create environment - with console.status(f"Creating environment '{name}'..."): - create_deployment_environment(name, config) - - # Success message - panel_content = f"Environment '[bold]{name}[/bold]' created successfully\n\n" - panel_content += f"Region: {config['region']}\n" - panel_content += f"Instance: {config['instance_type']}\n" - panel_content += f"Auto-scale: {'Enabled' if config['auto_scale'] else 'Disabled'}" - - console.print(Panel(panel_content, title="🚀 Environment Created", expand=False)) - - console.print(f"\nNext: [bold]flash deploy send {name}[/bold]") - - -def send_command(name: str): - """Deploy project to deployment environment.""" - - environments = get_deployment_environments() - - if name not in environments: - console.print(f"Environment '{name}' not found") - console.print("Available environments:") - for env_name in environments.keys(): - console.print(f" • {env_name}") - raise typer.Exit(1) - - # Deploy with mock progress - console.print(f"🚀 Deploying to '[bold]{name}[/bold]'...") - - try: - result = deploy_to_environment(name) - - panel_content = f"Deployed to '[bold]{name}[/bold]' successfully\n\n" - panel_content += f"Version: {result['version']}\n" - panel_content += f"URL: {result['url']}\n" - panel_content += "Status: 🟢 Active" - - console.print( - Panel(panel_content, title="🚀 Deployment Complete", expand=False) - ) - - except Exception as e: - console.print(f"Deployment failed: {e}") - raise typer.Exit(1) - - -def report_command(name: str): - """Show detailed environment status and metrics.""" - - environments = get_deployment_environments() - - if name not in environments: - console.print(f"Environment '{name}' not found") - raise typer.Exit(1) - - env_info = get_environment_info(name) - - # Environment status - status = env_info.get("status", "unknown") - status_display = { - "active": "🟢 Active", - "idle": "🟡 Idle", - "error": "🔴 Error", - }.get(status, "❓ Unknown") - - # Main info panel - main_info = f"Status: {status_display}\n" - main_info += f"Current Version: {env_info.get('current_version', 'N/A')}\n" - main_info += f"URL: {env_info.get('url', 'N/A')}\n" - main_info += f"Last Deployed: {env_info.get('last_deployed', 'Never')}\n" - main_info += f"Uptime: {env_info.get('uptime', 'N/A')}" - - console.print( - Panel(main_info, title=f"📊 Environment Report: {name}", expand=False) - ) - - # Version history - versions = env_info.get("version_history", []) - if versions: - version_table = Table(title="Version History") - version_table.add_column("Version", style="cyan") - version_table.add_column("Status", justify="center") - version_table.add_column("Deployed", style="yellow") - version_table.add_column("Description", style="white") - - for version in versions[:5]: # Show last 5 versions - version_status = ( - "🟢 Current" if version.get("is_current") else "📦 Previous" - ) - version_table.add_row( - version.get("version", "N/A"), - version_status, - version.get("deployed_at", "N/A"), - version.get("description", "No description"), - ) - - console.print(version_table) - - # Mock metrics - console.print("\n[bold]Metrics (Last 24h):[/bold]") - metrics_info = [ - "• Requests: 145,234", - "• Avg Response Time: 245ms", - "• Error Rate: 0.02%", - "• CPU Usage: 45%", - "• Memory Usage: 62%", - ] - - for metric in metrics_info: - console.print(f" {metric}") - - -def rollback_command(name: str): - """Rollback deployment to previous version.""" - - environments = get_deployment_environments() - - if name not in environments: - console.print(f"Environment '{name}' not found") - raise typer.Exit(1) - - env_info = get_environment_info(name) - versions = env_info.get("version_history", []) - - if len(versions) < 2: - console.print("No previous versions available for rollback") - raise typer.Exit(1) - - # Show available versions (excluding current) - previous_versions = [v for v in versions if not v.get("is_current")] - - if not previous_versions: - console.print("No previous versions available for rollback") - raise typer.Exit(1) - - try: - version_choices = [ - f"{v['version']} - {v.get('description', 'No description')}" - for v in previous_versions[:5] - ] - - selected = questionary.select( - "Select version to rollback to:", choices=version_choices - ).ask() - - if not selected: - console.print("Rollback cancelled") - raise typer.Exit(1) - - target_version = selected.split(" - ")[0] - - # Confirmation - confirmed = questionary.confirm( - f"Rollback environment '{name}' to version {target_version}?" - ).ask() - - if not confirmed: - console.print("Rollback cancelled") - raise typer.Exit(1) - - except KeyboardInterrupt: - console.print("\nRollback cancelled") - raise typer.Exit(1) - - # Perform rollback - with console.status(f"Rolling back to {target_version}..."): - rollback_deployment(name, target_version) - - console.print(f"Rolled back to version {target_version}") - console.print(f"Environment '{name}' is now running the previous version.") - - -def remove_command(name: str): - """Remove deployment environment.""" - - environments = get_deployment_environments() - - if name not in environments: - console.print(f"Environment '{name}' not found") - raise typer.Exit(1) - - env_info = get_environment_info(name) - - # Show removal preview - preview_content = f"Environment: {name}\n" - preview_content += f"Status: {env_info.get('status', 'unknown')}\n" - preview_content += f"URL: {env_info.get('url', 'N/A')}\n" - preview_content += f"Current Version: {env_info.get('current_version', 'N/A')}\n\n" - preview_content += "⚠️ This will permanently remove:\n" - preview_content += " • All deployment history\n" - preview_content += " • All associated resources\n" - preview_content += " • Environment configuration\n" - preview_content += " • Access URLs\n\n" - preview_content += "🚨 This action cannot be undone!" - - console.print(Panel(preview_content, title="⚠️ Removal Preview", expand=False)) - - try: - # Double confirmation for safety - confirmed = questionary.confirm( - f"Are you sure you want to remove environment '{name}'?" - ).ask() - - if not confirmed: - console.print("Removal cancelled") - raise typer.Exit(1) - - # Type confirmation - typed_name = questionary.text(f"Type '{name}' to confirm removal:").ask() - - if typed_name != name: - console.print("Confirmation failed - names do not match") - raise typer.Exit(1) - - except KeyboardInterrupt: - console.print("\nRemoval cancelled") - raise typer.Exit(1) - - # Remove environment - with console.status(f"Removing environment '{name}'..."): - remove_deployment_environment(name) - - console.print(f"Environment '{name}' removed successfully") diff --git a/src/tetra_rp/cli/commands/deploy_flash.py b/src/tetra_rp/cli/commands/deploy_flash.py new file mode 100644 index 0000000..a8f4f11 --- /dev/null +++ b/src/tetra_rp/cli/commands/deploy_flash.py @@ -0,0 +1,182 @@ +"""Flash deploy command - Deploy Flash project to production.""" + +import asyncio +import json +from pathlib import Path +from typing import Optional + +import typer +from rich.console import Console +from rich.panel import Panel +from rich.progress import Progress, SpinnerColumn, TextColumn + +console = Console() + + +def deploy_flash_command( + project_dir: Optional[Path] = typer.Option( + None, "--dir", "-d", help="Project directory (default: current directory)" + ), +): + """ + Deploy Flash project to RunPod. + + Deploys Flash Server (CPU) with Load Balancer endpoint. + GPU workers auto-deploy on first request to @remote endpoints. + + Examples: + flash deploy # Deploy to production + flash deploy --dir ./app # Deploy from specific directory + """ + # Resolve project directory + if project_dir is None: + project_dir = Path.cwd() + else: + project_dir = Path(project_dir).resolve() + + # Check for build artifacts + artifacts_file = project_dir / ".tetra" / "build_artifacts.json" + if not artifacts_file.exists(): + console.print( + "[red]Error:[/red] Build artifacts not found. Run [bold]flash build[/bold] first." + ) + raise typer.Exit(1) + + # Load build artifacts + try: + artifacts = json.loads(artifacts_file.read_text()) + except Exception as e: + console.print(f"[red]Error:[/red] Failed to read build artifacts: {e}") + raise typer.Exit(1) + + # Display deployment configuration + _display_deploy_config(artifacts) + + # Run deployment + try: + asyncio.run(_execute_deployment(artifacts, project_dir)) + except KeyboardInterrupt: + console.print("\n[yellow]Deployment cancelled by user[/yellow]") + raise typer.Exit(1) + except Exception as e: + console.print(f"\n[red]Deployment failed:[/red] {e}") + import traceback + + console.print(traceback.format_exc()) + raise typer.Exit(1) + + +def _display_deploy_config(artifacts: dict): + """Display deployment configuration.""" + project_name = artifacts.get("project_name", "unknown") + worker_count = len(artifacts.get("workers", [])) + + console.print( + Panel( + f"[bold]Project:[/bold] {project_name}\n" + f"[bold]Flash Server:[/bold] {artifacts['flash_server']['base_image']}\n" + f"[bold]GPU Workers:[/bold] {worker_count} worker(s)\n" + f"[bold]Build Time:[/bold] {artifacts.get('build_time', 'unknown')}", + title="Flash Deployment Configuration", + expand=False, + ) + ) + + +async def _execute_deployment(artifacts: dict, project_dir: Path): + """Execute deployment process.""" + from tetra_rp.core.resources import CpuLiveServerless, ServerlessType + + with Progress( + SpinnerColumn(), + TextColumn("[progress.description]{task.description}"), + console=console, + ) as progress: + # Deploy Flash Server + server_task = progress.add_task("[green]Deploying to RunPod...") + + try: + flash_server_config = artifacts["flash_server"] + + # Create CPU Live Serverless with Load Balancer type + import os + + endpoint = CpuLiveServerless( + name=f"{artifacts['project_name']}-flash-server", + imageName=flash_server_config["base_image"], + env={ + # Enable production mode for GPU worker deployment + "TETRA_PROD_MODE": "true", + # Flash Server baked mode configuration + "TETRA_BAKED_MODE": "true", + "TETRA_CODE_TARBALL": flash_server_config["tarball_s3_key"], + # Network volume configuration for GPU workers + "RUNPOD_VOLUME_ID": os.getenv("RUNPOD_VOLUME_ID", ""), + "RUNPOD_VOLUME_ENDPOINT": os.getenv("RUNPOD_VOLUME_ENDPOINT", ""), + "RUNPOD_VOLUME_ACCESS_KEY": os.getenv( + "RUNPOD_VOLUME_ACCESS_KEY", "" + ), + "RUNPOD_VOLUME_SECRET_KEY": os.getenv( + "RUNPOD_VOLUME_SECRET_KEY", "" + ), + "RUNPOD_VOLUME_BUCKET": os.getenv( + "RUNPOD_VOLUME_BUCKET", "tetra-code" + ), + # GPU worker image configuration + "TETRA_GPU_IMAGE": os.getenv( + "TETRA_GPU_IMAGE", "runpod/tetra-rp:latest" + ), + # RunPod API key for GPU worker deployment + "RUNPOD_API_KEY": os.getenv("RUNPOD_API_KEY", ""), + }, + type=ServerlessType.LB, + workersMin=1, + workersMax=3, + idleTimeout=30, + ) + + # Deploy endpoint + deployed_endpoint = await endpoint.deploy() + endpoint_id = deployed_endpoint.id + + progress.update( + server_task, + description="[green]✓ Deployed", + ) + progress.stop_task(server_task) + + except Exception as e: + progress.update(server_task, description=f"[red]✗ Failed: {e}") + progress.stop_task(server_task) + raise + + # Display deployment summary + console.print("\n") + _display_deployment_summary(artifacts, endpoint_id) + + +def _display_deployment_summary(artifacts: dict, endpoint_id: str): + """Display deployment summary.""" + project_name = artifacts.get("project_name", "unknown") + endpoint_url = f"https://{endpoint_id}.api.runpod.ai" + worker_count = len(artifacts.get("workers", [])) + + # Success panel + console.print( + Panel( + f"[bold]{project_name}[/bold] deployed successfully!