> ## Documentation Index
> Fetch the complete documentation index at: https://docs.agentscope.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Quickstart

> Get up and running with AgentScope 2.0 in minutes

## Installation

AgentScope requires Python 3.11+, and you can install it from PyPI or from source.

It's recommended to install AgentScope by using [uv](https://github.com/astral-sh/uv).

### From PyPI

```bash theme={null}
uv pip install agentscope
```

### From Source

```bash theme={null}
git clone -b main https://github.com/agentscope-ai/agentscope
cd agentscope
uv pip install -e .
```

### Verify Installation

To ensure AgentScope is installed successfully, check via executing the following code:

```python theme={null}
import agentscope

print(agentscope.__version__)
```

## Your First Agent

The snippet below builds the minimal agent: a DashScope credential, the matching chat model, an empty toolkit, and an `Agent`. The agent exposes two entry points — `reply` returns the final message, while `reply_stream` yields incremental events as the agent reasons and acts.

```python theme={null}
import asyncio
import os

from agentscope.agent import Agent
from agentscope.credential import DashScopeCredential
from agentscope.event import EventType
from agentscope.message import UserMsg
from agentscope.model import DashScopeChatModel
from agentscope.tool import Toolkit, Bash, Read, Write, Edit


async def main() -> None:
    agent = Agent(
        name="Friday",
        system_prompt="You are a helpful assistant named Friday.",
        model=DashScopeChatModel(
            credential=DashScopeCredential(
                api_key=os.getenv("DASHSCOPE_API_KEY"),
            ),
            model="qwen-plus",
        ),
        toolkit=Toolkit(tools=[Bash(), Read(), Write(), Edit()]),
    )

    user_msg = UserMsg(name="user", content="Hello, who are you?")

    # Option 1: await the final assistant message.
    reply_msg = await agent.reply(user_msg)
    # `reply_msg` is an `AssistantMsg` whose `content` is a list of blocks.
    # Inspect text blocks, tool calls, etc. as needed.
    ...

    # Option 2: stream incremental events (text deltas, tool calls, ...).
    async for event in agent.reply_stream(user_msg):
        # Dispatch on `event.type` — each branch handles one event kind.
        match event.type:
            case EventType.TEXT_BLOCK_DELTA:
                # Streaming text chunk from the model — append to UI / stdout.
                ...
            case EventType.TOOL_CALL_START:
                # The agent is about to invoke a tool — surface the call.
                ...
            case _:
                # Other events: thinking blocks, tool results, reply end, ...
                ...


asyncio.run(main())
```

<Tip>
  Set `DASHSCOPE_API_KEY` in your environment before running the script. To use a different provider, swap `DashScopeCredential` and `DashScopeChatModel` for the matching pair (e.g. `OpenAICredential` and `OpenAIChatModel`).
</Tip>

## Extra Dependencies

To satisfy the requirements of different functionalities, AgentScope provides extra dependencies that can be installed based on your needs.

* **full**: including extra dependencies for model APIs, tool functions and more.
* **dev**: development dependencies, including testing and documentation tools.

For example, when installing the full dependencies, the installation command varies depending on your operating system.

* For Windows users:

```bash theme={null}
uv pip install agentscope[full]
```

* For Mac and Linux users:

```bash theme={null}
uv pip install agentscope\[full\]
```