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Client Verbosity

• Fixed verbose request progress bar in Client.

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Simplified Query Client

• Added a simple method for executing queries while retaining support for customizable queries.
• Improved bulk request logic.
• Updated and added demos for both query methods.
• Updated error messages for failed queries to only print if verbose is set.

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Knowledge Graph

• Added OpenAI-driven knowledge graph extraction with deduplication and improved insertion logic. (apps/kg1.py)
• Added spaCy-driven knowledge graph extraction for entity/relationship extraction. (apps/kg2.py)

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Client Verbosity

• Progress bars in query execution can now be toggled via the verbose flag (default True).

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Providers

• Added support for OpenAI models (gpt-4o) for knowledge graph extraction.

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Knowledge Graph

• Used OpenAI for entity/edge extraction and improved deduplication and insertion logic.
• Added FastAPI-based HTTP service for embedding text using HuggingFace transformers in apps/texttovec.py.
• Added a new example for vector insert operations in examples/vec.py.

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Providers

• Added Ollama provider to interface with Ollama for language model tasks.

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Knowledge Graph

• Added a script to use the new Ollama provider to extract entities and relationships from text.

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Instance Management

• Fixed port not updated after deploy.
• Added auto stop instance on script exit.
• Removed auto-start instance on client creation.

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UV Installation

• Added support for UV installation.

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Knowledge Graph

• Added a script to take a PDF file as input, extract text from it, and then use a local model to generate embeddings for text chunks.

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Instance Management

• Added instance management via Python script.

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Initial Release With Official Rag Support

• This release includes initial support for creating AI RAG agents.
• Supplied are 2 new default queries ragloaddocs and ragsearchdocs with which you can load your chunks of documents and vectors and then vector search for them all in helix-db.
• Release also contains some bug fixes and more examples + rag demos that can be found in the examples/ directory.