![]() ![]() We also check Twitter and Stack Overflow. You can start a thread in Github Discussions or our Discord channel. If you'd like to discuss a topic, or get more general advice on how to make Haystack work for your project, We regularly check these and you can expect a quick response. If you have a feature request or a bug report, feel free to open an issue in Github. There is a very vibrant and active community around Haystack which we are regularly interacting with! To run the Explore The World demo on your own machine and customize it to your needs, check out the instructions on Explore the World repository on GitHub. ![]() Try out our hosted Explore The World live demo here!Īsk any question on countries or capital cities and let Haystack return the answers to you. To learn how to tweak pipelines, train models, and perform evaluation. To set up a question answering system using Python and start performing queries! You can find out more about our PyPi package on our PyPi page. See our installation guide for more options. GRPC_PYTHON_BUILD_SYSTEM_ZLIB=true pip install git+ # some additional dependencies needed on m1 mac Use pip to install a basic version of Haystack's latest release: We're hiring! Have a look at our open positions Speed & Accuracy of Retriever, Readers and DocumentStores ![]() See what Haystack can do with our Notebooks & Scriptsĭeploy a Haystack application with Docker Compose and a REST APIĭiscord, Twitter, Stack Overflow, GitHub Discussions Continuous Learning: Collect new training data from user feedback in production & improve your models continuously.Ĭomponents, Pipeline Nodes, Guides, API Reference.Customizable: Fine-tune models to your domain or implement your custom DocumentStore.Developer friendly: Easy to debug, extend, and modify.End-to-End: All tooling in one place: file conversion, cleaning, splitting, training, eval, inference, labeling, and more.Scalable: Scale to millions of docs using retrievers, production-ready backends like Elasticsearch / FAISS, and a fastAPI REST API.Tight interfaces to other frameworks (for example, transformers, FARM, sentence-transformers). Open: 100% compatible with Hugging Face's model hub.Pipelines: Use the Node and Pipeline design of Haystack to route queries to only the relevant components.Pick your favorite database, file converter, or modeling framework. Modular: Multiple choices to fit your tech stack and use case.Latest models: Utilize all latest transformer-based models (for example, BERT, RoBERTa, MiniLM) for extractive QA, generative QA, and document retrieval.Automate processes by automatically applying a list of questions to new documents and using the extracted answers.Leverage existing knowledge bases and better handle the long tail of queries that chatbots receive.Use user feedback to evaluate, benchmark, and continuously improve your live models.Use off-the-shelf models or fine-tune them to your domain.Perform semantic search and retrieve documents according to meaning, not keywords.Ask questions in natural language and find granular answers in your documents.Haystack is built in a modular fashion so that you can combine the best technology from other open source projects, like Hugging Face's transformers, Elasticsearch, or Milvus. Whether you want to perform question answering (QA) or semantic document search, you can use the state-of-the-art NLP models in Haystack to provide unique search experiences and allow your users to query in natural language. Haystack is an end-to-end framework that enables you to build powerful and production-ready pipelines for different search use cases.
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