llm-python
LLM tutorials and scripts covering langchain, openai, llamaindex, GPT, ChromaDB, Pinecone
GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026
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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 (211d since push)
- As of Sep 20, 2026
- Provenance
- Not a fork · Personal account
- As of Sep 20, 2026
- Security (OSV)
- 159 low (159 low)
- As of Jul 11, 2026
Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.
Install
git clone https://github.com/onlyphantom/llm-pythonHow it fits your stack(10)
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Evidence and technical details
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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 · Sep 20, 2026
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Compatibility
Sourced claims from the README excerpt - not unsourced marketing copy.
Source: README excerpt (regex_v1, Sep 20, 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, Sep 20, 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 1. Clone this repo 2. Install requirements: 3. Some sample data are provided to you in the foldeer, but you can use your own data by replacing the content (or adding to it) with your own text files. 4. Create a file which contains your OpenAI API key. You can get one...
For agents
This page has a .md twin and JSON over the API.