mirror of
https://github.com/qdrant/landing_page.git
synced 2026-09-30 16:38:31 +02:00
reorder content
This commit is contained in:
@@ -1,6 +1,6 @@
|
|||||||
---
|
---
|
||||||
title: Agentic RAG Discord Bot with CAMEL-AI
|
title: Agentic RAG Discord Bot with CAMEL-AI
|
||||||
weight: 14
|
weight: 4
|
||||||
partition: build
|
partition: build
|
||||||
social_preview_image: /documentation/examples/agentic-rag-camelai-discord/social-preview.png
|
social_preview_image: /documentation/examples/agentic-rag-camelai-discord/social-preview.png
|
||||||
---
|
---
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
---
|
---
|
||||||
title: Simple Agentic RAG System
|
title: Simple Agentic RAG System
|
||||||
weight: 12
|
weight: 2
|
||||||
partition: build
|
partition: build
|
||||||
social_preview_image: /documentation/examples/agentic-rag-crewai-zoom/social_preview.png
|
social_preview_image: /documentation/examples/agentic-rag-crewai-zoom/social_preview.png
|
||||||
---
|
---
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
---
|
---
|
||||||
title: Agentic RAG With LangGraph
|
title: Agentic RAG With LangGraph
|
||||||
weight: 13
|
weight: 3
|
||||||
partition: build
|
partition: build
|
||||||
---
|
---
|
||||||
# Agentic RAG With LangGraph and Qdrant
|
# Agentic RAG With LangGraph and Qdrant
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
---
|
---
|
||||||
title: Data Ingestion for Beginners
|
title: Data Ingestion for Beginners
|
||||||
weight: 11
|
weight: 2
|
||||||
partition: build
|
partition: build
|
||||||
social_preview_image: /documentation/examples/data-ingestion-beginners/social_preview.png
|
social_preview_image: /documentation/examples/data-ingestion-beginners/social_preview.png
|
||||||
---
|
---
|
||||||
|
|||||||
@@ -0,0 +1,11 @@
|
|||||||
|
---
|
||||||
|
#Delimiter files are used to separate the list of documentation pages into sections.
|
||||||
|
title: "Ecosystem"
|
||||||
|
type: delimiter
|
||||||
|
weight: 10 # Position before Integrations (weight 17)
|
||||||
|
sitemapExclude: True
|
||||||
|
_build:
|
||||||
|
publishResources: false
|
||||||
|
render: never
|
||||||
|
partition: build
|
||||||
|
---
|
||||||
@@ -2,7 +2,7 @@
|
|||||||
#Delimiter files are used to separate the list of documentation pages into sections.
|
#Delimiter files are used to separate the list of documentation pages into sections.
|
||||||
title: "Essentials"
|
title: "Essentials"
|
||||||
type: delimiter
|
type: delimiter
|
||||||
weight: 10 # Change this weight to change order of sections
|
weight: 1 # Change this weight to change order of sections
|
||||||
sitemapExclude: True
|
sitemapExclude: True
|
||||||
_build:
|
_build:
|
||||||
publishResources: false
|
publishResources: false
|
||||||
|
|||||||
@@ -1,7 +1,7 @@
|
|||||||
---
|
---
|
||||||
title: "FastEmbed"
|
title: "FastEmbed"
|
||||||
weight: 7
|
weight: 11
|
||||||
partition: qdrant
|
partition: build
|
||||||
---
|
---
|
||||||
|
|
||||||
# What is FastEmbed?
|
# What is FastEmbed?
|
||||||
@@ -21,7 +21,7 @@ FastEmbed easily integrates with Qdrant for a variety of multimodal search purpo
|
|||||||
|
|
||||||
- Light: Unlike other inference frameworks, such as PyTorch, FastEmbed requires very little external dependencies. Because it uses the ONNX runtime, it is perfect for serverless environments like AWS Lambda.
|
- Light: Unlike other inference frameworks, such as PyTorch, FastEmbed requires very little external dependencies. Because it uses the ONNX runtime, it is perfect for serverless environments like AWS Lambda.
|
||||||
- Fast: By using ONNX, FastEmbed ensures high-performance inference across various hardware platforms.
|
- Fast: By using ONNX, FastEmbed ensures high-performance inference across various hardware platforms.
|
||||||
- Accurate: FastEmbed aims for better accuracy and recall than models like OpenAI’s `Ada-002`. It always uses model which demonstrate strong results on the MTEB leaderboard.
|
- Accurate: FastEmbed aims for better accuracy and recall than models like OpenAI's `Ada-002`. It always uses model which demonstrate strong results on the MTEB leaderboard.
|
||||||
- Support: FastEmbed supports a wide range of models, including multilingual ones, to meet diverse use case needs.
|
- Support: FastEmbed supports a wide range of models, including multilingual ones, to meet diverse use case needs.
|
||||||
|
|
||||||
|
|
||||||
|
|||||||
@@ -1,6 +1,6 @@
|
|||||||
---
|
---
|
||||||
title: Multilingual & Multimodal RAG with LlamaIndex
|
title: Multilingual & Multimodal RAG with LlamaIndex
|
||||||
weight: 14
|
weight: 5
|
||||||
partition: build
|
partition: build
|
||||||
social_preview_image: /documentation/examples/multimodal-search/social_preview.png
|
social_preview_image: /documentation/examples/multimodal-search/social_preview.png
|
||||||
aliases:
|
aliases:
|
||||||
|
|||||||
@@ -0,0 +1,8 @@
|
|||||||
|
---
|
||||||
|
title: "MCP Server"
|
||||||
|
weight: 12
|
||||||
|
externalUrl: https://github.com/qdrant/mcp-server-qdrant
|
||||||
|
partition: build
|
||||||
|
---
|
||||||
|
|
||||||
|
This links to the official Qdrant Model Context Protocol (MCP) server implementation repository on GitHub.
|
||||||
@@ -1,6 +1,6 @@
|
|||||||
---
|
---
|
||||||
title: 5 Minute RAG with Qdrant and DeepSeek
|
title: 5 Minute RAG with Qdrant and DeepSeek
|
||||||
weight: 15
|
weight: 6
|
||||||
partition: build
|
partition: build
|
||||||
social_preview_image: /documentation/examples/rag-deepseek/social_preview.png
|
social_preview_image: /documentation/examples/rag-deepseek/social_preview.png
|
||||||
---
|
---
|
||||||
|
|||||||
Reference in New Issue
Block a user