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updated tutorial names, reverted integrations tutorials to build, cleaned file organization, hid older tutorials

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kanungle
2026-01-28 19:31:13 -08:00
parent 13b667dc0c
commit fe6796f1da
34 changed files with 155 additions and 160 deletions
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qdrant-landing/content/documentation/data-management/_index.md
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title: Data Management
weight: 18
weight: 11
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qdrant-landing/content/documentation/dl-integration-examples.md
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#Delimiter files are used to separate the list of documentation pages into sections.
title: "Integration Guides"
type: delimiter
weight: 24 # Change this weight to change order of sections
weight: 20 # Change this weight to change order of sections
partition: build
sitemapExclude: True
_build:
qdrant-landing/content/documentation/dl-integrations.md
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#Delimiter files are used to separate the list of documentation pages into sections.
title: "Integrations"
type: delimiter
weight: 17 # Change this weight to change order of sections
weight: 10 # Change this weight to change order of sections
sitemapExclude: True
_build:
publishResources: false
qdrant-landing/content/documentation/embeddings/_index.md
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title: Embeddings
weight: 19
weight: 12
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qdrant-landing/content/documentation/frameworks/_index.md
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title: Frameworks
weight: 20
weight: 13
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aliases: ["/documentation/frameworks/memgpt/"]
---
qdrant-landing/content/documentation/observability/_index.md
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title: Observability
weight: 21
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qdrant-landing/content/documentation/platforms/_index.md
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title: Platforms
weight: 22
weight: 15
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qdrant-landing/content/documentation/send-data/_index.md
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title: Send Data to Qdrant
weight: 25
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---
## How to Send Your Data to a Qdrant Cluster
qdrant-landing/content/documentation/send-data/data-streaming-kafka-qdrant.md
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title: How to Setup Seamless Data Streaming with Kafka and Qdrant
weight: 49
hideInSidebar: true
aliases:
- /examples/data-streaming-kafka-qdrant/
---
qdrant-landing/content/documentation/send-data/databricks.md
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title: Qdrant on Databricks
weight: 36
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aliases:
- /documentation/examples/databricks/
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qdrant-landing/content/documentation/send-data/qdrant-airflow-astronomer.md
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title: Semantic Querying with Airflow and Astronomer
weight: 36
hideInSidebar: true
aliases:
- /documentation/examples/qdrant-airflow-astronomer/
---
qdrant-landing/content/documentation/tutorials-and-examples/_index.md
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---
## Cloud Tutorials & Examples
| Example | Description |
| ----------------------------------- | ------------------------------------------------------------------------------------------- |
| [Using Cloud Inference to Build Hybrid Search](/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Cloud inference hybrid example |
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Qdrant Cloud Prometheus Monitoring](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Self-Hosted Prometheus Monitoring](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
qdrant-landing/content/documentation/tutorials-and-examples/cloud-inference-hybrid-search.md
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---
title: Using Cloud Inference to Build Hybrid Search
hideInSidebar: true
weight: 35
---
# Using Cloud Inference with Qdrant for Vector Search
qdrant-landing/content/documentation/tutorials-ecosystem/huggingface-datasets.md → qdrant-landing/content/documentation/tutorials-basics/huggingface-datasets.md
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qdrant-landing/content/documentation/tutorials-build-essentials/_index.md
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---
title: Essential Examples
weight: 21
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---
# Essential Examples
*Step-by-step guides for connecting Qdrant to the broader AI ecosystem and data stacks.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [5-Minute RAG with DeepSeek](/documentation/tutorials-build-essentials/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
| [Discord RAG Bot](/documentation/tutorials-build-essentials/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | <span class="pill">OpenAI</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Agentic RAG with CrewAI](/documentation/tutorials-build-essentials/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | <span class="pill">CrewAI</span> | 45m | <span class="text-green">Beginner</span> |
