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Building an LLM open source search engine in 100 lines using LangChain and Ray

Anyscale · published 18 April 2023

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Links from this post

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Host
https://python.langchain.com/docs/get_started/introduction
python.langchain.com
https://docs.ray.io/en/latest/serve/index.html
docs.ray.io
https://www.ray.io/
ray.io
https://huggingface.co/
huggingface.co
https://huggingface.co/sentence-transformers
huggingface.co
https://github.com/facebookresearch/faiss
github.com
https://gist.github.com/waleedkadous/d06097768abbea54d59e5d3ed4f045f3
gist.github.com
https://gist.github.com/waleedkadous/aea1d312d68c9431949442cc562d5f2c
gist.github.com
https://gist.github.com/waleedkadous/d0915e52cbe56dff328f5c00ded21107
gist.github.com
https://gist.github.com/waleedkadous/4c41f3ee66040f57d34c6a40e42b5969
gist.github.com
https://docs.google.com/forms/d/e/1FAIpQLSfAcoiLCHOguOm8e7Jnn-JJdZaCxPGjgVCvFijHB5PLaQLeig/viewform
docs.google.com
https://discuss.ray.io/
discuss.ray.io
https://github.com/ray-project/ray-educational-materials/blob/main/NLP_workloads/Text_generation/LLM_finetuning_and_batch_inference.ipynb
github.com
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