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The Together Cookbook is a collection of code and guides designed to help developers build with open source models using Together AI. The best way to use the recipes is to copy code snippets and integrate them into your own projects!
We welcome contributions to this repository! If you have a cookbook you'd like to add, please reach out to use the Discord or open a pull request!
To make the most of the examples in this cookbook, you'll need a Together AI API key (sign up for free here).
While the code examples are primarily written in Python/JS, the concepts can be adapted to any programming language that supports interaction with the Together API.
| Cookbook | Description | Open |
|---|---|---|
| Agents | ||
| Serial Chain Agent | Chain multiple LLM calls sequentially to process complex tasks. |  |
| Conditional Router Agent Workflow | Create an agent that routes tasks to specialized models. | |
| Parallel Agent Workflow | Run multiple LLMs in parallel and aggregate their solutions. | |
| Orchestrator Subtask Agent Workflow | Break down tasks into parallel subtasks to be executed by LLMs. | |
| Looping Agent Workflow | Build an agent that iteratively improves responses | |
| Fine-tuning | ||
| LoRA Inference and Fine-tuning | Perform LoRA fine-tuning and inference on Together AI. | |
| Long Context Finetuning For Repetition | Fine-tuning LLMs to repeat back words in long sequences. | |
| Summarization Long Context Finetuning | Long context fine-tuning to improve summarization capabilities. | |
| Conversation Finetuning | Fine-tuning LLMs on multi-step conversations. | |
| Retrieval-augmented generation | ||
| MultiModal_RAG_with_Nvidia_Deck | Multimodal RAG using Nvidia investor slides |  |
| Open_Contextual_RAG | An implementation of Contextual Retrieval using open models. | |
| Text_RAG | Implement text-based Retrieval-Augmented Generation | |
| Search | ||
| Multimodal Search and Conditional Image Generation | Text-to-image and image-to-image search and condtional image generation. | |
| Embedding_Visualization | Visualize vector embeddings | |
| Search_with_Reranking | Improve search results with rerankers | |
| Semantic_Search | Implement vector search with embedding models | |
| Miscellaneous | ||
| Structured_Text_Extraction_from_Images | Extract structured text from images | |
| Summarization Evaluation | Summarizing and evaluating outputs with LLMs. | |
| PDF_to_Podcast | Generate a podcast from PDF content NotebookLM style! | |
| Knowledge_Graphs_with_Structured_Outputs | Get LLMs to generate knowledge graphs | |
Looking for more resources to enhance your experience with open source models? Check out these helpful links:
- Together AI Research: Explore papers and technical blog posts from our research team.
- Together AI Blog: Explore technical blogs, product announcements and more on our blog.