RAG Overview If you've been looking for a good overview of LangChain + RAG, then you're in luck! @sophiamyang recently released a FANTASTIC presentation on exactly that. Covers both the basics as well as more advanced topics Presentation: https://
sophiamyang.github.io/slides-langcha
in-rag-panel/
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@langchain
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LangChain RAG Overview: Basics and Advanced Topics
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Building RAG from Scratch for Your AI Product
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"Why your next AI product needs RAG implemented in it" There are a LOT of different options for RAG But sometimes it's best to go back to the basics and build RAG from scratch @Avra_b wrote a fantastic article on why RAG is needed and how to get started, including a GitHub
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Community Contributions and Open Source Engagement Welcomed
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Again, we're really excited to see how this develops! We are extremely open to contributions and suggestions – please open PRs, file issues, DM us, or get in touch on the discord:
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MRKL agents and Hub loading in LangChain
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Agents MRKL: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/load_from_hub
… Load from Hub: https://
hwchase17.github.io/langchainjs/do
cs/modules/agents/load_from_hub
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LangChain Buffer Memory: Essential Tool for AI Agents
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Memory Buffer Memory: https://
hwchase17.github.io/langchainjs/do
cs/modules/memory/buffer_memory
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LangChain Chains: LLM, Vector DB QA, Conversation Guide
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Chains (just a selection) LLM Chain: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/llm_chain
… Vector DB QA: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/vector_db_qa
… Conversation Chain: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/conversation_chain
… Load from Hub: https://
hwchase17.github.io/langchainjs/do
cs/modules/chains/load_from_hub
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OpenAI LLMs and LangChain Integration Guide
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LLMs OpenAI: https://
hwchase17.github.io/langchainjs/do
cs/modules/llms/openai
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LangChain JS Indexes: Text Splitter, Embeddings, Vectorstores
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Indexes Text Splitter: https://
hwchase17.github.io/langchainjs/do
cs/modules/indexes/text_splitter
… Embeddings: https://
hwchase17.github.io/langchainjs/do
cs/modules/indexes/embeddings
… Vectorstores: https://
hwchase17.github.io/langchainjs/do
cs/modules/indexes/vectorstore
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LangChain JS Prompt Templates and Few Shot Examples Guide
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Prompts: Prompt Templates: https://
hwchase17.github.io/langchainjs/do
cs/modules/prompts/prompt_template
… Few Shot Examples: https://
hwchase17.github.io/langchainjs/do
cs/modules/prompts/few_shot_examples
… Load from Hub: https://
hwchase17.github.io/langchainjs/do
cs/modules/prompts/load_from_hub
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Cross-language AI abstractions with shared serializable formats
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Relationship to Python Package We built the same abstractions (prompts, LLMs, etc) we had in Python In particular, we built them in a way where they share the same serializable format This means you can load the same prompt, chain, agent in both languages