style: format
This commit is contained in:
Andy Lee
@@ -138,7 +138,9 @@ class LAIONEvaluator:
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sizes["index_only_mb"] = index_mb
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# Other files for reference (not counted in index_only_mb)
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sizes["metadata_mb"] = meta_file.stat().st_size / (1024 * 1024) if meta_file.exists() else 0.0
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sizes["metadata_mb"] = (
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meta_file.stat().st_size / (1024 * 1024) if meta_file.exists() else 0.0
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)
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sizes["passages_text_mb"] = (
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passages_file.stat().st_size / (1024 * 1024) if passages_file.exists() else 0.0
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)
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@@ -308,25 +310,41 @@ class LAIONEvaluator:
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print("\n🎯 LAION MULTIMODAL BENCHMARK RESULTS")
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print("=" * 60)
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# Index comparison analysis
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# Index comparison analysis (prefer .index-only view if present)
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if "current_index" in timing_metrics and "non_compact_index" in timing_metrics:
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print("\n📏 Index Comparison Analysis:")
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current = timing_metrics["current_index"]
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non_compact = timing_metrics["non_compact_index"]
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print(f" Compact index (current): {current.get('total_with_embeddings', 0):.1f} MB")
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print(
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f" Non-compact index (with embeddings): {non_compact.get('total_with_embeddings', 0):.1f} MB"
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)
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print(
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f" Storage saving by compact: {timing_metrics.get('storage_saving_percent', 0):.1f}%"
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)
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print(" Component breakdown (non-compact):")
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print(f" - Main index: {non_compact.get('index', 0):.1f} MB")
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print(f" - Passages text: {non_compact.get('passages_text', 0):.1f} MB")
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print(f" - Passages index: {non_compact.get('passages_index', 0):.1f} MB")
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print(f" - Metadata: {non_compact.get('metadata', 0):.1f} MB")
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if "index_only_mb" in current and "index_only_mb" in non_compact:
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print("\n📏 Index Comparison Analysis (.index only):")
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print(f" Compact index (current): {current.get('index_only_mb', 0):.1f} MB")
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print(f" Non-compact index: {non_compact.get('index_only_mb', 0):.1f} MB")
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print(
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f" Storage saving by compact: {timing_metrics.get('storage_saving_percent', 0):.1f}%"
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)
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# Show excluded components for reference if available
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if any(k in non_compact for k in ("passages_text_mb", "passages_index_mb", "metadata_mb")):
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print(" (passages excluded in totals, shown for reference):")
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print(
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f" - Passages text: {non_compact.get('passages_text_mb', 0):.1f} MB, "
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f"Passages index: {non_compact.get('passages_index_mb', 0):.1f} MB, "
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f"Metadata: {non_compact.get('metadata_mb', 0):.3f} MB"
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)
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else:
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# Fallback to legacy totals if running with older metrics
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print("\n📏 Index Comparison Analysis:")
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print(f" Compact index (current): {current.get('total_with_embeddings', 0):.1f} MB")
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print(
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f" Non-compact index (with embeddings): {non_compact.get('total_with_embeddings', 0):.1f} MB"
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)
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print(
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f" Storage saving by compact: {timing_metrics.get('storage_saving_percent', 0):.1f}%"
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)
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print(" Component breakdown (non-compact):")
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print(f" - Main index: {non_compact.get('index', 0):.1f} MB")
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print(f" - Passages text: {non_compact.get('passages_text', 0):.1f} MB")
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print(f" - Passages index: {non_compact.get('passages_index', 0):.1f} MB")
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print(f" - Metadata: {non_compact.get('metadata', 0):.1f} MB")
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# Performance comparison
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if "performance_comparison" in timing_metrics:
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@@ -433,7 +451,7 @@ def main():
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# Binary search for 90% recall complexity
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target_recall = 0.9
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min_complexity, max_complexity = 1, 64
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min_complexity, max_complexity = 1, 128
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print(f"🔍 Binary search for {target_recall * 100}% recall complexity...")
