Quick Start

Installation

You can install TaskWeaver by running the following command:

# [optional] create a conda environment to isolate the dependencies
# conda create -n taskweaver python=3.10
# conda activate taskweaver

# clone the repository
git clone https://github.com/microsoft/TaskWeaver.git
cd TaskWeaver
# install the requirements
pip install -r requirements.txt

Project Directory

TaskWeaver runs as a process, you need to create a project directory to store plugins and configuration files. We provided a sample project directory in the project folder. You can copy the project folder to your workspace. A project directory typically contains the following files and folders:

📦project
 ┣ 📜taskweaver_config.json # the configuration file for TaskWeaver
 ┣ 📂plugins # the folder to store plugins
 ┣ 📂planner_examples # the folder to store planner examples
 ┣ 📂codeinterpreter_examples # the folder to store code interpreter examples
 ┣ 📂sample_data # the folder to store sample data used for evaluations
 ┣ 📂logs # the folder to store logs, will be generated after program starts
 ┗ 📂workspace # the directory stores session data， will be generated after program starts
    ┗ 📂 session_id 
      ┣ 📂ces # the folder used by the code execution service
      ┗ 📂cwd # the current working directory to run the generated code

OpenAI Configuration

Before running TaskWeaver, you need to provide your OpenAI API key and other necessary information. You can do this by editing the taskweaver_config.json file. If you are using Azure OpenAI, you need to set the following parameters in the taskweaver_config.json file:

Azure OpenAI

{
"llm.api_base": "https://xxx.openai.azure.com/",
"llm.api_key": "your_api_key",
"llm.api_type": "azure",
"llm.api_version": "the api version",
"llm.model": "the model name, e.g., gpt-4"
}

OpenAI

{
"llm.api_key": "the api key",
"llm.model": "the model name, e.g., gpt-4"
}

💡 Only the latest OpenAI API supports the json_object response format. If you are using an older version of OpenAI API, you need to set the llm.response_format to null.

More configuration options can be found in the configuration documentation.

Start TaskWeaver

# assume you are in the taskweaver folder
# -p is the path to the project directory
python -m taskweaver -p ./project/

This will start the TaskWeaver process and you can interact with it through the command line interface. If everything goes well, you will see the following prompt:

=========================================================
 _____         _     _       __
|_   _|_ _ ___| | _ | |     / /__  ____ __   _____  _____
  | |/ _` / __| |/ /| | /| / / _ \/ __ `/ | / / _ \/ ___/
  | | (_| \__ \   < | |/ |/ /  __/ /_/ /| |/ /  __/ /
  |_|\__,_|___/_|\_\|__/|__/\___/\__,_/ |___/\___/_/
=========================================================
TaskWeaver: I am TaskWeaver, an AI assistant. To get started, could you please enter your request?
Human: ___