Tree Retrievers#

Summarize query.

class llama_index.core.indices.tree.all_leaf_retriever.TreeAllLeafRetriever(index: TreeIndex, callback_manager: Optional[CallbackManager] = None, object_map: Optional[dict] = None, verbose: bool = False, **kwargs: Any)#

GPT all leaf retriever.

This class builds a query-specific tree from leaf nodes to return a response. Using this query mode means that the tree index doesn’t need to be built when initialized, since we rebuild the tree for each query.

Parameters: text_qa_template (Optional[BasePromptTemplate]) – Question-Answer Prompt (see Prompt Templates).

as_query_component(partial: Optional[Dict[str, Any]] = None, **kwargs: Any) → QueryComponent#: Get query component.

get_prompts() → Dict[str, BasePromptTemplate]#: Get a prompt.

get_service_context() → Optional[ServiceContext]#: Attempts to resolve a service context. Short-circuits at self.service_context, self._service_context, or self._index.service_context.

retrieve(str_or_query_bundle: Union[str, QueryBundle]) → List[NodeWithScore]#

Retrieve nodes given query.

Parameters: str_or_query_bundle (QueryType) – Either a query string or a QueryBundle object.

update_prompts(prompts_dict: Dict[str, BasePromptTemplate]) → None#

Update prompts.

Other prompts will remain in place.

Leaf query mechanism.

class llama_index.core.indices.tree.select_leaf_retriever.TreeSelectLeafRetriever(index: TreeIndex, query_template: Optional[BasePromptTemplate] = None, text_qa_template: Optional[BasePromptTemplate] = None, refine_template: Optional[BasePromptTemplate] = None, query_template_multiple: Optional[BasePromptTemplate] = None, child_branch_factor: int = 1, verbose: bool = False, callback_manager: Optional[CallbackManager] = None, object_map: Optional[dict] = None, **kwargs: Any)#

Tree select leaf retriever.

This class traverses the index graph and searches for a leaf node that can best answer the query.

Parameters

query_template (Optional[BasePromptTemplate]) – Tree Select Query Prompt (see Prompt Templates).
query_template_multiple (Optional[BasePromptTemplate]) – Tree Select Query Prompt (Multiple) (see Prompt Templates).
child_branch_factor (int) – Number of child nodes to consider at each level. If child_branch_factor is 1, then the query will only choose one child node to traverse for any given parent node. If child_branch_factor is 2, then the query will choose two child nodes.

as_query_component(partial: Optional[Dict[str, Any]] = None, **kwargs: Any) → QueryComponent#: Get query component.

get_prompts() → Dict[str, BasePromptTemplate]#: Get a prompt.

get_service_context() → Optional[ServiceContext]#: Attempts to resolve a service context. Short-circuits at self.service_context, self._service_context, or self._index.service_context.

retrieve(str_or_query_bundle: Union[str, QueryBundle]) → List[NodeWithScore]#

Retrieve nodes given query.

Parameters: str_or_query_bundle (QueryType) – Either a query string or a QueryBundle object.

update_prompts(prompts_dict: Dict[str, BasePromptTemplate]) → None#

Update prompts.

Other prompts will remain in place.

llama_index.core.indices.tree.select_leaf_retriever.get_text_from_node(node: BaseNode, level: Optional[int] = None, verbose: bool = False) → str#: Get text from node.

Query Tree using embedding similarity between query and node text.

class llama_index.core.indices.tree.select_leaf_embedding_retriever.TreeSelectLeafEmbeddingRetriever(index: TreeIndex, embed_model: Optional[BaseEmbedding] = None, query_template: Optional[BasePromptTemplate] = None, text_qa_template: Optional[BasePromptTemplate] = None, refine_template: Optional[BasePromptTemplate] = None, query_template_multiple: Optional[BasePromptTemplate] = None, child_branch_factor: int = 1, verbose: bool = False, callback_manager: Optional[CallbackManager] = None, object_map: Optional[dict] = None, **kwargs: Any)#

Tree select leaf embedding retriever.

This class traverses the index graph using the embedding similarity between the query and the node text.

Parameters

query_template (Optional[BasePromptTemplate]) – Tree Select Query Prompt (see Prompt Templates).
query_template_multiple (Optional[BasePromptTemplate]) – Tree Select Query Prompt (Multiple) (see Prompt Templates).
text_qa_template (Optional[BasePromptTemplate]) – Question-Answer Prompt (see Prompt Templates).
refine_template (Optional[BasePromptTemplate]) – Refinement Prompt (see Prompt Templates).
child_branch_factor (int) – Number of child nodes to consider at each level. If child_branch_factor is 1, then the query will only choose one child node to traverse for any given parent node. If child_branch_factor is 2, then the query will choose two child nodes.
embed_model (Optional[BaseEmbedding]) – Embedding model to use for embedding similarity.

as_query_component(partial: Optional[Dict[str, Any]] = None, **kwargs: Any) → QueryComponent#: Get query component.

get_prompts() → Dict[str, BasePromptTemplate]#: Get a prompt.

get_service_context() → Optional[ServiceContext]#: Attempts to resolve a service context. Short-circuits at self.service_context, self._service_context, or self._index.service_context.

retrieve(str_or_query_bundle: Union[str, QueryBundle]) → List[NodeWithScore]#

Retrieve nodes given query.

Parameters: str_or_query_bundle (QueryType) – Either a query string or a QueryBundle object.

update_prompts(prompts_dict: Dict[str, BasePromptTemplate]) → None#

Update prompts.

Other prompts will remain in place.