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print(f"Search range: {min_complexity} to {max_complexity}")
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@@ -548,9 +566,7 @@ def main():
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print(
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f" Compact index (current): {compact_size_metrics.get('index_only_mb', 0):.1f} MB"
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)
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print(
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f" Non-compact index: {non_compact_size_metrics.get('index_only_mb', 0):.1f} MB"
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)
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print(f" Non-compact index: {non_compact_size_metrics.get('index_only_mb', 0):.1f} MB")
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storage_saving = 0.0
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if non_compact_size_metrics.get("index_only_mb", 0) > 0:
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@@ -118,12 +118,16 @@ class HNSWBuilder(LeannBackendBuilderInterface):
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# index_file_old = index_file.with_suffix(".old")
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# shutil.move(str(index_file), str(index_file_old))
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shutil.move(str(csr_temp_file), str(index_file))
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logger.info(f"INFO: Replaced original index with {mode_str} version at '{index_file}'")
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logger.info(
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f"INFO: Replaced original index with {mode_str} version at '{index_file}'"
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)
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else:
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# Clean up and fail fast
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if csr_temp_file.exists():
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os.remove(csr_temp_file)
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raise RuntimeError("CSR conversion failed - cannot proceed with compact format")
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raise RuntimeError(
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"CSR conversion failed - cannot proceed with compact format"
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)
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class HNSWSearcher(BaseSearcher):
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@@ -212,7 +216,9 @@ class HNSWSearcher(BaseSearcher):
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)
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if recompute_embeddings:
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if zmq_port is None:
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raise ValueError("zmq_port must be provided if recompute_embeddings is True")
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raise ValueError(
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"zmq_port must be provided if recompute_embeddings is True"
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)
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if query.dtype != np.float32:
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query = query.astype(np.float32)
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@@ -221,7 +227,9 @@ class HNSWSearcher(BaseSearcher):
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params = faiss.SearchParametersHNSW()
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if zmq_port is not None:
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params.zmq_port = zmq_port # C++ code won't use this if recompute_embeddings is False
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params.zmq_port = (
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zmq_port # C++ code won't use this if recompute_embeddings is False
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)
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params.efSearch = complexity
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params.beam_size = beam_width
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@@ -229,7 +237,8 @@ class HNSWSearcher(BaseSearcher):
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# This prevents early termination when all scores are in a narrow range
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embedding_model = self.meta.get("embedding_model", "").lower()
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if self.distance_metric == "cosine" and any(
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openai_model in embedding_model for openai_model in ["text-embedding", "openai"]
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openai_model in embedding_model
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for openai_model in ["text-embedding", "openai"]
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):
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params.check_relative_distance = False
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else:
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@@ -244,7 +253,9 @@ class HNSWSearcher(BaseSearcher):
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params.send_neigh_times_ratio = 0.0
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elif pruning_strategy == "proportional":
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params.local_prune = False
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params.send_neigh_times_ratio = 1.0 # Any value > 1e-6 triggers proportional mode
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params.send_neigh_times_ratio = (
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1.0 # Any value > 1e-6 triggers proportional mode
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)
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else: # "global"
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params.local_prune = False
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params.send_neigh_times_ratio = 0.0
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@@ -266,7 +277,9 @@ class HNSWSearcher(BaseSearcher):
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params,
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)
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search_time = time.time() - search_time
