Building NLP applications with LLMs just got easier with LangChain AI.
Now you can easily chain multiple prompts together to build sophisticated AI solutions.
(A thread) ππ§΅
Now you can easily chain multiple prompts together to build sophisticated AI solutions.
(A thread) ππ§΅
In very simple words, the idea behind @LangChainAI is to allow logical connection of prompts in a way that prompts can talk to each other that too out-of-the-box.
@LangChainAI LangChain is a python library designed to provide:
1. Comprehensive collection of pieces you would ever want to combine
2. Flexible interface for combining pieces into a single comprehensive βchainβ
3. Schema for easily saving and sharing those chains.
1. Comprehensive collection of pieces you would ever want to combine
2. Flexible interface for combining pieces into a single comprehensive βchainβ
3. Schema for easily saving and sharing those chains.
@LangChainAI Installing @LangChainAI is as simple as installing any other Python package. You can install it via PIP from PyPI with the following command:
"pip install langchain"
"pip install langchain"
@LangChainAI Here are some examples of LLM-powered applications where @LangChainAI comes in handy to logically connect prompts and make them talk to each other π
@LangChainAI 1. Solving complex word Math Problems
Just provide the math problem description in english, and the prompts will communicate with each and come up with the result.
Just provide the math problem description in english, and the prompts will communicate with each and come up with the result.
@LangChainAI 2. Reasoning between Prompts
Here is a simple QA example that makes the model think/reason step-by-step just like a human would to get to the answer.
Here is a simple QA example that makes the model think/reason step-by-step just like a human would to get to the answer.
@LangChainAI 3. Chain Reaction (Step-by-step derivation)
In this example, given a question, the prompt will ask follow-up questions and feed the answers of those questions to another prompt until it logically gets to the answer.
In this example, given a question, the prompt will ask follow-up questions and feed the answers of those questions to another prompt until it logically gets to the answer.
@LangChainAI π If you liked this reason-based prompt approach, do support the project on GitHub - github.com
Check out the full documentation here - langchain.readthedocs.io
Check out the full documentation here - langchain.readthedocs.io
langchain.readthedocs.io/en/latest/indeβ¦
Welcome to LangChain β π¦π LangChain 0.0.117
Large language models (LLMs) are emerging as a transformative technology, enabling developers to bui...
github.com/hwchase17/langβ¦
GitHub - hwchase17/langchain: β‘ Building applications with LLMs through composability β‘
β‘ Building applications with LLMs through composability β‘ - GitHub - hwchase17/langchain: β‘ Building...
@LangChainAI If you enjoyed reading this, two requests:
1. Follow me @Saboo_Shubham_ to read more such content.
2. Share the first tweet in this thread so others can also read it π
1. Follow me @Saboo_Shubham_ to read more such content.
2. Share the first tweet in this thread so others can also read it π
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