Integrate Bifrost LLM gateway, add test suite, implement memory pipeline

- Add Bifrost (maximhq/bifrost) as LLM gateway: all inference routes through
  bifrost:8080/v1 with retry logic and observability; VRAMManager keeps direct
  Ollama access for VRAM flush/prewarm operations
- Switch medium model from qwen3:4b to qwen2.5:1.5b (direct call, no tools)
  via _DirectModel wrapper; complex keeps create_deep_agent with qwen3:8b
- Implement out-of-agent memory pipeline: _retrieve_memories pre-fetches
  relevant context (injected into all tiers), _store_memory runs as background
  task after each reply writing to openmemory/Qdrant
- Add tests/unit/ with 133 tests covering router, channels, vram_manager,
  agent helpers; move integration test to tests/integration/
- Add bifrost-config.json with GPU Ollama (qwen2.5:0.5b/1.5b, qwen3:4b/8b,
  gemma3:4b) and CPU Ollama providers
- Integration test 28/29 pass (only grammy fails — no TELEGRAM_BOT_TOKEN)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

tests/unit/conftest.py

@@ -0,0 +1,80 @@
+"""
+Stub out all third-party packages that Adolf's source modules import.
+This lets the unit tests run without a virtualenv or Docker environment.
+Stubs are installed into sys.modules before any test file is collected.
+"""
+
+import sys
+from unittest.mock import MagicMock
+
+
+# ── helpers ────────────────────────────────────────────────────────────────────
+
+def _mock(name: str) -> MagicMock:
+    m = MagicMock(name=name)
+    sys.modules[name] = m
+    return m
+
+
+# ── pydantic: BaseModel must be a real class so `class Foo(BaseModel)` works ──
+
+class _FakeBaseModel:
+    model_fields: dict = {}
+
+    def __init_subclass__(cls, **kwargs):
+        pass
+
+    def __init__(self, **data):
+        for k, v in data.items():
+            setattr(self, k, v)
+
+
+_pydantic = _mock("pydantic")
+_pydantic.BaseModel = _FakeBaseModel
+
+# ── httpx: used by channels.py, vram_manager.py, agent.py ────────────────────
+
+_mock("httpx")
+
+# ── fastapi ───────────────────────────────────────────────────────────────────
+
+_fastapi = _mock("fastapi")
+_mock("fastapi.responses")
+
+# ── langchain stack ───────────────────────────────────────────────────────────
+
+_mock("langchain_openai")
+
+_lc_core = _mock("langchain_core")
+_lc_msgs = _mock("langchain_core.messages")
+_mock("langchain_core.tools")
+
+# Provide real-ish message classes so router.py can instantiate them
+class _FakeMsg:
+    def __init__(self, content=""):
+        self.content = content
+
+class SystemMessage(_FakeMsg):
+    pass
+
+class HumanMessage(_FakeMsg):
+    pass
+
+class AIMessage(_FakeMsg):
+    def __init__(self, content="", tool_calls=None):
+        super().__init__(content)
+        self.tool_calls = tool_calls or []
+
+_lc_msgs.SystemMessage = SystemMessage
+_lc_msgs.HumanMessage = HumanMessage
+_lc_msgs.AIMessage = AIMessage
+
+_mock("langchain_mcp_adapters")
+_mock("langchain_mcp_adapters.client")
+_mock("langchain_community")
+_mock("langchain_community.utilities")
+
+# ── deepagents (agent_factory.py) ─────────────────────────────────────────────
+
+_mock("deepagents")
+