core:services:kraken: Migrate kraken to secondary venv and update its dependencies

[joaomariolago]

Fix #3253
Closes #3276

Summary by Sourcery

Migrate the Kraken service into the secondary Python virtual environment and update its dependency stack accordingly.

Enhancements:

• Update Kraken service runtime dependencies to newer, compatible versions including FastAPI, Pydantic, aiohttp, and related libraries.
• Adjust Kraken manifest models to use Pydantic v2-style RootModel and validation APIs.
• Simplify type handling in Docker-related helpers by removing redundant casts and using explicit type annotations.

Build:

• Move Kraken from the primary core workspace into the python-venv2 environment, updating workspace membership and dependency wiring.
• Relax and align commonwealth library constraints on psutil, pydantic, and add packaging to support the updated dependency set.

Summary by Sourcery

Migrate the Kraken service into the secondary Python virtual environment and refresh its dependency stack to align with shared library constraints and newer frameworks.

Enhancements:

• Update Kraken service runtime dependencies (FastAPI, Pydantic, aiohttp, uvicorn and related libraries) to newer, compatible versions.
• Adjust Kraken manifest models and validation usage to Pydantic v2 APIs and RootModel semantics.
• Simplify Docker helper typing by removing unnecessary casts and clarifying type annotations.

Build:

• Move Kraken from the primary core workspace into the python-venv2 environment and wire it into that workspace configuration.
• Relax and align commonwealth dependency constraints for psutil, pydantic, and add packaging to support the updated dependency set.

[sourcery-ai]

Reviewer's Guide

Migrates the Kraken service into the secondary python-venv2 workspace and modernizes its dependency stack (notably FastAPI/Pydantic), including manifest model updates and minor Docker helper cleanups, while relaxing commonwealth’s dependency constraints to match.

Sequence diagram for updated manifest fetch and validation using ManifestData.model_validate

sequenceDiagram
    participant KrakenManifestService
    participant aiohttpClientSession as aiohttp_ClientSession
    participant RemoteManifestServer
    participant ManifestData

    KrakenManifestService->>aiohttpClientSession: get(url)
    aiohttpClientSession->>RemoteManifestServer: HTTP GET /manifest
    RemoteManifestServer-->>aiohttpClientSession: JSON manifest payload
    aiohttpClientSession-->>KrakenManifestService: resp

    KrakenManifestService->>aiohttpClientSession: resp.json(content_type=None)
    aiohttpClientSession-->>KrakenManifestService: raw_manifest_data

    KrakenManifestService->>ManifestData: model_validate(raw_manifest_data)
    ManifestData-->>KrakenManifestService: manifest_data_instance

    KrakenManifestService->>KrakenManifestService: entries = manifest_data_instance.root

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Class diagram for updated Kraken manifest models with Pydantic v2 RootModel

classDiagram
    class BaseModel
    class RootModel~List_RepositoryEntry~{
    }

    class ExtensionMetadata{
    }

    class RepositoryEntry{
    }

    class ManifestData{
    }

    ExtensionMetadata <|-- RepositoryEntry
    RootModel~List_RepositoryEntry~ <|-- ManifestData

    note for ManifestData "Pydantic v1 style: class ManifestData(BaseModel) with __root__ List[RepositoryEntry] replaced by Pydantic v2 style: class ManifestData(RootModel[List[RepositoryEntry]])"

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File-Level Changes

Change	Details	Files
Update Kraken service dependencies to newer versions compatible with python-venv2 and modern FastAPI/Pydantic.	Bump core runtime libraries such as aiocache, aiodocker, aiohttp, fastapi, fastapi-versioning, loguru, psutil, pydantic, semver, and uvicorn to newer versions. Align Kraken’s pydantic requirement with v2 (2.12.5) to match the shared environment. Remove explicit workspace source for commonwealth from Kraken’s pyproject since resolution now happens via the venv2 workspace.	core/services/kraken/pyproject.toml
Move Kraken from the primary core workspace into the python-venv2 workspace and wire it as a dependency there instead of in core.	Remove kraken from core’s direct dependencies and from the core workspace members while adding it to the workspace exclude list. Add kraken as a dependency and workspace member of python-venv2, and wire kraken as a workspace source in the venv2 config. Regenerate uv.lock files for core and python-venv2 plus adjust start-blueos-core script to reflect the environment layout changes.	core/pyproject.toml core/python-venv2/pyproject.toml core/python-venv2/uv.lock core/uv.lock core/start-blueos-core
Adapt Kraken’s manifest models and manifest loading to Pydantic v2 APIs.	Refactor ManifestData from a custom BaseModel with root to a Pydantic v2 RootModel[List[RepositoryEntry]]. Switch manifest JSON parsing from ManifestData.parse_obj(...) to ManifestData.model_validate(...), and access parsed entries via .root instead of .root. Keep other manifest models intact, relying on the updated Pydantic version for validation.	core/services/kraken/manifest/models.py core/services/kraken/manifest/manifest.py
Relax and expand commonwealth’s dependency constraints to support the updated global stack.	Allow psutil to range between 5.7.2 and 7.1.3 instead of requiring a single pinned version. Add packaging as a new dependency with a broad version range to support version handling. Permit Pydantic to be either 1.10.12 up to 2.12.5, enabling shared usage of Pydantic v2 in venv2.	core/libs/commonwealth/pyproject.toml
Simplify Docker-related helper type handling in Kraken to better match actual return types and reduce redundant casts.	Treat Docker image inspection result as a Dict[str, Any] via explicit variable annotation instead of cast(...). Return DockerContainer instances directly from container listing without an unnecessary cast in harbor.container.get_raw_container_by_name.	core/services/kraken/extension/extension.py core/services/kraken/harbor/container.py

Assessment against linked issues

Issue	Objective	Addressed	Explanation
#3253	Fix the Kraken service’s slowly growing RAM usage (memory leak) observed over long uptimes on idle systems.	✅

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