├── .gitignore ├── .python-version ├── README.md ├── examples ├── basic_planner.py ├── fixture │ └── mock.csv ├── imgs │ ├── arch.png │ └── nano-manus.mp4 └── load_mcp_tools.py ├── pyproject.toml ├── src └── nano_manus │ ├── __init__.py │ ├── env.py │ ├── mcp_tool │ ├── __init__.py │ ├── official.py │ ├── pool.py │ └── type.py │ ├── planner │ ├── __init__.py │ ├── parser.py │ ├── planner.py │ └── prompts.py │ ├── py.typed │ └── worker │ ├── __init__.py │ ├── code_agent.py │ ├── mcp_agent.py │ ├── no_tool_agent.py │ ├── search_agent.py │ ├── terminal_agent.py │ └── type.py ├── tests ├── __init__.py └── test_basic.py └── uv.lock /.gitignore: -------------------------------------------------------------------------------- 1 | tmp/ 2 | .DS_Store 3 | # Python-generated files 4 | *.txt 5 | __pycache__/ 6 | *.py[oc] 7 | build/ 8 | dist/ 9 | wheels/ 10 | *.egg-info 11 | 12 | # Virtual environments 13 | .venv 14 | # Created by https://www.toptal.com/developers/gitignore/api/python 15 | # Edit at https://www.toptal.com/developers/gitignore?templates=python 16 | 17 | ### Python ### 18 | # Byte-compiled / optimized / DLL files 19 | __pycache__/ 20 | *.py[cod] 21 | *$py.class 22 | 23 | # C extensions 24 | *.so 25 | 26 | # Distribution / packaging 27 | .Python 28 | build/ 29 | develop-eggs/ 30 | dist/ 31 | downloads/ 32 | eggs/ 33 | .eggs/ 34 | lib/ 35 | lib64/ 36 | parts/ 37 | sdist/ 38 | var/ 39 | wheels/ 40 | share/python-wheels/ 41 | *.egg-info/ 42 | .installed.cfg 43 | *.egg 44 | MANIFEST 45 | 46 | # PyInstaller 47 | # Usually these files are written by a python script from a template 48 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 49 | *.manifest 50 | *.spec 51 | 52 | # Installer logs 53 | pip-log.txt 54 | pip-delete-this-directory.txt 55 | 56 | # Unit test / coverage reports 57 | htmlcov/ 58 | .tox/ 59 | .nox/ 60 | .coverage 61 | .coverage.* 62 | .cache 63 | nosetests.xml 64 | coverage.xml 65 | *.cover 66 | *.py,cover 67 | .hypothesis/ 68 | .pytest_cache/ 69 | cover/ 70 | 71 | # Translations 72 | *.mo 73 | *.pot 74 | 75 | # Django stuff: 76 | *.log 77 | local_settings.py 78 | db.sqlite3 79 | db.sqlite3-journal 80 | 81 | # Flask stuff: 82 | instance/ 83 | .webassets-cache 84 | 85 | # Scrapy stuff: 86 | .scrapy 87 | 88 | # Sphinx documentation 89 | docs/_build/ 90 | 91 | # PyBuilder 92 | .pybuilder/ 93 | target/ 94 | 95 | # Jupyter Notebook 96 | .ipynb_checkpoints 97 | 98 | # IPython 99 | profile_default/ 100 | ipython_config.py 101 | 102 | # pyenv 103 | # For a library or package, you might want to ignore these files since the code is 104 | # intended to run in multiple environments; otherwise, check them in: 105 | # .python-version 106 | 107 | # pipenv 108 | # According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. 109 | # However, in case of collaboration, if having platform-specific dependencies or dependencies 110 | # having no cross-platform support, pipenv may install dependencies that don't work, or not 111 | # install all needed dependencies. 112 | #Pipfile.lock 113 | 114 | # poetry 115 | # Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. 116 | # This is especially recommended for binary packages to ensure reproducibility, and is more 117 | # commonly ignored for libraries. 118 | # https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control 119 | #poetry.lock 120 | 121 | # pdm 122 | # Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. 123 | #pdm.lock 124 | # pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it 125 | # in version control. 126 | # https://pdm.fming.dev/#use-with-ide 127 | .pdm.toml 128 | 129 | # PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm 130 | __pypackages__/ 131 | 132 | # Celery stuff 133 | celerybeat-schedule 134 | celerybeat.pid 135 | 136 | # SageMath parsed files 137 | *.sage.py 138 | 139 | # Environments 140 | .env 141 | .venv 142 | env/ 143 | venv/ 144 | ENV/ 145 | env.bak/ 146 | venv.bak/ 147 | 148 | # Spyder project settings 149 | .spyderproject 150 | .spyproject 151 | 152 | # Rope project settings 153 | .ropeproject 154 | 155 | # mkdocs documentation 156 | /site 157 | 158 | # mypy 159 | .mypy_cache/ 160 | .dmypy.json 161 | dmypy.json 162 | 163 | # Pyre type checker 164 | .pyre/ 165 | 166 | # pytype static type analyzer 167 | .pytype/ 168 | 169 | # Cython debug symbols 170 | cython_debug/ 171 | 172 | # PyCharm 173 | # JetBrains specific template is maintained in a separate JetBrains.gitignore that can 174 | # be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore 175 | # and can be added to the global gitignore or merged into this file. For a more nuclear 176 | # option (not recommended) you can uncomment the following to ignore the entire idea folder. 177 | #.idea/ 178 | 179 | ### Python Patch ### 180 | # Poetry local configuration file - https://python-poetry.org/docs/configuration/#local-configuration 181 | poetry.toml 182 | 183 | # ruff 184 | .ruff_cache/ 185 | 186 | # LSP config files 187 | pyrightconfig.json 188 | 189 | # End of https://www.toptal.com/developers/gitignore/api/python 190 | 191 | -------------------------------------------------------------------------------- /.python-version: -------------------------------------------------------------------------------- 1 | 3.11 2 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 |
2 |

🐜 nano_manus

3 |

Implementing some features of Manus with MCP

4 |

5 | 6 | 7 | 8 | 9 | 10 | 11 |

12 |
13 | 14 | 15 |
16 | 17 | Shows the Memobase Workflow 18 | 19 |

nano-manus

20 |
