feat(compression): U6 GEO Pipeline compression integration tests and config

Add GEO Pipeline end-to-end compression integration tests with
MockHeadroomCompressor. Add compression configuration section to
llm_config.yaml with headroom and summary mode examples.

configs/llm_config.yaml

@@ -28,3 +28,18 @@ model_aliases:
 fallbacks:
   deepseek/deepseek-chat:
     - "openai/qwen3-coder-plus"
+
+# 上下文压缩配置 — 长会话自动压缩历史消息，保持 Token 在预算内
+# GEO Pipeline 启用后，工具输出（搜索结果、网页抓取等）会自动压缩
+compression:
+  enabled: false                   # 是否启用压缩（生产环境建议 true）
+  provider: "headroom"             # "headroom" | "summary"
+  # --- Headroom 模式（推荐，需安装 headroom-ai）---
+  compressors:                     # 启用的压缩器
+    - "smart_crusher"              # JSON/结构化数据压缩
+    - "code_compressor"            # 代码内容压缩
+  ccr_ttl: 300                     # CCR 缓存 TTL（秒）
+  min_length: 500                  # 最小压缩长度（字符）
+  # --- Summary 模式（无需额外依赖）---
+  # max_tokens: 4000              # Token 预算
+  # keep_recent: 3                # 保留最近 N 条消息

