feat(stack): drop qdrant and embedding-server, use OmniRoute's built-in memory

OmniRoute's memory feature is self-contained: its bundled sqlite-vec
vector store plus a local ONNX embedding model (Transformers.js,
~400MB, fetched into the omniroute-data volume on first use) replace
the external qdrant + bge-small-en-v1.5 embedding-server pair, which
was never wired up in the dashboard. Two fewer containers, no
second GGUF download, no EMBEDDING_MODEL_FILE var. Memory stays
opt-in via the dashboard (Settings -> Memory, transformers source);
nothing here changes the gateway's static config.

.env.example

@@ -28,12 +28,6 @@ LLAMA_GPU_LAYERS=999
 # of dropping context: --cache-type-k/v q8_0 roughly halves it.
 LLAMA_CTX_SIZE=131072
 
-# --- embedding-server (OmniRoute memory) ---
-# bge-small-en-v1.5, CPU-only, 384-dim output — see docker-compose.yml's
-# embedding-server service comment for why this is a second model/process
-# rather than reusing llama-server.
-EMBEDDING_MODEL_FILE=bge-small-en-v1.5-q8_0.gguf
-
 # --- Lazytainer ---
 # Seconds of inactivity before llama-server is stopped. 900 = 15 min.
 LAZYTAINER_INACTIVE_TIMEOUT=900