| [n8n Workflow Automation](/documentation/tutorials-build-essentials/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | <span class="pill">n8n</span> | 45m | <span class="text-yellow">Intermediate</span> |
<!-- KEEP BELOW FOR REFERENCE -->
<!-- | [Multimodal & Multilingual RAG](/documentation/tutorials-build-essentials/multimodal-search/) | Search across image and text modalities. | <span class="pill">LlamaIndex</span> | 15m | <span class="text-green">Beginner</span> | -->
<!-- | [Agentic RAG with LangGraph](/documentation/tutorials-build-essentials/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | <span class="pill">LangGraph</span> | 45m | <span class="text-yellow">Intermediate</span> | -->
<!-- | [S3 Ingestion with LangChain](/documentation/tutorials-build-essentials/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | <span class="pill">LangChain</span> | 30m | <span class="text-green">Beginner</span> | -->
qdrant-landing/content/documentation/tutorials-rag-and-agents/agentic-rag-camelai-discord.md → qdrant-landing/content/documentation/tutorials-build-essentials/agentic-rag-camelai-discord.md
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---
title: Simple Agentic RAG System
weight: 2
#partition: build
partition: build
social_preview_image: /documentation/examples/agentic-rag-crewai-zoom/social_preview.png
aliases:
- /documentation/agentic-rag-crewai-zoom/
qdrant-landing/content/documentation/tutorials-rag-and-agents/agentic-rag-langgraph.md → qdrant-landing/content/documentation/tutorials-build-essentials/agentic-rag-langgraph.md
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---
title: Agentic RAG With LangGraph
weight: 3
#partition: build
partition: build
hideInSidebar: true
aliases:
- /documentation/agentic-rag-langgraph/
---
qdrant-landing/content/documentation/tutorials-ecosystem/data-ingestion-beginners.md → qdrant-landing/content/documentation/tutorials-build-essentials/data-ingestion-beginners.md
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title: Data Ingestion for Beginners
weight: 2
#partition: build
partition: build
hideInSidebar: true
social_preview_image: /documentation/examples/data-ingestion-beginners/social_preview.png
aliases:
- /documentation/data-ingestion-beginners/
qdrant-landing/content/documentation/tutorials-rag-and-agents/multimodal-search.md → qdrant-landing/content/documentation/tutorials-build-essentials/multimodal-search.md
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---
title: Multilingual & Multimodal RAG with LlamaIndex
weight: 5
#partition: build
hideInSidebar: true
partition: build
social_preview_image: /documentation/examples/multimodal-search/social_preview.png
aliases:
- /documentation/tutorials/multimodal-search-fastembed/
qdrant-landing/content/documentation/tutorials-ecosystem/qdrant-n8n.md → qdrant-landing/content/documentation/tutorials-build-essentials/qdrant-n8n.md
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qdrant-landing/content/documentation/tutorials-ecosystem/_index.md
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---
title: Ecosystem & Integrations
title: Integration Tutorials
weight: 36
is_empty: true
hideInSidebar: true
aliases:
- how-to
- tutorials
partition: qdrant
partition: build
---
<!-- Migrate Integration Tutorials here, gradually -->
# Ecosystem & Integrations
*Connect Qdrant to cloud providers, data streams, and ETL tools.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [S3 Ingestion with LangChain](/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | <span class="pill">LangChain</span> | 30m | <span class="text-green">Beginner</span> |
| [Hugging Face Datasets](/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | <span class="pill">Python</span> | 15m | <span class="text-green">Beginner</span> |
| [Databricks Integration](/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | <span class="pill">Databricks</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Airflow & Astronomer](/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | <span class="pill">Airflow</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [No-Code Automation (n8n)](/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | <span class="pill">n8n</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Kafka Data Streaming](/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | <span class="pill">Kafka</span> | 60m | <span class="text-red">Advanced</span> |
qdrant-landing/content/documentation/tutorials-lp-basics.md
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partition: qdrant
---
# Basic Tutorials
### Basic Tutorials
*Get up and running with Qdrant in minutes.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Local Qdrant Setup](/documentation/quickstart/) | Basic CRUD operations and local deployment. | <span class="pill">Python</span> | 10m | <span class="text-green">Beginner</span> |
| [5-Minute Semantic Search](/documentation/tutorials-basics/search-beginners/) | Build a search engine for science fiction books. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
| [5-Minute RAG with DeepSeek](/documentation/tutorials-basics/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
| [Qdrant Local Quickstart](/documentation/quickstart/) | Basic CRUD operations and local deployment. | <span class="pill">Python</span> | 10m | <span class="text-green">Beginner</span> |
| [Semantic Search 101](/documentation/tutorials-basics/search-beginners/) | Build a search engine for science fiction books. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
qdrant-landing/content/documentation/tutorials-lp-develop.md
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partition: qdrant
