chore: initialize sandbox and overwrite remote content

docs/tutorial/en/src/task_token.py

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+# -*- coding: utf-8 -*-
+"""
+.. _token:
+
+Token
+=========================
+
+AgentScope provides a token counter module under ``agentscope.token`` to
+calculate the number of tokens in the given messages, allowing developers
+to estimate the number of tokens in a prompt before sending it to an API.
+
+Specifically, the following token counters are available:
+
+.. list-table::
+    :header-rows: 1
+
+    * - Provider
+      - Class
+      - Support Image Data
+      - Support Tools
+    * - Anthropic
+      - ``AnthropicTokenCounter``
+      - ✅
+      - ✅
+    * - OpenAI
+      - ``OpenAITokenCounter``
+      - ✅
+      - ✅
+    * - Gemini
+      - ``GeminiTokenCounter``
+      - ✅
+      - ✅
+    * - HuggingFace
+      - ``HuggingFaceTokenCounter``
+      - Depends on the model
+      - Depends on the model
+
+.. tip:: The formatter module has integrated the token counters to support prompt truncation. Refer to the :ref:`prompt` section for more details.
+
+.. note:: For DashScope models, the dashscope library doesn't provide a token counting API. So we recommend using the HuggingFace token counter instead.
+
+We show an example of using the OpenAI token counter to count the number of tokens:
+"""
+
+import asyncio
+from agentscope.token import OpenAITokenCounter
+
+
+async def example_token_counting():
+    # Example messages
+    messages = [
+        {"role": "user", "content": "Hello!"},
+        {"role": "assistant", "content": "Hi, how can I help you?"},
+    ]
+
+    # OpenAI token counting
+    openai_counter = OpenAITokenCounter(model_name="gpt-4.1")
+    n_tokens = await openai_counter.count(messages)
+
+    print(f"Number of tokens: {n_tokens}")
+
+
+asyncio.run(example_token_counting())
+
+
+# %%
+# Further Reading
+# ------------------------------
+#
+# - :ref:`prompt`
+#