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This PR adds full GraphRAG implementation to AllyCAT with two deployment options - local and cloud.

New Features:

  • Entity and relationship extraction from documents
  • Community detection using Louvain algorithm
  • Graph database storage in Neo4j
  • 7-phase query system with query-aware ranking
  • Hybrid search combining vector and graph traversal
  • Two complete setups: local (Ollama+Milvus) and cloud (Nebius+Zilliz)

New Folders:

  • graphrag-neo4j-milvus-ollama: Local setup with Ollama LLM and Milvus vector DB
  • graphrag-neo4j-zilliz-nebius: Cloud setup with Nebius LLM and Zilliz Cloud

Implementation Details:

  • GraphRAG processing pipeline with 4 phases
  • Query system with preprocessing, retrieval, augmentation, and synthesis
  • Docker support with simplified configurations
  • Auto-run pipeline option
  • Memory optimization with dependency cleanup

Files Changed:

  • Added 94 files across both GraphRAG implementations
  • Updated main README with GraphRAG features and quickstart
  • Added comprehensive READMEs for both setups
  • Clean separation between local and cloud dependencies

Testing:

  • Tested on local setup with Ollama
  • Verified Docker builds and deployments
  • Confirmed query system with Neo4j integration

Signed-off-by: Niloy Deb Barma [email protected]

- graphrag-neo4j-milvus-ollama: Local setup with Ollama + Milvus
- graphrag-neo4j-zilliz-nebius: Cloud setup with Nebius + Zilliz

Signed-off-by: Niloy Deb Barma <[email protected]>
- Added READMEs for both local and cloud GraphRAG setups
- Updated main README with GraphRAG features and quickstart options
-

Signed-off-by: Niloy Deb Barma <[email protected]>
- Removed flask and chainlit vector RAG options
- Only GraphRAG apps (flask_graph, chainlit_graph) remain

Signed-off-by: Niloy Deb Barma <[email protected]>
Signed-off-by: Niloy Deb Barma <[email protected]>
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