---
# Develop & Implement Tutorials
### Develop & Implement Tutorials
*Core tools and APIs for building with Qdrant.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Bulk Data Uploads](/documentation/tutorials-develop/bulk-upload/) | High-scale ingestion tricks for power users. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Python Async API](/documentation/tutorials-develop/async-api/) | Use Asynchronous programming for efficiency. | <span class="pill">Python</span> | 25m | <span class="text-yellow">Intermediate</span> |
| [Bulk Operations](/documentation/tutorials-develop/bulk-upload/) | High-scale ingestion approaches. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Async API](/documentation/tutorials-develop/async-api/) | Use Asynchronous programming for efficiency. | <span class="pill">Python</span> | 25m | <span class="text-yellow">Intermediate</span> |
qdrant-landing/content/documentation/tutorials-lp-ecosystem.md
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---
title: Ecosystem & Integrations
weight: 22
is_empty: false
aliases:
- how-to
- tutorials
partition: qdrant
---
# Ecosystem & Integrations
*Connect Qdrant to cloud providers, data streams, and ETL tools.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [S3 Ingestion with LangChain](/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | <span class="pill">LangChain</span> | 30m | <span class="text-green">Beginner</span> |
| [Hugging Face Datasets](/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | <span class="pill">Python</span> | 15m | <span class="text-green">Beginner</span> |
| [Databricks Integration](/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | <span class="pill">Databricks</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Airflow & Astronomer](/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | <span class="pill">Airflow</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [No-Code Automation (n8n)](/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | <span class="pill">n8n</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Kafka Data Streaming](/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | <span class="pill">Kafka</span> | 60m | <span class="text-red">Advanced</span> |
qdrant-landing/content/documentation/tutorials-lp-operations.md
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partition: qdrant
---
# Operations & Scale Tutorials
### Operations & Scale Tutorials
*Production-grade management, monitoring, and high-volume optimization.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Snapshot & Backup](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | <span class="pill">Python</span> | 20m | <span class="text-green">Beginner</span> |
| [Cloud Inference Search](/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | <span class="pill">Any</span> | 20m | <span class="text-green">Beginner</span> |
| [Embedding Migration](/documentation/tutorials-operations/migration/) | Move dense and sparse embeddings to Qdrant. | <span class="pill">CLI</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Monitor Managed Cloud](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Monitor Private Cloud](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Billion-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | <span class="pill">None</span> | 2 days | <span class="text-red">Advanced</span> |
| [Snapshots](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | <span class="pill">Python</span> | 20m | <span class="text-green">Beginner</span> |
| [Data Migration](/documentation/tutorials-operations/migration/) | Move embeddings to Qdrant. | <span class="pill">CLI</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Qdrant Cloud Prometheus Monitoring](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Self-Hosted Prometheus Monitoring](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Large-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | <span class="pill">None</span> | 2d | <span class="text-red">Advanced</span> |
qdrant-landing/content/documentation/tutorials-lp-overview.md
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- tutorials
partition: qdrant
---
# Qdrant Tutorial Repository
### Basic Tutorials
@@ -14,8 +15,61 @@ partition: qdrant
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Local Qdrant Setup](/documentation/quickstart/) | Basic CRUD operations and local deployment. | <span class="pill">Python</span> | 10m | <span class="text-green">Beginner</span> |
| [5-Minute Semantic Search](/documentation/tutorials-basics/search-beginners/) | Build a search engine for science fiction books. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
| [Qdrant Local Quickstart](/documentation/quickstart/) | Basic CRUD operations and local deployment. | <span class="pill">Python</span> | 10m | <span class="text-green">Beginner</span> |
| [Semantic Search 101](/documentation/tutorials-basics/search-beginners/) | Build a search engine for science fiction books. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
---
### Search Engineering
*Master vector search modalities, reranking, and retrieval quality.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Hybrid Search with FastEmbed](/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search. | <span class="pill">FastAPI</span> | 20m | <span class="text-green">Beginner</span> |
| [Semantic Search Basics](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | <span class="pill">FastAPI</span> | 30m | <span class="text-green">Beginner</span> |
