haystack
https://github.com/deepset-ai/haystack
Python
:mag: LLM orchestration framework to build customizable, production-ready LLM applications. Connect components (models, vector DBs, file converters) to pipelines or agents that can interact with your data. With advanced retrieval methods, it's best suited
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- Issues
- Add a ranker component that uses an LLM to rerank documents
- Update Filter Tests for Document Stores
- Support default_headers for AzureOpenAIDocumentEmbedder and AzureOpenAITextEmbedder
- feat: add default_headers for azure embeddings
- Allow subclassing of `Document`
- feat: Add XLSXToDocument converter
- Allow for Haystack native data types as outputs to ConditionalRouter
- pEBR: A Probabilistic Approach to Embedding Based Retrieval
- Improve RAG capabilities of `DocumentStore`
- Expose relevance_score for ranker models through `pipeline.eval()`
- Docs
- Python not yet supported