Difference between revisions of "LangChain"

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* [[Generative AI]]  ... [[OpenAI]]'s [[ChatGPT]] ... [[Perplexity]]  ... [[Microsoft]]'s [[BingAI]] ... [[You]] ...[[Google]]'s [[Bard]]
 
* [[Generative AI]]  ... [[OpenAI]]'s [[ChatGPT]] ... [[Perplexity]]  ... [[Microsoft]]'s [[BingAI]] ... [[You]] ...[[Google]]'s [[Bard]]
 
* [[Prompt Engineering (PE)]]
 
* [[Prompt Engineering (PE)]]
 +
* [https://www.youtube.com/watch?v=_v_fgW2SkkQ&list=PLqZXAkvF1bPNQER9mLmDbntNfSpzdDIU5 Data Independent video series]
  
 
LangChain is a framework built around [[Large Language Model (LLM)]] that can be used for chatbots, Generative Question-Answering (GQA), summarization, and more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around [[Large Language Model (LLM)|LLMs]]. [[Large Language Model (LLM)|LLMs]] are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you are able to combine them with other sources of computation or knowledge.
 
LangChain is a framework built around [[Large Language Model (LLM)]] that can be used for chatbots, Generative Question-Answering (GQA), summarization, and more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around [[Large Language Model (LLM)|LLMs]]. [[Large Language Model (LLM)|LLMs]] are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you are able to combine them with other sources of computation or knowledge.

Revision as of 06:46, 22 March 2023

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LangChain is a framework built around Large Language Model (LLM) that can be used for chatbots, Generative Question-Answering (GQA), summarization, and more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs. LLMs are emerging as a transformative technology, enabling developers to build applications that they previously could not. But using these LLMs in isolation is often not enough to create a truly powerful app - the real power comes when you are able to combine them with other sources of computation or knowledge.

  • Python library
  • Javascript



Javascript


Colab



Pinecone

Supabase


Visual ChatGPT

Summarization

Emails


Zapier