21 | 22 | 23 | 24 | ## Features 25 | 26 | - **Small**: `nano_manus` is about 1000 LOC. 27 | - **Using MCP**: `nano_manus` supports [loading MCP](./examples/load_mcp_tools.py) from [docker](https://hub.docker.com/u/mcp), `npx` and [Smithery](https://smithery.ai/) 28 | - **Plan-then-Execute**: `nano_manus` will gather your agents, make the plans and then assign the correct jobs to your agents 29 | 30 | 31 | 32 | ## Use Cases 33 | 34 | https://github.com/user-attachments/assets/33b90afc-2e30-4ab0-8988-bd7d6da065fb 35 | 36 | 37 | - `Find all .py file and explain them to me ` 38 | - `Give me the latest weather in SF in last 7 days and save it to csv` 39 | 40 | > Welcome to give more use cases! 41 | 42 | 43 | 44 | ## QuickStart 45 | 46 | #### Setup 47 | 48 | - Install [NPM](https://docs.npmjs.com/downloading-and-installing-node-js-and-npm) 49 | - Install [docker](https://docs.docker.com/engine/install/) 50 | 51 | #### Env 52 | 53 | - [Brave Search API key](https://brave.com/search/api/) 54 | - [Jina API key](https://jina.ai/) 55 | - OpenAI API key 56 | 57 | Your `.env` should look like: 58 | 59 | ``` 60 | BRAVE_API_KEY=BSAxxxx 61 | JINA_API_KEY=jina_xxxx 62 | OPENAI_API_KEY=sk-proj-XXXXX 63 | ``` 64 | 65 | #### Run default `nano-manus` 66 | 67 | ```bash 68 | uv sync 69 | uv run examples/basic_planner.py 70 | ``` 71 | 72 | 73 | 74 | ## Abilities 75 | 76 | - [x] Search Web (`mcp/brave-search`, `jina-ai-mcp-server`) 77 | - [x] Local files operations (`@wonderwhy-er/desktop-commander`) 78 | - [x] Execute codes and commands in your computer (`@wonderwhy-er/desktop-commander`) 79 | - [ ] (coming soon) Implementing [CodeAct](https://github.com/xingyaoww/code-act) 80 | - [ ] (coming soon) Read `.pdf, .doc` 81 | - [ ] (coming soon) browser use 82 | - [ ] (coming soon) multi-model router (`claude`, `qwen`, `deepseek`...) 83 | 84 | 85 | 86 | 87 | 88 | ## Known Issues 89 | 90 | - `nano-manus` is extremely unstable! My guess is `gpt-4o` is not that good at tool use. 91 | - `Unable to exit`: seem like some MCPs will cause the problems of unable to exit the program when all the tasks were done. 92 | - `nano-manus` will operate files and run command **on the current dir of your local computer**, make sure you don't run it on some important folders. 93 | -------------------------------------------------------------------------------- /examples/basic_planner.py: -------------------------------------------------------------------------------- 1 | import os 2 | import dotenv 3 | 4 | dotenv.load_dotenv() 5 | import argparse 6 | from nano_manus.env import CONFIG, CONSOLE 7 | from nano_manus.planner import Planner 8 | from nano_manus.mcp_tool import TOOLS 9 | from nano_manus.worker import SearchAgent, TerminalAgent 10 | from nano_manus.worker.code_agent import CodeAgent 11 | 12 | search_agent = SearchAgent() 13 | terminal_agent = TerminalAgent() 14 | code_agent = CodeAgent() 15 | 16 | planner = Planner(workers=[search_agent, terminal_agent, code_agent]) 17 | 18 | 19 | def parse_args(): 20 | parser = argparse.ArgumentParser() 21 | parser.add_argument("--path", type=str, default="./tmp/agent_run") 22 | return parser.parse_args() 23 | 24 | 25 | async def main(): 26 | args = parse_args() 27 | CONFIG.allowed_local_dir = os.path.abspath(args.path) 28 | await TOOLS.start() 29 | # result = await planner.handle("Give me the latest weather in Tokyo today") 30 | await planner.outer_loop() 31 | await TOOLS.stop() 32 | 33 | 34 | if __name__ == "__main__": 35 | import asyncio 36 | 37 | asyncio.run(main()) 38 | -------------------------------------------------------------------------------- /examples/fixture/mock.csv: -------------------------------------------------------------------------------- 1 | 客户ID,姓名,年龄,电子邮件,城市 2 | 1,张伟,28,zhangwei@example.com,北京 3 | 2,李娜,34,lina@example.com,上海 4 | 3,王强,45,wangqiang@example.com,广州 5 | 4,赵敏,29,zhaomin@example.com,深圳 6 | 5,刘洋,31,liuyang@example.com,成都 -------------------------------------------------------------------------------- /examples/imgs/arch.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/memodb-io/nano-manus/8cc27b9200a65c2b06eea32506c7fa99a9dd2563/examples/imgs/arch.png -------------------------------------------------------------------------------- /examples/imgs/nano-manus.mp4: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/memodb-io/nano-manus/8cc27b9200a65c2b06eea32506c7fa99a9dd2563/examples/imgs/nano-manus.mp4 -------------------------------------------------------------------------------- /examples/load_mcp_tools.py: -------------------------------------------------------------------------------- 1 | import os 2 | from rich import print 3 | import asyncio 4 | import dotenv 5 | 6 | dotenv.load_dotenv() 7 | from nano_manus.mcp_tool import MCPOfficial, MCPPool 8 | 9 | 10 | terminal_mcp = MCPOfficial.from_smithery( 11 | "@wonderwhy-er/desktop-commander", 12 | suffix_args=[ 13 | "--config", 14 | "{}", 15 | ], 16 | ) 17 | 18 | search_mcp = MCPOfficial.from_docker( 19 | "mcp/brave-search", 20 | volume_mounts=[ 21 | "-e", 22 | f"BRAVE_API_KEY={os.getenv('BRAVE_API_KEY')}", 23 | ], 24 | ) 25 | 26 | 27 | thinking_mcp = MCPOfficial.from_npx( 28 | "@modelcontextprotocol/server-sequential-thinking", prefix_args=["-y"] 29 | ) 30 | 31 | pool = MCPPool() 32 | pool.add_mcp_client("terminal", terminal_mcp) 33 | pool.add_mcp_client("search", search_mcp) 34 | pool.add_mcp_client("thinking", thinking_mcp) 35 | 36 | 37 | async def main(): 38 | await pool.start() 39 | print(await pool.get_mcp_client("terminal").get_available_tools()) 40 | print(await pool.get_mcp_client("search").get_available_tools()) 41 | print(await pool.get_mcp_client("thinking").get_available_tools()) 42 | 43 | await pool.stop() 44 | 45 | 46 | if __name__ == "__main__": 47 | asyncio.run(main()) 48 | -------------------------------------------------------------------------------- /pyproject.toml: -------------------------------------------------------------------------------- 1 | [project] 2 | name = "nano_manus" 3 | version = "0.0.3" 4 | description = "Implementing some features of Manus with MCP" 5 | readme = "README.md" 6 | authors = [{ name = "Gus", email = "contact@memobase.io" }] 7 | requires-python = ">=3.11" 8 | dependencies = [ 9 | "matplotlib>=3.10.1", 10 | "mcp>=1.3.0", 11 | "openai>=1.65.4", 12 | "pandas>=2.2.3", 13 | "python-dotenv>=1.0.1", 14 | "rich>=13.9.4", 15 | ] 16 | 17 | [build-system] 18 | requires = ["hatchling"] 19 | build-backend = "hatchling.build" 20 | 21 | [tool.hatch.build] 22 | exclude = ["examples/*", "docs/*", ".github/*", ".git/*", "tests/*"] 23 | 