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# rag

Retrieval augmented generation, or RAG, is an architectural approach that can improve the efficacy of large language model (LLM) applications by leveraging custom data.

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Serverless LLM Chatbot Using Your Custom Data - built with Langtail and Qdrant
thyrst profile

Serverless LLM Chatbot Using Your Custom Data - built with Langtail and Qdrant

#llm #openai #rag
1
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5 min read
Langchain — RAG — Retrieval Augmented Generation
airton_lirajunior_2ddebd profile

Langchain — RAG — Retrieval Augmented Generation

#langchain #rag #llm #ia
3
Comments
3 min read
Retrieving Original Documents via Summaries with Weaviate and LangChain
oleh-halytskyi profile

Retrieving Original Documents via Summaries with Weaviate and LangChain

#rag #ai #llm #langchain
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12 min read
RAG Explained: Indexing and Vector Database
busycaesar profile

RAG Explained: Indexing and Vector Database

#rag #indexing #vectordatabase #llm
1
Comments
2 min read
Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate
tutti profile
Tutty

Can LLMs Produce Faithful Explanations For Fact-checking? Towards Faithful Explainable Fact-Checking via Multi-Agent Debate

#rag #chatgpt #nlp
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1 min read
The Demise Of Human Coding, Rise Of AI, And Why It's Good For Devs Too
danielrosehill profile

The Demise Of Human Coding, Rise Of AI, And Why It's Good For Devs Too

#programming #ai #llm #rag
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4 min read
Comprehensive Guide to the Capabilities and Applications of Large Language Models (LLMs)
jayadev_rayavarapu_014955 profile

Comprehensive Guide to the Capabilities and Applications of Large Language Models (LLMs)

#ai #llm #rag
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12 min read
RAG Explained: Generation of Embeddings
busycaesar profile

RAG Explained: Generation of Embeddings

#rag #llm #vectordatabase