Langflow is an open-source visual programming framework built on top of LangChain. It offers a graphical interface for building and managing applications that use large language models (LLMs). With Langflow, developers (and even non-developers) can design, test, and deploy LLM-powered workflows using a no-code/low-code approach.
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LangChain is an open-source framework designed to help developers build applications that leverage language models (LLMs). It provides tools and abstractions to simplify the development of applications centered around natural language processing (NLP), such as language generation, retrieval, summarization, and question answering.
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Retrieval Augmented Generation or RAG is a technique that enables generative artificial intelligence (Gen AI) models to retrieve and incorporate new information. It modifies interactions with a large language model (LLM) so that the model responds to user queries with reference to a specified set of documents, using this information to supplement information from its pre-existing training data. This allows LLMs to use domain-specific and/or updated information (Wikipedia) .
Read MorePrompt Engineering or Prompting is the process of structuring or crafting an instruction or prompt in order to produce the best possible output from a generative artificial intelligence (AI) model. A prompt is natural language text describing the task that an AI should perform. A prompt for a text-to-text language model can be a query, a command, or a longer statement including context, instructions, and conversation history. (Wikipedia).
Read MoreA large language model or LLM is a type of machine learning model designed for natural language processing or NLP. These models have an extremely high number of parameters (trillions as of this writing) and are trained on vast amounts of human-generated and human-consumed data. Due to their extensive training on this data, LLMs develop predictive capabilities in syntax, semantics, and knowledge within human language. This enables them to generate coherent and contextually relevant responses, giving the impression of intelligence.
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