Difference between revisions of "LangChain"
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* [https://www.youtube.com/watch?v=_v_fgW2SkkQ&list=PLqZXAkvF1bPNQER9mLmDbntNfSpzdDIU5 Tutorial video series | Data Independent] | * [https://www.youtube.com/watch?v=_v_fgW2SkkQ&list=PLqZXAkvF1bPNQER9mLmDbntNfSpzdDIU5 Tutorial video series | Data Independent] | ||
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Revision as of 07:08, 22 March 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Langchain | GitHub
- Harrison Chase | LinkedIn ... GitHub ... Twitter
- Case Studies
- Assistants ... Hybrid Assistants ... Agents ... Negotiation ... Langchain
- Python ... Generative AI with Python ... Javascript ... Generative AI with Javascript ... Game Development with Generative AI
- Development ...AI Pair Programming Tools ... Analytics ... Visualization ... Diagrams for Business Analysis
- Generative AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's BingAI ... You ...Google's Bard
- Natural Language Processing (NLP) ...Generation ...LLM ...Tools & Services
- Generative AI ... OpenAI's ChatGPT ... Perplexity ... Microsoft's BingAI ... You ...Google's Bard
- Prompt Engineering (PE)
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
Contents
Data Independent
Colab
Javascript
Pinecone
Supabase
Visual ChatGPT
Summarization
Emails
Zapier
