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Fix TDS links #106

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Feb 14, 2025
Merged

Fix TDS links #106

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2 changes: 1 addition & 1 deletion modules/genai-ecosystem/pages/graphrag.adoc
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Expand Up @@ -221,7 +221,7 @@ image::https://dist.neo4j.com/wp-content/uploads/20240618104511/build-kg-genai-e
// * https://huggingface.co/graphrag[GraphRAG HuggingFace Paper Collection^]
// * https://dev.neo4j.com/free-kg-book[(free) Knowledge Graph Book^]
* https://neo4j.com/developer-blog/global-graphrag-neo4j-langchain/[Implementing GraphRAG with Neo4j, GDS and LangChain^]
* https://towardsdatascience.com/integrating-microsoft-graphrag-into-neo4j-e0d4fa00714c[Store MSFT GraphRAG output into Neo4j and implement local and global retrievers with LangChain or LlamaIndex^]
* https://medium.com/towards-data-science/integrating-microsoft-graphrag-into-neo4j-e0d4fa00714c[Store MSFT GraphRAG output into Neo4j and implement local and global retrievers with LangChain or LlamaIndex^]

* https://www.googlecloudcommunity.com/gc/Cloud-Product-Articles/GenAI-GraphRAG-and-AI-agents-using-Vertex-AI-Reasoning-Engine/ta-p/789066[Deploy Neo4j-LangChain GraphRAG w/ GCP Vertex AI Reasoning Engine^]

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4 changes: 2 additions & 2 deletions modules/genai-ecosystem/pages/langchain.adoc
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Expand Up @@ -19,7 +19,7 @@ The broad and deep Neo4j integration allows for vector search, cypher generation

Here is an overview of the https://python.langchain.com/docs/use_cases/graph/quickstart[Graph Integrations^].

* https://towardsdatascience.com/integrating-neo4j-into-the-langchain-ecosystem-df0e988344d2[Integrating Neo4j into the LangChain Ecosystem^]
* https://medium.com/towards-data-science/integrating-neo4j-into-the-langchain-ecosystem-df0e988344d2[Integrating Neo4j into the LangChain Ecosystem^]

NOTE: When upgrading to LangChain 0.1.0+ make sure to read this article: https://medium.com/neo4j/langchain-v0-1-updating-graphacademy-neo4j-llm-courses-689e7c4eff3e[Updating GraphAcademy Neo4j & LLM Courses to Langchain v0.1^].

Expand Down Expand Up @@ -269,7 +269,7 @@ Examples for such tools or functions include:
* retrieve the neighbors of a node
* retrieve a shortest path between two nodes

* https://towardsdatascience.com/enhancing-interaction-between-language-models-and-graph-databases-via-a-semantic-layer-0a78ad3eba49[ Enhancing Interaction Between Language Models and Graph Databases via a Semantic Layer^]
* https://medium.com/towards-data-science/enhancing-interaction-between-language-models-and-graph-databases-via-a-semantic-layer-0a78ad3eba49[ Enhancing Interaction Between Language Models and Graph Databases via a Semantic Layer^]


=== Conversational Memory
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2 changes: 2 additions & 0 deletions modules/genai-ecosystem/pages/llamaindex.adoc
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Expand Up @@ -380,3 +380,5 @@ This https://llamahub.ai/l/tools/llama-index-tools-neo4j[Neo4j Query Engine Llam
* https://levelup.gitconnected.com/a-simpler-way-to-query-neo4j-knowledge-graphs-99c0a8bbf1d7[A Simpler Way to Query Neo4j Knowledge Graphs^]

* https://medium.com/@yu-joshua/using-llamaparse-for-knowledge-graph-creation-from-documents-3bd1e1849754[Using LlamaParse for Knowledge Graph Creation from Documents^]

* https://medium.com/neo4j/building-knowledge-graph-agents-with-llamaindex-workflows-b81f8d372f19[Build Knowledge Graph Agents With LlamaIndex Workflows]