\n\n" + f"[bold cyan]URL:[/bold cyan] {endpoint_url}", + title="✓ Live", + expand=False, + border_style="green", + ) + ) + + # Test command + console.print("\n[bold]Test your endpoint:[/bold]") + console.print(f"[dim]curl {endpoint_url}/[/dim]") + + if worker_count > 0: + console.print( + f"\n[dim]GPU workers ({worker_count}) will deploy on first request[/dim]" + ) diff --git a/src/tetra_rp/cli/commands/init.py b/src/tetra_rp/cli/commands/init.py index 8301317..ac78959 100644 --- a/src/tetra_rp/cli/commands/init.py +++ b/src/tetra_rp/cli/commands/init.py @@ -1,77 +1,119 @@ """Project initialization command.""" +from pathlib import Path + import typer -from typing import Optional from rich.console import Console from rich.panel import Panel from rich.table import Table -import questionary -from tetra_rp.config import get_paths -from ..utils.skeleton import create_project_skeleton, get_available_templates +from ..utils.skeleton import create_project_skeleton +from ..utils.conda import ( + check_conda_available, + create_conda_environment, + install_packages_in_env, + environment_exists, + get_activation_command, +) console = Console() +# Required packages for flash run to work smoothly +REQUIRED_PACKAGES = [ + "fastapi>=0.104.0", + "uvicorn[standard]>=0.24.0", + "python-dotenv>=1.0.0", + "pydantic>=2.0.0", + "aiohttp>=3.9.0", +] + def init_command( - template: Optional[str] = typer.Option( - None, "--template", "-t", help="Project template to use" + project_name: str = typer.Argument(..., help="Project name"), + no_env: bool = typer.Option( + False, "--no-env", help="Skip conda environment creation" + ), + force: bool = typer.Option( + False, "--force", "-f", help="Overwrite existing directory" ), - force: bool = typer.Option(False, "--force", "-f", help="Overwrite existing files"), ): - """Create skeleton application with starter files.""" + """Create new Flash project with Flash Server and GPU workers.""" - # Check if we're already in a Tetra project - paths = get_paths() - if paths.tetra_dir.exists() and not force: - console.print("Already in a Tetra project directory") - console.print("Use --force to overwrite existing configuration") - raise typer.Exit(1) + # Create project directory + project_dir = Path(project_name) - # Get available templates - available_templates = get_available_templates() - - # Interactive template selection if not provided - if not template: - template_choices = [] - for name, info in available_templates.items(): - template_choices.append(f"{name} - {info['description']}") - - try: - selected = questionary.select( - "Choose a project template:", choices=template_choices - ).ask() - - if not selected: - console.print("Template selection cancelled") - raise typer.Exit(1) - - template = selected.split(" - ")[0] - except KeyboardInterrupt: - console.print("\nTemplate selection cancelled") - raise typer.Exit(1) - - # Validate template choice - if template not in available_templates: - console.print(f"Unknown template: {template}") - console.print("Available templates:") - for name, info in available_templates.items(): - console.print(f" • {name} - {info['description']}") + if project_dir.exists() and not force: + console.print(f"Directory '{project_name}' already exists") + console.print("Use --force to overwrite") raise typer.Exit(1) - # Create project skeleton - template_info = available_templates[template] - - with console.status(f"Creating project with {template} template..."): - created_files = create_project_skeleton(template, template_info, force) + # Create project directory + project_dir.mkdir(parents=True, exist_ok=True) + + with console.status(f"Creating Flash project '{project_name}'..."): + create_project_skeleton(project_dir, force) + + # Create conda environment if requested + env_created = False + if not no_env: + if not check_conda_available(): + console.print( + "[yellow]Warning: conda not found. Skipping environment creation.[/yellow]" + ) + console.print( + "Install Miniconda or Anaconda, or use --no-env flag to skip this step." + ) + else: + # Check if environment already exists + if environment_exists(project_name): + console.print( + f"[yellow]Conda environment '{project_name}' already exists. Skipping creation.[/yellow]" + ) + env_created = True + else: + # Create conda environment + with console.status(f"Creating conda environment '{project_name}'..."): + success, message = create_conda_environment(project_name) + + if not success: + console.print(f"[yellow]Warning: {message}[/yellow]") + console.print( + "You can manually create the environment and install dependencies." + ) + else: + env_created = True + + # Install required packages + with console.status("Installing dependencies..."): + success, message = install_packages_in_env( + project_name, REQUIRED_PACKAGES, use_pip=True + ) + + if not success: + console.print(f"[yellow]Warning: {message}[/yellow]") + console.print( + "You can manually install dependencies: pip install -r requirements.txt" + ) # Success output - panel_content = f"Project initialized with [bold]{template}[/bold] template\n\n" - panel_content += "Created files:\n" - for file_path in created_files: - panel_content += f" • {file_path}\n" - - console.print(Panel(panel_content, title="Project Initialized", expand=False)) + panel_content = ( + f"Flash project '[bold]{project_name}[/bold]' created successfully!\n\n" + ) + panel_content += "Project structure:\n" + panel_content += f" {project_name}/\n" + panel_content += " ├── main.py # Flash Server (FastAPI)\n" + panel_content += " ├── workers/ # GPU workers\n" + panel_content += " │ └── example_worker.py\n" + panel_content += " ├── .env.example\n" + panel_content += " ├── requirements.txt\n" + panel_content += " └── README.md\n" + + if env_created: + panel_content += ( + f"\nConda environment '[bold]{project_name}[/bold]' created and configured" + ) + + console.print(Panel(panel_content, title="Project Created", expand=False)) # Next steps console.print("\n[bold]Next steps:[/bold]") @@ -79,8 +121,15 @@ def init_command( steps_table.add_column("Step", style="bold cyan") steps_table.add_column("Description") - steps_table.add_row("1.", "Edit .env with your RunPod API key") - steps_table.add_row("2.", "Install dependencies: pip install -r requirements.txt") - steps_table.add_row("3.", "Run your project: flash run") + steps_table.add_row("1.", f"cd {project_name}") + + if env_created: + steps_table.add_row("2.", f"{get_activation_command(project_name)}") + steps_table.add_row("3.", "cp .env.example .env # Add your RUNPOD_API_KEY") + steps_table.add_row("4.", "flash run") + else: + steps_table.add_row("2.", "pip install -r requirements.txt") + steps_table.add_row("3.", "cp .env.example .env # Add your RUNPOD_API_KEY") + steps_table.add_row("4.", "flash run") console.print(steps_table) diff --git a/src/tetra_rp/cli/commands/resource.py b/src/tetra_rp/cli/commands/resource.py deleted file mode 100644 index 97b53f8..0000000 --- a/src/tetra_rp/cli/commands/resource.py +++ /dev/null @@ -1,191 +0,0 @@ -"""Resource management commands.""" - -import typer -from rich.console import Console -from rich.table import Table -from rich.panel import Panel -from rich.live import Live -from rich.progress import Progress, SpinnerColumn, TextColumn -import questionary -import time - -from ...core.resources.resource_manager import ResourceManager - -console = Console() - - -def report_command( - live: bool = typer.Option(False, "--live", "-l", help="Live updating status"), - refresh: int = typer.Option( - 2, "--refresh", "-r", help="Refresh interval for live mode" - ), -): - """Show resource status dashboard.""" - - resource_manager = ResourceManager() - - if live: - try: - with Live( - generate_resource_table(resource_manager), - console=console, - refresh_per_second=1 / refresh, - screen=True, - ) as live_display: - while True: - time.sleep(refresh) - live_display.update(generate_resource_table(resource_manager)) - except KeyboardInterrupt: - console.print("\n📊 Live monitoring stopped") - else: - table = generate_resource_table(resource_manager) - console.print(table) - - -def clean_command( - force: bool = typer.Option(False, "--force", "-f", help="Skip confirmation"), -): - """Remove all tracked resources after confirmation.""" - - resource_manager = ResourceManager() - resources = resource_manager._resources - - if not resources: - console.print("🧹 No resources to clean") - return - - # Show cleanup preview - console.print(generate_cleanup_preview(resources)) - - # Confirmation unless forced - if not force: - try: - confirmed = questionary.confirm( - "Are you sure you want to clean all resources?" - ).ask() - - if not confirmed: - console.print("Cleanup cancelled") - return - except KeyboardInterrupt: - console.print("\nCleanup cancelled") - return - - # Clean resources with progress - with Progress( - SpinnerColumn(), - TextColumn("[progress.description]{task.description}"), - console=console, - ) as progress: - task = progress.add_task("Cleaning resources...", total=len(resources)) - - for uid in list(resources.keys()): - resource = resources[uid] - progress.update( - task, description=f"Removing {resource.__class__.__name__}..." - ) - - # Remove resource (this will also clean up remotely if needed) - resource_manager.remove_resource(uid) - - progress.advance(task) - time.sleep(0.1) # Small delay for visual feedback - - console.print("All resources cleaned successfully") - - -def generate_resource_table(resource_manager: ResourceManager) -> Panel: - """Generate a formatted table of resources.""" - - resources = resource_manager._resources - - if not resources: - return Panel( - "📊 No resources currently tracked\n\n" - "Resources will appear here after running your Tetra applications.", - title="Resource Status Report", - expand=False, - ) - - table = Table(title="Resource Status Report") - table.add_column("Resource ID", style="cyan", no_wrap=True) - table.add_column("Status", justify="center") - table.add_column("Type", style="magenta") - table.add_column("URL", style="blue") - table.add_column("Health", justify="center") - - active_count = 0 - error_count = 0 - - for uid, resource in resources.items(): - # Determine status - try: - is_deployed = resource.is_deployed() - if is_deployed: - status = "🟢 Active" - active_count += 1 - else: - status = "🔴 Inactive" - error_count += 1 - except Exception: - status = "🟡 Unknown" - - # Get resource info - resource_type = resource.__class__.__name__ - - try: - url = resource.url if hasattr(resource, "url") else "N/A" - except Exception: - url = "N/A" - - # Health check (simplified for now) - health = "✓" if status == "🟢 Active" else "✗" - - table.add_row( - uid[:20] + "..." if len(uid) > 20 else uid, - status, - resource_type, - url, - health, - ) - - # Summary - total = len(resources) - idle_count = total - active_count - error_count - summary = f"Total: {total} resources ({active_count} active" - if idle_count > 0: - summary += f", {idle_count} idle" - if error_count > 0: - summary += f", {error_count} error" - summary += ")" - - return Panel(table, subtitle=summary, expand=False) - - -def generate_cleanup_preview(resources: dict) -> Panel: - """Generate a preview of resources to be cleaned.""" - - content = "The following resources will be removed:\n\n" - - for uid, resource in resources.items(): - resource_type = resource.__class__.