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116 lines
4.1 KiB
Markdown
116 lines
4.1 KiB
Markdown
# 🐺⚔️👨🌾 Nine-Player Werewolves Game
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This is a nine-players werewolves game example built using AgentScope, showcasing **multi-agent interactions**,
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**role-based gameplay**, and **structured output handling**.
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Specifically, this game is consisted of
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- three villagers 👨🌾,
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- three werewolves 🐺,
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- one seer 🔮,
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- one witch 🧙♀️ and
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- one hunter 🏹.
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## ✨Changelog
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- 2025-10: We update the example to support more features:
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- Allow the dead players to leave messages.
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- Support Chinese now.
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- Support **continuous gaming** by loading and saving session states, so the same agents can play multiple games and continue learning and optimizing their strategies.
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## QuickStart
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Run the following command to start the game, ensuring you have set up your DashScope API key as an environment variable.
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```bash
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python main.py
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```
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> Note:
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> - You can adjust the language, model and other parameters in `main.py`.
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> - Different models may yield different game experiences.
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Running the example with AgentScope Studio provides a more interactive experience.
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- Demo Video in Chinese (click to play):
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[](https://cloud.video.taobao.com/vod/KxyR66_CWaWwu76OPTvOV2Ye1Gas3i5p4molJtzhn_s.mp4)
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- Demo Video in English (click to play):
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[](https://cloud.video.taobao.com/vod/bMiRTfxPg2vm76wEoaIP2eJfkCi8CUExHRas-1LyK1I.mp4)
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## Details
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The game is built with the ``ReActAgent`` in AgentScope, utilizing its ability to generate structured outputs to
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control the game flow and interactions.
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We also use the ``MsgHub`` and pipelines in AgentScope to manage the complex interactions like discussion and voting.
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It's very interesting to see how agents play the werewolf game with different roles and objectives.
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# Advanced Usage
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## Change Language
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The game is played in English by default. Just uncomment the following line in `game.py` to switch to Chinese.
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```python
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# from prompt import ChinesePrompts as Prompts
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```
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## Play with Agents
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You can replace one of the agents with a `UserAgent` to play with AI agents.
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## Change Models
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Just modify the `model` parameter in `main.py` to try different models. Note you need to change the formatter at the same time to match the model's output format.
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## Enable Text-to-Speech (TTS)
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The game supports Text-to-Speech functionality. To enable TTS:
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1. **In `main.py`**:
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- Uncomment the import statement:
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```python
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import random
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from agentscope.tts import DashScopeTTSModel
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```
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- Uncomment the `tts_model` parameter in the `get_official_agents` function:
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```python
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tts_model=DashScopeTTSModel(
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api_key=os.environ.get("DASHSCOPE_API_KEY"),
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model_name="qwen3-tts-flash",
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voice=random.choice(["Cherry", "Serena", "Ethan", "Chelsie"]),
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stream=True,
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),
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```
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2. **In `game.py`** (optional, for moderator TTS):
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- Uncomment the import statement:
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```python
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import random
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from agentscope.tts import DashScopeTTSModel
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```
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- Uncomment the `tts_model` parameter in the `moderator` initialization:
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```python
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tts_model=DashScopeTTSModel(
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api_key=os.environ.get("DASHSCOPE_API_KEY"),
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model_name="qwen3-tts-flash",
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voice=random.choice(["Cherry", "Serena", "Ethan", "Chelsie"]),
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stream=True,
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),
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```
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3. **Set up your API key**:
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- Make sure you have set the `DASHSCOPE_API_KEY` environment variable.
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After enabling TTS, the game will synthesize speech for player messages and moderator announcements, providing a more immersive audio experience.
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## Further Reading
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- [Structured Output](https://doc.agentscope.io/tutorial/task_agent.html#structured-output)
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- [MsgHub and Pipelines](https://doc.agentscope.io/tutorial/task_pipeline.html)
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- [Prompt Formatter](https://doc.agentscope.io/tutorial/task_prompt.html)
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- [AgentScope Studio](https://doc.agentscope.io/tutorial/task_studio.html)
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- [TTS](https://doc.agentscope.io/tutorial/task_tts.html)
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