diff --git a/qdrant-landing/content/documentation/tutorials-ecosystem/_index.md b/qdrant-landing/content/documentation/tutorials-ecosystem/_index.md index a6ee29459..31731ca43 100644 --- a/qdrant-landing/content/documentation/tutorials-ecosystem/_index.md +++ b/qdrant-landing/content/documentation/tutorials-ecosystem/_index.md @@ -13,10 +13,10 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Embedding Migration](https://qdrant.tech/documentation/tutorials-ecosystem/migration/) | Move dense and sparse embeddings to Qdrant. | CLI | 30m | Intermediate | -| [S3 Ingestion with LangChain](https://qdrant.tech/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | LangChain | 30m | Beginner | -| [Hugging Face Datasets](https://qdrant.tech/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | Python | 15m | Beginner | -| [Databricks Integration](https://qdrant.tech/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | Databricks | 30m | Intermediate | -| [Airflow & Astronomer](https://qdrant.tech/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | Airflow | 45m | Intermediate | -| [Kafka Data Streaming](https://qdrant.tech/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | Kafka | 60m | Advanced | -| [No-Code Automation (n8n)](https://qdrant.tech/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | n8n | 45m | Intermediate | \ No newline at end of file +| [Embedding Migration](/documentation/tutorials-ecosystem/migration/) | Move dense and sparse embeddings to Qdrant. | CLI | 30m | Intermediate | +| [S3 Ingestion with LangChain](/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | LangChain | 30m | Beginner | +| [Hugging Face Datasets](/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | Python | 15m | Beginner | +| [Databricks Integration](/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | Databricks | 30m | Intermediate | +| [Airflow & Astronomer](/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | Airflow | 45m | Intermediate | +| [Kafka Data Streaming](/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | Kafka | 60m | Advanced | +| [No-Code Automation (n8n)](/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | n8n | 45m | Intermediate | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials-ecosystem/huggingface-datasets.md b/qdrant-landing/content/documentation/tutorials-ecosystem/huggingface-datasets.md index c43943d2e..a0f7bc865 100644 --- a/qdrant-landing/content/documentation/tutorials-ecosystem/huggingface-datasets.md +++ b/qdrant-landing/content/documentation/tutorials-ecosystem/huggingface-datasets.md @@ -2,6 +2,7 @@ title: Load a HuggingFace Dataset aliases: - /documentation/tutorials/huggingface-datasets/ + - /documentation/database-tutorials/huggingface-datasets/ weight: 3 --- diff --git a/qdrant-landing/content/documentation/tutorials-ecosystem/migration.md b/qdrant-landing/content/documentation/tutorials-ecosystem/migration.md index 4fdfc12c6..c8d94a99c 100644 --- a/qdrant-landing/content/documentation/tutorials-ecosystem/migration.md +++ b/qdrant-landing/content/documentation/tutorials-ecosystem/migration.md @@ -1,5 +1,7 @@ --- title: Migration to Qdrant +aliases: + - /documentation/database-tutorials/migration/ weight: 180 --- diff --git a/qdrant-landing/content/documentation/tutorials-operations/_index.md b/qdrant-landing/content/documentation/tutorials-operations/_index.md index 0c6e40726..dcf985e09 100644 --- a/qdrant-landing/content/documentation/tutorials-operations/_index.md +++ b/qdrant-landing/content/documentation/tutorials-operations/_index.md @@ -13,10 +13,10 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Bulk Data Uploads](https://qdrant.tech/documentation/tutorials-operations/bulk-upload/) | High-scale ingestion tricks for power users. | Python | 20m | Intermediate | -| [Snapshot & Backup](https://qdrant.tech/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | Python | 20m | Beginner | -| [Billion-Scale Search](https://qdrant.tech/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | None | 2 days | Advanced | -| [Python Async API](https://qdrant.tech/documentation/tutorials-operations/async-api/) | Use Asynchronous programming for efficiency. | Python | 25m | Intermediate | -| [Cloud Inference Search](https://qdrant.tech/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | Any | 20m | Beginner | -| [Monitor Managed Cloud](https://qdrant.tech/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate | -| [Monitor Private Cloud](https://qdrant.tech/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate | \ No newline at end of file +| [Bulk Data Uploads](/documentation/tutorials-operations/bulk-upload/) | High-scale ingestion tricks for power users. | Python | 20m | Intermediate | +| [Snapshot & Backup](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | Python | 20m | Beginner | +| [Billion-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | None | 2 days | Advanced | +| [Python Async API](/documentation/tutorials-operations/async-api/) | Use Asynchronous programming for efficiency. | Python | 25m | Intermediate | +| [Cloud Inference Search](/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | Any | 20m | Beginner | +| [Monitor Managed Cloud](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate | +| [Monitor Private Cloud](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials-operations/async-api.md b/qdrant-landing/content/documentation/tutorials-operations/async-api.md index 537c3b16f..05673071b 100644 --- a/qdrant-landing/content/documentation/tutorials-operations/async-api.md +++ b/qdrant-landing/content/documentation/tutorials-operations/async-api.md @@ -2,6 +2,7 @@ title: Build With Async API aliases: - /documentation/tutorials/async-api/ + - /documentation/database-tutorials/async-api/ weight: 4 --- diff --git a/qdrant-landing/content/documentation/tutorials-operations/bulk-upload.md b/qdrant-landing/content/documentation/tutorials-operations/bulk-upload.md index 43c629fa2..d12c80476 100644 --- a/qdrant-landing/content/documentation/tutorials-operations/bulk-upload.md +++ b/qdrant-landing/content/documentation/tutorials-operations/bulk-upload.md @@ -2,6 +2,7 @@ title: Bulk Upload Vectors aliases: - /documentation/tutorials/bulk-upload/ + - /documentation/database-tutorials/bulk-upload/ weight: 1 --- diff --git a/qdrant-landing/content/documentation/tutorials-operations/create-snapshot.md b/qdrant-landing/content/documentation/tutorials-operations/create-snapshot.md index 877e9ffc6..a1491f508 100644 --- a/qdrant-landing/content/documentation/tutorials-operations/create-snapshot.md +++ b/qdrant-landing/content/documentation/tutorials-operations/create-snapshot.md @@ -2,6 +2,7 @@ title: Create & Restore Snapshots aliases: - /documentation/tutorials/create-snapshot/ + - /documentation/database-tutorials/create-snapshot/ weight: 2 --- diff --git a/qdrant-landing/content/documentation/tutorials-operations/large-scale-search.md b/qdrant-landing/content/documentation/tutorials-operations/large-scale-search.md index 782481d61..6e3fbfed7 100644 --- a/qdrant-landing/content/documentation/tutorials-operations/large-scale-search.md +++ b/qdrant-landing/content/documentation/tutorials-operations/large-scale-search.md @@ -1,5 +1,7 @@ --- title: Large Scale Search +aliases: + - /documentation/database-tutorials/large-scale-search/ weight: 2 --- diff --git a/qdrant-landing/content/documentation/tutorials-overview/_index.md b/qdrant-landing/content/documentation/tutorials-overview/_index.md index 93ad2e326..7b844b266 100644 --- a/qdrant-landing/content/documentation/tutorials-overview/_index.md +++ b/qdrant-landing/content/documentation/tutorials-overview/_index.md @@ -15,9 +15,9 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Local Qdrant Setup](https://qdrant.tech/documentation/quickstart/) | Basic CRUD operations and local deployment. | Python | 10m | Beginner | -| [5-Minute Semantic Search](https://qdrant.tech/documentation/tutorials-quickstart/search-beginners/) | Build a search engine for science fiction books. | Python | 5m | Beginner | -| [5-Minute RAG with DeepSeek](https://qdrant.tech/documentation/tutorials-quickstart/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | Python | 5m | Beginner | +| [Local Qdrant Setup](/documentation/quickstart/) | Basic CRUD operations and local deployment. | Python | 10m | Beginner | +| [5-Minute Semantic Search](/documentation/tutorials-quickstart/search-beginners/) | Build a search engine for science fiction books. | Python | 5m | Beginner | +| [5-Minute RAG with DeepSeek](/documentation/tutorials-quickstart/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | Python | 5m | Beginner | --- @@ -26,15 +26,15 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Neural Search Service](https://qdrant.tech/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | FastAPI | 30m | Beginner | -| [Hybrid Search with FastEmbed](https://qdrant.tech/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search for startups. | FastAPI | 20m | Beginner | -| [Movie Recommendations](https://qdrant.tech/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate | -| [Advanced PDF Retrieval](https://qdrant.tech/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate | -| [Retrieval Quality Benchmarking](https://qdrant.tech/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | Python | 30m | Intermediate | -| [Multivector Reranking](https://qdrant.tech/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | Python | 30m | Intermediate | -| [Hybrid Search Reranking](https://qdrant.tech/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | Python | 40m | Intermediate | -| [Semantic Code Search](https://qdrant.tech/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | Python | 45m | Intermediate | -| [Static Embeddings Analysis](https://qdrant.tech/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | Python | 20m | Intermediate | +| [Neural Search Service](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | FastAPI | 30m | Beginner | +| [Hybrid Search with FastEmbed](/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search for startups. | FastAPI | 20m | Beginner | +| [Movie Recommendations](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate | +| [Advanced PDF Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate | +| [Retrieval Quality Benchmarking](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | Python | 30m | Intermediate | +| [Multivector Reranking](/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | Python | 30m | Intermediate | +| [Hybrid Search Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | Python | 40m | Intermediate | +| [Semantic Code Search](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | Python | 45m | Intermediate | +| [Static Embeddings Analysis](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | Python | 20m | Intermediate | --- @@ -43,11 +43,11 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Agentic RAG with CrewAI](https://qdrant.tech/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | CrewAI | 45m | Beginner | -| [Agentic RAG with LangGraph](https://qdrant.tech/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | LangGraph | 45m | Intermediate | -| [Agentic Discord ChatBot](https://qdrant.tech/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | OpenAI | 45m | Intermediate | -| [Multimodal Search (LlamaIndex)](https://qdrant.tech/documentation/multimodal-search/) | Search across image and text modalities. | LlamaIndex | 15m | Beginner | -| [Automate Metadata Filtering](https://qdrant.tech/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | Python | 30m | Intermediate | +| [Agentic RAG with CrewAI](/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | CrewAI | 45m | Beginner | +| [Agentic RAG with LangGraph](/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | LangGraph | 45m | Intermediate | +| [Agentic Discord ChatBot](/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | OpenAI | 45m | Intermediate | +| [Multimodal Search (LlamaIndex)](/documentation/multimodal-search/) | Search across image and text modalities. | LlamaIndex | 15m | Beginner | +| [Automate Metadata Filtering](/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | Python | 30m | Intermediate | --- @@ -56,13 +56,13 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Embedding Migration](https://qdrant.tech/documentation/tutorials-ecosystem/migration/) | Move dense and sparse embeddings to Qdrant. | CLI | 30m | Intermediate | -| [S3 Ingestion with LangChain](https://qdrant.tech/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | LangChain | 30m | Beginner | -| [Hugging Face Datasets](https://qdrant.tech/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | Python | 15m | Beginner | -| [Databricks Integration](https://qdrant.tech/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | Databricks | 30m | Intermediate | -| [Airflow & Astronomer](https://qdrant.tech/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | Airflow | 45m | Intermediate | -| [Kafka Data Streaming](https://qdrant.tech/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | Kafka | 60m | Advanced | -| [No-Code Automation (n8n)](https://qdrant.tech/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | n8n | 45m | Intermediate | +| [Embedding Migration](/documentation/tutorials-ecosystem/migration/) | Move dense and sparse embeddings to Qdrant. | CLI | 30m | Intermediate | +| [S3 Ingestion with LangChain](/documentation/data-ingestion-beginners/) | Stream data from AWS S3 to vector store. | LangChain | 30m | Beginner | +| [Hugging Face Datasets](/documentation/tutorials-ecosystem/huggingface-datasets/) | Load and search public ML datasets. | Python | 15m | Beginner | +| [Databricks Integration](/documentation/send-data/databricks/) | Vectorize datasets using FastEmbed on Databricks. | Databricks | 30m | Intermediate | +| [Airflow & Astronomer](/documentation/send-data/qdrant-airflow-astronomer/) | Orchestrate data engineering workflows. | Airflow | 45m | Intermediate | +| [Kafka Data Streaming](/documentation/send-data/data-streaming-kafka-qdrant/) | Setup Qdrant Sink Connector for real-time data. | Kafka | 60m | Advanced | +| [No-Code Automation (n8n)](/documentation/qdrant-n8n/) | Combine Qdrant with low-code n8n workflows. | n8n | 45m | Intermediate | --- @@ -71,10 +71,10 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Bulk Data Uploads](https://qdrant.tech/documentation/tutorials-operations/bulk-upload/) | High-scale ingestion tricks for power users. | Python | 20m | Intermediate | -| [Snapshot & Backup](https://qdrant.tech/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | Python | 20m | Beginner | -| [Billion-Scale Search](https://qdrant.tech/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | None | 2 days | Advanced | -| [Python Async API](https://qdrant.tech/documentation/tutorials-operations/async-api/) | Use Asynchronous programming for efficiency. | Python | 25m | Intermediate | -| [Cloud Inference Search](https://qdrant.tech/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | Any | 20m | Beginner | -| [Monitor Managed Cloud](https://qdrant.tech/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate | -| [Monitor Private Cloud](https://qdrant.tech/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate | \ No newline at end of file +| [Bulk Data Uploads](/documentation/tutorials-operations/bulk-upload/) | High-scale ingestion tricks for power users. | Python | 20m | Intermediate | +| [Snapshot & Backup](/documentation/tutorials-operations/create-snapshot/) | Create and restore collection snapshots. | Python | 20m | Beginner | +| [Billion-Scale Search](/documentation/tutorials-operations/large-scale-search/) | Cost-efficient search for LAION-400M datasets. | None | 2 days | Advanced | +| [Python Async API](/documentation/tutorials-operations/async-api/) | Use Asynchronous programming for efficiency. | Python | 25m | Intermediate | +| [Cloud Inference Search](/documentation/tutorials-and-examples/cloud-inference-hybrid-search/) | Hybrid search using Qdrant's built-in inference. | Any | 20m | Beginner | +| [Monitor Managed Cloud](/documentation/tutorials-and-examples/managed-cloud-prometheus/) | Observability with Prometheus and Grafana. | Prometheus | 30m | Intermediate | +| [Monitor Private Cloud](/documentation/tutorials-and-examples/hybrid-cloud-prometheus/) | Observability for hybrid/private cloud setups. | Prometheus | 30m | Intermediate | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials-quickstart/_index.md b/qdrant-landing/content/documentation/tutorials-quickstart/_index.md index 7ed82a709..6698bfb7f 100644 --- a/qdrant-landing/content/documentation/tutorials-quickstart/_index.md +++ b/qdrant-landing/content/documentation/tutorials-quickstart/_index.md @@ -13,6 +13,6 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Local Qdrant Setup](https://qdrant.tech/documentation/quickstart/) | Basic CRUD operations and local deployment. | Python | 10m | Beginner | -| [5-Minute Semantic Search](https://qdrant.tech/documentation/tutorials-quickstart/search-beginners/) | Build a search engine for science fiction books. | Python | 5m | Beginner | -| [5-Minute RAG with DeepSeek](https://qdrant.tech/documentation/tutorials-quickstart/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | Python | 5m | Beginner | \ No newline at end of file +| [Local Qdrant Setup](/documentation/quickstart/) | Basic CRUD operations and local deployment. | Python | 10m | Beginner | +| [5-Minute Semantic Search](/documentation/tutorials-quickstart/search-beginners/) | Build a search engine for science fiction books. | Python | 5m | Beginner | +| [5-Minute RAG with DeepSeek](/documentation/tutorials-quickstart/rag-deepseek/) | Build a RAG pipeline with DeepSeek enrichment. | Python | 5m | Beginner | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials-quickstart/search-beginners.md b/qdrant-landing/content/documentation/tutorials-quickstart/search-beginners.md index 7e2d18b2a..82c05d8ae 100644 --- a/qdrant-landing/content/documentation/tutorials-quickstart/search-beginners.md +++ b/qdrant-landing/content/documentation/tutorials-quickstart/search-beginners.md @@ -4,6 +4,7 @@ weight: 1 aliases: - /documentation/tutorials/mighty.md/ - /documentation/tutorials/search-beginners/ + - /documentation/beginner-tutorials/search-beginners/ --- # Build Your First Semantic Search Engine in 5 Minutes diff --git a/qdrant-landing/content/documentation/tutorials-rag-and-agents/_index.md b/qdrant-landing/content/documentation/tutorials-rag-and-agents/_index.md index 90067a152..636873990 100644 --- a/qdrant-landing/content/documentation/tutorials-rag-and-agents/_index.md +++ b/qdrant-landing/content/documentation/tutorials-rag-and-agents/_index.md @@ -13,8 +13,8 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Agentic RAG with CrewAI](https://qdrant.tech/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | CrewAI | 45m | Beginner | -| [Agentic RAG with LangGraph](https://qdrant.tech/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | LangGraph | 45m | Intermediate | -| [Agentic Discord ChatBot](https://qdrant.tech/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | OpenAI | 45m | Intermediate | -| [Multimodal Search (LlamaIndex)](https://qdrant.tech/documentation/multimodal-search/) | Search across image and text modalities. | LlamaIndex | 15m | Beginner | -| [Automate Metadata Filtering](https://qdrant.tech/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | Python | 30m | Intermediate | \ No newline at end of file +| [Agentic RAG with CrewAI](/documentation/agentic-rag-crewai-zoom/) | Step-by-step multi-agent RAG system. | CrewAI | 45m | Beginner | +| [Agentic RAG with LangGraph](/documentation/agentic-rag-langgraph/) | Build AI agents to answer library documentation. | LangGraph | 45m | Intermediate | +| [Agentic Discord ChatBot](/documentation/agentic-rag-camelai-discord/) | Develop a functional bot with CAMEL-AI. | OpenAI | 45m | Intermediate | +| [Multimodal Search (LlamaIndex)](/documentation/multimodal-search/) | Search across image and text modalities. | LlamaIndex | 15m | Beginner | +| [Automate Metadata Filtering](/documentation/search-precision/automate-filtering-with-llms/) | Use LLM structured output for dynamic filters. | Python | 30m | Intermediate | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/_index.md b/qdrant-landing/content/documentation/tutorials-search-engineering/_index.md index 1803ca930..414af321d 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/_index.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/_index.md @@ -13,12 +13,12 @@ partition: qdrant | Tutorial | Objective | Stack | Time | Level | | :--- | :--- | :--- | :--- | :--- | -| [Neural Search Service](https://qdrant.tech/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | FastAPI | 30m | Beginner | -| [Hybrid Search with FastEmbed](https://qdrant.tech/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search for startups. | FastAPI | 20m | Beginner | -| [Movie Recommendations](https://qdrant.tech/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate | -| [Advanced PDF Retrieval](https://qdrant.tech/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate | -| [Retrieval Quality Benchmarking](https://qdrant.tech/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | Python | 30m | Intermediate | -| [Multivector Reranking](https://qdrant.tech/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | Python | 30m | Intermediate | -| [Hybrid Search Reranking](https://qdrant.tech/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | Python | 40m | Intermediate | -| [Semantic Code Search](https://qdrant.tech/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | Python | 45m | Intermediate | -| [Static Embeddings Analysis](https://qdrant.tech/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | Python | 20m | Intermediate | \ No newline at end of file +| [Neural Search Service](/documentation/tutorials-search-engineering/neural-search/) | Deploy a search service for company descriptions. | FastAPI | 30m | Beginner | +| [Hybrid Search with FastEmbed](/documentation/tutorials-search-engineering/hybrid-search-fastembed/) | Combine dense and sparse search for startups. | FastAPI | 20m | Beginner | +| [Movie Recommendations](/documentation/tutorials-search-engineering/collaborative-filtering/) | Collaborative filtering using sparse embeddings. | Python | 45m | Intermediate | +| [Advanced PDF Retrieval](/documentation/tutorials-search-engineering/pdf-retrieval-at-scale/) | PDF RAG using ColPali and embedding pooling. | Python | 30m | Intermediate | +| [Retrieval Quality Benchmarking](/documentation/tutorials-search-engineering/retrieval-quality/) | Measure quality and tune HNSW parameters. | Python | 30m | Intermediate | +| [Multivector Reranking](/documentation/search-precision/reranking-semantic-search/) | Use multivector representations for better ranking. | Python | 30m | Intermediate | +| [Hybrid Search Reranking](/documentation/tutorials-search-engineering/reranking-hybrid-search/) | Implement late interaction and sparse reranking. | Python | 40m | Intermediate | +| [Semantic Code Search](/documentation/tutorials-search-engineering/code-search/) | Navigate codebases using vector similarity. | Python | 45m | Intermediate | +| [Static Embeddings Analysis](/documentation/tutorials-search-engineering/static-embeddings/) | Evaluate the renaissance of static embeddings. | Python | 20m | Intermediate | \ No newline at end of file diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/code-search.md b/qdrant-landing/content/documentation/tutorials-search-engineering/code-search.md index 44a7937d2..a6be36324 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/code-search.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/code-search.md @@ -2,6 +2,7 @@ title: Search Through Your Codebase aliases: - /documentation/tutorials/code-search/ + - /documentation/advanced-tutorials/code-search/ weight: 2 --- diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/collaborative-filtering.md b/qdrant-landing/content/documentation/tutorials-search-engineering/collaborative-filtering.md index 8e871f05c..db71fb55f 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/collaborative-filtering.