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report](https://codecov.io/gh/touale/FrameX-kit/branch/master/graph/badge.svg)](https://app.codecov.io/gh/touale/FrameX-kit)\n[![Latest Release](https://img.shields.io/github/v/release/touale/FrameX-kit?label=latest)](https://github.com/touale/FrameX-kit/releases)\n\n**FrameX** is a lightweight, pluggable Python framework designed for building modular and extensible algorithmic systems.\\\\\n\nIt provides a clean architecture that supports **dynamic plugin registration**, **isolated execution**, and **secure invocation**, making it well-suited for multi-algorithm collaboration, heterogeneous task scheduling, and distributed deployments.\n\nEach algorithm can be developed, deployed, and loaded as an independent plugin, achieving infinite scalability.\n\n![](./book/src/img/v2andv3.svg)\n\n______________________________________________________________________\n\n## Project Information\n\n- **Author:** Touale Cula\n- **License:** MIT\n- **Source Code:** [FrameX Repository](https://github.com/touale/FrameX-kit)\n- **Online Documentation:** [FrameX Docs](https://touale.github.io/FrameX-kit/)\n\n______________________________________________________________________\n\n## Key Features\n\n- **Plugin-Based Architecture**\\\n  Algorithms are encapsulated as independent plugins, which can be added, removed, or updated without impacting others.\n- **Distributed Execution with Ray**\\\n  Optional Ray integration delivers high concurrency, high throughput, and resilience against blocking tasks.\n- **Cross-plugin Calls**\\\n  Enables interaction between local and remote plugins. If a plugin is not available locally, the system automatically routes the request to the corresponding cloud plugin.\n- **Backward Compatibility**\\\n  FrameX can seamlessly forward requests to standard FastAPI endpoints, enabling smooth integration without code changes.\n- **Streaming Support**\\\n  Native support for streaming responses, suitable for long-running or large-scale inference tasks.\n- **Built-in Observability**\\\n  Integrated logging, tracing, and performance monitoring to ease debugging and root-cause analysis.\n- **Flexible Configuration \u0026 Tooling**\\\n  Clean configuration management (`.toml`, `.env`) plus scaffolding, packaging, and CI/CD integration for automation.\n\n## Installation\n\n```\npip install framex-kit\n```\n\n### 1) Execute by loading your plugin\n\nCreate foo.py file\n\n```\nfrom typing import Any\nfrom pydantic import BaseModel\n\nfrom framex.consts import VERSION\nfrom framex.plugin import BasePlugin, PluginMetadata, on_register, on_request\n\n\n__plugin_meta__ = PluginMetadata(\n    name=\"foo\",\n    version=VERSION,\n    description=\"A simple Foo plugin example\",\n    author=\"touale\",\n    url=\"https://github.com/touale/FrameX-kit\",\n)\n\n\nclass FooModel(BaseModel):\n    text: str = \"Hello Foo\"\n\n\n@on_register()\nclass FooPlugin(BasePlugin):\n    def __init__(self, **kwargs: Any) -\u003e None:\n        super().__init__(**kwargs)\n\n    @on_request(\"/foo\", methods=[\"GET\"])\n    async def foo(self, message: str) -\u003e str:\n        return f\"Foo says: {message}\"\n\n    @on_request(\"/foo_model\", methods=[\"POST\"])\n    async def foo_model(self, model: FooModel) -\u003e str:\n        return f\"Foo received model: {model.text}\"#   \n```\n\nRun the following command to start the project creation process:\n\n```\n$ PYTHONPATH=. framex run --load-plugins foo\n🚀 Starting FrameX with configuration:\n{\n  \"host\": \"127.0.0.1\",\n  \"port\": 8080,\n  \"dashboard_host\": \"127.0.0.1\",\n  \"dashboard_port\": 8260,\n  \"use_ray\": false,\n  \"enable_proxy\": false,\n  \"num_cpus\": 8,\n  \"excluded_log_paths\": []\n}\n11-05 16:01:13 [SUCCESS] framex.plugin.manage | Succeeded to load plugin \"foo\" from foo\n11-05 16:01:13 [INFO] framex | Start initializing all DeploymentHandle...