feat: Jon Snow Phase 2 — FastAPI orchestrator with LiteLLM brain

OpenAI-compatible API at :8900. Intent classifier routes status queries
to FAST_MODEL (Ollama), task submissions to Plane, planning to SMART_MODEL.
Reads agent-os logs for status context. Phase 3: approval gate + execution.

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

app/brain.py

@@ -0,0 +1,40 @@
+import logging
+import os
+
+import litellm
+
+logger = logging.getLogger("jon-snow.brain")
+litellm.set_verbose = False
+
+FAST_MODEL = os.getenv("FAST_MODEL", "ollama/gemma4")
+SMART_MODEL = os.getenv("SMART_MODEL", "ollama/gemma4")
+OLLAMA_BASE_URL = os.getenv("OLLAMA_BASE_URL", "http://172.27.40.20:11434")
+
+
+def _extra_kwargs(model: str) -> dict:
+    if model.startswith("ollama/"):
+        return {"api_base": OLLAMA_BASE_URL}
+    return {}
+
+
+async def stream_completion(messages: list[dict], use_smart: bool = False):
+    model = SMART_MODEL if use_smart else FAST_MODEL
+    logger.info(f"Brain: model={model} smart={use_smart}")
+    try:
+        return await litellm.acompletion(
+            model=model,
+            messages=messages,
+            stream=True,
+            **_extra_kwargs(model),
+        )
+    except Exception as e:
+        logger.error(f"Brain error ({model}): {e}")
+        if use_smart and model != FAST_MODEL:
+            logger.info("Falling back to FAST_MODEL")
+            return await litellm.acompletion(
+                model=FAST_MODEL,
+                messages=messages,
+                stream=True,
+                **_extra_kwargs(FAST_MODEL),
+            )
+        raise