AutoRAG
Automatically Evaluate RAG pipelines with your own data. Find optimal structure for new RAG product.
Installation
In a virtualenv (see these instructions if you need to create one):
pip3 install autorag
Dependencies
- aiohttp
- rank-bm25
- ipykernel
- grpcio-tools
- langchain-core
- llama-index-retrievers-bm25
- grpcio-health-checking
- fastapi
- emoji
- scikit-learn
- tokenlog
- langsmith
- voyageai
- datasets
- llama-index-llms-openai
- pyyaml
- grpcio
- pydantic
- tiktoken
- tqdm
- quart
- langchain-upstage
- llama-index-core
- llama-index-llms-bedrock
- rouge-score
- openai
- fastparquet
- langchain-unstructured
- rich
- llama-index-embeddings-openai-like
- panel
- pymilvus
- qdrant-client
- pinecone
- click
- chromadb
- pyarrow
- cohere
- ipywidgets-bokeh
- mixedbread-ai
- banks
- langchain-community
- llama-index-readers-file
- llama-index-embeddings-openai
- sacrebleu
- pandas
- llama-index
- evaluate
- pyngrok
- grpcio-status
- seaborn
- ipywidgets
- gradio
- weaviate-client
- couchbase
- llama-index-llms-openai-like
- numpy
- streamlit
- llama-index-embeddings-ollama
Releases
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