\n11-05 16:01:13 [SUCCESS] framex.plugin.manage | Found plugin HTTP API \"['/api/v1/foo', '/api/v1/foo_model']\" from plugin(foo)\n11-05 16:01:13 [SUCCESS] framex.driver.ingress | Succeeded to register api(['GET']): /api/v1/foo from foo.FooPlugin\n11-05 16:01:13 [SUCCESS] framex.driver.ingress | Succeeded to register api(['POST']): /api/v1/foo_model from foo.FooPlugin\nINFO:     Started server process [59373]\nINFO:     Waiting for application startup.\n11-05 16:01:13 [INFO] framex.driver.application | Starting FastAPI application...\nINFO:     Application startup complete.\nINFO:     Uvicorn running on http://127.0.0.1:8080 (Press CTRL+C to quit)\n```\n\n### 2) Execute by loading a system plugin\n\n```\n$ framex run --load-builtin-plugins echo\n🚀 Starting FrameX with configuration:\n{\n  \"host\": \"127.0.0.1\",\n  \"port\": 8080,\n  \"dashboard_host\": \"127.0.0.1\",\n  \"dashboard_port\": 8260,\n  \"use_ray\": false,\n  \"enable_proxy\": false,\n  \"num_cpus\": 8,\n  \"excluded_log_paths\": []\n}\n11-05 16:27:36 [SUCCESS] framex.plugin.manage | Succeeded to load plugin \"echo\" from framex.plugins.echo\n11-05 16:27:36 [INFO] framex | Start initializing all DeploymentHandle...\n11-05 16:27:36 [SUCCESS] framex.plugin.manage | Found plugin HTTP API \"['/api/v1/echo', '/api/v1/echo_model', '/api/v1/echo_stream']\" from plugin(echo)\n11-05 16:27:36 [SUCCESS] framex.plugin.manage | Found plugin FUNC API \"['echo.EchoPlugin.confess']\" from plugin(echo)\n11-05 16:27:36 [SUCCESS] framex.driver.ingress | Succeeded to register api(['GET']): /api/v1/echo from echo.EchoPlugin\n11-05 16:27:36 [SUCCESS] framex.driver.ingress | Succeeded to register api(['POST']): /api/v1/echo_model from echo.EchoPlugin\n11-05 16:27:36 [SUCCESS] framex.driver.ingress | Succeeded to register api(['GET']): /api/v1/echo_stream from echo.EchoPlugin\nINFO:     Started server process [554]\nINFO:     Waiting for application startup.\n11-05 16:27:36 [INFO] framex.driver.application | Starting FastAPI application...\nINFO:     Application startup complete.\nINFO:     Uvicorn running on http://127.0.0.1:8080 (Press CTRL+C to quit)\n```\n\n### 3) Execute by loading a third-party plugin\n\n```\nframex run --load-plugins \u003cplugin_name\u003e,\u003cplugin_name\u003e\n```\n\n## Application Scenarios\n\n- **Quick Onboarding \u0026 Project Setup**\\\n  New developers can rapidly bootstrap projects and reuse existing algorithms via remote calls, without accessing legacy code.\n\n- **Multi-Team Parallel Development \u0026 Isolation**\\\n  Different teams manage their own isolated plugin spaces. Access control ensure security and reduce interference.\n\n- **Hybrid Deployment \u0026 Smooth Migration**\\\n  Supports hybrid calls with other FastAPI services, dynamic endpoint registration, and multi-instance FrameX deployment with inter-instance communication.\n\n- **Modular Delivery \u0026 Commercial Licensing**\\\n  Deliver selected algorithm modules locally to clients while keeping others as remotely callable services. This supports licensing, pay-per-use, and flexible business models.\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftouale%2Fframex-kit","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ftouale%2Fframex-kit","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ftouale%2Fframex-kit/lists"}