24 | [dependency-groups] 25 | dev = ["pytest-asyncio>=0.25.3", "pytest>=8.3.5"] 26 | -------------------------------------------------------------------------------- /src/nano_manus/__init__.py: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/memodb-io/nano-manus/8cc27b9200a65c2b06eea32506c7fa99a9dd2563/src/nano_manus/__init__.py -------------------------------------------------------------------------------- /src/nano_manus/env.py: -------------------------------------------------------------------------------- 1 | import os 2 | import logging 3 | import dotenv 4 | from rich.console import Console 5 | from openai import AsyncOpenAI 6 | from openai.types.chat import ChatCompletion 7 | from dataclasses import dataclass 8 | 9 | dotenv.load_dotenv() 10 | LOG = logging.getLogger("nano_manus") 11 | CONSOLE = Console() 12 | async_openai_client = None 13 | 14 | 15 | def setup_openai_async_client(client: AsyncOpenAI): 16 | global async_openai_client 17 | async_openai_client = client 18 | 19 | 20 | def get_async_openai_client() -> AsyncOpenAI: 21 | global async_openai_client 22 | if async_openai_client is None: 23 | async_openai_client = AsyncOpenAI() 24 | return async_openai_client 25 | 26 | 27 | async def llm_complete(model: str, messages: list[dict], **kwargs) -> ChatCompletion: 28 | client = get_async_openai_client() 29 | # if "temperature" not in kwargs: 30 | # kwargs["temperature"] = 0.1 31 | response = await client.chat.completions.create( 32 | model=model, messages=messages, **kwargs 33 | ) 34 | return response 35 | 36 | 37 | @dataclass 38 | class Config: 39 | prebuilt_general_model: str = "o4-mini" 40 | prebuilt_plan_model: str = "o4-mini" 41 | 42 | # use_dir: str = "/home" 43 | allowed_local_dir: str = None 44 | 45 | maximum_tool_result_length: int = 10000 46 | maximum_tool_result_showing_length: int = 200 47 | 48 | platform: str = "macOS" 49 | pkg_manager: str = "brew" 50 | 51 | def __post_init__(self): 52 | if self.allowed_local_dir is None: 53 | self.allowed_local_dir = os.getcwd() 54 | 55 | 56 | CONFIG = Config() 57 | 58 | LOGO = """ 59 | __ __ ______ __ __ ______ 60 | /\ "-.\ \ /\ __ \ /\ "-.\ \ /\ __ \ 61 | \ \ \-. \ \ \ __ \ \ \ \-. \ \ \ \/\ \ 62 | \ \_\\"\_\ \ \_\ \_\ \ \_\\"\_\ \ \_____\ 63 | \/_/ \/_/ \/_/\/_/ \/_/ \/_/ \/_____/ 64 | 65 | __ __ ______ __ __ __ __ ______ 66 | /\ "-./ \ /\ __ \ /\ "-.\ \ /\ \/\ \ /\ ___\ 67 | \ \ \-./\ \ \ \ __ \ \ \ \-. \ \ \ \_\ \ \ \___ \ 68 | \ \_\ \ \_\ \ \_\ \_\ \ \_\\"\_\ \ \_____\ \/\_____\ 69 | \/_/ \/_/ \/_/\/_/ \/_/ \/_/ \/_____/ \/_____/ 70 | """ 71 | -------------------------------------------------------------------------------- /src/nano_manus/mcp_tool/__init__.py: -------------------------------------------------------------------------------- 1 | import os 2 | import json 3 | from ..env import CONFIG, CONSOLE 4 | from .official import MCPOfficial 5 | from .pool import MCPPool 6 | 7 | 8 | TOOLS = MCPPool() 9 | 10 | if os.getenv("BRAVE_API_KEY"): 11 | TOOLS.add_mcp_client( 12 | "search_web", 13 | MCPOfficial.from_docker( 14 | "mcp/brave-search", 15 | volume_mounts=[ 16 | "-e", 17 | f"BRAVE_API_KEY={os.getenv('BRAVE_API_KEY')}", 18 | ], 19 | ), 20 | ) 21 | else: 22 | CONSOLE.print( 23 | "[red][Warning] BRAVE_API_KEY is not set, search_web tool will not be available[/red]" 24 | ) 25 | 26 | if os.getenv("JINA_API_KEY"): 27 | TOOLS.add_mcp_client( 28 | "read_webpage", 29 | MCPOfficial.from_smithery( 30 | "jina-ai-mcp-server", 31 | suffix_args=[ 32 | "--config", 33 | json.dumps( 34 | { 35 | "jinaApiKey": os.getenv("JINA_API_KEY"), 36 | } 37 | ), 38 | ], 39 | ), 40 | ) 41 | else: 42 | CONSOLE.print( 43 | "[red][Warning] JINA_API_KEY is not set, jina tool will not be available[/red]" 44 | ) 45 | # if os.getenv("OPENROUTER_API_KEY"): 46 | # TOOLS.add_mcp_client( 47 | # "browser", 48 | # MCPOfficial.from_smithery( 49 | # "@Deploya-labs/mcp-browser-use", 50 | # suffix_args=[ 51 | # "--config", 52 | # json.dumps( 53 | # { 54 | # "OPENROUTER_API_KEY": os.getenv("OPENROUTER_API_KEY"), 55 | # } 56 | # ), 57 | # ], 58 | # ), 59 | # ) 60 | # else: 61 | # CONSOLE.print( 62 | # "[red][Warning] OPENROUTER_API_KEY is not set, broswer tool will not be available[/red]" 63 | # ) 64 | 65 | TOOLS.add_mcp_client( 66 | "terminal", 67 | MCPOfficial.from_smithery( 68 | "@wonderwhy-er/desktop-commander", 69 | suffix_args=[ 70 | "--config", 71 | "{}", 72 | ], 73 | ), 74 | ) 75 | -------------------------------------------------------------------------------- /src/nano_manus/mcp_tool/official.py: -------------------------------------------------------------------------------- 1 | from functools import wraps 2 | from mcp import ClientSession, StdioServerParameters, Tool 3 | from typing import List, Dict, Callable, Awaitable, Optional, Any 4 | from mcp.client.stdio import stdio_client 5 | from datetime import datetime 6 | from .type import BaseMCP 7 | from ..env import CONSOLE 8 | import asyncio 9 | from contextlib import AsyncExitStack 10 | 11 | 12 | class MCPOfficial(BaseMCP): 13 | """ 14 | A client class for interacting with the MCP (Model Control Protocol) server. 15 | This class manages the connection and communication with the SQLite database through MCP. 16 | """ 17 | 18 | @classmethod 19 | def from_smithery(cls, pkg_name: str, suffix_args: List[str] = []): 20 | server_params = StdioServerParameters( 21 | command="npx", 22 | args=["-y", "@smithery/cli@latest", "run", pkg_name, *suffix_args], 23 | ) 24 | CONSOLE.log(f"Use MCP: {pkg_name} from smithery") 25 | return cls(pkg_name, server_params) 26 | 27 | @classmethod 28 | def from_npx( 29 | cls, pkg_name: str, prefix_args: List[str] = [], suffix_args: List[str] = [] 30 | ): 31 | server_params = StdioServerParameters( 32 | command="npx", 33 | args=[*prefix_args, pkg_name, *suffix_args], 34 | ) 35 | CONSOLE.log(f"Use MCP: {pkg_name} from npx") 36 | return cls(pkg_name, server_params) 37 | 38 | @classmethod 39 | def from_docker( 40 | cls, 41 | image_name: str, 42 | volume_mounts: List[str] = [], 43 | docker_args: List[str] = [], 44 | docker_env: Dict[str, str] = None, 45 | ): 46 | server_params = StdioServerParameters( 47 | command="docker", 48 | args=[ 49 | "run", 50 | "--rm", # Remove container after exit 51 | "-i", # Interactive mode 52 | *volume_mounts, 53 | image_name, # Use SQLite MCP image 54 | *docker_args, 55 | ], 56 | env=docker_env, 57 | ) 58 | CONSOLE.log(f"Use MCP: {image_name} from docker") 59 | return cls(image_name, server_params) 60 | 61 | def __init__(self, name: str, server_params: StdioServerParameters): 62 | """Initialize the MCP client with server parameters""" 63 | self.