| [Collaborative Filtering](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Multivector Document Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Retrieval Quality Evaluation](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Hybrid Search with Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | <span class="pill">Python</span> | 40m | <span class="text-yellow">Intermediate</span> |
| [Semantic Search for Code](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Multivectors and Late Interaction](/documentation/advanced-tutorials/using-multivector-representations/) | Effective use of multivector representations. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Static Embeddings](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the utility of static embeddings. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
---
### Operations & Scale
*Production-grade management, monitoring, and high-volume optimization.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Snapshots](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | <span class="pill">Python</span> | 20m | <span class="text-green">Beginner</span> |
| [Data Migration](/documentation/tutorials-operations/migration/) | Move embeddings to Qdrant. | <span class="pill">CLI</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Qdrant Cloud Prometheus Monitoring](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Self-Hosted Prometheus Monitoring](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Large-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | <span class="pill">None</span> | 2d | <span class="text-red">Advanced</span> |
---
### Develop & Implement
*Core tools and APIs for building with Qdrant.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Bulk Operations](/documentation/tutorials-develop/bulk-upload/) | High-scale ingestion approaches. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Async API](/documentation/tutorials-develop/async-api/) | Use Asynchronous programming for efficiency. | <span class="pill">Python</span> | 25m | <span class="text-yellow">Intermediate</span> |
<!-- KEEP BELOW FOR REFERENCE -->
<!--
# Qdrant Tutorial Repository
### Basic Tutorials
*Get up and running with Qdrant in minutes.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Qdrant Quickstart](/documentation/quickstart/) | Basic CRUD operations and local deployment. | <span class="pill">Python</span> | 10m | <span class="text-green">Beginner</span> |
| [Semantic Search 101](/documentation/tutorials-basics/search-beginners/) | Build a search engine for science fiction books. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
| [5-Minute RAG with DeepSeek](/documentation/tutorials-basics/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | <span class="pill">Python</span> | 5m | <span class="text-green">Beginner</span> |
---
@@ -26,14 +80,14 @@ partition: qdrant
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Hybrid Search with FastEmbed](/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search for startups. | <span class="pill">FastAPI</span> | 20m | <span class="text-green">Beginner</span> |
| [Neural Search Service](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | <span class="pill">FastAPI</span> | 30m | <span class="text-green">Beginner</span> |
| [Movie Recommendations](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Advanced PDF Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Retrieval Quality Benchmarking](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Multivector Reranking](/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Hybrid Search Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | <span class="pill">Python</span> | 40m | <span class="text-yellow">Intermediate</span> |
| [Semantic Code Search](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Static Embeddings Analysis](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Semantic Search Basics](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | <span class="pill">FastAPI</span> | 30m | <span class="text-green">Beginner</span> |
| [Collaborative Filtering](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Multivector Document Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Retrieval Quality Evaluation](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Reranking for Better Search](/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Hybrid Search with Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | <span class="pill">Python</span> | 40m | <span class="text-yellow">Intermediate</span> |
| [Semantic Search for Code](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Static Embeddings](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
---
@@ -42,11 +96,11 @@ partition: qdrant
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Multimodal Search (LlamaIndex)](/documentation/multimodal-search/) | Search across image and text modalities. | <span class="pill">LlamaIndex</span> | 15m | <span class="text-green">Beginner</span> |
| [Multimodal & Multilingual RAG](/documentation/multimodal-search/) | Search across image and text modalities. | <span class="pill">LlamaIndex</span> | 15m | <span class="text-green">Beginner</span> |
| [Agentic RAG with CrewAI](/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | <span class="pill">CrewAI</span> | 45m | <span class="text-green">Beginner</span> |