tests/integration/test_geo_compression.py

@@ -0,0 +1,196 @@
+"""GEO Pipeline 压缩集成测试
+
+验证 GEO Pipeline 在 Headroom 压缩下的端到端工作。
+"""
+
+import asyncio
+import json
+from unittest.mock import AsyncMock, MagicMock, patch
+
+import pytest
+
+from agentkit.core.compressor import CompressionStrategy, ContextCompressor, create_compressor
+from agentkit.core.react import ReActEngine, ReActResult
+from agentkit.llm.gateway import LLMGateway
+from agentkit.llm.protocol import LLMResponse, TokenUsage, ToolCall
+from agentkit.tools.registry import ToolRegistry
+
+
+def make_mock_gateway(tool_name: str = "baidu_search") -> MagicMock:
+    """创建 mock LLMGateway"""
+    gateway = MagicMock(spec=LLMGateway)
+    # First call: tool call. Second call: final answer.
+    tool_call = ToolCall(id="tc_1", name=tool_name, arguments={"query": "GEO优化"})
+    tool_response = LLMResponse(
+        content="",
+        model="test",
+        usage=TokenUsage(prompt_tokens=100, completion_tokens=50),
+        tool_calls=[tool_call],
+    )
+    final_response = LLMResponse(
+        content="GEO优化建议：1. 添加Schema.org标记 2. 优化页面标题",
+        model="test",
+        usage=TokenUsage(prompt_tokens=80, completion_tokens=40),
+    )
+    gateway.chat = AsyncMock(side_effect=[tool_response, final_response])
+    return gateway
+
+
+class MockHeadroomCompressor:
+    """Mock HeadroomCompressor for testing without headroom-ai"""
+
+    def __init__(self, config=None):
+        self._config = config or {}
+        self._ccr_cache = {}
+        self._compress_count = 0
+
+    async def compress(self, messages):
+        result = []
+        for msg in messages:
+            if msg.get("role") == "tool" and len(str(msg.get("content", ""))) > 100:
+                original = str(msg.get("content", ""))
+                # Simulate compression: keep first 50 chars
+                compressed = original[:50] + "...[compressed]"
+                ccr_hash = self._store_ccr(original)
+                compressed += f"\n<!-- CCR:hash={ccr_hash} -->"
+                result.append({**msg, "content": compressed})
+                self._compress_count += 1
+            else:
+                result.append(msg)
+        return result
+
+    async def compress_tool_result(self, tool_name, result):
+        content = str(result)
+        if len(content) > 100:
+            compressed = content[:50] + "...[compressed]"
+            ccr_hash = self._store_ccr(content)
+            compressed += f"\n<!-- CCR:hash={ccr_hash} -->"
+            self._compress_count += 1
+            return compressed
+        return content
+
+    def is_available(self):
+        return True
+
+    def _store_ccr(self, original):
+        import hashlib
+        ccr_hash = hashlib.sha256(original.encode()).hexdigest()[:16]
+        self._ccr_cache[ccr_hash] = original
+        return ccr_hash
+
+    def retrieve(self, ccr_hash=None, query=None):
+        if ccr_hash and ccr_hash in self._ccr_cache:
+            return {"content": self._ccr_cache[ccr_hash], "ccr_hash": ccr_hash, "success": True}
+        return {"error": "Not found", "success": False}
+
+
+class TestGEOPipelineCompression:
+    """GEO Pipeline 压缩集成测试"""
+
+    @pytest.mark.asyncio
+    async def test_pipeline_with_compression_enabled(self):
+        """启用压缩后 GEO Pipeline 端到端执行成功"""
+        gateway = make_mock_gateway()
+        engine = ReActEngine(gateway, max_steps=5)
+        compressor = MockHeadroomCompressor()
+
+        # Create a mock tool
+        from agentkit.tools.base import Tool
+        mock_tool = MagicMock(spec=Tool)
+        mock_tool.name = "baidu_search"
+        mock_tool.description = "Search Baidu"
+        mock_tool.input_schema = {"type": "object", "properties": {"query": {"type": "string"}}}
+        mock_tool.safe_execute = AsyncMock(return_value={
+            "results": [{"title": f"Result {i}", "url": f"https://example.com/{i}"} for i in range(20)],
+            "success": True,
+        })
+
+        result = await engine.execute(
+            messages=[{"role": "user", "content": "分析GEO优化策略"}],
+            tools=[mock_tool],
+            compressor=compressor,
+        )
+
+        assert result.status == "success" or result.output
+        assert compressor._compress_count > 0
+
+    @pytest.mark.asyncio
+    async def test_tool_outputs_are_compressed(self):
+        """工具输出被压缩"""
+        gateway = make_mock_gateway(tool_name="web_crawl")
+        engine = ReActEngine(gateway, max_steps=5)
+        compressor = MockHeadroomCompressor()
+
+        from agentkit.tools.base import Tool
+        mock_tool = MagicMock(spec=Tool)
+        mock_tool.name = "web_crawl"
+        mock_tool.description = "Crawl web page"
+        mock_tool.input_schema = {"type": "object", "properties": {"url": {"type": "string"}}}
+        mock_tool.safe_execute = AsyncMock(return_value={
+            "content": "A" * 5000,  # Long content that should be compressed
+            "success": True,
+        })
+
+        result = await engine.execute(
+            messages=[{"role": "user", "content": "抓取网页"}],
+            tools=[mock_tool],
+            compressor=compressor,
+        )
+
+        assert compressor._compress_count > 0
+
+    @pytest.mark.asyncio
+    async def test_ccr_retrieve_works(self):
+        """CCR 检索可取回原始数据"""
+        compressor = MockHeadroomCompressor()
+
+        # Simulate storing content
+        original = "这是一段很长的搜索结果" * 100
+        compressed = await compressor.compress_tool_result("baidu_search", original)
+
+        # Extract CCR hash from compressed content
+        import re
+        match = re.search(r'CCR:hash=([a-f0-9]+)', compressed)
+        assert match, f"No CCR hash found in compressed content: {compressed[:100]}"
+
+        ccr_hash = match.group(1)
+        retrieved = compressor.retrieve(ccr_hash=ccr_hash)
+
+        assert retrieved["success"] is True
+        assert retrieved["content"] == original
+
+    @pytest.mark.asyncio
+    async def test_compression_disabled_pipeline_works(self):
+        """compression.enabled=false 时 Pipeline 行为与之前完全一致"""
+        gateway = make_mock_gateway()
+        engine = ReActEngine(gateway, max_steps=5)
+
+        from agentkit.tools.base import Tool
+        mock_tool = MagicMock(spec=Tool)
+        mock_tool.name = "baidu_search"
+        mock_tool.description = "Search Baidu"
+        mock_tool.input_schema = {"type": "object", "properties": {"query": {"type": "string"}}}
+        mock_tool.safe_execute = AsyncMock(return_value={"results": [], "success": True})
+
+        # No compressor
+        result = await engine.execute(
+            messages=[{"role": "user", "content": "搜索"}],
+            tools=[mock_tool],
+            compressor=None,
+        )
+
+        assert result.output  # Should still produce output
+
+    @pytest.mark.asyncio
+    async def test_create_compressor_with_geo_config(self):
+        """GEO 配置正确创建压缩器"""
+        # Disabled
+        assert create_compressor({"enabled": False}) is None
+
+        # Summary mode
+        c = create_compressor({"enabled": True, "provider": "summary", "max_tokens": 2000})
+        assert isinstance(c, ContextCompressor)
+
+        # Headroom mode (falls back since not installed)
+        c = create_compressor({"enabled": True, "provider": "headroom"})
+        assert isinstance(c, (ContextCompressor, CompressionStrategy))