DiffbotGraphTransformer#

class langchain_experimental.graph_transformers.diffbot.DiffbotGraphTransformer(diffbot_api_key: str | None = None, fact_confidence_threshold: float = 0.7, include_qualifiers: bool = True, include_evidence: bool = True, simplified_schema: bool = True, extract_types: List[TypeOption] = [TypeOption.FACTS], *, include_confidence: bool = False)[source]#

Transform documents into graph documents using Diffbot NLP API.

A graph document transformation system takes a sequence of Documents and returns a sequence of Graph Documents.

Example

Initialize the graph transformer with various options.

Parameters:

  • diffbot_api_key (str) – The API key for Diffbot’s NLP services.

  • fact_confidence_threshold (float) – Minimum confidence level for facts to be included.

  • include_qualifiers (bool) – Whether to include qualifiers in the relationships.

  • include_evidence (bool) – Whether to include evidence for the relationships.

  • simplified_schema (bool) – Whether to use a simplified schema for relationships.

  • extract_types (List[TypeOption]) – A list of data types to extract. Facts, entities, and sentiment are supported. By default, the option is set to facts. A fact represents a combination of source and target nodes with a relationship type.

  • include_confidence (bool) – Whether to include confidence scores on nodes and rels

Methods

__init__([diffbot_api_key, ...])

Initialize the graph transformer with various options.

convert_to_graph_documents(documents)

Convert a sequence of documents into graph documents.

nlp_request(text)

Make an API request to the Diffbot NLP endpoint.

process_response(payload, document)

Transform the Diffbot NLP response into a GraphDocument.
__init__(diffbot_api_key: str | None = None, fact_confidence_threshold: float = 0.7, include_qualifiers: bool = True, include_evidence: bool = True, simplified_schema: bool = True, extract_types: List[TypeOption] = [TypeOption.FACTS], *, include_confidence: bool = False) → None[source]#

Initialize the graph transformer with various options.

Parameters:

  • diffbot_api_key (str) – The API key for Diffbot’s NLP services.

  • fact_confidence_threshold (float) – Minimum confidence level for facts to be included.

  • include_qualifiers (bool) – Whether to include qualifiers in the relationships.

  • include_evidence (bool) – Whether to include evidence for the relationships.

  • simplified_schema (bool) – Whether to use a simplified schema for relationships.

  • extract_types (List[TypeOption]) – A list of data types to extract. Facts, entities, and sentiment are supported. By default, the option is set to facts. A fact represents a combination of source and target nodes with a relationship type.

  • include_confidence (bool) – Whether to include confidence scores on nodes and rels

Return type:

None

convert_to_graph_documents(documents: Sequence[Document]) → List[GraphDocument][source]#

Convert a sequence of documents into graph documents.

Parameters:

  • documents (Sequence[Document]) – The original documents.

  • kwargs – Additional keyword arguments.

Returns:

The transformed documents as graphs.

Return type:

Sequence[GraphDocument]

nlp_request(text: str) → Dict[str, Any][source]#

Make an API request to the Diffbot NLP endpoint.

Parameters:

text (str) – The text to be processed.

Returns:

The JSON response from the API.

Return type:

Dict[str, Any]

process_response(payload: Dict[str, Any], document: Document) → GraphDocument[source]#

Transform the Diffbot NLP response into a GraphDocument.

Parameters:

  • payload (Dict[str, Any]) – The JSON response from Diffbot’s NLP API.

  • document (Document) – The original document.

Returns:

The transformed document as a graph.

Return type:

GraphDocument

Examples using DiffbotGraphTransformer