AgenticSeek：完全本地的 Manus AI 替代方案，可自主浏览网页、写代码、规划并执行复杂任务

Before you begin, ensure you have the following software installed:

• Git: For cloning the repository. Download Git

Python 3.10.x: We strongly recommend using Python version 3.10.x. Using other versions might lead to dependency errors. Download Python 3.10 (pick a 3.10.x version).

Docker Engine & Docker Compose: For running bundled services like SearxNG.

• Install Docker Desktop (which includes Docker Compose V2): Windows | Mac | Linux

Alternatively, install Docker Engine and Docker Compose separately on Linux:

Docker Engine | Docker Compose (ensure you install Compose V2, e.g., sudo apt-get install docker-compose-plugin ).

1. Clone the repository and setup

git clone https://github.com/Fosowl/agenticSeek.git

cd agenticSeek

mv .env.example .env

SEARXNG_BASE_URL= " http://searxng:8080 " # value depends on where the backend runs — see the SEARXNG note below

1. Change the .env file content

SEARXNG_PORT=8080

REDIS_BASE_URL= " redis://redis:6379/0 " WORK_DIR= " /Users/mlg/Documents/workspace_for_ai " OLLAMA_PORT= " 11434 " LM_STUDIO_PORT= " 1234 " CUSTOM_ADDITIONAL_LLM_PORT= " 11435 " OPENAI_API_KEY= ' optional ' DEEPSEEK_API_KEY= ' optional ' OPENROUTER_API_KEY= ' optional ' TOGETHER_API_KEY= ' optional ' GOOGLE_API_KEY= ' optional ' ANTHROPIC_API_KEY= ' optional ' Update the .

env file with your own values as needed:

How you run AgenticSeek SEARXNG_BASE_URL Web interface — backend in Docker ( ./start_services.sh full ) http://searxng:8080 — always port 8080 , even if you changed SEARXNG_PORT CLI mode — backend on host ( uv run cli.

py ) http://localhost:8080 — if you changed SEARXNG_PORT , use that port instead (e.g. http://localhost:8001 ). http://searxng:.

does not work here: that hostname only exists inside Docker To check SearXNG in a browser, always use the host port: http://localhost:<SEARXNG_PORT> . After changing .env , restart the backend — the file is only read at process start.

API Key are totally optional for user who choose to run LLM locally. Which is the primary purpose of this project. Leave empty if you have sufficient hardware

• SEARXNG_PORT : The host port Docker publishes SearXNG on. If port 8080 is already taken on your machine, set another one (e.g. 8001 ). Inside Docker the container always listens on 8080 — this variable never changes that.
• SEARXNG_BASE_URL : The address the backend uses to reach SearXNG. It is set here in .env (not in config.ini ) and depends only on where the backend runs:
• REDIS_BASE_URL : Leave unchanged
• WORK_DIR : Path to your working directory on your local machine. AgenticSeek will be able to read and interact with these files.
• OLLAMA_PORT : Port number for the Ollama service.
• LM_STUDIO_PORT : Port number for the LM Studio service.
• CUSTOM_ADDITIONAL_LLM_PORT : Port for any additional custom LLM service.

1. Start Docker

Make sure Docker is installed and running on your system. You can start Docker using the following commands:

- On Linux/macOS: Open a terminal and run: sudo systemctl start docker Or launch Docker Desktop from your applications menu if installed. - On Windows: Start Docker Desktop from the Start menu. You can verify Docker is running by executing:

docker info

If you see information about your Docker installation, it is running correctly. See the table of Local Providers below for a summary. Next step: Run AgenticSeek locally See the Troubleshooting section if you are having issues.

If your hardware can't run LLMs locally, see Setup to run with an API . For detailed config.ini explanations, see Config Section . Setup for running LLM locally on your machine Hardware Requirements: To run LLMs locally, you'll need sufficient hardware.

At a minimum, a GPU capable of running Magistral, Qwen or Deepseek 14B is required. See the FAQ for detailed model/performance recommendations.

Setup your local provider Start your local provider (for example with ollama): Unless you wish to to run AgenticSeek on host (CLI mode), export or set the provider listen address:

export OLLAMA_HOST=0.0.0.0:11434

Then, start you provider: ollama serve See below for a list of local supported provider. Update the config.ini Change the config.ini file to set the provider_name to a supported provider and provider_model to a LLM supported by your provider.

We recommend reasoning model such as Magistral or Deepseek . See the FAQ at the end of the README for required hardware. [MAIN] is_local = True # Whenever you are running locally or with remote provider. provider_name = ollama # or lm-studio, openai, etc.

provider_model = deepseek-r1:14b # choose a model that fit your hardware provider_server_address = 127.0.0.

1:11434 agent_name = Jarvis # name of your AI recover_last_session = True # whenever to recover the previous session save_session = True # whenever to remember the current session speak = False # text to speech listen = False # Speech to text, only for CLI, experimental jarvis_personality = False # Whenever to use a more "Jarvis" like personality (experimental) languages = en zh # The list of languages, Text to speech will default to the first language on the list [BROWSER] headless_browser = True # leave unchanged unless using CLI on host.

stealth_mode = True # Use undetected selenium to reduce browser detection Warning : - The config.ini file format does not support comments. Do not copy and paste the example configuration directly, as comments will cause errors.

Instead, manually modify the config.ini file with your desired settings, excluding any comments.