https://github.com/deepset-ai/haystack-cookbook

👩🏻‍🍳 A collection of example notebooks
https://github.com/deepset-ai/haystack-cookbook

Last synced: 2 months ago
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👩🏻‍🍳 A collection of example notebooks

• Host: GitHub
• URL: https://github.com/deepset-ai/haystack-cookbook
• Owner: deepset-ai
• Created: 2024-01-02T12:11:38.000Z (about 1 year ago)
• Default Branch: main
• Last Pushed: 2024-04-22T10:22:05.000Z (9 months ago)
• Last Synced: 2024-04-22T11:34:58.313Z (9 months ago)
• Language: Jupyter Notebook
• Size: 1.63 MB
• Stars: 122
• Watchers: 3
• Forks: 24
• Open Issues: 11
• Metadata Files:
  • Readme: README.md

Awesome Lists containing this project

• awesome - deepset-ai/haystack-cookbook - 👩🏻‍🍳 A collection of example notebooks (Jupyter Notebook)
• dmg-data-science-awesome - Haystack Cookbook - Farklı araçlar kullanılarak yapılmış çeşitli GenAI uygulama örnekleri bulabileceğiniz bir repo. (🤖Generative AI / 🔗 Useful Links)
• dmg-data-science-awesome - Haystack Cookbook - Farklı araçlar kullanılarak yapılmış çeşitli GenAI uygulama örnekleri bulabileceğiniz bir repo. (🤖Generative AI / 🔗 Useful Links)

README

        
# 👩🏻‍🍳 Haystack Cookbook



  



# 🧑‍🍳🍳[Discover The Haystack Cookbook here](https://haystack.deepset.ai/cookbook)

A collection of example notebooks using [Haystack](https://github.com/deepset-ai/haystack) 👇

You can use these examples as guidelines on how to make use of different model providers, vector databases, retrieval techniques and more with Haystack. Most of them showcase a specific, small demo.

> 🧑‍🍳 [Guidelines on How to Contribute a Cookbook](#how-to-contribute-to-this-repository)

To learn more about _how_ to use Haystack, please visit our [Docs](https://docs.haystack.deepset.ai/docs) and official [Tutorials](https://haystack.deepset.ai/tutorials).

For more examples, you may also find our [Blog](https://haystack.deepset.ai/blog) useful.

**Note:** Unless '(Haystack 1.x)' is mentioned in the title, all of these examples use Haystack 2.0 onwards.

| Name | Colab|

| ---- | ---- |

| Improving Retrieval with Auto-Merging | |

| Speaker Diarization with AssemblyAI | |

| Advance Prompt Customization for Anthropic | |

| Advanced RAG: Query Decomposition and Reasoning | |

| Advanced RAG: Automated Structured Metadata Enrichment | |

| Techcrunch News Digest with Local LLMs using TitanML Takeoff | |

| Use Gemini Models with Vertex AI| |

| Gradient AI Embedders and Generators for RAG | |

| Mixtral 8x7B with Hugging Face TGI for Web QA | |

| Amazon Bedrock and OpenSearch for PDF QA | |

| Use Zephyr 7B Beta with Hugging Face for RAG | |

| Hacker News RAG with Custom Component | |

| Use Chroma for RAG and Indexing | |

| Using the Jina-embeddings-v2-base-en model in a Haystack RAG pipeline for legal document analsysis| |

| Multilingual RAG from a podcast with Whisper, Qdrant and Mistral| |

| Improve retrieval by embedding meaningful metadata| |

| Advanced RAG: Query Expansion| |

| Information extraction via LLMs (Gorilla OpenFunctions)| |

| Information extraction via LLMs (NexusRaven)| |

| Using AstraDB as a data store in your Haystack pipelines| |

| Streaming model explorer: compare how different models handle the same prompt.| |

| Function Calling with OpenAIChatGenerator| |

| Use the vLLM inference engine in Haystack 2.x| |

| Build with Google Gemma: chat and RAG| |

| Optimizing Retrieval with HyDE| |

| RAG pipeline using FastEmbed for embeddings generation| |

| Sparse Embedding Retrieval with Qdrant and FastEmbed| |

| Hybrid Retrieval: BM42 + Dense Retrieval (with Qdrant and FastEmbed)| |

| Air-Gapped RAG pipelines with NVIDIA NIMs| |

| Evaluate a RAG pipeline using Haystack-UpTrain integration| |

| RAG on the Oscars using Llama 3.1 models| |

| Chatting with SQL Databases | |

| Evaluate a RAG pipeline using DeepEval integration| |

| Evaluate a RAG pipeline using Ragas integration| |

| Extract Metadata Filters from a Query | |

| Run tasks concurrently within a custom component | |

| Prompt Optimization with DSPy | |

| RAG Evaluation with Prometheus 2 | |

| Build quizzes and adventures with Character Codex and llamafile | |

| Invoking APIs with `OpenAPITool` | |

| Extract and use website content for RAG with Apify | |

| Analyze Your Instagram Comments’ Vibe with Apify and Haystack | |

| Conversational RAG using Memory | |

| Evaluating RAG Pipelines with EvaluationHarness | |

| Define & Run Tools | |

| Agentic RAG with Llama 3.2 3B | |

| Cohere for Multilingual QA (Haystack 1.x)| |

| GPT-4 and Weaviate for Custom Documentation QA (Haystack 1.x)| |

| Whisper Transcriber and Weaviate for YouTube video QA (Haystack 1.x)| |

## How to Contribute a Cookbook

If you have an example that uses Haystack, you can add it to this repository by creating a PR. You can also create a PR from Colab by creating a Fork of this repository and selecting "Save a Copy to GitHub". Once you add your example to your fork, you can create a PR onto this repository. 

1. Add your Notebook

2. Give a descriptive name to your file that includes the names of (if applicable) the model providers, databases the technologies you use in your example and/or the task you are completing in the example.

3. Make sure you add it to `index.toml` including its title and topics.

4. Make sure to add a row in the table above 🎉