Difference between revisions of "LangChain"
m (→Zapier) |
m |
||
| Line 20: | Line 20: | ||
* [[Attention]] Mechanism ...[[Transformer]] Model ...[[Generative Pre-trained Transformer (GPT)]] | * [[Attention]] Mechanism ...[[Transformer]] Model ...[[Generative Pre-trained Transformer (GPT)]] | ||
* [[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)]] | |
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. | ||
| Line 68: | Line 68: | ||
= Emails = | = Emails = | ||
| − | + | <youtube>y1pyAQM-3Bo</youtube> | |
| − | = Zapier = | + | == Zapier == |
<youtube>7tNm0yiDigU</youtube> | <youtube>7tNm0yiDigU</youtube> | ||
Revision as of 06:05, 22 March 2023
YouTube ... Quora ...Google search ...Google News ...Bing News
- Langchain | GitHub
- Case Studies
- Natural Language Processing (NLP) ...Generation ...LLM ...Tools & Services
- Assistants ... Hybrid Assistants ... Agents ... Negotiation
- Attention Mechanism ...Transformer Model ...Generative Pre-trained Transformer (GPT)
- 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
Javascript
Colab
Emails
Zapier
Pinecone
Supabase
Visual ChatGPT
