Search for similar documents in Qdrant.

Embeds the query text using Ollama, then searches for similar vectors in the specified Qdrant collection. Returns matching documents with similarity scores.

Supports advanced features:

• Query expansion: generates multiple query variations and merges results

• HyDE: generates hypothetical documents for semantic enrichment

• RRF: Reciprocal Rank Fusion for merging multiple result sets

• Reranking: uses LLM to reorder results by relevance

Args: params (SearchInput): Validated parameters: - collection_name (str): Collection to search in - query_text (str): Text to search for (auto-embedded) - limit (int): Max results, 1-100 (default: 5) - score_threshold (float): Min similarity 0.0-1.0 (default: 0.0) - fields (str): Comma-separated metadata fields to return (optional) - response_format (str): 'markdown' or 'json' - expand_query (bool): Enable query expansion (default: False) - expand_query_count (int): Number of variations (default: 3) - use_hyde (bool): Enable HyDE (default: False) - hyde_combine_original (bool): Include original query with HyDE (default: True) - rerank (bool): Enable LLM reranking (default: False) - rerank_top_n (int): Candidates for reranking (default: 10)

Returns: str: Formatted search results with document IDs, texts, and scores

Errors: - Collection not found: "Collection 'xyz' does not exist" - Embedding failed: "Failed to embed query text" - Connection error: "Cannot connect to Qdrant at {url}"

List all collections in Qdrant.

Retrieves metadata about all collections including point counts and vector dimensions.

Args: params (ListCollectionsInput): Validated parameters: - response_format (str): 'markdown' or 'json'

Returns: str: Formatted list of collections with metadata

Errors: - Connection error: "Cannot connect to Qdrant at {url}"