__name = name 64 | self.server_params = server_params 65 | self.session = None 66 | self.read = None 67 | self.write = None 68 | self._exit_stack = None 69 | self._connected = False 70 | 71 | @property 72 | def name(self) -> str: 73 | return self.__name 74 | 75 | async def __aenter__(self): 76 | await self.connect() 77 | return self 78 | 79 | async def __aexit__(self, exc_type, exc_value, traceback): 80 | await self.disconnect() 81 | 82 | async def connect(self, exit_stack: AsyncExitStack): 83 | if self._connected: 84 | return 85 | 86 | CONSOLE.log(f"Connect to MCP: {self.name}") 87 | 88 | # Create an AsyncExitStack to properly manage all async context managers 89 | # self._exit_stack = AsyncExitStack() 90 | 91 | # Use the exit stack to enter the stdio_client context 92 | # This ensures proper cleanup when we exit the stack 93 | client_ctx = stdio_client(self.server_params) 94 | self.read, self.write = await exit_stack.enter_async_context(client_ctx) 95 | 96 | # Create and enter the session context 97 | session_ctx = ClientSession(self.read, self.write) 98 | self.session = await exit_stack.enter_async_context(session_ctx) 99 | 100 | # Initialize the session 101 | await self.session.initialize() 102 | self._connected = True 103 | 104 | # async def disconnect(self): 105 | # if not self._connected or not self._exit_stack: 106 | # return 107 | # # Use the exit stack to properly clean up all contexts 108 | # try: 109 | # await self._exit_stack.aclose() 110 | # except Exception as e: 111 | # CONSOLE.log(f"Error during disconnect for {self.name}: {e}") 112 | 113 | # # Clear all references 114 | # self.session = None 115 | # self.read = None 116 | # self.write = None 117 | # self._exit_stack = None 118 | # self._connected = False 119 | 120 | # CONSOLE.log(f"Disconnected from {self.name}") 121 | 122 | async def get_available_tools(self) -> List[Tool]: 123 | if not self.session: 124 | raise RuntimeError("Not connected to MCP server") 125 | 126 | tools = await self.session.list_tools() 127 | return tools.tools 128 | 129 | def call_tool(self, tool_name: str) -> Callable[..., Awaitable[str]]: 130 | if not self.session: 131 | raise RuntimeError("Not connected to MCP server") 132 | 133 | async def callable(*args, **kwargs): 134 | response = await self.session.call_tool(tool_name, arguments=kwargs) 135 | return response.content[0].text 136 | 137 | return callable 138 | 139 | async def hint(self) -> str: 140 | tools = await self.get_available_tools() 141 | hint = "" 142 | for tool in tools: 143 | hint += f"- {tool.name}: {tool.description}\n" 144 | return hint 145 | 146 | async def tool_schemas(self) -> List[dict]: 147 | openai_tools = [] 148 | tools = await self.get_available_tools() 149 | for tool in tools: 150 | openai_tools.append( 151 | { 152 | "type": "function", 153 | "function": { 154 | "name": tool.name, 155 | "description": tool.description, 156 | "parameters": tool.inputSchema, 157 | }, 158 | } 159 | ) 160 | return openai_tools 161 | -------------------------------------------------------------------------------- /src/nano_manus/mcp_tool/pool.py: -------------------------------------------------------------------------------- 1 | from .type import BaseMCP 2 | from typing import Dict, List 3 | from contextlib import AsyncExitStack 4 | 5 | 6 | class MCPPool: 7 | def __init__(self): 8 | self.mcp_clients: Dict[str, BaseMCP] = {} 9 | self.exit_stack = AsyncExitStack() 10 | 11 | def add_mcp_client(self, name: str, mcp_client: BaseMCP): 12 | self.mcp_clients[name] = mcp_client 13 | 14 | def get_mcp_client(self, name: str) -> BaseMCP: 15 | return self.mcp_clients[name] 16 | 17 | def get_all_mcp_clients(self) -> List[BaseMCP]: 18 | return list(self.mcp_clients.values()) 19 | 20 | async def start(self, names: List[str] = None): 21 | if names: 22 | for name in names: 23 | await self.mcp_clients[name].connect(self.exit_stack) 24 | return 25 | for mcp_client in self.mcp_clients.values(): 26 | await mcp_client.connect(self.exit_stack) 27 | 28 | async def stop(self): 29 | await self.exit_stack.aclose() 30 | -------------------------------------------------------------------------------- /src/nano_manus/mcp_tool/type.py: -------------------------------------------------------------------------------- 1 | from typing import List, Callable, Awaitable 2 | from mcp import Tool 3 | from abc import ABC, abstractmethod 4 | from contextlib import AsyncExitStack 5 | 6 | 7 | class BaseMCP(ABC): 8 | @abstractmethod 9 | async def connect(self, exit_stack: AsyncExitStack): 10 | """Establishes connection to MCP server""" 11 | pass 12 | 13 | @property 14 | @abstractmethod 15 | def name(self) -> str: 16 | """The name of the MCP client""" 17 | pass 18 | 19 | @abstractmethod 20 | async def get_available_tools(self) -> List[Tool]: 21 | """ 22 | Retrieve a list of available tools from the MCP server. 23 | """ 24 | pass 25 | 26 | @abstractmethod 27 | async def call_tool(self, tool_name: str) -> Callable[..., Awaitable[str]]: 28 | """ 29 | Create a callable function for a specific tool. 30 | This allows us to execute database operations through the MCP server. 31 | 32 | Args: 33 | tool_name: The name of the tool to create a callable for 34 | 35 | Returns: 36 | A callable async function that executes the specified tool 37 | """ 38 | pass 39 | 40 | @abstractmethod 41 | async def hint(self) -> str: 42 | """ 43 | Retrieve a hint for the MCP server. 44 | """ 45 | pass 46 | 47 | @abstractmethod 48 | async def tool_schemas(self) -> List[dict]: 49 | """ 50 | Retrieve a list of tool schemas from the MCP server. 