Neo4j-graphrag

Added
- Added `SinglePropertyExactMatchResolver` component allowing to merge entities with exact same property (e.g. name)

Added
- Added AzureOpenAILLM and AzureOpenAIEmbeddings to support Azure served OpenAI models
- Added `template` validation in `PromptTemplate` class upon construction.
- Examples demonstrating the use of Mistral embeddings and LLM in RAG pipelines.
- Added feature to include kwargs in `Text2CypherRetriever.search()` that will be injected into a custom prompt, if provided.
- Added validation to `custom_prompt` parameter of `Text2CypherRetriever` to ensure that `query_text` placeholder exists in prompt.
- Introduced a fixed size text splitter component for splitting text into specified fixed size chunks with overlap. Updated examples and tests to utilize this new component.
- Introduced Vertex AI LLM class for integrating Vertex AI models.
- Added unit tests for the Vertex AI LLM class.
- Added support for Cohere LLM and embeddings - added optional dependency to `cohere`.
- Added support for Anthropic LLM - added optional dependency to `anthropic`.
- Added support for MistralAI LLM - added optional dependency to `mistralai`.
- Added support for Qdrant - added optional dependency to `qdrant-client`.

Fixed
- Resolved import issue with the Vertex AI Embeddings class.
- Fixed bug in `Text2CypherRetriever` using `custom_prompt` arg where the `search` method would not inject the `query_text` content.
- `custom_prompt` arg is now converted to `Text2CypherTemplate` class within the `Text2CypherRetriever.get_search_results` method.
- `Text2CypherTemplate` and `RAGTemplate` prompt templates now require `query_text` arg and will error if it is not present. Previous `query_text` aliases may be used, but will warn of deprecation.
- Resolved issue where Neo4jWriter component would raise an error if the start or end node ID was not defined properly in the input.
- Resolved issue where relationship types was not escaped in the insert Cypher query.
- Improved query performance in Neo4jWriter: created nodes now have a generic `__KGBuilder__` label and an index is created on the `__KGBuilder__.id` property. Moreover, insertion queries are now batched. Batch size can be controlled using the `batch_size` parameter in the `Neo4jWriter` component.

Changed
- Moved the Embedder class to the neo4j_graphrag.embeddings directory for better organization alongside other custom embedders.
- Removed query argument from the GraphRAG class' `.search` method; users must now use `query_text`.
- Neo4jWriter component now runs a single query to merge node and set its embeddings if any.
- Nodes created by the `Neo4jWriter` now have an extra `__KGBuilder__` label. Nodes from the entity graph also have an `__Entity__` label.
- Dropped support for Python 3.8 (end of life).

Changed
- Updated documentation links in README.
- Renamed deprecated package references in documentation.

Added
- Introduction page to the documentation content tree.
- Introduced a new Vertex AI embeddings class for generating text embeddings using Vertex AI.
- Updated documentation to include OpenAI and Vertex AI embeddings classes.
- Added google-cloud-aiplatform as an optional dependency for Vertex AI embeddings.

Fixed
- Make `pygraphviz` an optional dependency - it is now only required when calling `pipeline.draw`.

Fixed
- Moved pygraphviz to optional dependencies under [tool.poetry.extras] in pyproject.toml to resolve an issue where pip install neo4j-graphrag incorrectly required pygraphviz as a mandatory dependency.

Changed
- Officially renamed neo4j-genai to neo4j-graphrag. For the final release version of neo4j-genai, please visit https://pypi.org/project/neo4j-genai/.