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Memory Implementation for Follow-up Questions in AI Systems

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05 July 2023 17h02

And finally, chat: we explain how to use memory to enable follow up questions, why that is necessary, and methods for doing so Big shout to to @RLanceMartin for helping prep all these materials!!!! Always fun to do these! What topic should we do next?

Six RAG Modules: Deep Dive on Text Splitters and Retrieval

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05 July 2023 17h02

There are six modules: – Document loaders
– Text splitters
– Embeddings and vector stores
– Retrieval
– QA generation
– Chat We go deep on each one. The three I think are most interesting/insightful: text splitters, retrieval, chat

Advanced Text Splitting and Semantic Retrieval in LangChain

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05 July 2023 17h02

Text splitters: there's a lot of nuance in how you split text!! We cover a few examples of the advanced methods we have in LangChain Retrieval: semantic search can get you 80% of the way there easily, but getting that last bit can be hard. We cover methods to push further

→ View original post on X — @rasbt

New scikit-learn Version Released with PyTorch Support and Features

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@rasbt

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05 July 2023 16h23

It doesn't get much attention these days (in both senses) but a new version of @scikit_learn
, my favorite machine learning library, is out! – PyTorch support for LinearDiscriminant Analysis
– Validation Curves
– Decision tree with N/A features
– and more

→ View original post on X — @_akhaliq

GPT-Migrate: Migrate Your Codebase Between Frameworks

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@_akhaliq

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05 July 2023 16h10

◐ GPT-Migrate ◑

migrate your codebase from one framework or language to another

github: https://t.co/FkMdhzW2Kj pic.twitter.com/JWZW19TtNv
— AK (@_akhaliq) 5 juillet 2023

◐ GPT-Migrate ◑ migrate your codebase from one framework or language to another github: https://
github.com/0xpayne/gpt-mi
grate
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Refine Documents Chain: Iterative Document Processing with LangChain

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05 July 2023 16h06

Refine Documents Chain This chain uses the first document to get an initial response It then loops over the remaining docs, making a call to the language model to combining the response with the next document Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.refine.RefineDocumentsChain.html#langchain.chains.combine_documents.refine.RefineDocumentsChain
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Map Rerank Chain: LLM Document Scoring and Ranking

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05 July 2023 16h06

Map Rerank Finally, the Map Rerank Chain calls an LLM on each document, asking not only for an answer but also a score It then sorts the responses by the score and returns the highest one Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain.html#langchain.chains.combine_documents.map_rerank.MapRerankDocumentsChain
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MapReduceDocumentsChain: Processing Documents with LLM

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05 July 2023 16h06

Map Reduce Chain This builds on top of the ReduceDocumentsChain It takes an LLMChain and a ReduceDocumentsChain. It first applies the LLMChain to each document, and then passes all the results to the ReduceDocumentsChain Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain.html#langchain.chains.combine_documents.map_reduce.MapReduceDocumentsChain
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StuffDocumentsChain: Basic Document Combination for LLMs

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05 July 2023 16h05

Stuff Documents Chain The most basic CombineDocumentsChain, this takes N documents, formats them into a string using a PromptTemplate and `format_document`, and then combines them into a single prompt and passes them to an LLM Docs: https://
api.python.langchain.com/en/latest/chai
ns/langchain.chains.combine_documents.stuff.StuffDocumentsChain.html#langchain.chains.combine_documents.stuff.StuffDocumentsChain
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