llm-python
LLM tutorials and scripts covering langchain, openai, llamaindex, GPT, ChromaDB, Pinecone
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Decision brief
Jupyter Notebook tutorials and scripts for working with LangChain, OpenAI API, llamaindex, GPT models, ChromaDB, and Pinecone.
Good fit when
- When you want comprehensive Jupyter-based tutorials on integrating multiple LLM tools including OpenAI and LangChain.
- If you seek hands-on practice with advanced concepts like tool-use agents that interact with real-world financial data APIs.
Avoid when
- Avoid if you require a purely code-library without tutorial-like content in Jupyter Notebooks.
- Not suitable if your project strictly demands proprietary or closed-access LLM tools not covered in the repo, like those beyond OpenAI and LangChain.
Observed Jul 14, 2026 · Source: enrich:decision_facts
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Maintenance and security
Full trust report- Maintenance
- Slowing (151d since push)
- As of 1mo
- Provenance
- Not a fork · Personal account
- As of 1mo
- Security (OSV)
- 159 low (159 low)
- As of 1mo
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Install
git clone https://github.com/onlyphantom/llm-pythonHow it fits your stack(10)
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Overview
A repository featuring Jupyter Notebook-based tutorials and sample scripts for working with Large Language Models (LLMs) incorporating tools like LangChain, OpenAI API, llamaindex, ChatGPT models, ChromaDB, and Pinecone.
Capability facts
- Languages
- jupyter notebook
Source: github.language · Jul 21, 2026
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Jul 21, 2026)
4. Create a `.env` file which contains your OpenAI API key. You can get one from [here](https://beta.openai.com/). `HUGGINGFACEHUB_APISource link
Source: README excerpt (regex_v1, Jul 21, 2026)
d Generative AI 5-course series](https://docs.sectors.app/recipes/generative-ai-python/01-background) to learn how to use the API to build sophisticated LLM applicatiSource link
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README
Quick Start
- Clone this repo
- Install requirements:
pip install -r requirements.txt - Some sample data are provided to you in the
newsfoldeer, but you can use your own data by replacing the content (or adding to it) with your own text files. - Create a
.envfile which contains your OpenAI API key. You can get one from here.HUGGINGFACEHUB_API_TOKENandPINECONE_API_KEYare optional, but they are used in some of the lessons.- Lesson 10 uses Cohere and Stability AI, both of which offers a free tier (no credit card required). You can add the respective keys as
COHERE_API_KEYandSTABILITY_API_KEYin the.envfile. - Some of the most advanced examples that feature tool-use, function-calling Agents will require you working with a real-world financial data API. My team at Supertype and I built a LLM-first financial API platform called Sectors. You can register for a free account, read our API documentation and Generative AI 5-course series to learn how to use the API to build sophisticated LLM application. Examples of these applications are all in the repo.
- Lesson 10 uses Cohere and Stability AI, both of which offers a free tier (no credit card required). You can add the respective keys as
Your .env file should look like this:
---
### License
MIT © [Supertype](https://supertype.ai) 2024
For agents
This page has a .md twin and JSON over the API.