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/collaborative-filtering.md @@ -2,6 +2,7 @@ title: Build a Recommendation System with Collaborative Filtering aliases: - /documentation/tutorials/collaborative-filtering/ + - /documentation/advanced-tutorials/collaborative-filtering/ short_description: "Build an effective movie recommendation system using collaborative filtering and Qdrant's similarity search." description: "Build an effective movie recommendation system using collaborative filtering and Qdrant's similarity search." preview_image: /blog/collaborative-filtering/social_preview.png diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/hybrid-search-fastembed.md b/qdrant-landing/content/documentation/tutorials-search-engineering/hybrid-search-fastembed.md index d7db0050a..7fbdcbf5b 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/hybrid-search-fastembed.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/hybrid-search-fastembed.md @@ -2,6 +2,7 @@ title: Setup Hybrid Search with FastEmbed aliases: - /documentation/tutorials/hybrid-search-fastembed/ + - /documentation/beginner-tutorials/hybrid-search-fastembed/ weight: 3 --- diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/neural-search.md b/qdrant-landing/content/documentation/tutorials-search-engineering/neural-search.md index 495e1273e..422912376 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/neural-search.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/neural-search.md @@ -2,6 +2,7 @@ title: Build a Neural Search Service aliases: - /documentation/tutorials/neural-search/ + - /documentation/beginner-tutorials/neural-search/ weight: 2 --- diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/pdf-retrieval-at-scale.md b/qdrant-landing/content/documentation/tutorials-search-engineering/pdf-retrieval-at-scale.md index e27655e0d..89f98bd55 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/pdf-retrieval-at-scale.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/pdf-retrieval-at-scale.md @@ -2,6 +2,7 @@ title: Scaling PDF Retrieval with Qdrant aliases: - /documentation/tutorials/pdf-retrieval-at-scale/ + - /documentation/advanced-tutorials/pdf-retrieval-at-scale/ short_description: "Optimizing PDF retrieval at scale with Qdrant and Vision Large Language Models (VLLMs) such as ColPali and ColQwen." description: "Optimizing PDF retrieval at scale with Qdrant and Vision Large Language Models (VLLMs) such as ColPali and ColQwen. Two-stage retrieval with multivector representations mean pooling." weight: 4 diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/reranking-hybrid-search.md b/qdrant-landing/content/documentation/tutorials-search-engineering/reranking-hybrid-search.md index 19b6bfe7c..c0a3516e2 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/reranking-hybrid-search.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/reranking-hybrid-search.md @@ -3,6 +3,7 @@ title: Reranking in Hybrid Search weight: 2 aliases: - /documentation/search-precision/reranking-hybrid-search/ + - /documentation/advanced-tutorials/reranking-hybrid-search/ --- # Reranking Hybrid Search Results with Qdrant Vector Database diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality.md b/qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality.md index 2a9eee8bc..f1140aff4 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/retrieval-quality.md @@ -2,6 +2,7 @@ title: Measure Search Quality aliases: - /documentation/tutorials/retrieval-quality/ + - /documentation/beginner-tutorials/retrieval-quality/ weight: 4 --- diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/static-embeddings.md b/qdrant-landing/content/documentation/tutorials-search-engineering/static-embeddings.md index e062bad21..7181f4336 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/static-embeddings.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/static-embeddings.md @@ -3,6 +3,7 @@ title: Static Embeddings. Should you pay attention? weight: 181 aliases: - /blog/static-embeddings/ + - /documentation/database-tutorials/static-embeddings/ --- # Static Embeddings: should you pay attention? In the world of resource-constrained computing, a quiet revolution is taking place. While transformers dominate diff --git a/qdrant-landing/content/documentation/tutorials-search-engineering/using-multivector-representations.md b/qdrant-landing/content/documentation/tutorials-search-engineering/using-multivector-representations.md index 5d225fc2a..9087bcec7 100644 --- a/qdrant-landing/content/documentation/tutorials-search-engineering/using-multivector-representations.md +++ b/qdrant-landing/content/documentation/tutorials-search-engineering/using-multivector-representations.md @@ -3,6 +3,7 @@ title: How to Use Multivector Representations with Qdrant Effectively weight: 2 aliases: - /documentation/search-precision/multivector-representations-with-Qdrant/ + - /documentation/advanced-tutorials/using-multivector-representations/ --- # How to Effectively Use Multivector Representations in Qdrant for Reranking Multivector Representations are one of the most powerful features of Qdrant. However, most people don't use them effectively, resulting in massive RAM overhead, slow inserts, and wasted compute.