__name__ - - try: - status = "Active" if resource.is_deployed() else "Inactive" - except Exception: - status = "Unknown" - - try: - url = ( - f" - {resource.url}" - if hasattr(resource, "url") and resource.url != "N/A" - else "" - ) - except Exception: - url = "" - - content += f" • {resource_type} ({status}){url}\n" - - content += "\n⚠️ This action cannot be undone!" - - return Panel(content, title="🧹 Cleanup Preview", expand=False) diff --git a/src/tetra_rp/cli/commands/run.py b/src/tetra_rp/cli/commands/run.py index 7b6f165..42f1044 100644 --- a/src/tetra_rp/cli/commands/run.py +++ b/src/tetra_rp/cli/commands/run.py @@ -1,122 +1,100 @@ -"""Execute main entry point command.""" +"""Run Flash development server.""" -import asyncio +import subprocess import sys from pathlib import Path from typing import Optional + import typer from rich.console import Console -from rich.progress import Progress, SpinnerColumn, TextColumn -from rich.panel import Panel - -from tetra_rp.config import get_paths console = Console() def run_command( - entry_point: Optional[str] = typer.Option( - None, "--entry", "-e", help="Entry point file to execute" - ), - no_deploy: bool = typer.Option( - False, "--no-deploy", help="Skip resource deployment" + host: str = typer.Option("localhost", "--host", help="Host to bind to"), + port: int = typer.Option(8888, "--port", "-p", help="Port to bind to"), + reload: bool = typer.Option( + True, "--reload/--no-reload", help="Enable auto-reload" ), ): - """Execute the main entry point of the app.""" + """Run Flash development server with uvicorn.""" - # Discover entry point if not provided + # Discover entry point + entry_point = discover_entry_point() if not entry_point: - entry_point = discover_entry_point() - if not entry_point: - console.print("No entry point found") - console.print("Specify entry point with --entry or create main.py") - raise typer.Exit(1) - - # Validate entry point exists - entry_path = Path(entry_point) - if not entry_path.exists(): - console.print(f"Entry point not found: {entry_point}") + console.print("[red]Error:[/red] No entry point found") + console.print("Create main.py with a FastAPI app") raise typer.Exit(1) - console.print(f"🚀 Executing entry point: [bold]{entry_point}[/bold]") + # Check if entry point has FastAPI app + app_location = check_fastapi_app(entry_point) + if not app_location: + console.print(f"[red]Error:[/red] No FastAPI app found in {entry_point}") + console.print("Make sure your main.py contains: app = FastAPI()") + raise typer.Exit(1) - # Run the entry point + console.print("[green]Starting Flash Server[/green]") + console.print(f"Entry point: [bold]{app_location}[/bold]") + console.print(f"Server: [bold]http://{host}:{port}[/bold]") + console.print(f"Auto-reload: [bold]{'enabled' if reload else 'disabled'}[/bold]") + console.print("\nPress CTRL+C to stop\n") + + # Build uvicorn command + cmd = [ + sys.executable, + "-m", + "uvicorn", + app_location, + "--host", + host, + "--port", + str(port), + ] + + if reload: + cmd.append("--reload") + + # Run uvicorn try: - asyncio.run(execute_entry_point(entry_path, no_deploy)) + subprocess.run(cmd) except KeyboardInterrupt: - console.print("\nExecution interrupted by user") - raise typer.Exit(1) + console.print("\n[yellow]Server stopped[/yellow]") + raise typer.Exit(0) except Exception as e: - console.print(f"Execution failed: {e}") + console.print(f"[red]Error:[/red] {e}") raise typer.Exit(1) def discover_entry_point() -> Optional[str]: """Discover the main entry point file.""" - # Check common entry point names - candidates = ["main.py", "app.py", "run.py", "__main__.py"] + candidates = ["main.py", "app.py", "server.py"] for candidate in candidates: if Path(candidate).exists(): return candidate - # Check for .tetra/config.json entry point - paths = get_paths() - config_path = paths.config_file - if config_path.exists(): - try: - import json + return None - with open(config_path) as f: - config = json.load(f) - return config.get("entry_point") - except (json.JSONDecodeError, KeyError): - pass - return None +def check_fastapi_app(entry_point: str) -> Optional[str]: + """ + Check if entry point has a FastAPI app and return the app location. + + Returns: + App location in format "module:app" or None + """ + try: + # Read the file + content = Path(entry_point).read_text() + + # Check for FastAPI app + if "app = FastAPI(" in content or "app=FastAPI(" in content: + # Extract module name from file path + module = entry_point.replace(".py", "").replace("/", ".") + return f"{module}:app" + return None -async def execute_entry_point(entry_path: Path, no_deploy: bool = False): - """Execute the entry point with progress tracking.""" - - with Progress( - SpinnerColumn(), - TextColumn("[progress.description]{task.description}"), - console=console, - ) as progress: - if not no_deploy: - # Deployment phase - deploy_task = progress.add_task("Preparing resources...", total=None) - await asyncio.sleep(1) # Mock deployment time - progress.update(deploy_task, description="Resources ready") - progress.stop_task(deploy_task) - - # Execution phase - exec_task = progress.add_task("Executing...", total=None) - - # Execute the Python file - try: - # Import and run the module - spec = __import__("importlib.util").util.spec_from_file_location( - entry_path.stem, entry_path - ) - module = __import__("importlib.util").util.module_from_spec(spec) - - # Add the directory to sys.path so imports work - sys.path.insert(0, str(entry_path.parent)) - - spec.loader.exec_module(module) - - progress.update(exec_task, description="Complete!") - await asyncio.sleep(0.5) # Brief pause to show completion - - except Exception as e: - progress.update(exec_task, description=f"Failed: {e}") - raise - finally: - progress.stop_task(exec_task) - - # Success message - console.print( - Panel("Execution completed successfully", title="Success", expand=False) - ) + except Exception: + return None diff --git a/src/tetra_rp/cli/docs/README.md b/src/tetra_rp/cli/docs/README.md new file mode 100644 index 0000000..9d302d8 --- /dev/null +++ b/src/tetra_rp/cli/docs/README.md @@ -0,0 +1,182 @@ +# Flash CLI Documentation + +Command-line interface for Flash - distributed inference and serving framework. + +## Quick Start + +```bash +# 1. Create new project +flash init my-project +cd my-project + +# 2. Setup environment +conda activate my-project +cp .env.example .env # Add your credentials + +# 3. Local development +flash run + +# 4. Production deployment +flash build --upload +flash deploy +``` + +## Commands + +### flash init + +Create a new Flash project. + +```bash +flash init PROJECT_NAME [OPTIONS] +``` + +**Options:** +- `--no-env`: Skip conda environment creation +- `--force, -f`: Overwrite existing directory + +**Example:** +```bash +flash init my-project +flash init my-project --no-env +``` + +[Full documentation](./flash-init.md) + +--- + +### flash run + +Run Flash development server. + +```bash +flash run [OPTIONS] +``` + +**Options:** +- `--host`: Host to bind to (default: localhost) +- `--port, -p`: Port to bind to (default: 8888) +- `--reload/--no-reload`: Enable auto-reload (default: enabled) + +**Example:** +```bash +flash run +flash run --port 3000 +``` + +[Full documentation](./flash-run.md) + +--- + +### flash build + +Build Flash project for production deployment. + +```bash +flash build [OPTIONS] +``` + +**Options:** +- `--upload/--no-upload`: Upload to S3 (default: enabled) +- `--dir, -d`: Project directory +- `--name, -n`: Project name +- `--workers-only`: Build only GPU workers +- `--flash-server-only`: Build only Flash Server + +**Example:** +```bash +flash build --upload +flash build --no-upload +flash build --workers-only +``` + +[Full documentation](./flash-build.md) + +--- + +### flash deploy + +Deploy Flash project to RunPod. + +```bash +flash deploy [OPTIONS] +``` + +**Options:** +- `--dir, -d`: Project directory (default: current directory) + +**Example:** +```bash +flash deploy +flash deploy --dir ./my-project +``` + +[Full documentation](./flash-deploy.md) + +--- + +## Project Structure + +``` +my-project/ +├── main.py # Flash Server (FastAPI) +├── workers/ # GPU workers +│ ├── __init__.py +│ └── example_worker.py +├── .env.example +├── requirements.txt +└── README.md +``` + +## Environment Variables + +### For Local Development (`flash run`) +```bash +RUNPOD_API_KEY=your_api_key_here +``` + +### For Production Build (`flash build --upload`) +```bash +# S3/Volume Configuration +RUNPOD_S3_ENDPOINT=https://s3api-eu-ro-1.runpod.io +RUNPOD_S3_BUCKET=your-bucket-name +RUNPOD_VOLUME_ENDPOINT=https://s3api-eu-ro-1.runpod.io +RUNPOD_VOLUME_ACCESS_KEY=your_access_key +RUNPOD_VOLUME_SECRET_KEY=your_secret_key +RUNPOD_VOLUME_BUCKET=your-bucket-name + +# Optional +TETRA_GPU_IMAGE=runpod/worker-tetra:latest +``` + +### For Production Deploy (`flash deploy`) +```bash +RUNPOD_API_KEY=your_api_key_here +RUNPOD_VOLUME_ENDPOINT=https://s3api-eu-ro-1.runpod.io +RUNPOD_VOLUME_ACCESS_KEY=your_access_key +RUNPOD_VOLUME_SECRET_KEY=your_secret_key +RUNPOD_VOLUME_BUCKET=your-bucket-name +TETRA_GPU_IMAGE=runpod/worker-tetra:latest +``` + +## Testing Your Server + +```bash +# Health check +curl http://localhost:8888/ + +# Call GPU worker +curl -X POST http://localhost:8888/process \ + -H "Content-Type: application/json" \ + -d '{"data": "test input"}' +``` + +## Getting Help + +```bash +flash --help +flash init --help +flash run --help +flash build --help +flash deploy --help +``` diff --git a/src/tetra_rp/cli/docs/flash-build.md b/src/tetra_rp/cli/docs/flash-build.md new file mode 100644 index 0000000..00db8e0 --- /dev/null +++ b/src/tetra_rp/cli/docs/flash-build.md @@ -0,0 +1,130 @@ +# flash build + +Build Flash project for production deployment. + +## Usage + +```bash +flash build [OPTIONS] +``` + +## Description + +Packages your Flash Server and GPU workers for deployment to RunPod. Creates optimized build artifacts and uploads them to S3-compatible storage. + +## Options + +| Option | Description | Default | +|--------|-------------|---------| +| `--upload/--no-upload` | Upload build artifacts to S3 | `--upload` | +| `--dir, -d` | Project directory | Current directory | +| `--name, -n` | Project name | Auto-detected | +| `--workers-only` | Build only GPU workers | `False` | +| `--flash-server-only` | Build only Flash Server | `False` | + +## Environment Variables + +### Required (when using `--upload`) + +```bash +RUNPOD_S3_ENDPOINT # S3 endpoint URL +RUNPOD_S3_BUCKET # S3 bucket name +RUNPOD_VOLUME_ENDPOINT # Volume endpoint URL +RUNPOD_VOLUME_ACCESS_KEY # S3 access key +RUNPOD_VOLUME_SECRET_KEY # S3 secret key +RUNPOD_VOLUME_BUCKET # Volume bucket name +``` + +### Optional + +```bash +TETRA_GPU_IMAGE # Custom GPU worker image + # Default: runpod/worker-tetra:latest +``` + +## Examples + +### Basic Build + +```bash +# Build and upload to S3 +flash build --upload +``` + +### Build Locally + +```bash +# Build without uploading +flash build --no-upload +``` + +### Build Specific Components + +```bash +# Build only GPU workers +flash build --workers-only + +# Build only Flash Server +flash build --flash-server-only +``` + +### Custom Project Directory + +```bash +# Build from specific directory +flash build --dir ./my-project --upload +``` + +## Output + +After a successful build, you'll see: + +``` +Preparing GPU workers... ✓ 1 GPU worker(s) ready +Preparing Flash Server... ✓ Flash Server ready + +GPU Workers 1 (ExampleWorker) +Flash Server ✓ + +Ready to deploy! +Run: flash deploy + +╭─────────────────────────╮ +│ ✓ Success │ +│ Build complete for test │ +╰─────────────────────────╯ +``` + +Build artifacts are saved to `.tetra/build_artifacts.json`. + +## Next Steps + +After building, deploy your project: + +```bash +flash deploy +``` + +## Troubleshooting + +### "No GPU workers found" + +Make sure you have `@remote` decorated classes in your `workers/` directory: + +```python +from tetra_rp import remote + +@remote() +class MyWorker: + def run(self, input_data): + return {"result": input_data} +``` + +### "Volume not configured" + +Set the required S3 environment variables in your `.env` file or use `--no-upload` for local builds. + +## See Also + +- [flash deploy](./flash-deploy.md) +- [flash init](./flash-init.md) diff --git a/src/tetra_rp/cli/docs/flash-deploy.md b/src/tetra_rp/cli/docs/flash-deploy.md new file mode 100644 index 0000000..d1be44f --- /dev/null +++ b/src/tetra_rp/cli/docs/flash-deploy.md @@ -0,0 +1,157 @@ +# flash deploy + +Deploy Flash project to RunPod production environment. + +## Usage + +```bash +flash deploy [OPTIONS] +``` + +## Description + +Deploys your Flash Server as a CPU endpoint with Load Balancer. GPU workers automatically deploy on first request to `@remote` decorated endpoints. + +## Prerequisites + +### 1. Build Your Project + +```bash +flash build --upload +``` + +### 2. Set Environment Variables + +```bash +RUNPOD_API_KEY=your_api_key_here +RUNPOD_VOLUME_ENDPOINT=https://s3api-eu-ro-1.runpod.io +RUNPOD_VOLUME_ACCESS_KEY=your_access_key +RUNPOD_VOLUME_SECRET_KEY=your_secret_key +RUNPOD_VOLUME_BUCKET=your-bucket-name +``` + +## Options + +| Option | Description | Default | +|--------|-------------|---------| +| `--dir, -d` | Project directory | Current directory | +| `--name, -n` | Project name | Auto-detected | + +## Examples + +### Basic Deployment + +```bash +# Deploy to production +flash deploy +``` + +### Custom Project Directory + +```bash +# Deploy from specific directory +flash deploy --dir ./my-project +``` + +## Output + +After successful deployment: + +``` +Deploying