| [Agentic RAG with LangGraph](/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | <span class="pill">LangGraph</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Agentic Discord ChatBot](/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | <span class="pill">OpenAI</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Automate Metadata Filtering](/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Discord RAG Bot](/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | <span class="pill">OpenAI</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [LLM-Powered Filter Automation](/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
---
@@ -55,12 +109,12 @@ partition: qdrant
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Snapshot & Backup](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | <span class="pill">Python</span> | 20m | <span class="text-green">Beginner</span> |
| [Cloud Inference Search](/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | <span class="pill">Any</span> | 20m | <span class="text-green">Beginner</span> |
| [Embedding Migration](/documentation/tutorials-operations/migration/) | Move dense and sparse embeddings to Qdrant. | <span class="pill">CLI</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Monitor Managed Cloud](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Monitor Private Cloud](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Billion-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | <span class="pill">None</span> | 2 days | <span class="text-red">Advanced</span> |
| [Snapshots](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | <span class="pill">Python</span> | 20m | <span class="text-green">Beginner</span> |
| [Cloud Inference Hybrid Search](/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | <span class="pill">Any</span> | 20m | <span class="text-green">Beginner</span> |
| [Data Migration](/documentation/tutorials-operations/migration/) | Move dense and sparse embeddings to Qdrant. | <span class="pill">CLI</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Qdrant Cloud Prometheus Monitoring](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Self-Hosted Prometheus Monitoring](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | <span class="pill">Prometheus</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Large-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | <span class="pill">None</span> | 2 days | <span class="text-red">Advanced</span> |
---
@@ -69,8 +123,8 @@ partition: qdrant
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Bulk Data Uploads](/documentation/tutorials-develop/bulk-upload/) | High-scale ingestion tricks for power users. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Python Async API](/documentation/tutorials-develop/async-api/) | Use Asynchronous programming for efficiency. | <span class="pill">Python</span> | 25m | <span class="text-yellow">Intermediate</span> |
| [Bulk Operations](/documentation/tutorials-develop/bulk-upload/) | High-scale ingestion tricks for power users. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Async API](/documentation/tutorials-develop/async-api/) | Use Asynchronous programming for efficiency. | <span class="pill">Python</span> | 25m | <span class="text-yellow">Intermediate</span> |
---
@@ -80,8 +134,10 @@ partition: qdrant
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [S3 Ingestion with LangChain](/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | <span class="pill">LangChain</span> | 30m | <span class="text-green">Beginner</span> |
| [Hugging Face Datasets](/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | <span class="pill">Python</span> | 15m | <span class="text-green">Beginner</span> |
| [Databricks Integration](/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | <span class="pill">Databricks</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Airflow & Astronomer](/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | <span class="pill">Airflow</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [No-Code Automation (n8n)](/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | <span class="pill">n8n</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Kafka Data Streaming](/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | <span class="pill">Kafka</span> | 60m | <span class="text-red">Advanced</span> |
| [Hugging Face Dataset Ingestion](/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | <span class="pill">Python</span> | 15m | <span class="text-green">Beginner</span> |
| [Databricks Ingestion](/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | <span class="pill">Databricks</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Querying with Airflow](/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | <span class="pill">Airflow</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [n8n Workflow Automation](/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | <span class="pill">n8n</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Kafka Streaming into Qdrant](/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | <span class="pill">Kafka</span> | 60m | <span class="text-red">Advanced</span> |
-->
qdrant-landing/content/documentation/tutorials-lp-rag-and-agents.md
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@@ -1,20 +0,0 @@
---
title: RAG & AI Agents
weight: 19
is_empty: false
aliases:
- how-to
- tutorials
partition: qdrant
---
# RAG & AI Agents Tutorials
*Build intelligent agents and complex LLM-driven applications.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Multimodal Search (LlamaIndex)](/documentation/multimodal-search/) | Search across image and text modalities. | <span class="pill">LlamaIndex</span> | 15m | <span class="text-green">Beginner</span> |
