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nebius/token-factory-cookbook

Language: Jupyter Notebook

License: MIT

Stars: 103

Forks: 24

Open issues: 3

Created: 2025-04-09T13:00:55Z

Pushed: 2026-06-10T06:28:40Z

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README:

Nebius Token Factory Cookbook

A collection of guides and examples for building intelligent applications with open models on Nebius Token Factory.

> ⭐ If you find this repo useful, give it a star! You'll be notified of new updates and help others discover it too — thank you!

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Table of Contents

  • [Nebius Token Factory Cookbook](#nebius-token-factory-cookbook)
  • [Table of Contents](#table-of-contents)
  • [😎 Featured](#-featured)
  • [👷 For Builders](#-for-builders)
  • [🚀 Getting Started](#-getting-started)
  • [🎁 Models](#-models)
  • [📘 APIs](#-apis)
  • [🎠 Agents](#-agents)
  • [🔍 RAG](#-rag)
  • [⛓️ Integrations](#️-integrations)
  • [🔧 Function / Tool Calling](#-function--tool-calling)
  • [🛠️ Post Training](#️-post-training)
  • [🫗 Distillation](#-distillation)
  • [🏫 Workshops](#-workshops)
  • [🕶️ Fun and Cool Stuff](#️-fun-and-cool-stuff)
  • [🤝 Contributing](#-contributing)
  • [📔 Resources](#-resources)
  • [📜 License](#-license)
  • [🌟 GitHub Star History](#-github-star-history)
  • [✨ Contributors](#-contributors)

---

😎 Featured

  • [Token Factory Workshop](workshops/token-factory-workshop/README.md)
  • [Builder Hour](builder-hour/README.md) • [Events](community/events.md) supported by Nebius AI
  • [LangChain deep agent examples](agents/langchain/README.md)
  • [Community contributions](community/README.md)
  • [Post training examples](post-training/)
  • [Distillation guide](distillation/distillation-1/)
  • [Cool Apps / Demos](apps/README.md)

---

👷 [For Builders](community/events.md)

Network, learn, and build with fellow builders - including hackathons, workshops, and community events.

Join [Builder Hour](builder-hour/README.md) online.

[Events / hackathons / workshops](community/events.md)

---

🚀 [Getting Started](getting-started.md)

1. Prerequisites

  • A Nebius Token Factory account and API key — sign up for free here
  • Python runtime (local, Google Colab, etc.)

2. Follow the [getting started guide](getting-started.md) 3. Follow project-specific instructions in each example's README

---

🎁 [Models](models/)

Checkout the latest [model guides and sample code](models/README.md).

Featuring: [DeepSeek V4 Pro](models/deepseek-v4.md) • [GLM-5.1](models/glm5.1.md) • [Qwen3.5-397B-A17B](models/qwen3.5.md) • [Kimi-K2.5](models/kimi-k2.5.md) • [Nemotron family](models/nemotron/README.md)

---

📘 [APIs](api/)

Access Token Factory using various APIs:

[OpenAI-compatible API](api/api_native.ipynb) • [LiteLLM](api/api_litellm.ipynb) • [ai-suite](api/api_aisuite.ipynb) • [Llama-index](api/api_llamaindex.ipynb)

---

🎠 [Agents](agents/)

Numerous agent examples ranging from [starter](agents/README.md#-starter-agents) to [intermediate](agents/README.md#intermediate-agents) and [advanced](agents/README.md#advanced-agents).

Featured AI Agent frameworks:

[ CrewAI](agents/README.md#crewai) • [ Agno](agents/README.md#agno) • [ LangChain](agents/README.md#langchain) • [ Google ADK](agents/README.md#google-adk-agent-development-kit) • [ Llama-index](agents/README.md#llama-index) • [ Pydantic](agents/README.md#pydantic-ai) • [ AWS Strands](agents/README.md#strands-agent)

---

🔍 [RAG](rag/)

| Example | Description | Tech Stack | |---------|-------------|------------| | [PDF RAG](rag/rag-pdf-llama-index/) | Simple PDF RAG application | LlamaIndex + Nebius AI | | [Chat with Documents](rag/chat-with-pdf) | Web app to chat interactively with PDF documents | LlamaIndex + Nebius AI + Streamlit | | [Internal Content Generation Platform](rag/content-gen-pipeline-qdrant/) | Create social posts, articles, and demos with a RAG pipeline | Qdrant + Nebius AI + Qwen3-Embedding | | [End-to-end RAG Pipeline for PDFs](rag/rag-milvus-1/) | Process and query PDF documents using vector DB and open-source embeddings | LlamaIndex + Milvus + Nebius AI + Qwen3-Embedding + GPT-OSS | | [Internal Support Agent](rag/support-agent-weaviate/) | Multi-agent support agent with web search, document RAG, Notion/Calendly tools, and Slack bot | Nebius AI + LangGraph + Weaviate |

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⛓️ [Integrations](integrations/README.md)

Guides for connecting third-party tools to Token Factory:

  • [OpenClaw](integrations/openclaw/README.md) — self-hosted AI agents on open models
  • [Tavily](integrations/tavily/README.md) — LLM-optimized search API for agentic research

See also the official catalog: docs.tokenfactory.nebius.com/integrations

---

🔧 [Function / Tool Calling](tool-calling/)

| Example | Description | Tech Stack | |---------|-------------|------------| | [Simple function calling](tool-calling/function_calling_1.ipynb) | Demonstrates how to call functions | Nebius AI |

---

🛠️ [Post Training](post-training/)

Post-training lets you customize and improve pre-trained language models for your specific use cases through fine-tuning and other optimization methods.

[View post training examples →](post-training/)

---

🫗 [Distillation](distillation/)

| Name | Description | Tech Stack | |------|-------------|------------| | [Distillation 1](distillation/distillation-1/) | Example of a distilled model for grammar checking | Nebius AI |

---

🏫 [Workshops](workshops/)

Hands-on, guided learning sessions:

  • [Token Factory Workshop](workshops/token-factory-workshop/README.md)
  • [Deep Research + Writing Agents Workshop with Nebius and Okahu](workshops/deep-research-writing-agents-nebius-okahu/README.md)

---

🕶️ [Fun and Cool Stuff](fun/)

Have some fun with models:

  • [Creating cool images using LORA adapters](lora/lora-1/README.md)
  • [Try the "Pelican Riding a Bicycle" benchmark](fun/pelican-riding-bicycle/)

---

🤝 [Contributing](community/README.md)

We welcome your contributions! Open issues, submit pull requests, and share your experience.

🧑🏻‍🤝‍🧑🏼 [View community contributions](community/README.md)

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📔 Resources

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📜 License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

---

🌟 GitHub Star History

[![Star History…

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