to RunPod... ✓ Deployed + +╭──────────────────────────────────────╮ +│ ✓ Live │ +│ my-project deployed successfully! │ +│ │ +│ URL: https://abc123.api.runpod.ai │ +╰──────────────────────────────────────╯ + +Test your endpoint: +curl https://abc123.api.runpod.ai/ +``` + +## Testing Your Deployment + +### Test Flash Server + +```bash +# Health check +curl https://YOUR_ENDPOINT_ID.api.runpod.ai/health + +# Call your FastAPI endpoint +curl https://YOUR_ENDPOINT_ID.api.runpod.ai/your-endpoint +``` + +### Test GPU Workers + +GPU workers deploy automatically when you call a `@remote` endpoint: + +```python +# In your FastAPI endpoint +result = await MyWorker.run.remote({"input": "data"}) +``` + +First request will be slower (worker deployment), subsequent requests are fast. + +## Managing Your Deployment + +### View Deployment Status + +```bash +# Check your endpoint in RunPod dashboard +# https://www.runpod.io/console/serverless +``` + +### Update Deployment + +```bash +# Rebuild and redeploy +flash build --upload +flash deploy +``` + +### Environment Variables + +Your Flash Server has access to all environment variables from your local `.env` file during deployment. + +## Troubleshooting + +### "No build artifacts found" + +Run `flash build --upload` before deploying: + +```bash +flash build --upload +flash deploy +``` + +### "API key not configured" + +Set your RunPod API key: + +```bash +export RUNPOD_API_KEY=your_api_key_here +``` + +### "Volume not configured" + +Ensure all volume environment variables are set in your `.env` file. + +### GPU Worker Not Starting + +Check your `@remote` decorator: + +```python +from tetra_rp import remote + +@remote() +class MyWorker: + def run(self, input_data): + return {"result": input_data} +``` + +## See Also + +- [flash build](./flash-build.md) +- [flash init](./flash-init.md) diff --git a/src/tetra_rp/cli/docs/flash-init.md b/src/tetra_rp/cli/docs/flash-init.md new file mode 100644 index 0000000..98b8a5f --- /dev/null +++ b/src/tetra_rp/cli/docs/flash-init.md @@ -0,0 +1,64 @@ +# flash init + +Create a new Flash project with Flash Server and GPU workers. + +## Usage + +```bash +flash init PROJECT_NAME [OPTIONS] +``` + +## Arguments + +- `PROJECT_NAME` (required): Name of the project directory to create + +## Options + +- `--no-env`: Skip conda environment creation +- `--force, -f`: Overwrite existing directory + +## Examples + +```bash +# Create project with conda environment +flash init my-project + +# Create without conda environment +flash init my-project --no-env + +# Overwrite existing directory +flash init my-project --force +``` + +## What It Creates + +``` +my-project/ +├── main.py # Flash Server (FastAPI) +├── workers/ # GPU workers +│ ├── __init__.py +│ └── example_worker.py +├── .env.example +├── requirements.txt +├── .gitignore +└── README.md +``` + +## Dependencies Installed + +When conda environment is created: +- `fastapi>=0.104.0` +- `uvicorn[standard]>=0.24.0` +- `python-dotenv>=1.0.0` +- `pydantic>=2.0.0` +- `aiohttp>=3.9.0` +- `tetra-rp>=0.12.0` + +## Next Steps + +```bash +cd my-project +conda activate my-project # if env created +cp .env.example .env # add RUNPOD_API_KEY +flash run +``` diff --git a/src/tetra_rp/cli/docs/flash-run.md b/src/tetra_rp/cli/docs/flash-run.md new file mode 100644 index 0000000..bcdad9d --- /dev/null +++ b/src/tetra_rp/cli/docs/flash-run.md @@ -0,0 +1,54 @@ +# flash run + +Run Flash development server. + +## Usage + +```bash +flash run [OPTIONS] +``` + +## Options + +- `--host`: Host to bind to (default: localhost) +- `--port, -p`: Port to bind to (default: 8888) +- `--reload/--no-reload`: Enable auto-reload (default: enabled) + +## Examples + +```bash +# Start server with defaults +flash run + +# Custom port +flash run --port 3000 + +# Disable auto-reload +flash run --no-reload + +# Custom host and port +flash run --host 0.0.0.0 --port 8000 +``` + +## What It Does + +1. Discovers `main.py` (or `app.py`, `server.py`) +2. Checks for FastAPI app +3. Starts uvicorn server with hot reload +4. GPU workers use LiveServerless (no packaging needed) + +## Testing + +```bash +# Health check +curl http://localhost:8888/ + +# Process endpoint (calls GPU worker) +curl -X POST http://localhost:8888/process \ + -H "Content-Type: application/json" \ + -d '{"data": "test input"}' +``` + +## Requirements + +- `RUNPOD_API_KEY` in `.env` file diff --git a/src/tetra_rp/cli/main.py b/src/tetra_rp/cli/main.py index 22d9791..0211c40 100644 --- a/src/tetra_rp/cli/main.py +++ b/src/tetra_rp/cli/main.py @@ -8,8 +8,8 @@ from .commands import ( init, run, - resource, - deploy, + build, + deploy_flash, ) @@ -26,7 +26,7 @@ def get_version() -> str: # command: flash app = typer.Typer( name="flash", - help="Flash CLI - Distributed inference and serving framework", + help="Runpod Flash CLI - Distributed inference and serving framework", no_args_is_help=True, rich_markup_mode="rich", ) @@ -34,25 +34,8 @@ def get_version() -> str: # command: flash app.command("init")(init.init_command) app.command("run")(run.run_command) -app.command("report")(resource.report_command) -app.command("clean")(resource.clean_command) - -# command: flash deploy -deploy_app = typer.Typer( - name="deploy", - help="Deployment environment management commands", - no_args_is_help=True, -) - -# command: flash deploy * -deploy_app.command("list")(deploy.list_command) -deploy_app.command("new")(deploy.new_command) -deploy_app.command("send")(deploy.send_command) -deploy_app.command("report")(deploy.report_command) -deploy_app.command("rollback")(deploy.rollback_command) -deploy_app.command("remove")(deploy.remove_command) - -app.add_typer(deploy_app, name="deploy") +app.command("build")(build.build_command) +app.command("deploy")(deploy_flash.deploy_flash_command) @app.callback(invoke_without_command=True) @@ -60,15 +43,15 @@ def main( ctx: typer.Context, version: bool = typer.Option(False, "--version", "-v", help="Show version"), ): - """Flash CLI - Distributed inference and serving framework.""" + """Runpod Flash CLI - Distributed inference and serving framework.""" if version: - console.print(f"Flash CLI v{get_version()}") + console.print(f"Runpod Flash CLI v{get_version()}") raise typer.Exit() if ctx.invoked_subcommand is None: console.print( Panel( - "[bold blue]Flash CLI[/bold blue]\n\n" + "[bold blue]Runpod Flash CLI[/bold blue]\n\n" "A framework for distributed inference and serving of ML models.\n\n" "Use [bold]flash --help[/bold] to see available commands.", title="Welcome", diff --git a/src/tetra_rp/cli/templates/advanced/.env.example b/src/tetra_rp/cli/templates/advanced/.env.example deleted file mode 100644 index fec5ae2..0000000 --- a/src/tetra_rp/cli/templates/advanced/.env.example +++ /dev/null @@ -1,6 +0,0 @@ -# RunPod API Configuration -RUNPOD_API_KEY=your_runpod_api_key_here - -# Development settings -DEBUG=false -LOG_LEVEL=INFO diff --git a/src/tetra_rp/cli/templates/advanced/config.json b/src/tetra_rp/cli/templates/advanced/config.json deleted file mode 100644 index 96f3a49..0000000 --- a/src/tetra_rp/cli/templates/advanced/config.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "name": "advanced-project", - "version": "1.0.0", - "entry_point": "main.py", - "template": "advanced", - "dependencies": ["numpy", "pandas"] -} diff --git a/src/tetra_rp/cli/templates/advanced/main.py b/src/tetra_rp/cli/templates/advanced/main.py deleted file mode 100644 index 59cc634..0000000 --- a/src/tetra_rp/cli/templates/advanced/main.py +++ /dev/null @@ -1,58 +0,0 @@ -import asyncio -from dotenv import load_dotenv -from tetra_rp import remote, LiveServerless -from utils import generate_report - -# Load environment variables from .env file -load_dotenv() - -# Configuration for compute workload -compute_config = LiveServerless( - name="advanced_compute", - workersMax=2, - cpu=2, - memory=4096, -) - - -@remote(compute_config) -def analyze_data(data): - """Process and analyze data remotely.""" - import pandas as pd - - # Convert to DataFrame - df = pd.DataFrame(data) - - # Perform analysis - result = { - "mean": df.mean().to_dict(), - "std": df.std().to_dict(), - "count": len(df), - "summary": df.describe().to_dict(), - } - - return result - - -async def main(): - print("🚀 Running advanced Tetra example...") - - # Sample data - sample_data = { - "values": [1, 2, 3, 4, 5, 10, 15, 20], - "categories": ["A", "B", "A", "C", "B", "A", "C", "B"], - } - - # Process remotely - result = await analyze_data(sample_data) - - # Generate report - report = generate_report(result) - print(report) - - -if __name__ == "__main__": - try: - asyncio.run(main()) - except Exception as e: - print(f"An error occurred: {e}") diff --git a/src/tetra_rp/cli/templates/advanced/requirements.txt b/src/tetra_rp/cli/templates/advanced/requirements.txt deleted file mode 100644 index 235e606..0000000 --- a/src/tetra_rp/cli/templates/advanced/requirements.txt +++ /dev/null @@ -1,4 +0,0 @@ -tetra-rp>=0.4.2 -python-dotenv>=1.0.0 -numpy>=1.24.0 -pandas>=2.0.0 diff --git a/src/tetra_rp/cli/templates/advanced/utils.py b/src/tetra_rp/cli/templates/advanced/utils.py deleted file mode 100644 index a5d410e..0000000 --- a/src/tetra_rp/cli/templates/advanced/utils.py +++ /dev/null @@ -1,24 +0,0 @@ -"""Utility functions for advanced example.""" - - -def process_data(data): - """Process raw data before analysis.""" - # Add any preprocessing logic here - return data - - -def generate_report(analysis_result): - """Generate a formatted report from analysis results.""" - report = "\n=== Analysis Report ===\n" - - if "mean" in analysis_result: - report += "\nMean values:\n" - for key, value in analysis_result["mean"].items(): - report += f" {key}: {value:.2f}\n" - - if "count" in analysis_result: - report += f"\nTotal records: {analysis_result['count']}\n" - - report += "\n" + "=" * 25 - - return report diff --git a/src/tetra_rp/cli/templates/basic/.env.example b/src/tetra_rp/cli/templates/basic/.env.example deleted file mode 100644 index fec5ae2..0000000 --- a/src/tetra_rp/cli/templates/basic/.env.example +++ /dev/null @@ -1,6 +0,0 @@ -# RunPod API Configuration -RUNPOD_API_KEY=your_runpod_api_key_here - -# Development settings -DEBUG=false -LOG_LEVEL=INFO diff --git a/src/tetra_rp/cli/templates/basic/config.json b/src/tetra_rp/cli/templates/basic/config.json deleted file mode 100644 index 9a719e3..0000000 --- a/src/tetra_rp/cli/templates/basic/config.json +++ /dev/null @@ -1,6 +0,0 @@ -{ - "name": "basic-project", - "version": "1.0.0", - "entry_point": "main.py", - "template": "basic" -} diff --git a/src/tetra_rp/cli/templates/basic/main.py b/src/tetra_rp/cli/templates/basic/main.py deleted file mode 100644 index 6866af6..0000000 --- a/src/tetra_rp/cli/templates/basic/main.py +++ /dev/null @@ -1,32 +0,0 @@ -import asyncio -from dotenv import load_dotenv -from tetra_rp import remote, LiveServerless - -# Load environment variables from .env file -load_dotenv() - -# Configuration for a simple resource -config = LiveServerless( - name="basic_example", - workersMax=1, -) - - -@remote(config) -def hello_world(): - """Simple remote function example.""" - print("Hello from the remote function!") - return "Hello, World!" - - -async def main(): - print("🚀 Running basic Tetra example...") - result = await hello_world() - print(f"Result: {result}") - - -if __name__ == "__main__": - try: - asyncio.run(main()) - except Exception as e: - print(f"An error occurred: {e}") diff --git a/src/tetra_rp/cli/templates/basic/requirements.txt b/src/tetra_rp/cli/templates/basic/requirements.txt deleted file mode 100644 index d8d6d7a..0000000 --- a/src/tetra_rp/cli/templates/basic/requirements.txt +++ /dev/null @@ -1,2 +0,0 @@ -tetra-rp>=0.4.2 -python-dotenv>=1.0.0 diff --git a/src/tetra_rp/cli/templates/gpu-compute/.env.example b/src/tetra_rp/cli/templates/gpu-compute/.env.example deleted file mode 100644 index fec5ae2..0000000 --- a/src/tetra_rp/cli/templates/gpu-compute/.env.example +++ /dev/null @@ -1,6 +0,0 @@ -# RunPod API Configuration -RUNPOD_API_KEY=your_runpod_api_key_here - -# Development settings -DEBUG=false -LOG_LEVEL=INFO diff --git a/src/tetra_rp/cli/templates/gpu-compute/config.json b/src/tetra_rp/cli/templates/gpu-compute/config.json deleted file mode 100644 index 9a2130a..0000000 --- a/src/tetra_rp/cli/templates/gpu-compute/config.