openssa.deprecated.ooda_rag.resources.dense_x.base.store_nodes_dict(nodes_dict: Dict[str, TextNode], nodes_cache_path) → None

Store nodes dict.

openssa.deprecated.ooda_rag.resources.dense_x.base.load_nodes_dict(nodes_cache_path: str) → Dict[str, TextNode]

Load nodes dict.

class openssa.deprecated.ooda_rag.resources.dense_x.base.DenseXRetrievalPack(documents: ~typing.List[~llama_index.core.schema.Document], proposition_llm: ~llama_index.core.llms.llm.LLM | None = None, query_llm: ~llama_index.core.llms.llm.LLM | None = None, embed_model: ~llama_index.core.base.embeddings.base.BaseEmbedding | None = None, text_splitter: ~llama_index.core.node_parser.interface.TextSplitter = SentenceSplitter(include_metadata=True, include_prev_next_rel=True, callback_manager=<llama_index.core.callbacks.base.CallbackManager object>, id_func=<function default_id_func>, chunk_size=1024, chunk_overlap=200, separator=' ', paragraph_separator='\n\n\n', secondary_chunking_regex='[^,.;。？！]+[,.;。？！]?'), similarity_top_k: int = 10)

Bases: BaseLlamaPack

get_modules() → Dict[str, Any]

Get modules.

run(query_str: str, **kwargs: Any) → Any

Run the pipeline.