{"data":{"slug":"onlyphantom-llm-python","name":"llm-python","tagline":"LLM tutorials and scripts covering langchain, openai, llamaindex, GPT, ChromaDB, Pinecone","github_url":"https://github.com/onlyphantom/llm-python","owner":"onlyphantom","repo":"llm-python","owner_avatar_url":"https://avatars.githubusercontent.com/u/16984453?v=4","primary_language":"Jupyter Notebook","stars":927,"forks":316,"topics":["chromadb","gpt-3","langchain","langchain-python","llamaindex","llm","llmops","openai-api","pinecone","tutorial"],"archived":false,"github_pushed_at":"2026-02-20T10:42:19+00:00","maintenance_label":"Slowing","stars_delta_30d":1,"url":"https://www.graphcanon.com/tools/onlyphantom-llm-python","markdown_url":"https://www.graphcanon.com/tools/onlyphantom-llm-python.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/onlyphantom-llm-python","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=onlyphantom-llm-python","description":"Large Language Models (LLMs) tutorials & sample scripts, ft. langchain, openai, llamaindex, gpt, chromadb & pinecone","homepage_url":"https://www.youtube.com/playlist?list=PLXsFtK46HZxUQERRbOmuGoqbMD-KWLkOS","license":"MIT","open_issues":0,"watchers":14,"ai_summary":"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.","readme_excerpt":"### Quick Start\n\n1. Clone this repo\n2. Install requirements: `pip install -r requirements.txt`\n3. Some sample data are provided to you in the `news` foldeer, but you can use your own data by replacing the content (or adding to it) with your own text files.\n4. Create a `.env` file which contains your OpenAI API key. You can get one from [here](https://beta.openai.com/). `HUGGINGFACEHUB_API_TOKEN` and `PINECONE_API_KEY` are optional, but they are used in some of the lessons.\n   - [Lesson 10](./11_worldbuilding.py) 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_KEY` and `STABILITY_API_KEY` in the `.env` file.\n   - 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](https://sectors.app). You can register for a free account, read our [API documentation and 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 application. Examples of these applications are all in the repo.\n\nYour `.env` file should look like this:\n\n```\n\n---\n\n### License\n\nMIT © [Supertype](https://supertype.ai) 2024","github_created_at":"2023-04-06T12:38:17+00:00","created_at":"2026-07-07T17:43:10.002651+00:00","updated_at":"2026-08-21T00:01:06.234624+00:00","categories":[{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"vector-databases","name":"Vector Databases","url":"https://www.graphcanon.com/categories/vector-databases","markdown_url":"https://www.graphcanon.com/categories/vector-databases.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/vector-databases"}],"tags":[{"slug":"chromadb","name":"chromadb"},{"slug":"gpt-3","name":"gpt-3"},{"slug":"langchain","name":"langchain"},{"slug":"llama-index","name":"llama-index"},{"slug":"openai","name":"openai"},{"slug":"pinecone","name":"pinecone"},{"slug":"tutorial","name":"tutorial"}],"trust":{"provenance":{"is_fork":false,"github_id":624421862,"owner_type":"User","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-21T00:01:05.506Z","maintenance":{"label":"Slowing","score":36,"methodology":"github_public_v1","releases_90d":0,"days_since_push":181,"last_release_at":null,"stars_delta_30d":1,"open_issues_delta_30d":0},"security_summary":{"status":"findings","scanner":"osv@v1","low_count":159,"high_count":0,"last_scan_at":"2026-07-11T11:23:00.763Z","medium_count":0,"scan_profile":"deps","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-21T00:01:05.954Z"},"languages":{"value":["jupyter notebook"],"source":"github.language","observed_at":"2026-08-21T00:01:05.954Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-21T00:01:05.954Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["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."],"when_not_to_use":["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."],"source":"enrich:decision_facts","observed_at":"2026-07-14T20:21:20.495Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"Jupyter Notebook tutorials and scripts for working with LangChain, OpenAI API, llamaindex, GPT models, ChromaDB, and Pinecone."}]}}