Memory support for chains with multi inputs Previously, memory only worked if there was single input This meant it couldn't work in cases like question/answering, where you passed in multiple inputs (documents and a question) Now it can: https://
langchain.readthedocs.io/en/latest/exam
ples/memory/adding_memory_chain_multiple_inputs.html
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OPEN SOURCE
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Memory Support Now Works with Multiple Chain Inputs
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LangChain v0.0.51 Release: Enhanced Tools, Memory, and Documentation
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v0.0.51 Unify return types for intermediate steps – h/t @johnjnay Add sports & knowledge graph results to SerpAPI wrapper – @brunotorious Document improvements: @eltociear @samcwl Making tools editable – h/t @brunotorious Memory support for chains with multi inputs
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Customizable AI Response Prefix in Conversational Memory
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More customizability for conversational memory A small change, but allows for specification of the prefix to use for for the AI response Was previously hardcoded to "AI", but can now be set to whatever Idea came from the discord! https://
langchain.readthedocs.io/en/latest/exam
ples/memory/conversational_customization.html
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LangChain Improves Memory Documentation Organization
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Improved memory docs In order to keep up with all these changes to memory, we also revamped the memory docs slightly to be more organized https://
langchain.readthedocs.io/en/latest/exam
ples/memory.html
… As always, let us know if you have feedback! -
New Memory Type Combining Summary and Context Window
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New memory type Previously, we had one memory type that created a summary, another that kept a window of recent lines of conversation. jaloo555 added a new type of memory which does both! It decides the window based on token length. https://langchain.readthedocs.io/en/latest/examples/memory/conversational_memory.html#ConversationSummaryBufferMemory
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Weaviate Vectorstore: New add_texts Method Implementation
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add_texts for @weaviate_io The @weaviate_io vectorstore implementation was previously missing an `add_texts` method @CShorten30 added one! This allows you to easily insert embeddings (eg, of examples for the example selector)
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Map-Reduce and Refine Chains Now Return Intermediate Steps
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Return intermediate steps for map-reduce & refine chains @johnjnay had the great idea to allow for returning of intermediate steps of these chains to the user This makes it easy to inspect things like Q&A over each document, before combining https://
langchain.readthedocs.io/en/latest/exam
ples/data_augmented_generation/question_answering.html#The-map_reduce-Chain
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Optimizing minGPT: Performance improvements from 495ms to 102ms
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having fun optimizing minGPT today
– base: 495ms
– zero_grad(set_to_none=True): 492
– torch.jit.script gelu: 463
– OMP_PROC_BIND=CLOSE: 453
– torch.backends.cuda.matmul.allow_tf32: 143
– torch.autocast(torch.bfloat16): 121
– FlashAttention: 102
now: more fused kernels more better -
Splitting minGPT into educational and efficient versions
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Context I realized I have to split up minGPT because I can't properly simultaneously satisfy both 1) educational and 2) efficient in one repo. So I'm separately writing 1) the maximally educational minGPT (+video etc.) and 2) a more efficient (still ~clean) version that has teeth
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Open Source Chatbot Creation Example Released
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There's been lots of chatbots announced recently Check out for an open source example of how to create one! @brunotorious