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82 lines
2.4 KiB
Markdown
82 lines
2.4 KiB
Markdown
---
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title: Dynamiq
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---
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# Dynamiq
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Dynamiq is your all-in-one Gen AI framework, designed to streamline the development of AI-powered applications. Dynamiq specializes in orchestrating retrieval-augmented generation (RAG) and large language model (LLM) agents.
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Qdrant is a vector database available in Dynamiq, capable of serving multiple roles. It can be used for writing and retrieving documents, acting as memory for agent interactions, and functioning as a retrieval tool that agents can call when needed.
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## Installing
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First, ensure you have the `dynamiq` library installed:
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```bash
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$ pip install dynamiq
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```
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## Retriever node
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The QdrantDocumentRetriever node enables efficient retrieval of relevant documents based on vector similarity search.
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```python
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from dynamiq.nodes.retrievers import QdrantDocumentRetriever
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from dynamiq import Workflow
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# Define a retriever node to fetch most relevant documents
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retriever_node = QdrantDocumentRetriever(
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index_name="default",
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top_k=5, # Optional: Maximum number of documents to retrieve
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filters={...} # Optional: Additional filtering conditions
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)
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# Create a workflow and add the retriever node
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wf = Workflow()
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wf.flow.add_nodes(retriever_node)
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# Execute retrieval
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result = wf.run(input_data={
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'embedding': query_embedding # Provide an embedded query for similarity search
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})
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```
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## Writer node
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The QdrantDocumentWriter node allows storing documents in the Qdrant vector database.
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```python
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from dynamiq.nodes.writers import QdrantDocumentWriter
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# Define a writer node to store documents in Qdrant
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writer_node = QdrantDocumentWriter(
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index_name="default",
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create_if_not_exist=True
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)
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# Create a workflow and add the writer node
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wf = Workflow()
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wf.flow.add_nodes(writer_node)
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# Execute writing
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result = wf.run(input_data={
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'documents': embedded_documents # Provide embedded documents for storage
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})
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```
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# Additional Tutorials
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Discover additional examples and use cases of Qdrant with Dynamiq:
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- [Using Qdrant with Dynamiq – A Hands-on Tutorial](https://colab.research.google.com/drive/1rlZJW4lOM36b7ZxK-dVJv5dE2xrgwxU_?usp=sharing)
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- [End-to-End Application with Qdrant and Dynamiq](https://colab.research.google.com/drive/1RaR25BCj_D5wzQ70ejUQyKzdCM6DUXMF?usp=sharing)
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## For more details, please refer to:
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- [Dynamiq Documentation](https://docs.getdynamiq.ai/)
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- [Dynamiq GitHub](https://github.com/dynamiq-ai/dynamiq)
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