Neo4j GenAI package for Python 0.5.0

https://github.com/neo4j/neo4j-genai-python/blob/main/CHANGELOG.md#050

Minor Changes

• Experimental Knowledge Graph Constructor: Introduces a PDF-to-knowledge-graph constructor in experimental mode. This constructor uses a flexible component/pipeline architecture and includes components such as text splitters, a schema builder, an entity-relation extractor, and a Neo4j database writer.
• Hybrid Retriever Fix: Fixes the hybrid retriever query to ensure proper normalization of scores returned by both vector and full-text indexes.

Neo4j GenAI package for Python 0.4.0

https://github.com/neo4j/neo4j-genai-python/blob/main/CHANGELOG.md#040

Minor Changes

• Introduced an optional custom_prompt argument to the Text2CypherRetriever class for enhanced customization capabilities.
• Renamed the first parameter of GraphRAG.search from query to query_text for consistency, while ensuring backward compatibility with deprecation warnings for the query parameter.

Neo4j GenAI package for Python 0.3.1

https://github.com/neo4j/neo4j-genai-python/blob/main/CHANGELOG.md#031

Patch Changes

• OpenAIEmbedding fixes: Fixed embedding model initialization and removed unused import to prevent ImportError when sentence_transformers is not installed.

Neo4j GenAI package for Python 0.3.0

https://github.com/neo4j/neo4j-genai-python/blob/main/CHANGELOG.md#030

Minor Changes

• GraphRAG Integration: Introducing the GraphRAG object to enable a complete Retrieval-Augmented Generation pipeline. This major feature supports context retrieval, sophisticated prompt formatting, and dynamic answer generation, streamlining the use of RAG techniques within Neo4j.
• Enhanced Customization Options: Added PromptTemplate and RagTemplate for customizable prompt generation. Also, a new result_formatter argument across all retrievers allows for tailored formatting of retrieval results, offering greater flexibility in how results are presented and utilized.
• VectorRetriever Updates: Enhanced to return metadata such as nodeLabels and id without direct embedding output, simplifying data handling.
• Developer Experience: Enhanced developer interactions with improved documentation, including a new User Guide that provides comprehensive instructions and tips for getting started and effectively using the neo4j-genai-python package.