feat: context token counting support for multimodal content (images, audio, and chain-of-thought) (#6596)

EstimateTokenCounter 之前只计算 TextPart，完全忽略 ImageURLPart、
AudioURLPart 和 ThinkPart。多模态对话中图片占 500-2000 token，
不被计入会导致 context 压缩触发过晚，API 先报 context_length_exceeded。

改动：
- ImageURLPart 按 765 token 估算（OpenAI vision 低/高分辨率中位数）
- AudioURLPart 按 500 token 估算
- ThinkPart 的文本内容正常计算
- 10 个新测试覆盖各类型单独和混合场景

Co-authored-by: Yufeng He <40085740+universeplayer@users.noreply.github.com>

astrbot/core/agent/context/token_counter.py

@@ -1,7 +1,7 @@
 import json
 from typing import Protocol, runtime_checkable
 
-from ..message import Message, TextPart
+from ..message import AudioURLPart, ImageURLPart, Message, TextPart, ThinkPart
 
 
 @runtime_checkable
@@ -28,9 +28,19 @@ class TokenCounter(Protocol):
         ...
 
 
+# 图片/音频 token 开销估算值，参考 OpenAI vision pricing:
+# low-res ~85 tokens, high-res ~170 per 512px tile, 通常几百到上千。
+# 这里取一个保守中位数，宁可偏高触发压缩也不要偏低导致 API 报错。
+IMAGE_TOKEN_ESTIMATE = 765
+AUDIO_TOKEN_ESTIMATE = 500
+
+
 class EstimateTokenCounter:
     """Estimate token counter implementation.
     Provides a simple estimation of token count based on character types.
+
+    Supports multimodal content: images, audio, and thinking parts
+    are all counted so that the context compressor can trigger in time.
     """
 
     def count_tokens(
@@ -45,12 +55,16 @@ class EstimateTokenCounter:
             if isinstance(content, str):
                 total += self._estimate_tokens(content)
             elif isinstance(content, list):
-                # 处理多模态内容
                 for part in content:
                     if isinstance(part, TextPart):
                         total += self._estimate_tokens(part.text)
+                    elif isinstance(part, ThinkPart):
+                        total += self._estimate_tokens(part.think)
+                    elif isinstance(part, ImageURLPart):
+                        total += IMAGE_TOKEN_ESTIMATE
+                    elif isinstance(part, AudioURLPart):
+                        total += AUDIO_TOKEN_ESTIMATE
 
-            # 处理 Tool Calls
             if msg.tool_calls:
                 for tc in msg.tool_calls:
                     tc_str = json.dumps(tc if isinstance(tc, dict) else tc.model_dump())

tests/agent/test_token_counter.py

@@ -0,0 +1,103 @@
+"""Tests for EstimateTokenCounter multimodal support."""
+
+from astrbot.core.agent.context.token_counter import (
+    AUDIO_TOKEN_ESTIMATE,
+    IMAGE_TOKEN_ESTIMATE,
+    EstimateTokenCounter,
+)
+from astrbot.core.agent.message import (
+    AudioURLPart,
+    ImageURLPart,
+    Message,
+    TextPart,
+    ThinkPart,
+)
+
+
+counter = EstimateTokenCounter()
+
+
+def _msg(role: str, content) -> Message:
+    return Message(role=role, content=content)
+
+
+class TestTextCounting:
+    def test_plain_string(self):
+        tokens = counter.count_tokens([_msg("user", "hello world")])
+        assert tokens > 0
+
+    def test_chinese(self):
+        # 中文字符权重更高
+        en = counter.count_tokens([_msg("user", "abc")])
+        zh = counter.count_tokens([_msg("user", "你好啊")])
+        assert zh > en
+
+    def test_text_part(self):
+        msg = _msg("user", [TextPart(text="hello")])
+        assert counter.count_tokens([msg]) > 0
+
+
+class TestMultimodalCounting:
+    def test_image_counted(self):
+        msg = _msg("user", [
+            ImageURLPart(image_url=ImageURLPart.ImageURL(url="data:image/png;base64,abc")),
+        ])
+        tokens = counter.count_tokens([msg])
+        assert tokens == IMAGE_TOKEN_ESTIMATE
+
+    def test_audio_counted(self):
+        msg = _msg("user", [
+            AudioURLPart(audio_url=AudioURLPart.AudioURL(url="https://x.com/a.mp3")),
+        ])
+        tokens = counter.count_tokens([msg])
+        assert tokens == AUDIO_TOKEN_ESTIMATE
+
+    def test_think_counted(self):
+        msg = _msg("assistant", [ThinkPart(think="let me think about this")])
+        tokens = counter.count_tokens([msg])
+        assert tokens > 0
+
+    def test_mixed_content(self):
+        """文本 + 图片的多模态消息，token 数 = 文本 token + 图片估算。"""
+        text_only = _msg("user", [TextPart(text="describe this image")])
+        mixed = _msg("user", [
+            TextPart(text="describe this image"),
+            ImageURLPart(image_url=ImageURLPart.ImageURL(url="data:image/png;base64,x")),
+        ])
+        text_tokens = counter.count_tokens([text_only])
+        mixed_tokens = counter.count_tokens([mixed])
+        assert mixed_tokens == text_tokens + IMAGE_TOKEN_ESTIMATE
+
+    def test_multiple_images(self):
+        """多张图片应该各自计算。"""
+        msg = _msg("user", [
+            ImageURLPart(image_url=ImageURLPart.ImageURL(url="data:image/png;base64,a")),
+            ImageURLPart(image_url=ImageURLPart.ImageURL(url="data:image/png;base64,b")),
+            ImageURLPart(image_url=ImageURLPart.ImageURL(url="data:image/png;base64,c")),
+        ])
+        tokens = counter.count_tokens([msg])
+        assert tokens == IMAGE_TOKEN_ESTIMATE * 3
+
+
+class TestTrustedUsage:
+    def test_trusted_overrides(self):
+        """如果 API 返回了 token 数，直接用它不做估算。"""
+        msg = _msg("user", [
+            TextPart(text="hello"),
+            ImageURLPart(image_url=ImageURLPart.ImageURL(url="data:image/png;base64,x")),
+        ])
+        tokens = counter.count_tokens([msg], trusted_token_usage=42)
+        assert tokens == 42
+
+
+class TestToolCalls:
+    def test_tool_calls_counted(self):
+        msg = Message(
+            role="assistant",
+            content="calling tool",
+            tool_calls=[{"type": "function", "id": "1", "function": {"name": "get_weather", "arguments": '{"city": "Beijing"}'}}],
+        )
+        tokens = counter.count_tokens([msg])
+        # 文本 + tool call JSON 都应被计算
+        text_only = counter.count_tokens([_msg("assistant", "calling tool")])
+        assert tokens > text_only