Phase 3: AI integration with Ollama via Python sidecar

- sidecar: FastAPI app with /embed, /generate, /rerank hitting Ollama
- sidecar: Dockerfile, env var config (EMBED_MODEL, GEN_MODEL, RERANK_MODEL)
- aibridge: reqwest HTTP client with typed request/response structs
- aibridge: Axum proxy endpoints (POST /ai/embed, /ai/generate, /ai/rerank)
- gateway: wires AiClient with SIDECAR_URL env var
- e2e verified: nomic-embed-text returns 768d vectors, qwen2.5 generates text

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

sidecar/pyproject.toml

@@ -0,0 +1,14 @@
+[project]
+name = "lakehouse-sidecar"
+version = "0.1.0"
+requires-python = ">=3.11"
+dependencies = [
+    "fastapi>=0.115",
+    "uvicorn>=0.34",
+    "httpx>=0.28",
+    "pydantic>=2.0",
+]
+
+[tool.uvicorn]
+host = "0.0.0.0"
+port = 3200