Uploaded October 2023 | Updated September 2026, 2 weeks ago
If you are new to LLM and want to start you learning, the best tool is LangChain which is super easy to use with Python. Basically, LangChain is a framework built around LLMs. We can use it for chatbots, Generative Question-Answering (GQA), summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.
This video can be your kick-start to your journey into Generative AI or Large Language Models from coding perspective. With this tutorial you will be able to write questions, queries or other requests to OpenAI, to be more specific, to ChatGPT chat models.
I think, as a good start is LangChain's generation function, which generate random outputs to your inputs within Python code.
With OpenAI.generate method you will be able to construct and manage multiple queries at once.
The content of the tutorial:
0:00 - Intro
0:26 - Prepare Python virtual environment and install LangChain
1:00 - Setup OpenAI API Key
2:10 - Load OpenAI API Key to Python code
2:56 - Install OpenAI Python package
3:14 - LM Object Initialization with LangChain
4:17 - Simple LLM usage example and increase OpenAPI quote
5:59 - Use generations in LLMs with LangChain
8:47 - Final word
Note: text-davinci-003 text completion model was used when the video was recorded.
References to material mentioned in the video:
- LangChain installation: python.langchain.com/docs/get_started/installation
- OpenAI quote: platform.openai.com/account/billing/limits
If you want to get more GenerativeAI, Data Science, Python programming or any new related high quality content, please subscribe the channel @DataScienceGarage !
#langchain #python #LLM
If you are new to LLM and want to start you learning, the best tool is LangChain which is super easy to use with Python. Basically, LangChain is a framework built around LLMs. We can use it for chatbots, Generative Question-Answering (GQA), summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.
This video can be your kick-start to your journey into Generative AI or Large Language Models from coding perspective. With this tutorial you will be able to write questions, queries or other requests to OpenAI, to be more specific, to ChatGPT chat models.
I think, as a good start is LangChain's generation function, which generate random outputs to your inputs within Python code.
With OpenAI.generate method you will be able to construct and manage multiple queries at once.
The content of the tutorial:
0:00 - Intro
0:26 - Prepare Python virtual environment and install LangChain
1:00 - Setup OpenAI API Key
2:10 - Load OpenAI API Key to Python code
2:56 - Install OpenAI Python package
3:14 - LM Object Initialization with LangChain
4:17 - Simple LLM usage example and increase OpenAPI quote
5:59 - Use generations in LLMs with LangChain
8:47 - Final word
Note: text-davinci-003 text completion model was used when the video was recorded.
References to material mentioned in the video:
- LangChain installation: python.langchain.com/docs/get_started/installation
- OpenAI quote: platform.openai.com/account/billing/limits
If you want to get more GenerativeAI, Data Science, Python programming or any new related high quality content, please subscribe the channel @DataScienceGarage !
#langchain #python #LLM
