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Add links to blog posts in the README (#236)
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* Add links to blog posts in README

* Fix CHANGELOG, add link to neo4j GenAI ecosystem
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stellasia authored Dec 16, 2024
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10 changes: 5 additions & 5 deletions CHANGELOG.md
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## Next

## Added
- Integrated json-repair package to handle and repair invalid JSON generated by LLMs.
- Introduced InvalidJSONError exception for handling cases where JSON repair fails.
### Added
- Integrated `json-repair` package to handle and repair invalid JSON generated by LLMs.
- Introduced `InvalidJSONError` exception for handling cases where JSON repair fails.
- Ability to create a Pipeline or SimpleKGPipeline from a config file. See [the example](examples/build_graph/from_config_files/simple_kg_pipeline_from_config_file.py).
- Added `OllamaLLM` and `OllamaEmbeddings` classes to make Ollama support more explicit. Implementations using the `OpenAILLM` and `OpenAIEmbeddings` classes will still work.

## Changed
- Updated LLM prompts to include stricter instructions for generating valid JSON.
### Changed
- Updated LLM prompt for Entity and Relation extraction to include stricter instructions for generating valid JSON.

### Fixed
- Added schema functions to the documentation.
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16 changes: 16 additions & 0 deletions README.md
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Expand Up @@ -7,6 +7,22 @@ As a first-party library, it offers a robust, feature-rich, and high-performance

Documentation can be found [here](https://neo4j.com/docs/neo4j-graphrag-python/)

### Resources

A series of blog posts demonstrating how to use this package:

- Build a Knowledge Graph and use GenAI to answer questions:
- [GraphRAG Python Package: Accelerating GenAI With Knowledge Graphs](https://neo4j.com/blog/graphrag-python-package/)
- Retrievers: when the Neo4j graph is already populated:
- [Getting Started With the Neo4j GraphRAG Python Package](https://neo4j.com/developer-blog/get-started-graphrag-python-package/)
- [Enriching Vector Search With Graph Traversal Using the GraphRAG Python Package](https://neo4j.com/developer-blog/graph-traversal-graphrag-python-package/)
- [Hybrid Retrieval for GraphRAG Applications Using the GraphRAG Python Package](https://neo4j.com/developer-blog/hybrid-retrieval-graphrag-python-package/)
- [Enhancing Hybrid Retrieval With Graph Traversal Using the GraphRAG Python Package](https://neo4j.com/developer-blog/enhancing-hybrid-retrieval-graphrag-python-package/)
- [Effortless RAG With Text2CypherRetriever](https://medium.com/neo4j/effortless-rag-with-text2cypherretriever-cb1a781ca53c)

A list of Neo4j GenAI-related features can also be found at [Neo4j GenAI Ecosystem](https://neo4j.com/labs/genai-ecosystem/).


## 🐍 Python Version Support

| Version | Supported? |
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