Is llm-python open source?

Yes — onlyphantom/llm-python is open source, released under the MIT license.

What language is llm-python written in?

onlyphantom/llm-python is primarily written in Jupyter Notebook.

How popular is llm-python?

onlyphantom/llm-python has 926 stars on GitHub.

Where can I find llm-python?

onlyphantom/llm-python is on GitHub at https://github.com/onlyphantom/llm-python.

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onlyphantom/llm-python

Nine Hours of LLM Tutorials, Bottled as Python Scripts

A growing collection of self-contained Python scripts and notebooks that teach LLM patterns—from basic OpenAI calls to multi-agent guardrails—through runnable examples tied to video courses.

★926 stars Jupyter Notebook Learning Language Models RAG · Search LLMOps · Eval

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What it does This repository houses roughly two dozen self-contained Python scripts and Jupyter notebooks that demonstrate how to wire together popular LLM tools—LangChain, LlamaIndex, OpenAI’s Agent SDK, ChromaDB, Pinecone, and others. Each script corresponds to a video lesson (about nine hours total) and focuses on a single pattern, from querying CSVs with natural language to building multi-agent systems with guardrails. It is essentially a curated syllabus turned into runnable code.

The interesting bit Unlike static tutorial repos that fossilize, this one gets refreshed: a May 2025 update added six scripts covering modern agentic patterns using the then-latest OpenAI Agent SDK, while earlier updates tackled RAG, structured output, and conversational memory. The author treats the repo as living reference material for public courses and workshops rather than a one-off blog post.

Key highlights

Self-contained scripts: pick any single file (e.g., 19_agents_handsoff.py) and run it without navigating a monolithic framework.
Covers the full arc from beginner (OpenAI API basics) to specialized (ReAct agents with streaming, tool-use RAG, local offline LLMs via OPT).
Tightly coupled to free video walkthroughs and public courses, including a multi-agent workshop and a finance-focused generative AI series.
Recently updated for contemporary library versions (LangChain v0.3.2, LlamaIndex 0.6.31, OpenAI Agent SDK as of May 2025).

Caveats

Many examples require API keys (OpenAI, and optionally Pinecone, HuggingFace, Cohere, or a proprietary financial data API) so “free to access” does not mean “free to run.”
The triton dependency is x86_64-only, which can break installation on ARM machines.
Video recordings sometimes lag behind the repo code by several library versions, so following along may require minor line-by-line adjustments.

Verdict Good for developers who want to bridge from “I read the LangChain docs” to “I built a working agent” by studying small, focused examples. Skip it if you are looking for a reusable library or a production framework; this is coursework, not infrastructure.

Frequently asked

What is onlyphantom/llm-python?: A growing collection of self-contained Python scripts and notebooks that teach LLM patterns—from basic OpenAI calls to multi-agent guardrails—through runnable examples tied to video courses.
Is llm-python open source?: Yes — onlyphantom/llm-python is open source, released under the MIT license.
What language is llm-python written in?: onlyphantom/llm-python is primarily written in Jupyter Notebook.
How popular is llm-python?: onlyphantom/llm-python has 926 stars on GitHub.
Where can I find llm-python?: onlyphantom/llm-python is on GitHub at https://github.com/onlyphantom/llm-python.