Haystack 3.2 is here 🚀 This release keeps agents lean and in control as conversations grow. Three highlights: 🧵 SummarizationCompactor for smarter context compaction Pair SummarizationCompactor with CompactionHook (shipped in v3.1) to progressively summarize long-running Agent conversations. 💰 TokenBudgetHook caps what a run can spend A ready-made hook that ends the run at "token_budget_exceeded" once you hit your token ceiling through the stop_run hook point. 🛠️ Faster Pipeline building New add_components() and connect_many() let you add and wire up multiple components in one call. 💙 70 contributors made this release happen; huge thanks to everyone! 🔗 Full release notes: haystack.deepset.ai/release-…

Full-text search without semantic understanding leaves gaps. Dense vector search without keyword matching misses precision. @ApacheSolr is now available as a Document Store and retriever in Haystack. Use SolrDocumentStore with SolrHybridRetriever to combine BM25 full-text search and dense vectors in one pipeline - getting both lexical and semantic matching without extra infrastructure. Solr has been a trusted open-source search engine for over a decade, and its hybrid retrieval approach fits naturally into Haystack pipelines whether you're prototyping locally or scaling to production. 🐍 pip install solr-haystack 🔗 haystack.deepset.ai/integrat…

📣 We're hosting our next unconference in Berlin with @prior_labs, exploring open-weight models and open-source agents! Come join us if you'd like to discuss: → Structured data in agentic workflows → When agents should hand off to TabPFN for prediction → Benchmarking tabular models vs. LLMs → Why orchestration matters for production agents → What owning your stack end-to-end actually requires → Open-weight vs. closed models in practice Or anything else that's been challenging you lately! 📍 @deepset_ai HQ, Berlin 🗓️ September 24th, 6PM-9PM Register: luma.com/haystack-priorlabs

If you are a @mariadb user, you can now store your embeddings right alongside your documents and metadata in the same system - no need for a separate vector database. MariaDBDocumentStore and MariaDBEmbeddingRetriever let you build semantic search pipelines that keep all your data unified and easy to manage. Embed your content, persist vectors in the same MariaDB instance where your source data lives, and retrieve similar results in seconds. Everything stays in one place. 🐍 pip install mariadb-haystack 🔗 haystack.deepset.ai/integrat…

Haystack 3.1 is here 🚀 This release is all about smarter context management with token accounting, context compaction & precision. Three highlights: 🪝 Context compaction for agents New CompactionHook automatically shortens long-running conversations before they blow through the context window. 🪙 New token counters for estimating usage Three new counters, from a zero-dependency approximation to an exact, OpenAI API-backed count, so you know when to compact before you hit the wall. 🛠️ AgentTool for multi-agent systems Wrap any Agent as a Tool so another Agent can delegate to it. Only the final reply crosses back, the coordinator's context stays clean. 💙 42 contributors made this release happen; huge thanks to everyone! 👉 Full release notes: haystack.deepset.ai/release-…

HetznerChatGenerator brings European sovereign cloud LLMs to Haystack. Process text and images through @Hetzner_Online infrastructure while keeping your AI workloads within EU borders. 🐍 pip install hetzner-haystack 🔗 haystack.deepset.ai/integrat…

We are thrilled to be among the ten finalists for The Spark – The Technology Award. For eleven years, @handelsblatt and @McKinsey have been recognizing Germany’s most innovative technology startups. This year’s theme is "Scaling Deep Tech", focusing on technologies that are already making a real-world impact today and shaping the future of industry and the economy. Now, we need your support. Vote by September 7th to help us reach the Top 3! Your vote counts directly toward the jury's decision. Vote for us here: cmk.handelsblatt.com/cms/art…

Finally, @Linkup_platform joins Haystack's growing search component library. Fetch real-time web results, get ranked documents with source links, and integrate them into your pipeline in a few lines. Same philosophy as other Haystack components - simple, direct, pluggable. haystack.deepset.ai/integrat…

📷 DDGS (Dux Distributed Global Search) is now available in Haystack. Query Google, Bing, Brave, Yahoo, Yandex and more from your pipelines and agents. Multi-source web search without the infrastructure overhead. pip install ddgs-haystack haystack.deepset.ai/integrat…