style(hnsw-server): apply ruff-format after robustness changes
This commit is contained in:
Andy Lee
@@ -84,6 +84,11 @@ def create_hnsw_embedding_server(
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# Let PassageManager handle path resolution uniformly
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passages = PassageManager(meta["passage_sources"], metadata_file_path=passages_file)
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# Dimension from metadata for shaping responses
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try:
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embedding_dim: int = int(meta.get("dimensions", 0))
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except Exception:
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embedding_dim = 0
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logger.info(
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f"Loaded PassageManager with {len(passages.global_offset_map)} passages from metadata"
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)
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@@ -255,6 +260,10 @@ def create_hnsw_embedding_server(
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rep_socket.setsockopt(zmq.RCVTIMEO, 1000)
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rep_socket.setsockopt(zmq.SNDTIMEO, 300000)
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# Track last request type/length for shape-correct fallbacks
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last_request_type = "unknown" # 'text' | 'distance' | 'embedding' | 'unknown'
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last_request_length = 0
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try:
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while not shutdown_event.is_set():
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try:
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@@ -276,45 +285,135 @@ def create_hnsw_embedding_server(
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and request
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and all(isinstance(item, str) for item in request)
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):
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last_request_type = "text"
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last_request_length = len(request)
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embeddings = compute_embeddings(request, model_name, mode=embedding_mode)
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rep_socket.send(msgpack.packb(embeddings.tolist()))
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e2e_end = time.time()
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logger.info(f"⏱️ Text embedding E2E time: {e2e_end - e2e_start:.6f}s")
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continue
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node_ids = request if isinstance(request, list) else []
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logger.info(f"ZMQ received {len(node_ids)} node IDs")
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# Handle distance calculation request: [[ids], [query_vector]]
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if (
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isinstance(request, list)
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and len(request) == 2
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and isinstance(request[0], list)
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and isinstance(request[1], list)
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):
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node_ids = request[0]
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query_vector = np.array(request[1], dtype=np.float32)
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last_request_type = "distance"
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last_request_length = len(node_ids)
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texts = []
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for nid in node_ids:
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logger.debug("Distance calculation request received")
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logger.debug(f" Node IDs: {node_ids}")
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logger.debug(f" Query vector dim: {len(query_vector)}")
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# Gather texts for found ids
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texts: list[str] = []
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found_indices: list[int] = []
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for idx, nid in enumerate(node_ids):
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try:
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passage_data = passages.get_passage(str(nid))
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txt = passage_data.get("text", "")
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if isinstance(txt, str) and len(txt) > 0:
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texts.append(txt)
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found_indices.append(idx)
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else:
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logger.error(f"Empty text for passage ID {nid}")
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except KeyError:
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logger.error(f"Passage ID {nid} not found")
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except Exception as e:
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logger.error(f"Exception looking up passage ID {nid}: {e}")
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# Prepare full-length response with large sentinel values
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large_distance = 1e9
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response_distances = [large_distance] * len(node_ids)
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if texts:
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try:
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embeddings = compute_embeddings(
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texts, model_name, mode=embedding_mode
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)
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logger.info(
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f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
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)
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if distance_metric == "l2":
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partial = np.sum(
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np.square(embeddings - query_vector.reshape(1, -1)), axis=1
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)
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else: # mips or cosine
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partial = -np.dot(embeddings, query_vector)
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for pos, dval in zip(found_indices, partial.flatten().tolist()):
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response_distances[pos] = float(dval)
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except Exception as e:
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logger.error(f"Distance computation error, using sentinels: {e}")
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# Send response in expected shape [[distances]]
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rep_socket.send(msgpack.packb([response_distances], use_single_float=True))
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e2e_end = time.time()
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logger.info(f"⏱️ Distance calculation E2E time: {e2e_end - e2e_start:.6f}s")
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continue
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# Fallback: treat as embedding-by-id request [[ids]]
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node_ids = request if isinstance(request, list) else []
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last_request_type = "embedding"
