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54 lines
2.1 KiB
Markdown
54 lines
2.1 KiB
Markdown
---
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title: Explore the Qdrant Ecosystem
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short_description: "Explore the Qdrant ecosystem of integrations, partners, frameworks, and community tools built around vector search."
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description: "Discover the Qdrant ecosystem — integrations with frameworks, embedding providers, cloud platforms, and community-built tools for vector search."
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slug: ecosystem
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aliases:
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- /documentation/build/
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breadcrumb: false
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content:
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- partial: documentation/banners/banner-c
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title: Explore the Qdrant Ecosystem
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description: Dev-portal Ecosystem
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image:
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src: /img/dev-portal-build/spanish-ai-app-hero.png
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alt: Spanish AI app.png
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startedButton:
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text: Get Started
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url: https://qdrant.to/cloud
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- partial: documentation/sections/cards-section
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title: Start Building
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description: Deploy and manage high-performance vector search clusters across cloud environments. Easily scale with fully managed cloud solutions, integrate seamlessly across hybrid setups, or maintain complete control with private cloud deployments in Kubernetes.
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cardsPartial: documentation/cards/docs-cards
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cards:
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- id: 1
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image:
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src: /img/dev-portal-build/search.png
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alt: Search
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title: Search
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description: Build a simple neural search service with Qdrant and FastEmbed. Learn how to upload data, create indexes, and run search queries.
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link:
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url: /documentation/tutorials-search-engineering/hybrid-search-fastembed/
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text: Read More
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- id: 2
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image:
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src: /img/dev-portal-build/rag.png
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alt: RAG
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title: RAG
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description: Build end-to-end prototype chatbots. Learn how Qdrant integrates with popular RAG frameworks like LangChain and LlamaIndex.
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link:
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url: /documentation/frameworks/langchain/
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text: Read More
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- id: 3
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image:
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src: /img/dev-portal-build/pipelines.png
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alt: Pipelines
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title: Pipelines
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description: Integrate Qdrant into your data infrastructure by connecting with popular data engineering tools.
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link:
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url: /documentation/send-data/
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text: Read More
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partition: ecosystem
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hideInSidebar: true
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---
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