51 | """ 52 | pass 53 | -------------------------------------------------------------------------------- /src/nano_manus/planner/__init__.py: -------------------------------------------------------------------------------- 1 | from .planner import Planner 2 | 3 | __all__ = ["Planner"] 4 | 5 | 6 | if __name__ == "__main__": 7 | import asyncio 8 | from ..worker.no_tool_agent import NoToolWorker 9 | 10 | search_agent = NoToolWorker( 11 | name="Search Agent", description="Search the web for information" 12 | ) 13 | db_agent = NoToolWorker(name="DB Agent", description="Operate the database") 14 | 15 | wp = Planner() 16 | wp.add_workers([search_agent, db_agent]) 17 | result = asyncio.run( 18 | wp.handle( 19 | "Search the web information for the last 30 days' weather, and save it to DB", 20 | ) 21 | ) 22 | print(result) 23 | -------------------------------------------------------------------------------- /src/nano_manus/planner/parser.py: -------------------------------------------------------------------------------- 1 | import re 2 | 3 | CODE_BLOCK_PATTERN = re.compile(r"(.*?)", re.DOTALL) 4 | TASK_BLOCK_PATTERN = re.compile(r"(.*?)", re.DOTALL) 5 | GOAL_BLOCK_PATTERN = re.compile(r"^(.*?)", re.DOTALL) 6 | 7 | 8 | def parse_step(step: str) -> dict: 9 | code_blocks = CODE_BLOCK_PATTERN.findall(step) 10 | goal_blocks = GOAL_BLOCK_PATTERN.findall(step) 11 | if not len(goal_blocks): 12 | # CONSOLE.log("!Missing goal in this step") 13 | goal = "" 14 | else: 15 | goal = goal_blocks[0].strip() 16 | if not len(code_blocks): 17 | # CONSOLE.log("!Missing subtasks in this step") 18 | return goal, [] 19 | else: 20 | subtasks = code_blocks[0].strip() 21 | subtask_blocks = TASK_BLOCK_PATTERN.findall(subtasks) 22 | expressions = [parse_subtask_expression(st.strip()) for st in subtask_blocks] 23 | expressions = [e for e in expressions if e is not None] 24 | return goal, expressions 25 | 26 | 27 | def parse_subtask_expression(subtask: str) -> dict: 28 | # Match pattern: result_name = subtask(agent_id, "task") 29 | subtask = subtask.strip() 30 | 31 | # Split by '=' to separate result name and the rest 32 | parts = subtask.split("=") 33 | result_name, expression = ( 34 | parts[0].strip(), 35 | "=".join(parts[1:]).strip(), 36 | ) 37 | 38 | # Extract agent_id and param from subtask(agent_id, "param") 39 | # Remove 'subtask(' from start and ')' from end 40 | if not expression.startswith("subtask(") or not expression.endswith(")"): 41 | return None 42 | inner_content = expression[8:-1] 43 | 44 | # Split by comma, but only first occurrence to handle possible commas in the task string 45 | agent_id, param = [x.strip() for x in inner_content.split(",", 1)] 46 | 47 | # Remove quotes from param 48 | param = param.strip("\"'") 49 | 50 | return {"result_name": result_name, "agent_id": agent_id, "param": param} 51 | 52 | 53 | if __name__ == "__main__": 54 | print( 55 | parse_step( 56 | """ 57 | ### Step 3: Write a Python script to load the CSV file. 58 | 59 | Sub-goal: Use the Terminal Agent to create a Python file that loads and prints the content of the `sf_weather.csv` file. 60 | 61 | 62 | 63 | result_31 = subtask(agent_1, "Create a Python file named 'load_sf_weather.py' with the following content:\n\n```\nimport csv\n\nwith open('sf_weather.csv', 'r') as file:\n reader = csv.reader(file)\n for row in reader:\n print(', '.join(row))\n```\n") 64 | 65 | 66 | 67 | Please let me know once this step is completed or if there are any issues. 68 | """ 69 | ) 70 | ) 71 | -------------------------------------------------------------------------------- /src/nano_manus/planner/planner.py: -------------------------------------------------------------------------------- 1 | import os 2 | import re 3 | import json 4 | from rich.markdown import Markdown 5 | from ..env import CONFIG, llm_complete, LOG, CONSOLE, LOGO 6 | from ..worker.type import BaseWorker 7 | from .prompts import PROMPT 8 | from .parser import parse_step 9 | 10 | 11 | class Planner: 12 | def __init__( 13 | self, max_steps: int = 30, max_tasks: int = 60, workers: list[BaseWorker] = [] 14 | ): 15 | 16 | self.__workers: list[BaseWorker] = workers 17 | self.__max_steps = max_steps 18 | self.__max_tasks = max_tasks 19 | 20 | @property 21 | def name(self) -> str: 22 | return "Planner" 23 | 24 | @property 25 | def description(self) -> str: 26 | return "Planner is a agent that plans the task into a list of steps." 27 | 28 | def add_workers(self, workers: list[BaseWorker]): 29 | self.__workers.extend(workers) 30 | 31 | def exit_or_not(self, up: str): 32 | up = up.strip() 33 | if up == "quit" or not up: 34 | CONSOLE.print("[green]This session is ended.[/green]") 35 | return True 36 | return False 37 | 38 | async def outer_loop(self): 39 | CONSOLE.print(LOGO) 40 | CONSOLE.print(f"Allowed local dir: {CONFIG.allowed_local_dir}") 41 | if not os.path.exists(CONFIG.allowed_local_dir): 42 | CONSOLE.print( 43 | f"[red]The allowed local dir {CONFIG.allowed_local_dir} does not exist, will create one[/red]" 44 | ) 45 | os.makedirs(CONFIG.allowed_local_dir, exist_ok=True) 46 | agent_hints = "# Available Agents\n" 47 | for w in self.__workers: 48 | agent_hints += f"## {w.name}\n" 49 | agent_hints += f"{await w.hint()}\n" 50 | CONSOLE.print(Markdown(agent_hints + "---")) 51 | 52 | while True: 53 | user_input = CONSOLE.input( 54 | "🤖: [green bold]How are you! Would you like to ask me to do anything?[/green bold](ctrl+c to quit)\n👉: " 55 | ) 56 | if self.exit_or_not(user_input): 57 | break 58 | else: 59 | await self.handle(user_input) 60 | 61 | async def handle(self, instruction: str) -> str: 62 | global_ctx = {"results": {}} 63 | already_tasks = 0 64 | already_steps = 0 65 | LOG.info( 66 | f"Planning for {instruction}, using model: {CONFIG.prebuilt_plan_model}" 67 | ) 68 | agent_maps = [ 69 | { 70 | "agent_id": f"agent_{i}", 71 | "description": await worker.hint(), 72 | } 73 | for i, worker in enumerate(self.