| [Agentic RAG with CrewAI](/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | <span class="pill">CrewAI</span> | 45m | <span class="text-green">Beginner</span> |
| [Agentic RAG with LangGraph](/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | <span class="pill">LangGraph</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Agentic Discord ChatBot](/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | <span class="pill">OpenAI</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Automate Metadata Filtering](/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
qdrant-landing/content/documentation/tutorials-lp-search-engineering.md
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@@ -8,17 +8,17 @@ aliases:
partition: qdrant
---
# Search Engineering Tutorials
### Search Engineering Tutorials
*Master vector search modalities, reranking, and retrieval quality.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Hybrid Search with FastEmbed](/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search for startups. | <span class="pill">FastAPI</span> | 20m | <span class="text-green">Beginner</span> |
| [Neural Search Service](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | <span class="pill">FastAPI</span> | 30m | <span class="text-green">Beginner</span> |
| [Movie Recommendations](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Advanced PDF Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Retrieval Quality Benchmarking](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Multivector Reranking](/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Hybrid Search Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | <span class="pill">Python</span> | 40m | <span class="text-yellow">Intermediate</span> |
| [Semantic Code Search](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Static Embeddings Analysis](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
| [Hybrid Search with FastEmbed](/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search. | <span class="pill">FastAPI</span> | 20m | <span class="text-green">Beginner</span> |
| [Semantic Search Basics](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | <span class="pill">FastAPI</span> | 30m | <span class="text-green">Beginner</span> |
| [Collaborative Filtering](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Multivector Document Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Retrieval Quality Evaluation](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Hybrid Search with Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | <span class="pill">Python</span> | 40m | <span class="text-yellow">Intermediate</span> |
| [Semantic Search for Code](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | <span class="pill">Python</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Multivectors and Late Interaction](/documentation/advanced-tutorials/using-multivector-representations/) | Effective use of multivector representations. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
| [Static Embeddings](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the utility of static embeddings. | <span class="pill">Python</span> | 20m | <span class="text-yellow">Intermediate</span> |
qdrant-landing/content/documentation/tutorials-rag-and-agents/_index.md
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@@ -1,21 +0,0 @@
---
title: RAG & AI Agents
weight: 33
is_empty: true
hideInSidebar: true
aliases:
- how-to
- tutorials
partition: qdrant
---
# RAG & AI Agents Tutorials
*Build intelligent agents and complex LLM-driven applications.*
| Tutorial | Objective | Stack | Time | Level |
| :--- | :--- | :--- | :--- | :--- |
| [Multimodal Search (LlamaIndex)](/documentation/multimodal-search/) | Search across image and text modalities. | <span class="pill">LlamaIndex</span> | 15m | <span class="text-green">Beginner</span> |
| [Agentic RAG with CrewAI](/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | <span class="pill">CrewAI</span> | 45m | <span class="text-green">Beginner</span> |
| [Agentic RAG with LangGraph](/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | <span class="pill">LangGraph</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Agentic Discord ChatBot](/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | <span class="pill">OpenAI</span> | 45m | <span class="text-yellow">Intermediate</span> |
| [Automate Metadata Filtering](/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | <span class="pill">Python</span> | 30m | <span class="text-yellow">Intermediate</span> |
qdrant-landing/content/learn/_index.md
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@@ -62,8 +62,8 @@ content:
title: "Tutorial categories:"
elements:
- "Search Engineering"
- "RAG and Agents"
- "Ecosystem and Integrations"
- "Operations and Scale"
- "Develop and Implement"
link:
url: /documentation/tutorials-lp-overview
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---
#Delimiter files are used to separate the list of documentation pages into sections.
type: reference
reference: /documentation/tutorials-lp-ecosystem
weight: 316
sitemapExclude: True
_build:
publishResources: false
render: never
partition: learn
---
qdrant-landing/content/learn/ref-tutorials-rag-and-agents.md
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---
#Delimiter files are used to separate the list of documentation pages into sections.
type: reference
reference: /documentation/tutorials-lp-rag-and-agents
weight: 313
sitemapExclude: True
_build:
publishResources: false
render: never
partition: learn
---