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last_request_length = len(node_ids)
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logger.info(f"ZMQ received {len(node_ids)} node IDs for embedding fetch")
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# Preallocate zero-filled flat data for robustness
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if embedding_dim <= 0:
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dims = [0, 0]
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flat_data: list[float] = []
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else:
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dims = [len(node_ids), embedding_dim]
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flat_data = [0.0] * (dims[0] * dims[1])
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# Collect texts for found ids
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texts: list[str] = []
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found_indices: list[int] = []
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for idx, nid in enumerate(node_ids):
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try:
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passage_data = passages.get_passage(str(nid))
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txt = passage_data["text"]
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if not txt:
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raise RuntimeError(f"FATAL: Empty text for passage ID {nid}")
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texts.append(txt)
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txt = passage_data.get("text", "")
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if isinstance(txt, str) and len(txt) > 0:
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texts.append(txt)
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found_indices.append(idx)
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else:
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logger.error(f"Empty text for passage ID {nid}")
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except KeyError:
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raise RuntimeError(f"FATAL: Passage with ID {nid} not found")
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logger.error(f"Passage with ID {nid} not found")
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except Exception as e:
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logger.error(f"Exception looking up passage ID {nid}: {e}")
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raise
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embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
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logger.info(
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f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
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)
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if texts:
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try:
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embeddings = compute_embeddings(texts, model_name, mode=embedding_mode)
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logger.info(
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f"Computed embeddings for {len(texts)} texts, shape: {embeddings.shape}"
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)
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if np.isnan(embeddings).any() or np.isinf(embeddings).any():
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logger.error(
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f"NaN or Inf detected in embeddings! Requested IDs: {node_ids[:5]}..."
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)
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raise AssertionError()
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if np.isnan(embeddings).any() or np.isinf(embeddings).any():
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logger.error(
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f"NaN or Inf detected in embeddings! Requested IDs: {node_ids[:5]}..."
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)
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dims = [0, embedding_dim]
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flat_data = []
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else:
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emb_f32 = np.ascontiguousarray(embeddings, dtype=np.float32)
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flat = emb_f32.flatten().tolist()
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for j, pos in enumerate(found_indices):
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start = pos * embedding_dim
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end = start + embedding_dim
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if end <= len(flat_data):
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flat_data[start:end] = flat[
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j * embedding_dim : (j + 1) * embedding_dim
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]
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except Exception as e:
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logger.error(f"Embedding computation error, returning zeros: {e}")
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hidden_contiguous_f32 = np.ascontiguousarray(embeddings, dtype=np.float32)
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response_payload = [
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list(hidden_contiguous_f32.shape),
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hidden_contiguous_f32.flatten().tolist(),
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]
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response_payload = [dims, flat_data]
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response_bytes = msgpack.packb(response_payload, use_single_float=True)
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rep_socket.send(response_bytes)
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@@ -327,8 +426,23 @@ def create_hnsw_embedding_server(
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except Exception as e:
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if not shutdown_event.is_set():
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logger.error(f"Error in ZMQ server loop: {e}")
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# Shape-correct fallback
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try:
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rep_socket.send(msgpack.packb([[], []]))
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if last_request_type == "distance":
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large_distance = 1e9
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fallback_len = max(0, int(last_request_length))
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safe = [[large_distance] * fallback_len]
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elif last_request_type == "embedding":
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bsz = max(0, int(last_request_length))
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dim = max(0, int(embedding_dim))
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safe = (
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[[bsz, dim], [0.0] * (bsz * dim)] if dim > 0 else [[0, 0], []]
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)
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elif last_request_type == "text":
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safe = [] # direct text embeddings expectation is a flat list
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else:
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safe = [[0, int(embedding_dim) if embedding_dim > 0 else 0], []]
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rep_socket.send(msgpack.packb(safe, use_single_float=True))
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except Exception:
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pass
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else:
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