Search the knowledge graph for information using various strategies. Ideal for answering questions based on indexed data.

Index raw text content directly into the knowledge graph. Useful for small snippets or dynamic data.

Index a specific local file from the file system. The file must be accessible by the running server.

Upload a file to the LightRAG server's input directory and trigger indexing. Handles file transfer if the server is remote.

Intelligently upload a document: if it doesn't exist, creates it; if it exists and is identical (same content length), skips upload; if it exists but was modified, deletes the old version and re-uploads.

Recursively index all files in a directory that match specific patterns.

List ALL documents currently in the system. WARNING: Can be slow if there are many documents. Use get_latest_documents for better performance.

Check if a document exists by its filename or path. Returns a dictionary with detailed status: 'id', 'status' (processed/failed/pending), 'created_at', 'updated_at', 'content_length', 'chunks_count', and 'error_msg' if any.

Get a paginated list of the most recently updated documents. Useful for monitoring ingestion progress.

Check the current status of the document processing pipeline (idle or busy).

Retrieve schema information about the knowledge graph, including available node labels and relationship types.

Check if the LightRAG server is reachable and healthy.

Manually insert specific entities into the knowledge graph.

Delete one or more specific entities from the knowledge graph by name.

Remove all entities and relationships associated with specific document IDs from the graph.

Update the properties (type, description, source_id) of existing entities.

Define or update relationships between entities, including edge weights and descriptions.

Merge multiple source entities into a single target entity to resolve duplicates or synonyms.