README.md

LangChain Simple Applications 🦜🛠️

This repo includes a bounce of tutorial notebooks to understand feature of LangChain framework which helps you build LLM-powered applications and of course LLMs.

Some example needs OpenAI APIs, so please creat secret key by using your OpenAI account and export to your environment variables but note that OpenAI APIs is not free but it is not expensive for trial either.

Please, follow the steps bellow for an easy demo.

Getting started

Install python dependencies;

pip install -r requirements.txt

Set up your OpenAI key;

export OPENAI_API_KEY='your-api-key-here'

Resources

[1] https://towardsdatascience.com/getting-started-with-langchain-a-beginners-guide-to-building-llm-powered-applications-95fc8898732c

[2] https://towardsdatascience.com/explaining-vector-databases-in-3-levels-of-difficulty-fc392e48ab78

[3] https://towardsdatascience.com/getting-started-with-weaviate-a-beginners-guide-to-search-with-vector-databases-14bbb9285839

[4] https://towardsdatascience.com/easily-estimate-your-openai-api-costs-with-tiktoken-c17caf6d015e

[5] https://towardsdatascience.com/why-openais-api-is-more-expensive-for-non-english-languages-553da4a1eecc

[6] https://towardsdatascience.com/retrieval-augmented-generation-rag-from-theory-to-langchain-implementation-4e9bd5f6a4f2

[7] https://medium.com/@iamleonie/recreating-amazons-new-generative-ai-feature-product-review-summaries-50640e40872a

[8] https://towardsdatascience.com/2023-in-review-recapping-the-post-chatgpt-era-and-what-to-expect-for-2024-bb4357a4e827

[9] https://python.langchain.com/docs/use_cases/summarization/#option-1.-stuff

[10] https://github.com/mendableai/QA_clustering

[11] https://platform.openai.com/docs/api-reference/authentication

[12] https://python.langchain.com/docs/get_started/introduction

Authors

Kubilay Tuna

License

GNU General Public License v3.0