src/agentkit/core/compressor.py

@@ -108,11 +108,7 @@ class ContextCompressor:
 
     def estimate_tokens(self, messages: list[dict]) -> int:
         """Estimate total tokens in message list (CJK 1:1, ASCII 4:1)"""
-        total = 0
-        for msg in messages:
-            content = msg.get("content", "")
-            total += estimate_text_tokens(str(content))
-        return total
+        return sum(estimate_text_tokens(str(m.get("content", ""))) for m in messages)
 
     async def compress(self, messages: list[dict]) -> list[dict]:
         """Compress messages if they exceed token budget.
@@ -205,7 +201,10 @@ class ContextCompressor:
         # Pre-truncate if conversation_text exceeds safe token threshold
         estimated_tokens = estimate_text_tokens(conversation_text)
         if estimated_tokens > max_input_tokens:
-            max_chars = max_input_tokens * 4
+            # CJK-aware char limit: max_input_tokens chars is exact for CJK (1:1),
+            # conservative for ASCII (4:1, truncates to 1/4 budget but safe).
+            # Review fix #1: old `* 4` allowed 4x token budget for CJK text.
+            max_chars = max_input_tokens
             conversation_text = conversation_text[:max_chars] + "\n...[truncated]"
 
         prompt = (

tests/unit/test_context_compressor.py

@@ -126,6 +126,29 @@ class TestEstimateTextTokensCJK:
         old_estimate = len("你好" * 50) // 4  # old: len // 4
         assert new_estimate >= old_estimate * 4
 
+    async def test_summarize_cjk_pre_truncation(self):
+        """Review fix #2: _summarize() CJK 文本预截断正确触发
+
+        构造 CJK 文本使 estimate_text_tokens > max_input_tokens 但
+        len(text) < max_input_tokens * 4（验证旧 bug：* 4 假设允许 4x 超预算）
+        """
+        gateway = make_mock_gateway("Summary result")
+        compressor = ContextCompressor(llm_gateway=gateway)
+        # 4000 CJK chars = 4000 tokens (1:1), > max_input_tokens=3200
+        # But len=4000 < 3200 * 4 = 12800, so old `* 4` limit wouldn't truncate
+        cjk_content = "你" * 4000
+        messages = [{"role": "user", "content": cjk_content}]
+        await compressor._summarize(messages, max_input_tokens=3200)
+
+        # Verify LLM was called with truncated text (not full 4000 chars)
+        call_messages = gateway.chat.call_args.kwargs["messages"]
+        prompt_content = call_messages[0]["content"]
+        # The conversation_text in the prompt should be truncated to <= 3200 chars
+        # (plus truncation marker), not the full 4000 chars
+        assert "...[truncated]" in prompt_content
+        # Verify the CJK content was actually shortened
+        assert prompt_content.count("你") < 4000
+
 
 class TestNoCompressionWhenUnderBudget:
     """Token 预算内不压缩"""
@@ -436,6 +459,8 @@ class TestCompressLinearFlow:
         # Truncate should have cut message content
         total_chars = sum(len(str(m.get("content", ""))) for m in result)
         assert total_chars < sum(len(str(m.get("content", ""))) for m in messages)
+        # Review fix #7: verify truncate actually triggered via truncation marker
+        assert any("...[truncated]" in str(m.get("content", "")) for m in result)
 
 
 class TestCompressionLogging:
@@ -654,3 +679,33 @@ class TestReActEngineWithCompressor:
         )
 
         assert result.output == "Answer"
+
+    async def test_should_compress_cjk_fallback_path(self):
+        """Review fix #5: _should_compress() CJK fallback for compressors
+        without should_compress() method (e.g. HeadroomCompressor)
+
+        Verifies R7: react.py fallback uses estimate_text_tokens, so CJK
+        long conversations correctly trigger compression.
+        """
+        from agentkit.core.react import ReActEngine
+
+        gateway = MagicMock()
+        engine = ReActEngine(llm_gateway=gateway)
+
+        # Mock compressor WITHOUT should_compress() method
+        # (simulates HeadroomCompressor which doesn't implement it)
+        mock_compressor = MagicMock(spec=["is_available", "compress", "compress_tool_result"])
+        mock_compressor.is_available.return_value = True
+
+        # CJK long conversation: 10000 CJK chars = 10000 tokens > 8000 threshold
+        cjk_conversation = [
+            {"role": "user", "content": "你" * 5000},
+            {"role": "assistant", "content": "好" * 5000},
+        ]
+        result = engine._should_compress(cjk_conversation, mock_compressor)
+        assert result is True
+
+        # ASCII short conversation should not trigger
+        ascii_short = [{"role": "user", "content": "Hello"}]
+        result = engine._should_compress(ascii_short, mock_compressor)
+        assert result is False