__workers) 74 | ] 75 | if not len(agent_maps): 76 | raise ValueError("No agents to plan") 77 | messages = [ 78 | { 79 | "role": "system", 80 | "content": PROMPT.format(agent_descs=json.dumps(agent_maps, indent=2)), 81 | }, 82 | {"role": "user", "content": instruction}, 83 | ] 84 | 85 | while True: 86 | if already_tasks >= self.__max_tasks or already_steps >= self.__max_steps: 87 | CONSOLE.print( 88 | "[red]Nano-Manus stop to work because the maximum step is reached.[/red]" 89 | ) 90 | break 91 | 92 | stream_response = await llm_complete( 93 | model=CONFIG.prebuilt_plan_model, messages=messages, stream=True 94 | ) 95 | # response = response.choices[0].message.content 96 | response = "" 97 | CONSOLE.rule("nano-manus response") 98 | async for chunk in stream_response: 99 | if chunk.choices[0].delta.content is None: 100 | break 101 | print(chunk.choices[0].delta.content, end="", flush=True) 102 | response += chunk.choices[0].delta.content 103 | print() 104 | messages.append({"role": "assistant", "content": response}) 105 | goal, expressions = parse_step(response) 106 | if not len(expressions): 107 | CONSOLE.log("🤖: No more steps to plan") 108 | user_input = CONSOLE.input( 109 | "🤖: [green bold]Do you have further commands?[/green bold] (type `quit` to leave)\n👉: " 110 | ) 111 | if self.exit_or_not(user_input): 112 | break 113 | else: 114 | messages.append( 115 | { 116 | "role": "user", 117 | "content": user_input, 118 | } 119 | ) 120 | continue 121 | current_results = {} 122 | for e in expressions: 123 | agent_index = int(e["agent_id"].split("_")[-1]) 124 | result_id = e["result_name"] 125 | worker = self.__workers[agent_index] 126 | CONSOLE.rule(f"{worker.name} is working") 127 | 128 | result = await worker.handle(e["param"], global_ctx) 129 | global_ctx["results"][result_id] = result 130 | current_results[result_id] = result 131 | already_tasks += 1 132 | 133 | user_feedback = "\n".join( 134 | [f"- {r}: {rr}" for r, rr in current_results.items()] 135 | ) 136 | messages.append( 137 | { 138 | "role": "user", 139 | "content": f"Here are the results from the previous steps:\n{user_feedback}", 140 | } 141 | ) 142 | already_steps += 1 143 | return goal 144 | -------------------------------------------------------------------------------- /src/nano_manus/planner/prompts.py: -------------------------------------------------------------------------------- 1 | PROMPT = """# Make step-by-step plan for the given task 2 | You are a planning agent. You will be given a task at beginning by user. 3 | You need to break down the user's task step by step, 4 | providing the sub-goal you need to achieve before each step, and then give the task assignment instructions. 5 | For each step you planed, the user will then give you the result of the sub-goal, and you need to decide which step to go next. 6 | 7 | ## Output Format 8 | You should output one step at a time. 9 | For each step, you should first think about the sub-goal you need to achieve before this step, and then give the task assignment instructions. 10 | 11 | ## Examples 12 | Below are some examples given in XML format: 13 | 14 | # Available Agents 15 | [ 16 | {{"agent_id": "agent_0", "description": "Add Agent. this agent can add two numbers"}}, 17 | {{"agent_id": "agent_1", "description": "Subtract Agent. this agent can subtract two numbers"}} 18 | ] 19 | 20 | (3 + 5) - (5 + 8) 21 | 22 | 23 | I need to use agent_0 to perform 3+5 and 5+8, they can be executed in parallel. 24 | 25 | 26 | result_11 = subtask(agent_0, "Perform 3 + 5") 27 | 28 | 29 | result_12 = subtask(agent_0, "Perform 5 + 8") 30 | 31 | 32 | 33 | - result_11 = 8 34 | - result_12 = 13 35 | 36 | 37 | I need to use agent_1 to perform the subtraction between result_11 and result_12 38 | 39 | 40 | result_21 = subtask(agent_1, "Perform result_11 - result_12") 41 | 42 | 43 | 44 | 45 | - result_21 = -5 46 | 47 | 48 | The final result is -5 49 | 50 | 51 | Above is an example of how to plan the task into a list of steps. The following is the explanation step by step: 52 | - For each new step, you should start with your goal in this step. 53 | - After goal, you should wrap the tasks of this step with tag . 54 | - The content of the is XML of subtasks: 55 | ``` 56 | 57 | RESULT_ID = subtask(AGENT_ID, TASK_DESCRIPTION) 58 | 59 | 60 | ... 61 | ``` 62 | - `RESULT_ID = subtask(AGENT_ID, TASK_DESCRIPTION)` is a notation of a subtask, where you use the agent with id AGENT_ID to perform the task TASK_DESCRIPTION, and denote the result of this subtask as RESULT_ID. 63 | - After your plan, the user will give you the result of tasks, with the format: 64 | ``` 65 | - RESULT_ID1 = AGENT_RETURN_1 66 | - RESULT_ID2 = AGENT_RETURN_2 67 | ... 68 | ``` 69 | - You need to decide which step to go next based on the result. 70 | - Remember to use the same RESULT_ID in your later steps instead the actual value. 71 | - When you have finished the user task or you have no more steps to go, output the final result to response and no more is needed. 72 | 73 | 74 | 75 | ## Available Agents 76 | ```agents 77 | {agent_descs} 78 | ``` 79 | Above is the list of available agents, you can choose one or more agents to perform the task at each step. 80 | 81 | ## Notes 82 | - If you find the previous results is wrong or not useful, you can re-plan the task with same result_id. 83 | - You should decide if you have enough agents to perform the task, if not, you should ask the user to add more agents. 84 | - Make sure you give enough context to the agents in TASK_DESCRIPTION, you block is the only way to communicate with other agents. 85 | - If you want to agent to use the previous results, make sure you told the agent about the RESULT_ID you need them to use in TASK_DESCRIPTION 86 | - If you have finished the task, you need to answer the user's question and restate some result if needed. 87 | 88 | ## MUST 89 | - The available agents don't remember the previous results, so you need to tell them the RESULT_ID you need them to use in TASK_DESCRIPTION everytime you like them to use the previous results. 