Fix #149: memory crash in Docker — missing vector index + pthread error

Three fixes for Docker-native install with --memory:

1. Add sqlite-vec to proxy extras — memory's vector index now installs
   with pip install headroom-ai[proxy]. No separate pip install needed.

2. Fix AUTO vector backend fallback — was: SQLITE_VEC → HNSW → crash.
   Now: SQLITE_VEC → HNSW → clear error message listing install options.

3. Fix ONNX pthread_setaffinity_np error in Docker containers — set
   intra/inter thread count to 1 in SessionOptions. Prevents the
   "Invalid argument" error on containers with limited CPU affinity.

headroom/memory/adapters/embedders.py

@@ -311,7 +311,13 @@ class OnnxLocalEmbedder:
         model_path = hf_hub_download(self.ONNX_REPO, "model.onnx")
         tok_path = hf_hub_download(self.ONNX_REPO, "tokenizer.json")
 
-        self._session = ort.InferenceSession(model_path, providers=["CPUExecutionProvider"])
+        # Set thread count to avoid pthread_setaffinity_np errors in Docker containers
+        sess_options = ort.SessionOptions()
+        sess_options.intra_op_num_threads = 1
+        sess_options.inter_op_num_threads = 1
+        self._session = ort.InferenceSession(
+            model_path, sess_options, providers=["CPUExecutionProvider"]
+        )
         self._tokenizer = Tokenizer.from_file(tok_path)
         self._tokenizer.enable_truncation(max_length=self._max_length)
         self._tokenizer.enable_padding(length=self._max_length)

headroom/memory/factory.py

@@ -148,14 +148,21 @@ def _create_vector_index(config: MemoryConfig) -> VectorIndex:
     """
     backend = config.vector_backend
 
-    # AUTO: prefer SQLITE_VEC if available, else HNSW
+    # AUTO: prefer SQLITE_VEC → HNSW → fail with helpful message
     if backend == VectorBackend.AUTO:
-        from headroom.memory.adapters import SQLITE_VEC_AVAILABLE
+        from headroom.memory.adapters import HNSW_AVAILABLE, SQLITE_VEC_AVAILABLE
 
         if SQLITE_VEC_AVAILABLE:
             backend = VectorBackend.SQLITE_VEC
-        else:
+        elif HNSW_AVAILABLE:
             backend = VectorBackend.HNSW
+        else:
+            raise ValueError(
+                "No vector index backend available for memory. Install one:\n"
+                "  pip install sqlite-vec   (recommended, lightweight)\n"
+                "  pip install hnswlib      (alternative)\n"
+                "Or install the full proxy bundle: pip install headroom-ai[proxy]"
+            )
 
     if backend == VectorBackend.SQLITE_VEC:
         from headroom.memory.adapters import SQLITE_VEC_AVAILABLE

pyproject.toml

@@ -67,6 +67,7 @@ proxy = [
     "onnxruntime>=1.16.0",        # Kompress ONNX INT8 text compression (no torch needed)
     "transformers>=4.30.0",       # Tokenizer only (for Kompress)
     "watchdog>=4.0.0",            # File watcher for live code graph reindexing (--code-graph)
+    "sqlite-vec>=0.1.6",          # Vector index for memory (--memory). Lightweight, no torch.
 ]
 # AST-based code compression (tree-sitter)
 code = [