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "name": "gpu-project", - "version": "1.0.0", - "entry_point": "main.py", - "template": "gpu-compute", - "gpu_required": true -} diff --git a/src/tetra_rp/cli/templates/gpu-compute/main.py b/src/tetra_rp/cli/templates/gpu-compute/main.py deleted file mode 100644 index 9a2295a..0000000 --- a/src/tetra_rp/cli/templates/gpu-compute/main.py +++ /dev/null @@ -1,64 +0,0 @@ -import asyncio -from dotenv import load_dotenv -from tetra_rp import remote, LiveServerless - -# Load environment variables from .env file -load_dotenv() - -# Configuration for GPU workload -gpu_config = LiveServerless( - name="gpu_compute", - workersMax=1, - gpu=1, - gpuType="A40", - cpu=4, - memory=8192, -) - - -@remote(gpu_config) -def gpu_computation(): - """GPU-accelerated computation example.""" - try: - import torch - - # Check GPU availability - if torch.cuda.is_available(): - device = torch.cuda.get_device_name(0) - print(f"Using GPU: {device}") - - # Simple GPU computation - x = torch.randn(1000, 1000).cuda() - y = torch.randn(1000, 1000).cuda() - result = torch.mm(x, y) - - return { - "device": device, - "matrix_shape": result.shape, - "result_mean": result.mean().item(), - "computation": "Matrix multiplication completed on GPU", - } - else: - return {"error": "GPU not available"} - - except ImportError: - return {"error": "PyTorch not available"} - - -async def main(): - print("🚀 Running GPU compute example...") - result = await gpu_computation() - - if "error" in result: - print(f"{result['error']}") - else: - print("GPU computation completed!") - print(f"Device: {result['device']}") - print(f"Result: {result['computation']}") - - -if __name__ == "__main__": - try: - asyncio.run(main()) - except Exception as e: - print(f"An error occurred: {e}") diff --git a/src/tetra_rp/cli/templates/gpu-compute/requirements.txt b/src/tetra_rp/cli/templates/gpu-compute/requirements.txt deleted file mode 100644 index 0911b29..0000000 --- a/src/tetra_rp/cli/templates/gpu-compute/requirements.txt +++ /dev/null @@ -1,3 +0,0 @@ -tetra-rp>=0.4.2 -python-dotenv>=1.0.0 -torch>=2.0.0 diff --git a/src/tetra_rp/cli/templates/web-api/.env.example b/src/tetra_rp/cli/templates/web-api/.env.example deleted file mode 100644 index fec5ae2..0000000 --- a/src/tetra_rp/cli/templates/web-api/.env.example +++ /dev/null @@ -1,6 +0,0 @@ -# RunPod API Configuration -RUNPOD_API_KEY=your_runpod_api_key_here - -# Development settings -DEBUG=false -LOG_LEVEL=INFO diff --git a/src/tetra_rp/cli/templates/web-api/api.py b/src/tetra_rp/cli/templates/web-api/api.py deleted file mode 100644 index 95f06b3..0000000 --- a/src/tetra_rp/cli/templates/web-api/api.py +++ /dev/null @@ -1,67 +0,0 @@ -"""FastAPI application with example endpoints.""" - -from fastapi import FastAPI, HTTPException -from pydantic import BaseModel - - -def create_api_app() -> FastAPI: - """Create and configure FastAPI application.""" - - app = FastAPI( - title="Tetra API Service", - description="Example web API deployed with Tetra", - version="1.0.0", - ) - - # Example models - class ComputeRequest(BaseModel): - operation: str - values: list[float] - - class ComputeResponse(BaseModel): - result: float - operation: str - input_count: int - - @app.get("/") - async def root(): - """Root endpoint.""" - return {"message": "Tetra API Service", "status": "running"} - - @app.get("/health") - async def health_check(): - """Health check endpoint.""" - return {"status": "healthy", "service": "tetra-rp-api"} - - @app.post("/compute", response_model=ComputeResponse) - async def compute(request: ComputeRequest): - """Perform computation on provided values.""" - - if not request.values: - raise HTTPException(status_code=400, detail="No values provided") - - try: - if request.operation == "sum": - result = sum(request.values) - elif request.operation == "mean": - result = sum(request.values) / len(request.values) - elif request.operation == "max": - result = max(request.values) - elif request.operation == "min": - result = min(request.values) - else: - raise HTTPException( - status_code=400, - detail=f"Unsupported operation: {request.operation}", - ) - - return ComputeResponse( - result=result, - operation=request.operation, - input_count=len(request.values), - ) - - except Exception as e: - raise HTTPException(status_code=500, detail=str(e)) - - return app diff --git a/src/tetra_rp/cli/templates/web-api/config.json b/src/tetra_rp/cli/templates/web-api/config.json deleted file mode 100644 index d0d6c30..0000000 --- a/src/tetra_rp/cli/templates/web-api/config.json +++ /dev/null @@ -1,7 +0,0 @@ -{ - "name": "api-project", - "version": "1.0.0", - "entry_point": "main.py", - "template": "web-api", - "service_type": "api" -} diff --git a/src/tetra_rp/cli/templates/web-api/main.py b/src/tetra_rp/cli/templates/web-api/main.py deleted file mode 100644 index 91d8a1d..0000000 --- a/src/tetra_rp/cli/templates/web-api/main.py +++ /dev/null @@ -1,42 +0,0 @@ -import asyncio -from dotenv import load_dotenv -from tetra_rp import remote, LiveServerless -from api import create_api_app - -# Load environment variables from .env file -load_dotenv() - -# Configuration for web API -api_config = LiveServerless( - name="web_api_service", - workersMax=3, - cpu=2, - memory=2048, - ports=[8000], -) - - -@remote(api_config) -def run_api_server(): - """Run FastAPI web service.""" - import uvicorn - - app = create_api_app() - - # Run the server - uvicorn.run(app, host="0.0.0.0", port=8000, log_level="info") - - return "API server started" - - -async def main(): - print("🚀 Starting web API service...") - result = await run_api_server() - print(f"Result: {result}") - - -if __name__ == "__main__": - try: - asyncio.run(main()) - except Exception as e: - print(f"An error occurred: {e}") diff --git a/src/tetra_rp/cli/templates/web-api/requirements.txt b/src/tetra_rp/cli/templates/web-api/requirements.txt deleted file mode 100644 index 0b2299c..0000000 --- a/src/tetra_rp/cli/templates/web-api/requirements.txt +++ /dev/null @@ -1,5 +0,0 @@ -tetra-rp>=0.4.2 -python-dotenv>=1.0.0 -fastapi>=0.100.0 -uvicorn>=0.23.0 -pydantic>=2.0.0 diff --git a/src/tetra_rp/cli/utils/conda.py b/src/tetra_rp/cli/utils/conda.py new file mode 100644 index 0000000..8621376 --- /dev/null +++ b/src/tetra_rp/cli/utils/conda.py @@ -0,0 +1,127 @@ +"""Conda environment management utilities.""" + +import subprocess +from typing import List, Tuple +from rich.console import Console + +console = Console() + + +def check_conda_available() -> bool: + """Check if conda is available on the system.""" + try: + result = subprocess.run( + ["conda", "--version"], + capture_output=True, + text=True, + timeout=5, + ) + return result.returncode == 0 + except (subprocess.SubprocessError, FileNotFoundError): + return False + + +def create_conda_environment( + env_name: str, python_version: str = "3.11" +) -> Tuple[bool, str]: + """ + Create a new conda environment. + + Args: + env_name: Name of the conda environment + python_version: Python version to use + + Returns: + Tuple of (success, message) + """ + try: + console.print(f"Creating conda environment: {env_name}") + + result = subprocess.run( + ["conda", "create", "-n", env_name, f"python={python_version}", "-y"], + capture_output=True, + text=True, + timeout=300, # 5 minutes timeout + ) + + if result.returncode == 0: + return True, f"Conda environment '{env_name}' created successfully" + else: + return False, f"Failed to create environment: {result.stderr}" + + except subprocess.TimeoutExpired: + return False, "Environment creation timed out" + except Exception as e: + return False, f"Error creating environment: {e}" + + +def install_packages_in_env( + env_name: str, packages: List[str], use_pip: bool = True +) -> Tuple[bool, str]: + """ + Install packages in a conda environment. + + Args: + env_name: Name of the conda environment + packages: List of packages to install + use_pip: If True, use pip install; otherwise use conda install + + Returns: + Tuple of (success, message) + """ + try: + console.print(f"Installing packages: {', '.join(packages)}") + + if use_pip: + # Use conda run to execute pip in the environment + cmd = [ + "conda", + "run", + "-n", + env_name, + "pip", + "install", + ] + packages + else: + cmd = ["conda", "install", "-n", env_name, "-y"] + packages + + result = subprocess.run( + cmd, + capture_output=True, + text=True, + timeout=600, # 10 minutes timeout + ) + + if result.returncode == 0: + return True, "Packages installed successfully" + else: + return False, f"Failed to install packages: {result.stderr}" + + except subprocess.TimeoutExpired: + return False, "Package installation timed out" + except Exception as e: + return False, f"Error installing packages: {e}" + + +def environment_exists(env_name: str) -> bool: + """Check if a conda environment exists.""" + try: + result = subprocess.run( + ["conda", "env", "list"], + capture_output=True, + text=True, + timeout=10, + ) + + if result.returncode == 0: + # Check if environment name appears in the output + return env_name in result.stdout + return False + + except Exception: + return False + + +def get_activation_command(env_name: str) -> str: + """Get the command to activate the conda environment.""" + return f"conda activate {env_name}" diff --git a/src/tetra_rp/cli/utils/skeleton.py b/src/tetra_rp/cli/utils/skeleton.py index 6dd8e37..a6ea091 100644 --- a/src/tetra_rp/cli/utils/skeleton.py +++ b/src/tetra_rp/cli/utils/skeleton.py @@ -1,101 +1,293 @@ """Project skeleton creation utilities.""" from pathlib import Path -from typing import Dict, List, Any +from typing import List -from tetra_rp.config import get_paths +# Template files content +MAIN_PY_TEMPLATE = '''""" +Flash Application - Flash Server +This is the main entry point for your Flash application. +It runs a FastAPI server that coordinates GPU workers. +""" -def get_template_directory() -> Path: - """Get the path to the templates directory.""" - return Path(__file__).parent.parent / "templates" +import asyncio +from fastapi import FastAPI +from pydantic import BaseModel +from dotenv import load_dotenv +from workers import ExampleWorker -def load_template_files(template_name: str) -> Dict[str, Any]: - """Load template files from filesystem.""" - template_dir = get_template_directory() / template_name +# Load environment variables +load_dotenv() - if not template_dir.exists(): - raise ValueError(f"Template '{template_name}' not found in {template_dir}") +# Create FastAPI app +app = FastAPI(title="Flash Application") - files = {} - # Load all files from the template directory - for file_path in template_dir.iterdir(): - if file_path.is_file(): - relative_path = file_path.name +class ProcessRequest(BaseModel): + """Request model for processing endpoint.""" + data: str - # Special handling for config.json - return as callable that generates tetra config - if file_path.name == "config.json": - config_content = file_path.read_text() - files[".tetra/config.json"] = lambda content=config_content: content - else: - files[relative_path] = file_path.read_text() - return files +@app.get("/") +def home(): + """Health check endpoint.""" + return {"status": "ok", "message": "Flash application running"} -def get_available_templates() -> Dict[str, Dict[str, Any]]: - """Get available project templates from filesystem.""" - template_dir = get_template_directory() - templates = {} +@app.get("/health") +def health(): + """Health check endpoint.""" + return {"healthy": True} - # Template descriptions - descriptions = { - "basic": "Simple remote function example", - "advanced": "Multi-function project with dependencies", - "gpu-compute": "GPU-optimized compute workload", - "web-api": "FastAPI web service deployment", + +@app.post("/process") +async def process(request: ProcessRequest): + """ + Process data using GPU worker. + + Example request: + { + "data": "test input" } + """ + # Instantiate worker + worker = ExampleWorker() + + # Call worker's process method + result = await worker.process({"input": request.data}) + + return result + + +if __name__ == "__main__": + import uvicorn + uvicorn.run(app, host="localhost", port=8888) +''' + +WORKER_EXAMPLE_PY_TEMPLATE = '''""" +Example GPU Worker + +This is an example of a GPU worker class that can be deployed +to RunPod serverless endpoints. +""" + +from tetra_rp import remote, LiveServerless + + +# Configure GPU resource +config = LiveServerless( + name="example_worker", + workersMax=3, +) + + +@remote(config) +class ExampleWorker: + """Example GPU worker for processing tasks.""" + + def __init__(self): + """Initialize the worker.""" + print("ExampleWorker initialized") + + def process(self, input_data: dict) -> dict: + """ + Process input data and return result. + + Args: + input_data: Dictionary with input parameters + + Returns: + Dictionary with processing results + """ + # Your GPU processing logic here + result = { + "status": "success", + "input": input_data, + "output": f"Processed: {input_data}" + } + + return result +''' + +WORKERS_INIT_PY_TEMPLATE = '''"""GPU Workers package.""" + +from .example_worker import ExampleWorker + +__all__ = ["ExampleWorker"] +''' + +ENV_EXAMPLE_TEMPLATE = """# RunPod API Configuration +RUNPOD_API_KEY=your_runpod_api_key_here + +# Development settings +DEBUG=false +LOG_LEVEL=INFO +""" + +REQUIREMENTS_TXT_TEMPLATE = """# Core dependencies for Flash +tetra-rp>=0.12.0 +fastapi>=0.104.0 +uvicorn[standard]>=0.24.0 +python-dotenv>=1.0.0 +pydantic>=2.0.0 +aiohttp>=3.9.0 +""" + +GITIGNORE_TEMPLATE = """# Python +__pycache__/ +*.py[cod] +*$py.class +*.so +.Python +env/ +venv/ +ENV/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +*.egg-info/ +.installed.cfg +*.egg + +# Environment +.env +.venv + +# IDE +.vscode/ +.idea/ +*.swp +*.swo +*~ - # Discover templates from filesystem - for template_path in template_dir.iterdir(): - if template_path.is_dir(): - template_name = template_path.name - try: - templates[template_name] = { - "description": descriptions.get( - template_name, f"{template_name} template" - ), - "files": load_template_files(template_name), - } - except Exception as e: - print(f"Warning: Failed to load template '{template_name}': {e}") - - return templates - - -def create_project_skeleton( - template_name: str, template_info: Dict[str, Any], force: bool = False -) -> List[str]: - """Create project skeleton from template.""" +# Tetra +.tetra/ + +# OS +.DS_Store +Thumbs.db +""" + +README_TEMPLATE = """# {{project_name}} + +Flash application with Flash Server and GPU workers. + +## Setup + +1. Activate the conda environment: +```bash +conda activate {{project_name}} +``` + +2. Configure your RunPod API key: +```bash +cp .env.example .env +# Edit .env and add your RUNPOD_API_KEY +``` + +3. Run the development server: +```bash +flash run +``` + +## Project Structure + +``` +{{project_name}}/ +├── main.py # Flash Server (FastAPI) +├── workers/ # GPU workers +│ ├── __init__.py +│ └── example_worker.py +├── .env.example # Environment variables template +├── requirements.txt # Python dependencies +└── README.md # This file +``` + +## Development + +The Flash Server runs on `localhost:8888` and coordinates GPU workers. + +### Adding New Workers + +1. Create a new file in `workers/` directory +2. Define a class with `@remote` decorator +3. Import it in `workers/__init__.py` +4. Use it in `main.py` + +Example: +```python +from tetra_rp import remote, LiveServerless + +config = LiveServerless(name="my_worker", workersMax=3) + +@remote(config) +class MyWorker: + def process(self, data): + return {{"result": f"Processed: {{data}}"}} +``` + +## Deployment + +Deploy to production: +```bash +flash deploy send production +``` + +## Documentation + +- [Flash CLI Docs](./docs/) +- [Tetra Documentation](https://docs.tetra.dev) +""" + + +def create_project_skeleton(project_dir: Path, force: bool = False) -> List[str]: + """ + Create Flash project skeleton. + + Args: + project_dir: Project directory path + force: Overwrite existing files + + Returns: + List of created file paths + """ created_files = [] - # Create .tetra directory using centralized config - paths = get_paths() - paths.ensure_tetra_dir() + # Define project structure + files_to_create = { + "main.py": MAIN_PY_TEMPLATE, + "workers/__init__.py": WORKERS_INIT_PY_TEMPLATE, + "workers/example_worker.py": WORKER_EXAMPLE_PY_TEMPLATE, + ".env.example": ENV_EXAMPLE_TEMPLATE, + "requirements.txt": REQUIREMENTS_TXT_TEMPLATE, + ".gitignore": GITIGNORE_TEMPLATE, + "README.md": README_TEMPLATE.format(project_name=project_dir.name), + } - # Create files from template - for file_path, content in template_info["files"].items(): - path = Path(file_path) + # Create files + for relative_path, content in files_to_create.items(): + file_path = project_dir / relative_path # Create parent directories if needed - path.parent.mkdir(parents=True, exist_ok=True) + file_path.parent.mkdir(parents=True, exist_ok=True) # Skip existing files unless force is True - if path.exists() and not force: + if file_path.exists() and not force: continue - # Get content (could be string or callable) - if callable(content): - file_content = content() - else: - file_content = content - # Write file - with open(path, "w") as f: - f.write(file_content) - - created_files.append(str(path)) + file_path.write_text(content) + created_files.append(str(file_path.relative_to(project_dir))) return created_files diff --git a/src/tetra_rp/client.py b/src/tetra_rp/client.py index 3cae589..5f6dc1e 100644 --- a/src/tetra_rp/client.py +++ b/src/tetra_rp/client.py @@ -1,3 +1,4 @@ +import os import inspect import logging from functools import wraps @@ -5,6 +6,7 @@ from .core.resources import ResourceManager, ServerlessResource from .execute_class import create_remote_class +from .prod_config import apply_production_config from .stubs import stub_resource log = logging.getLogger(__name__) @@ -15,44 +17,76 @@ def remote( dependencies: Optional[List[str]] = None, system_dependencies: Optional[List[str]] = None, accelerate_downloads: bool = True, + local: bool = False, **extra, ): """ Decorator to enable dynamic resource provisioning and dependency management for serverless functions. This decorator allows a function to be executed in a remote serverless environment, with support for - dynamic resource provisioning and installation of required dependencies. + dynamic resource provisioning and installation of required dependencies. It can also bypass remote + execution entirely for local testing. Args: resource_config (ServerlessResource): Configuration object specifying the serverless resource - to be provisioned or used. + to be provisioned or used. Not used when local=True. dependencies (List[str], optional): A list of pip package names to be installed in the remote - environment before executing the function. Defaults to None. + environment before executing the function. Not used when local=True. Defaults to None. system_dependencies (List[str], optional): A list of system packages to be installed in the remote - environment before executing the function. Defaults to None. + environment before executing the function. Not used when local=True. Defaults to None. accelerate_downloads (bool, optional): Enable download acceleration for dependencies and models. - Defaults to True. + Only applies to remote execution. Defaults to True. + local (bool, optional): Execute function/class locally instead of provisioning remote servers. + Returns the unwrapped function/class for direct local execution. Users must ensure all required + dependencies are already installed in their local environment. Defaults to False. extra (dict, optional): Additional parameters for the execution of the resource. Defaults to an empty dict. Returns: - Callable: A decorator that wraps the target function, enabling remote execution with the - specified resource configuration and dependencies. + Callable: A decorator that wraps the target function, enabling remote execution with the specified + resource configuration and dependencies, or returns the unwrapped function/class for local execution. Example: ```python + # Remote execution (production) @remote( resource_config=my_resource_config, dependencies=["numpy", "pandas"], - accelerate_downloads=True, + accelerate_downloads=True ) async def my_function(data): # Function logic here pass + + # Local execution (testing/development) + # Note: Ensure numpy and pandas are installed locally first + @remote( + resource_config=my_resource_config, + dependencies=["numpy", "pandas"], # Only used for remote execution + local=True, + ) + async def my_test_function(data): + # Runs locally - dependencies must be pre-installed + pass ``` """ def decorator(func_or_class): + if os.getenv("RUNPOD_POD_ID") or os.getenv("RUNPOD_ENDPOINT_ID"): + # Worker mode when running on RunPod platform + return func_or_class + + # Local execution mode - execute without provisioning remote servers + if local: + return func_or_class + + # Remote execution mode if inspect.isclass(func_or_class): + # Apply production configuration if TETRA_PROD_MODE is enabled + try: + apply_production_config(resource_config, func_or_class.__name__) + except Exception as e: + log.warning(f"Failed to apply production config: {e}") + # Handle class decoration return create_remote_class( func_or_class, @@ -63,7 +97,7 @@ def decorator(func_or_class): extra, ) else: - # Handle function decoration (unchanged) + # Handle function decoration @wraps(func_or_class) async def wrapper(*args, **kwargs): resource_manager = ResourceManager() diff --git a/src/tetra_rp/core/resources/__init__.py b/src/tetra_rp/core/resources/__init__.py index 10aa5bc..682c190 100644 --- a/src/tetra_rp/core/resources/__init__.py +++ b/src/tetra_rp/core/resources/__init__.py @@ -9,6 +9,7 @@ ServerlessEndpoint, JobOutput, CudaVersion, + ServerlessType, ) from .serverless_cpu import CpuServerlessEndpoint from .template import PodTemplate @@ -32,6 +33,7 @@ "ResourceManager", "ServerlessResource", "ServerlessEndpoint", + "ServerlessType", "PodTemplate", "NetworkVolume", ] diff --git a/src/tetra_rp/core/resources/cpu.py b/src/tetra_rp/core/resources/cpu.py index e03487b..0bbe288 100644 --- a/src/tetra_rp/core/resources/cpu.py +++ b/src/tetra_rp/core/resources/cpu.py @@ -16,6 +16,9 @@ class CpuInstanceType(str, Enum): - cpu5g: Not available """ + ANY = "any" + """Any CPU""" + # 3rd Generation General Purpose (RAM multiplier: 4.0) CPU3G_1_4 = "cpu3g-1-4" @@ -58,6 +61,11 @@ class CpuInstanceType(str, Enum): CPU5C_8_16 = "cpu5c-8-16" """8 vCPU, 16GB RAM, max 120GB container disk""" + @classmethod + def all(cls) -> List["CpuInstanceType"]: + """Returns all CPU Instance Types.""" + return [c for c in cls if c != cls.ANY] + def calculate_max_disk_size(instance_type: CpuInstanceType) -> int: """ @@ -104,6 +112,7 @@ def calculate_max_disk_size(instance_type: CpuInstanceType) -> int: CPU_INSTANCE_DISK_LIMITS = { instance_type: calculate_max_disk_size(instance_type) for instance_type in CpuInstanceType + if instance_type != CpuInstanceType.ANY } diff --git a/src/tetra_rp/core/resources/live_serverless.py b/src/tetra_rp/core/resources/live_serverless.py index 193810b..2a4cfda 100644 --- a/src/tetra_rp/core/resources/live_serverless.py +++ b/src/tetra_rp/core/resources/live_serverless.py @@ -23,12 +23,12 @@ def _live_image(self) -> str: @property def imageName(self): - # Lock imageName to specific image + """Return the locked live image.""" return self._live_image @imageName.setter def imageName(self, value): - # Prevent manual setting of imageName + """Setter is a no-op - image is locked to live image.""" pass @@ -43,7 +43,11 @@ def _live_image(self) -> str: @classmethod def set_live_serverless_template(cls, data: dict): """Set default GPU image for Live Serverless.""" - data["imageName"] = TETRA_GPU_IMAGE + # Only set default if imageName is not provided + # If custom imageName IS provided, let it through (for production mode) + if "imageName" not in data or not data["imageName"]: + data["imageName"] = TETRA_GPU_IMAGE + # Otherwise keep the custom value - it will be used to create the template return data @@ -58,5 +62,8 @@ def _live_image(self) -> str: @classmethod def set_live_serverless_template(cls, data: dict): """Set default CPU image for Live