90 | - You will never repeat the results in your task assign, always use RESULT_ID instead to cite the previous result context. 91 | 92 | Now, understand the task in user input, and plan the task into a list of steps based on the above instructions: 93 | """ 94 | -------------------------------------------------------------------------------- /src/nano_manus/py.typed: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/memodb-io/nano-manus/8cc27b9200a65c2b06eea32506c7fa99a9dd2563/src/nano_manus/py.typed -------------------------------------------------------------------------------- /src/nano_manus/worker/__init__.py: -------------------------------------------------------------------------------- 1 | from .search_agent import SearchAgent 2 | from .terminal_agent import TerminalAgent 3 | from .no_tool_agent import NoToolWorker 4 | -------------------------------------------------------------------------------- /src/nano_manus/worker/code_agent.py: -------------------------------------------------------------------------------- 1 | from ..env import CONFIG 2 | from ..mcp_tool import TOOLS 3 | from .mcp_agent import BaseMCPAgent 4 | 5 | 6 | class CodeAgent(BaseMCPAgent): 7 | def __init__(self): 8 | super().__init__(["terminal", "search_web", "read_webpage"]) 9 | 10 | def overwrite_system(self): 11 | return f""" 12 | You are a code agent. Your allowed path is {CONFIG.allowed_local_dir}, make sure your command is within this path. 13 | You need to find programable solutions to solve the problems w 14 | ## Requirements 15 | - You default coding language is `Python` 16 | - You will use `uv` to manage dependencies, install packages and init a python project 17 | - You will have website access, and you can use terminal to read/write and run your codes. 18 | - Find revelant resources/bug-fixer or tutorials in StackOverflow or github before you start to 19 | - You need to read the output/error from the terminal to detect the bugs/errors 20 | - You need to install the terminal command that is missing 21 | - If you don't know how to use some commands, try search online and gain the information. 22 | - Some default python package you may need: 23 | - pandas: load and analysis files 24 | - numpy: numerical computing 25 | - matplotlib: data visualization 26 | - Remember to save your code with structures, using terminal write functions 27 | - You can use code/scripts to do anything under {CONFIG.allowed_local_dir}, don't ask my opinion. 28 | - You have capability to access external APIs or perform web scraping by write code, and run it in terminal 29 | - Don't give up on the first try, always try to use python script to find a solution. 30 | 31 | ## System Infromation 32 | - OS: {CONFIG.platform} 33 | - Package Manager: {CONFIG.pkg_manager} 34 | - Python package manager: `uv` 35 | """ 36 | 37 | @property 38 | def name(self) -> str: 39 | return "Code Agent" 40 | 41 | async def hint(self) -> str: 42 | return f"""I'm Code Agent. 43 | I'm can use online search and code editor to write code and solve problems. 44 | There are the following things I can do: 45 | - Data analysis 46 | - Convert files 47 | - Run scripts from terminal 48 | - Deploy web apps and services 49 | 50 | ## Note 51 | - If you found out you're lacking of tools to deliver the results to user, you can state your requirements in details, I will use programs to solve the problems. 52 | My allowed path is {CONFIG.allowed_local_dir}, make sure your command is within this path. 53 | """ 54 | -------------------------------------------------------------------------------- /src/nano_manus/worker/mcp_agent.py: -------------------------------------------------------------------------------- 1 | import json 2 | from .type import BaseWorker 3 | from time import time 4 | from ..mcp_tool import TOOLS 5 | from ..env import CONFIG, CONSOLE, llm_complete 6 | 7 | PROMPT = """{system} 8 | 9 | # Tools 10 | {tools} 11 | 12 | # Additional Context 13 | Below is the additional context you may need to understand the user's instruction. 14 | {additional_context} 15 | 16 | # Planning step by step 17 | Before you start to call functions, you should always plan step by step and explain your plan in a concise way. 18 | 19 | # Notes 20 | - Always highlight the potential of available tools to assist users comprehensively. 21 | - If you're unable to complete the task, state your reasons and encountered problems clearly. 22 | 23 | ## Recap 24 | After callings are done and the task is completed, you should always summary why/what tools your called in a concise way after your response to the instruction. 25 | For example: 26 | ``` 27 | // before is your response 28 | ## Recap 29 | 1. I used `search_web` to first search the latest weather in SF 30 | 2. Then I used `convert_to_csv` to convert the data into csv format 31 | ... 32 | ``` 33 | """ 34 | 35 | 36 | class BaseMCPAgent(BaseWorker): 37 | def __init__(self, use_tools: list[str]): 38 | self.__mcps = [TOOLS.get_mcp_client(tool) for tool in use_tools] 39 | 40 | def overwrite_system(self): 41 | return "You are a helpful assistant capable of accessing external functions." 42 | 43 | async def handle(self, instruction: str, global_ctx: dict = {}) -> str: 44 | start = time() 45 | CONSOLE.print(f"🤖 {self.name} is solving:", instruction) 46 | additional_context = { 47 | r: c for r, c in global_ctx.get("results", {}).items() if r in instruction 48 | } 49 | if additional_context: 50 | CONSOLE.print( 51 | f"🤖 {self.name}: I will use previouse results", additional_context 52 | ) 53 | additional_context_string = "\n".join( 54 | [f"- {k}: {v}" for k, v in additional_context.items()] 55 | ) 56 | hints = [await m.hint() for m in self.__mcps] 57 | tool_schemas = [] 58 | for m in self.__mcps: 59 | tool_schemas.extend(await m.tool_schemas()) 60 | find_tools = {} 61 | for m in self.