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Build a RAG Using LangChain with Google Gemini

The project’s main objective is to develop a large language model (LLM) application using LangChain.

LLMs are AI-based models trained on massive amounts of data to understand complex human-like texts and generate human-like content. LangChain is an open source used to build AI applications driven by large language models (LLMs) like GPT-3. It has many resources that aid in building LLM-based applications, such as chatbots, translators, content writing tools, and summarizers.

We’ll build a text content generator application where the input prompt will be a few sentences and the output paragraphs of relevant text. We’ll use the Google Gemini Pro model to create this application. We need an API to access the model and perform operations like text generation, fine-tuning, chat history generation, and RAG. The model parameters can be fine-tuned for optimal performance.