GPT-crawler template Easily building chat assistants for websites (documentation, etc) is an extremely popular use-case. GPT-crawler from @builderio is rapidly growing in popularity for building custom GPTs for sites: https://
builder.io/blog/custom-gpt This template shows how to
@langchain
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GPT-Crawler: Building Custom AI Chatbots for Websites
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Switching LLM Providers: Prompting Strategies and LangSmith Hub
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Wondering how to switch LLM providers? It's not as simple as changing the endpoint Different LLMs often require different prompting strategies. One way to explore different prompting strategies? LangSmith Prompt Hub – a collection of different prompts for
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RAG Enhancement with Decision-Making Agents and Neo4j
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Enhancing RAG with Decision-Making Agents and Neo4j Vector and Graph Chain Tools Using LangChain Templates and LangServe A length title – but the blog is well worth the read LLMs + Graph DBs are always a fun read Sourav Joshi covers how to integrate Neo4j Vector and
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Multi-Index Retrieval and Routing Strategies for AI
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Multi-index retrieval templates Sometimes you want to or need to use information from multiple indexes in your application. There's two basic ways to do this: Route: given a new input, choose (or route to) the most relevant index and retrieve from it. This is most useful when
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Building Research Assistants with Swappable Retrievers
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Building a research assistant (long form YouTube tutorial) Starts by building a web research assistant, but covers how to swap in an arbitrary retriever. Uses an Arxiv retriever… what retriever would you want to swap in?
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OpenGPTs Improvements: Catching Up with OpenAI GPTs
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Good overview of OpenGPTs improvements from @Saboo_Shubham_ Blog: https://
unwindai.substack.com/p/opengpt-catc
hing-up-with-openai-gpts-70a
… The only downside for Shubham is that he's going to have to write a lot more of these… we're planning another big release next week. And then another one the week after… got some -
OpenAI RAG Strategies for Improving Application Performance
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Applying OpenAI's RAG strategies At demo day, OpenAI reported a series of useful tricks for improving RAG app performance. In this short guide, we:
1/ Describe each of the strategies mentioned 2/ Link to docs so you can test each for yourself
3/ Show related ideas that -
Self-Query Template: Leveraging Metadata in RAG Systems
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Self Query Template (
@elastic
) Often times documents come with really useful metadata! But how can you best take advantage of this metadata when doing RAG? Self-query is one way to do so. This converts a natural language query into one piece that is embedded and -
Chain-of-Note Prompting Technique for RAG Applications
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Chain-of-Note Template Chain-of-Note is a new prompting technique by @wyu_nd et al for RAG applications that helps improve performance when the retrieved information might be noisy. We implemented a Chain-of-Note app as a LangChain template. Given a question, query Wikipedia
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Function Call Inspection and Dark Mode in AI Platform
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The improvements doesn't just stay within datasets! Inspect function calls and tools right in run details page and playground as well 🌟
— LangChain (@LangChain) 16 novembre 2023
Obligatory dark mode showcase for night owls🦉 https://t.co/HtI8ojfLxE pic.twitter.com/D0U72WRauqThe improvements doesn't just stay within datasets! Inspect function calls and tools right in run details page and playground as well Obligatory dark mode showcase for night owls