Serverless.""" - data["imageName"] = TETRA_CPU_IMAGE + # Only set default if imageName is not provided + if "imageName" not in data or not data["imageName"]: + data["imageName"] = TETRA_CPU_IMAGE + # Custom imageName will be stored in template during model construction return data diff --git a/src/tetra_rp/core/resources/serverless.py b/src/tetra_rp/core/resources/serverless.py index 8409f46..186d36c 100644 --- a/src/tetra_rp/core/resources/serverless.py +++ b/src/tetra_rp/core/resources/serverless.py @@ -43,6 +43,13 @@ class ServerlessScalerType(Enum): REQUEST_COUNT = "REQUEST_COUNT" +class ServerlessType(Enum): + """Serverless endpoint type.""" + + QB = "QB" # Queue-Based (default) + LB = "LB" # Load Balancer + + class CudaVersion(Enum): V11_8 = "11.8" V12_0 = "12.0" @@ -91,6 +98,7 @@ class ServerlessResource(DeployableResource): scalerType: Optional[ServerlessScalerType] = ServerlessScalerType.QUEUE_DELAY scalerValue: Optional[int] = 4 templateId: Optional[str] = None + type: Optional[ServerlessType] = ServerlessType.QB workersMax: Optional[int] = 3 workersMin: Optional[int] = 0 workersPFBTarget: Optional[int] = None @@ -132,6 +140,11 @@ def serialize_scaler_type( """Convert ServerlessScalerType enum to string.""" return value.value if value is not None else None + @field_serializer("type") + def serialize_type(self, value: Optional[ServerlessType]) -> Optional[str]: + """Convert ServerlessType enum to string.""" + return value.value if value is not None else None + @field_validator("gpus") @classmethod def validate_gpus(cls, value: List[GpuGroup]) -> List[GpuGroup]: diff --git a/src/tetra_rp/core/resources/serverless_cpu.py b/src/tetra_rp/core/resources/serverless_cpu.py index dfe8535..25d8af7 100644 --- a/src/tetra_rp/core/resources/serverless_cpu.py +++ b/src/tetra_rp/core/resources/serverless_cpu.py @@ -6,7 +6,7 @@ from typing import List, Optional -from pydantic import field_serializer, model_validator +from pydantic import field_serializer, model_validator, field_validator from .cpu import ( CpuInstanceType, @@ -105,7 +105,7 @@ class CpuServerlessEndpoint(CpuEndpointMixin, ServerlessEndpoint): Represents a CPU-only serverless endpoint distinct from a live serverless. """ - instanceIds: Optional[List[CpuInstanceType]] = [CpuInstanceType.CPU3G_2_8] + instanceIds: Optional[List[CpuInstanceType]] = [CpuInstanceType.ANY] def _create_new_template(self) -> PodTemplate: """Create a new PodTemplate with CPU-appropriate disk sizing.""" @@ -133,6 +133,14 @@ def _configure_existing_template(self) -> None: # Apply CPU-specific disk sizing self._apply_cpu_disk_sizing(self.template) + @field_validator("instanceIds") + @classmethod + def validate_cpus(cls, value: List[CpuInstanceType]) -> List[CpuInstanceType]: + """Expand ANY to all GPU groups""" + if value == [CpuInstanceType.ANY]: + return CpuInstanceType.all() + return value + @model_validator(mode="after") def set_serverless_template(self): # Sync CPU-specific fields first diff --git a/src/tetra_rp/execute_class.py b/src/tetra_rp/execute_class.py index 70db2fa..e21df5f 100644 --- a/src/tetra_rp/execute_class.py +++ b/src/tetra_rp/execute_class.py @@ -293,10 +293,23 @@ async def method_proxy(*args, **kwargs): for k, v in self._constructor_kwargs.items() } + # Check if we're in baked mode + env_value = None + if ( + hasattr(self._stub, "server") + and hasattr(self._stub.server, "env") + and self._stub.server.env is not None + ): + env = self._stub.server.env + if isinstance(env, dict): + env_value = env.get("TETRA_BAKED_MODE", "") + + is_baked = env_value and env_value.lower() in ("true", "1", "yes") + request = FunctionRequest( execution_type="class", class_name=self._class_type.__name__, - class_code=cached_data["class_code"], + class_code=None if is_baked else cached_data["class_code"], method_name=name, args=method_args, kwargs=method_kwargs, @@ -309,6 +322,7 @@ async def method_proxy(*args, **kwargs): create_new_instance=not hasattr( self, "_stub" ), # Create new only on first call + baked=is_baked, ) # Execute via stub diff --git a/src/tetra_rp/prod_builder.py.bak b/src/tetra_rp/prod_builder.py.bak new file mode 100644 index 0000000..0793f0a --- /dev/null +++ b/src/tetra_rp/prod_builder.py.bak @@ -0,0 +1,278 @@ +""" +Automatic production image builder for @remote decorated code. + +When mode="prod", this module: +1. Extracts the decorated function/class code +2. Generates a Dockerfile extending the worker base image +3. Builds the Docker image (for linux/amd64 platform) +4. Pushes to Docker registry +5. Updates ServerlessResource to use the new image with TETRA_BAKED_MODE=true +6. Deploys to RunPod when function is first called +""" + +import inspect +import json +import logging +import os +import subprocess +import tempfile +from pathlib import Path +from typing import Optional, List +import hashlib + +log = logging.getLogger(__name__) + + +def get_docker_registry() -> Optional[str]: + """ + Get Docker registry prefix from environment variable. + + Returns registry prefix like 'myregistry/' or 'docker.io/myuser/' + If not set, returns None (images stay local). + + Set TETRA_DOCKER_REGISTRY env var to enable automatic push. + Examples: + TETRA_DOCKER_REGISTRY=docker.io/myuser + TETRA_DOCKER_REGISTRY=ghcr.io/myorg + """ + registry = os.getenv('TETRA_DOCKER_REGISTRY') + if registry: + # Ensure it ends with / + return registry if registry.endswith('/') else f"{registry}/" + return None + + +def build_and_deploy_prod_image( + func_or_class, + resource_config, + dependencies: Optional[List[str]], + system_dependencies: Optional[List[str]], +): + """ + Build production Docker image and configure resource to use it. + + This is called automatically when mode="prod" is set on @remote decorator. + """ + callable_name = func_or_class.__name__ + + log.info(f"🔨 Building production image for {callable_name}") + + # Get worker base image from resource config + worker_base_image = getattr(resource_config, 'imageName', 'mwiki/tetra-worker:v1') + + # Extract source code + source_code = inspect.getsource(func_or_class) + callable_type = "class" if inspect.isclass(func_or_class) else "function" + + # Generate image name and tag from callable name + code hash + code_hash = hashlib.sha256(source_code.encode()).hexdigest()[:8] + image_name = f"{callable_name.lower().replace('_', '-')}" + image_tag = f"prod-{code_hash}" + + # Get registry prefix (if configured) + registry = get_docker_registry() + + # Local image name (for building) + local_image = f"{image_name}:{image_tag}" + + # Full image name with registry (for deployment) + if registry: + full_image = f"{registry}{image_name}:{image_tag}" + else: + full_image = local_image + + log.info(f" Local image: {local_image}") + if registry: + log.info(f" Registry image: {full_image}") + log.info(f" Base: {worker_base_image}") + + # Create temporary build directory + with tempfile.TemporaryDirectory() as tmpdir: + build_dir = Path(tmpdir) + baked_code_dir = build_dir / "baked_code" + baked_code_dir.mkdir() + + # Write the callable code to a module file + module_file = baked_code_dir / f"{callable_name}.py" + + # Remove @remote decorator from source code (simple approach) + cleaned_code = remove_remote_decorator(source_code) + + # Add necessary imports at the top if not present + if "import" not in cleaned_code[:100]: + cleaned_code = "# Auto-generated baked code\n" + cleaned_code + + module_file.write_text(cleaned_code) + + # Create __init__.py + init_file = baked_code_dir / "__init__.py" + init_file.write_text("") + + # Create registry.json + registry = { + callable_name: { + "module": f"baked_code.{callable_name}", + "type": callable_type, + } + } + registry_file = baked_code_dir / "registry.json" + registry_file.write_text(json.dumps(registry, indent=2)) + + # Generate Dockerfile + dockerfile = generate_dockerfile( + worker_base_image, + dependencies or [], + system_dependencies or [], + callable_name, + ) + dockerfile_path = build_dir / "Dockerfile" + dockerfile_path.write_text(dockerfile) + + log.info(f" Build dir: {build_dir}") + + # Build Docker image for linux/amd64 platform + log.info(f" Building Docker image (linux/amd64)...") + try: + # Build with local tag first + subprocess.run( + [ + "docker", "build", + "--platform", "linux/amd64", + "-t", local_image, + "-f", "Dockerfile", + "." + ], + cwd=build_dir, + capture_output=True, + text=True, + check=True, + ) + log.info(f" ✅ Image built successfully") + except subprocess.CalledProcessError as e: + log.error(f" ❌ Docker build failed:") + log.error(e.stderr) + raise RuntimeError(f"Failed to build production image: {e.stderr}") + + # Check if push should be skipped (for fast local testing) + skip_push = os.getenv('TETRA_SKIP_PUSH', 'false').lower() in ('true', '1', 'yes') + + # Push to registry if configured + if registry and not skip_push: + log.info(f" 📤 Pushing to registry: {full_image}") + log.info(f" This may take several minutes for large base images...") + try: + # Tag for registry + subprocess.run( + ["docker", "tag", local_image, full_image], + check=True, + ) + + # Push to registry (show progress) + subprocess.run( + ["docker", "push", full_image], + check=True, + ) + log.info(f" ✅ Image pushed successfully") + except subprocess.CalledProcessError as e: + log.error(f" ❌ Docker push failed") + raise RuntimeError(f"Failed to push production image") + elif registry and skip_push: + log.warning(f" ⚠️ TETRA_SKIP_PUSH=true - skipping push to registry") + log.warning(f" Image {full_image} is LOCAL ONLY") + log.warning(f" RunPod deployment will fail unless you manually push") + else: + log.warning(f" ⚠️ No registry configured - image is local only") + log.warning(f" Set TETRA_DOCKER_REGISTRY env var to enable automatic push") + log.warning(f" Example: export TETRA_DOCKER_REGISTRY=docker.io/myuser") + + # Update resource_config to use the new image + resource_config.imageName = full_image + + # Set TETRA_BAKED_MODE environment variable + if not hasattr(resource_config, 'env') or resource_config.env is None: + resource_config.env = {} + resource_config.env['TETRA_BAKED_MODE'] = 'true' + + log.info(f" ✅ Resource configured to use production image") + log.info(f" Image: {full_image}") + log.info(f" TETRA_BAKED_MODE=true") + + +def remove_remote_decorator(source_code: str) -> str: + """ + Remove @remote decorator from source code. + + Simple line-based approach - removes lines starting with @remote. + """ + lines = source_code.splitlines() + cleaned_lines = [] + in_decorator = False + + for line in lines: + stripped = line.strip() + + # Start of @remote decorator + if stripped.startswith('@remote'): + in_decorator = True + # Check if it's a multi-line decorator + if '(' in stripped and ')' not in stripped: + continue # Multi-line, skip this line + elif '(' in stripped and ')' in stripped: + # Single-line decorator, skip it + continue + else: + # Just @remote without parens + continue + + # Continuation of multi-line decorator + if in_decorator: + if ')' in stripped: + in_decorator = False + continue + + cleaned_lines.append(line) + + return '\n'.join(cleaned_lines) + + +def generate_dockerfile( + worker_base_image: str, + dependencies: List[str], + system_dependencies: List[str], + callable_name: str, +) -> str: + """Generate Dockerfile for production image.""" + + dockerfile = f"""# Production image for {callable_name} +# Auto-generated by Tetra + +FROM {worker_base_image} + +WORKDIR /app + +""" + + # Add system dependencies + if system_dependencies: + dockerfile += "# Install system dependencies\n" + dockerfile += "RUN apt-get update && apt-get install -y \\\n" + for dep in system_dependencies: + dockerfile += f" {dep} \\\n" + dockerfile += " && rm -rf /var/lib/apt/lists/*\n\n" + + # Add Python dependencies + if dependencies: + dockerfile += "# Install Python dependencies\n" + for dep in dependencies: + dockerfile += f"RUN uv pip install {dep}\n" + dockerfile += "\n" + + # Copy baked code + dockerfile += """# Copy baked code +COPY baked_code/ /app/baked_code/ + +# Enable baked mode +ENV TETRA_BAKED_MODE=true +""" + + return dockerfile diff --git a/src/tetra_rp/prod_config.py b/src/tetra_rp/prod_config.py new file mode 100644 index 0000000..5790016 --- /dev/null +++ b/src/tetra_rp/prod_config.py @@ -0,0 +1,146 @@ +""" +Production configuration loader for Flash CLI. + +Handles loading build artifacts and configuring resources for baked execution mode. +""" + +import json +import logging +import os +from pathlib import Path +from typing import Optional + +from .core.resources import ServerlessResource + +log = logging.getLogger(__name__) + + +class ProductionConfig: + """Factory for loading and applying production configuration.""" + + def __init__(self, artifacts_path: Optional[Path] = None): + """ + Initialize production config loader. + + Args: + artifacts_path: Path to build_artifacts.json. Defaults to .tetra/build_artifacts.json + """ + self.artifacts_path = ( + artifacts_path or Path.cwd() / ".tetra" / "build_artifacts.json" + ) + self._artifacts = None + + @property + def artifacts(self) -> dict: + """Load and cache build artifacts.""" + if self._artifacts is None: + if not self.artifacts_path.exists(): + raise FileNotFoundError( + f"Build artifacts not found at {self.artifacts_path}. " + f"Run 'flash build' first." + ) + with open(self.artifacts_path, "r") as f: + self._artifacts = json.load(f) + return self._artifacts + + def get_worker_config(self, worker_name: str) -> Optional[dict]: + """ + Get worker configuration by name from build artifacts. + + Args: + worker_name: Name of the worker class + + Returns: + Worker configuration dict or None if not found + """ + for worker in self.artifacts.get("workers", []): + if worker.get("name") == worker_name: + return worker + return None + + def inject_config( + self, resource_config: ServerlessResource, worker_name: str + ) -> None: + """ + Inject production configuration into resource config. + + Modifies resource_config in-place by setting: + - TETRA_BAKED_MODE=true + - TETRA_TARBALL_PATH=/runpod-volume/{s3_key} + - imageName from build artifacts + + Args: + resource_config: The serverless resource configuration to modify + worker_name: Name of the worker class for lookup + """ + # Get worker configuration + worker_config = self.get_worker_config(worker_name) + if not worker_config: + available = [w.get("name") for w in self.artifacts.get("workers", [])] + raise ValueError( + f"Worker '{worker_name}' not found in build artifacts. " + f"Available workers: {available}" + ) + + # Extract tarball S3 key + tarball_s3_key = worker_config.get("tarball_s3_key") + if not tarball_s3_key: + raise ValueError(f"No tarball_s3_key found for worker '{worker_name}'") + + # Configure environment variables for baked execution + if resource_config.env is None: + resource_config.env = {} + + resource_config.env.update( + { + "TETRA_BAKED_MODE": "true", + "TETRA_TARBALL_PATH": f"/runpod-volume/{tarball_s3_key}", + } + ) + + # Set base image from build artifacts + base_image = worker_config.get("base_image") + if base_image: + resource_config.imageName = base_image + + # Attach network volume if volume ID is provided + volume_id = os.getenv("RUNPOD_VOLUME_ID") + if volume_id: + resource_config.networkVolumeId = volume_id + log.info(f"Attached network volume: {volume_id}") + + log.info( + f"Production config applied for {worker_name}: " + f"tarball={tarball_s3_key}, image={base_image}" + ) + + +def is_production_mode() -> bool: + """Check if TETRA_PROD_MODE environment variable is enabled.""" + return os.getenv("TETRA_PROD_MODE", "").lower() in ("true", "1", "yes") + + +def apply_production_config( + resource_config: ServerlessResource, worker_name: str +) -> None: + """ + Apply production configuration if TETRA_PROD_MODE is enabled. + + Args: + resource_config: The serverless resource configuration to modify + worker_name: Name of the worker class + + Raises: + FileNotFoundError: If build artifacts not found + ValueError: If worker not found in artifacts + """ + if not is_production_mode(): + log.debug("Production mode not enabled, skipping config injection") + return + + try: + config = ProductionConfig() + config.inject_config(resource_config, worker_name) + except Exception as e: + log.error(f"Failed to apply production configuration: {e}") + raise diff --git a/src/tetra_rp/stubs/live_serverless.py b/src/tetra_rp/stubs/live_serverless.py index 04205c6..b710c11 100644 --- a/src/tetra_rp/stubs/live_serverless.py +++ b/src/tetra_rp/stubs/live_serverless.py @@ -71,23 +71,37 @@ def prepare_request( *args, **kwargs, ): - source, src_hash = get_function_source(func) + # Check if we're in baked mode (production) + env_value = None + if hasattr(self.server, "env") and self.server.env is not None: + env = self.server.env + if isinstance(env, dict): + env_value = env.get("TETRA_BAKED_MODE", "") + + is_baked = env_value and env_value.lower() in ("true", "1", "yes") request = { "function_name": func.__name__, "dependencies": dependencies, "system_dependencies": system_dependencies, "accelerate_downloads": accelerate_downloads, + "baked": is_baked, } - # Thread-safe cache access - with _function_cache_lock: - # check if the function is already cached - if src_hash not in _SERIALIZED_FUNCTION_CACHE: - # Cache the serialized function - _SERIALIZED_FUNCTION_CACHE[src_hash] = source + # Only send code if NOT in baked mode + if not is_baked: + source, src_hash = get_function_source(func) + + # Thread-safe cache access + with _function_cache_lock: + # check if the function is already cached + if src_hash not in _SERIALIZED_FUNCTION_CACHE: + # Cache the serialized function + _SERIALIZED_FUNCTION_CACHE[src_hash] = source - request["function_code"] = _SERIALIZED_FUNCTION_CACHE[src_hash] + request["function_code"] = _SERIALIZED_FUNCTION_CACHE[src_hash] + else: + log.info(f"Using baked mode for function: {func.__name__}") # Serialize arguments using cloudpickle if args: diff --git a/tests/unit/resources/test_cpu.py b/tests/unit/resources/test_cpu.py index a75b71b..bf15ade 100644 --- a/tests/unit/resources/test_cpu.py +++ b/tests/unit/resources/test_cpu.py @@ -10,9 +10,43 @@ ) +class TestCpuInstanceType: + """Test CpuInstanceType enum behavior.""" + + def test_any_enum_exists(self): + """Test that CpuInstanceType.ANY enum exists.""" + assert CpuInstanceType.ANY == "any" + + def test_all_returns_all_except_any(self): + """Test that all() returns all CPU instance types except ANY.""" + all_types = CpuInstanceType.all() + + # Should not include ANY + assert CpuInstanceType.ANY not in all_types + + # Should include all other types (12 total) + assert len(all_types) == 12 + assert CpuInstanceType.CPU3G_1_4 in all_types + assert CpuInstanceType.CPU3G_2_8 in all_types + assert CpuInstanceType.CPU3G_4_16 in all_types + assert CpuInstanceType.CPU3G_8_32 in all_types + assert CpuInstanceType.CPU3C_1_2 in all_types + assert CpuInstanceType.CPU3C_2_4 in all_types + assert CpuInstanceType.CPU3C_4_8 in all_types + assert CpuInstanceType.CPU3C_8_16 in all_types + assert CpuInstanceType.CPU5C_1_2 in all_types + assert CpuInstanceType.CPU5C_2_4 in all_types + assert CpuInstanceType.CPU5C_4_8 in all_types + assert CpuInstanceType.CPU5C_8_16 in all_types + + class TestCpuInstanceDiskLimits: """Test CPU instance disk limits constants and utilities.""" + def test_cpu_instance_disk_limits_excludes_any(self): + """Test that CPU_INSTANCE_DISK_LIMITS excludes ANY.""" + assert CpuInstanceType.ANY not in CPU_INSTANCE_DISK_LIMITS + def test_cpu_instance_disk_limits_mapping(self): """Test that all CPU instance types have disk limits defined.""" expected_limits = { @@ -91,6 +125,10 @@ def test_calculate_max_disk_size_cpu5c(self): def test_programmatic_limits_match_dictionary(self): """Test that programmatically calculated limits match the generated dictionary.""" for instance_type in CpuInstanceType: + # Skip ANY since it doesn't have a disk limit + if instance_type == CpuInstanceType.ANY: + continue + calculated = calculate_max_disk_size(instance_type) from_dict = CPU_INSTANCE_DISK_LIMITS[instance_type] assert calculated == from_dict, ( diff --git a/tests/unit/resources/test_live_serverless.py b/tests/unit/resources/test_live_serverless.py index cccd78c..3f082e4 100644 --- a/tests/unit/resources/test_live_serverless.py +++ b/tests/unit/resources/test_live_serverless.py @@ -63,10 +63,13 @@ def test_cpu_live_serverless_defaults(self): name="example_cpu_live_serverless", ) - # Should use default CPU3G_2_8 instance - assert live_serverless.instanceIds == [CpuInstanceType.CPU3G_2_8] + # Should expand ANY to all CPU instance types + assert live_serverless.instanceIds == CpuInstanceType.all() assert live_serverless.template is not None - assert live_serverless.template.containerDiskInGb == 20 + # When using ANY (all instances), disk size should be minimum of all limits + assert ( + live_serverless.template.containerDiskInGb == 10 + ) # Min disk size across all types assert "tetra-rp-cpu:" in live_serverless.imageName # CPU image def test_cpu_live_serverless_custom_instances(self): diff --git a/tests/unit/resources/test_serverless.py b/tests/unit/resources/test_serverless.py index eb1a780..5721147 100644 --- a/tests/unit/resources/test_serverless.py +++ b/tests/unit/resources/test_serverless.py @@ -694,7 +694,8 @@ def test_cpu_serverless_endpoint_defaults(self): imageName="test/cpu-image:latest", ) - assert endpoint.instanceIds == [CpuInstanceType.CPU3G_2_8] + # Should expand ANY to all CPU instance types + assert endpoint.instanceIds == CpuInstanceType.all() # Should trigger CPU mode in sync_input_fields assert endpoint.gpuCount == 0 assert endpoint.allowedCudaVersions == "" diff --git a/tests/unit/resources/test_serverless_cpu.py b/tests/unit/resources/test_serverless_cpu.py index d508511..97aa784 100644 --- a/tests/unit/resources/test_serverless_cpu.py +++ b/tests/unit/resources/test_serverless_cpu.py @@ -18,10 +18,12 @@ def test_cpu_serverless_endpoint_defaults(self): imageName="test/cpu-image:latest", ) - # Should use default CPU3G_2_8 instance - assert endpoint.instanceIds == [CpuInstanceType.CPU3G_2_8] + # Should expand ANY to all CPU instance types + assert endpoint.instanceIds == CpuInstanceType.all() assert endpoint.template is not None - assert endpoint.template.containerDiskInGb == 20 + assert ( + endpoint.template.containerDiskInGb == 10 + ) # Min disk size across all types def test_cpu_serverless_endpoint_custom_instances(self): """Test CpuServerlessEndpoint with custom instance types.""" @@ -190,6 +192,47 @@ def test_validation_mixed_instance_types_different_generations(self): assert endpoint.template.containerDiskInGb == 10 # Minimum across all types +class TestCpuValidation: + """Test CPU instance type validation.""" + + def test_validate_cpus_expands_any(self): + """Test that validate_cpus expands ANY to all instance types.""" + endpoint = CpuServerlessEndpoint( + name="test-endpoint", + imageName="test/image:latest", + instanceIds=[CpuInstanceType.ANY], + ) + + # Should be expanded to all CPU instance types + assert endpoint.instanceIds == CpuInstanceType.all() + assert len(endpoint.instanceIds) == 12 + assert CpuInstanceType.ANY not in endpoint.instanceIds + + def test_validate_cpus_preserves_explicit_list(self): + """Test that validate_cpus preserves explicit instance type lists.""" + explicit_types = [CpuInstanceType.CPU3G_1_4, CpuInstanceType.CPU5C_2_4] + + endpoint = CpuServerlessEndpoint( + name="test-endpoint", + imageName="test/image:latest", + instanceIds=explicit_types, + ) + + # Should preserve the explicit list + assert endpoint.instanceIds == explicit_types + + def test_validate_cpus_preserves_single_instance(self): + """Test that validate_cpus preserves single explicit instance type.""" + endpoint = CpuServerlessEndpoint( + name="test-endpoint", + imageName="test/image:latest", + instanceIds=[CpuInstanceType.CPU3C_4_8], + ) + + # Should preserve the single instance type + assert endpoint.instanceIds == [CpuInstanceType.CPU3C_4_8] + + class TestCpuEndpointMixin: """Test CpuEndpointMixin functionality.""" diff --git a/uv.lock b/uv.lock index 0a9ffbf..c5d1e72 100644 --- a/uv.lock +++ b/uv.lock @@ -29,7 +29,7 @@ wheels = [ [[package]] name = "aiohttp" -version = "3.12.15" +version = "3.13.2" source = { registry = "https://pypi.org/simple" } dependencies = [ { name = "aiohappyeyeballs" }, @@ -41,98 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