📦 deps(thirdparty): update snapshots

2026-06-29 16:09:10 +00:00
parent 90c6c04c3f
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+# Semantic Search
+
+Pure vector similarity search using embeddings on a single collection.
+
+## Usage
+
+```bash
+uv run scripts/semantic_search.py --query "USER_QUERY" --collection "CollectionName" [--limit 10] [--distance 0.5] [--target-vector "vector_name"] [--json]
+```
+
+## Parameters
+
+| Parameter | Flag | Required | Default | Description |
+|-----------|------|----------|---------|-------------|
+| `--query` | `-q` | Yes | — | Search query text |
+| `--collection` | `-c` | Yes | — | Collection name |
+| `--limit` | `-l` | No | `10` | Maximum number of results |
+| `--distance` | `-d` | No | — | Maximum distance threshold (filters out less similar results) |
+| `--target-vector` | `-t` | No | — | Target vector name for named vector collections |
+| `--json` | — | No | `false` | Output in JSON format |
+
+## Output
+
+- **Default**: Markdown table with object properties and distance scores
+- **JSON**: Array of objects with properties and distance metadata
+
+## Examples
+
+Basic semantic search:
+
+```bash
+uv run scripts/semantic_search.py --query "environmental impact of urbanization" --collection "Research"
+```
+
+With distance threshold:
+
+```bash
+uv run scripts/semantic_search.py --query "machine learning" --collection "Papers" --distance 0.3 --limit 5
+```
+
+With named vector:
+
+```bash
+uv run scripts/semantic_search.py --query "abstract art" --collection "Artworks" --target-vector "description_vector"
+```
+