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logger.info(f" Search time in HNSWSearcher.search() backend: {search_time} seconds")
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logger.info(
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f" Search time in HNSWSearcher.search() backend: {search_time} seconds"
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)
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if self._id_map:
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def map_label(x: int) -> str:
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@@ -274,10 +287,13 @@ class HNSWSearcher(BaseSearcher):
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return self._id_map[x]
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return str(x)
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string_labels = [[map_label(int(l)) for l in batch_labels] for batch_labels in labels]
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string_labels = [
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[map_label(int(l)) for l in batch_labels] for batch_labels in labels
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]
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else:
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string_labels = [
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[str(int_label) for int_label in batch_labels] for batch_labels in labels
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[str(int_label) for int_label in batch_labels]
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for batch_labels in labels
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]
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return {"labels": string_labels, "distances": distances}
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627
uv.lock
generated
627
uv.lock
generated
@@ -334,21 +334,21 @@ css = [
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[[package]]
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name = "boto3"
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version = "1.40.14"
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version = "1.40.16"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "botocore" },
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{ name = "jmespath" },
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{ name = "s3transfer" },
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]
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sdist = { url = "https://files.pythonhosted.org/packages/03/2e/606fa848f0b6fb0acdcfaefed5b6c663bdb9bcf611760be3f273848d149c/boto3-1.40.14.tar.gz", hash = "sha256:d1d9998fc2b9619fc796c859d263ac81793d783e79331be62931b353dd1b68b9", size = 112001, upload-time = "2025-08-20T19:24:08.346Z" }
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sdist = { url = "https://files.pythonhosted.org/packages/ad/d4/ad261cb17f202082ba8598fd6d1d27eac5d11307ce99e3f5867bc9e376ee/boto3-1.40.16.tar.gz", hash = "sha256:667bc3a9bd1f26579957d95a2612359103c343dd74d44f202d09a155ed4189c6", size = 111944, upload-time = "2025-08-22T19:28:30.643Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/7d/d7/83ddd51e8304bea0c24117de9724506a1c407ba995f07c5dc5069f6ad6eb/boto3-1.40.14-py3-none-any.whl", hash = "sha256:ab5798a03582d09c0de132d080c9aee53d5647b6461261a5b7621170ec80d92b", size = 140072, upload-time = "2025-08-20T19:24:06.689Z" },
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{ url = "https://files.pythonhosted.org/packages/f1/ce/6030ebcde6a19920c36d633643811a80e53d2b92a4a125ddf07520b2da66/boto3-1.40.16-py3-none-any.whl", hash = "sha256:4b7fbd2b469d5fa6325f0e90310b2d430c9a35e8a984a9919103e6d248422537", size = 140076, upload-time = "2025-08-22T19:28:28.656Z" },
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[[package]]
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name = "botocore"
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version = "1.40.14"
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version = "1.40.16"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "jmespath" },
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@@ -356,9 +356,9 @@ dependencies = [
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{ name = "urllib3", version = "1.26.20", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
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{ name = "urllib3", version = "2.5.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.10'" },
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]
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sdist = { url = "https://files.pythonhosted.org/packages/25/4c/7087a282f10dc2258a107e4a29645678b5d3fa7cbabed05d540370aa8c57/botocore-1.40.16.tar.gz", hash = "sha256:522a8b7e3837667aca978b5b2dd2d12c3834f58f13df3c8d3369070d883d608d", size = 14368291, upload-time = "2025-08-22T19:28:20.227Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/cd/c3/47a5ee306a52c99b1ca5e6712c27666ddc7b9c102296d86ff90eda598331/botocore-1.40.14-py3-none-any.whl", hash = "sha256:06c852be83543c8d45e18a530abcad31659db8b16bcb66fd371c930d38017e7c", size = 14025263, upload-time = "2025-08-20T19:23:52.793Z" },
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[[package]]
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@@ -1169,74 +1169,6 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/7b/8f/c4d9bafc34ad7ad5d8dc16dd1347ee0e507a52c3adb6bfa8887e1c6a26ba/executing-2.2.0-py2.py3-none-any.whl", hash = "sha256:11387150cad388d62750327a53d3339fad4888b39a6fe233c3afbb54ecffd3aa", size = 26702, upload-time = "2025-01-22T15:41:25.929Z" },
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]
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[[package]]
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name = "faiss-cpu"
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version = "1.12.0"
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source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "numpy", version = "2.0.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.10'" },
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{ name = "numpy", version = "2.2.6", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version == '3.10.*'" },
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{ name = "numpy", version = "2.3.2", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.11'" },
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{ name = "packaging" },
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]
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wheels = [
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Reference in New Issue
Block a user