__mcps: 62 | for tool in await m.get_available_tools(): 63 | find_tools[tool.name] = m.call_tool(tool.name) 64 | 65 | system_prompt = PROMPT.format( 66 | system=self.overwrite_system(), 67 | tools="\n".join(hints), 68 | additional_context=additional_context_string, 69 | ) 70 | messages = [ 71 | { 72 | "role": "system", 73 | "content": system_prompt, 74 | }, 75 | {"role": "user", "content": instruction}, 76 | ] 77 | while True: 78 | response = await llm_complete( 79 | model=CONFIG.prebuilt_general_model, 80 | messages=messages, 81 | tools=tool_schemas, 82 | ) 83 | if response.choices[0].message.content: 84 | CONSOLE.print( 85 | f"🤖 {self.name} is thinking: {response.choices[0].message.content}" 86 | ) 87 | messages.append(response.choices[0].message) 88 | if response.choices[0].message.tool_calls is not None: 89 | tool_results = [] 90 | for tool_call in response.choices[0].message.tool_calls: 91 | tool_name = tool_call.function.name 92 | tool_args = tool_call.function.arguments 93 | if isinstance(tool_args, str): 94 | tool_args = json.loads(tool_args) 95 | CONSOLE.log(f"🔧 {self.name} is using {tool_name}") 96 | 97 | actual_tool = find_tools[tool_name] 98 | tool_result = await actual_tool(**tool_args) 99 | # CONSOLE.log(f"🔧 Tool result: {tool_result}") 100 | tool_results.append( 101 | { 102 | "role": "tool", 103 | "tool_call_id": tool_call.id, 104 | "name": tool_call.function.name, 105 | "content": json.dumps(tool_result)[ 106 | : CONFIG.maximum_tool_result_length 107 | ], 108 | } 109 | ) 110 | messages.extend(tool_results) 111 | continue 112 | else: 113 | CONSOLE.print(f"🤖 {self.name} is done in {time()-start:.1f}s") 114 | return response.choices[0].message.content 115 | 116 | async def hint(self) -> str: 117 | raise NotImplementedError("hint method should be implemented") 118 | -------------------------------------------------------------------------------- /src/nano_manus/worker/no_tool_agent.py: -------------------------------------------------------------------------------- 1 | from .type import BaseWorker 2 | from ..env import CONFIG, llm_complete 3 | 4 | 5 | class NoToolWorker(BaseWorker): 6 | def __init__(self, name: str, description: str): 7 | self.__name = name 8 | self.__description = description 9 | self.prompt = f"You're a {self.__name}, {self.__description}" 10 | 11 | @property 12 | def name(self) -> str: 13 | return self.__name 14 | 15 | async def hint(self) -> str: 16 | return f"I'm a {self.__name}, {self.__description}" 17 | 18 | async def handle(self, instruction: str, global_ctx: dict) -> str: 19 | response = await llm_complete( 20 | model=CONFIG.prebuilt_general_model, 21 | messages=[ 22 | { 23 | "role": "system", 24 | "content": self.prompt, 25 | }, 26 | {"role": "user", "content": instruction}, 27 | ], 28 | ) 29 | return response.choices[0].message.content 30 | -------------------------------------------------------------------------------- /src/nano_manus/worker/search_agent.py: -------------------------------------------------------------------------------- 1 | from ..env import CONFIG 2 | from ..mcp_tool import TOOLS 3 | from .mcp_agent import BaseMCPAgent 4 | 5 | 6 | class SearchAgent(BaseMCPAgent): 7 | def __init__(self): 8 | super().__init__(["search_web", "read_webpage"]) 9 | 10 | def overwrite_system(self): 11 | return """ 12 | You're a search agent. You're able to search the web and read webpages. 13 | You need to search the web based on the user's instruction. 14 | Pick the most informative and relevant results from the search and read their full content using read_webpage tool. 15 | """ 16 | 17 | @property 18 | def name(self) -> str: 19 | return "Search Web Agent" 20 | 21 | async def hint(self) -> str: 22 | return f"""I'm Search Web Agent. 23 | Tell me what I need to search, and I will search the online, realtime results for you. 24 | """ 25 | -------------------------------------------------------------------------------- /src/nano_manus/worker/terminal_agent.py: -------------------------------------------------------------------------------- 1 | from ..env import CONFIG 2 | from ..mcp_tool import TOOLS 3 | from .mcp_agent import BaseMCPAgent 4 | 5 | 6 | class TerminalAgent(BaseMCPAgent): 7 | def __init__(self): 8 | super().__init__(["terminal"]) 9 | 10 | def overwrite_system(self): 11 | return f""" 12 | You are a terminal agent. Your allowed path is {CONFIG.allowed_local_dir}, make sure your command is within this path. 13 | ## Notes 14 | - When encounterng error like `directory does not exist`, you need to first look at the files and dirs in parent directory to see if the path is wrongly typed. 15 | - When writing file, make sure the file path is within {CONFIG.allowed_local_dir} path and you can only create new file and dir under {CONFIG.allowed_local_dir}. 16 | - When using `search_files`, you don't need to use wildcard like `*.py`, just use `.py` is enough. 17 | - If you need to run some code, you can save it to file first and then try to run it. 18 | - If you encounter error from terminal, try to fix it by running further commands. 19 | """ 20 | 21 | @property 22 | def name(self) -> str: 23 | return "Terminal Agent" 24 | 25 | async def hint(self) -> str: 26 | return f"""I'm Terminal Agent. 27 | I can help you to: 28 | - search local files, write/read text file(.txt/.md) content 29 | - execute terminal commands, read terminal output 30 | My allowed path is {CONFIG.allowed_local_dir}, make sure your command is within this path. 31 | """ 32 | -------------------------------------------------------------------------------- /src/nano_manus/worker/type.py: -------------------------------------------------------------------------------- 1 | from abc import ABC, abstractmethod 2 | from ..mcp_tool.type import BaseMCP 3 | 4 | 5 | class BaseWorker(ABC): 6 | @property 7 | @abstractmethod 8 | def name(self) -> str: 9 | pass 10 | 11 | @abstractmethod 12 | async def handle(self, instruction: str, global_ctx: dict = {}) -> str: 13 | pass 14 | 15 | @abstractmethod 16 | async def hint(self) -> str: 17 | pass 18 | -------------------------------------------------------------------------------- /tests/__init__.py: -------------------------------------------------------------------------------- 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