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35 lines
1.2 KiB
Markdown
35 lines
1.2 KiB
Markdown
---
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title: LlamaIndex
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weight: 200
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aliases: [ ../integrations/llama-index/ ]
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---
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# LlamaIndex (GPT Index)
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LlamaIndex (formerly GPT Index) acts as an interface between your external data and Large Language Models. So you can bring your
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private data and augment LLMs with it. LlamaIndex simplifies data ingestion and indexing, integrating Qdrant as a vector index.
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Installing LlamaIndex is straightforward if we use pip as a package manager. Qdrant is not installed by default, so we need to
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install it separately:
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```bash
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pip install llama-index qdrant-client
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```
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LlamaIndex requires providing an instance of `QdrantClient`, so it can interact with Qdrant server.
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```python
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from llama_index.vector_stores.qdrant import QdrantVectorStore
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import qdrant_client
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client = qdrant_client.QdrantClient(
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"<qdrant-url>",
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api_key="<qdrant-api-key>", # For Qdrant Cloud, None for local instance
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)
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index = QdrantVectorStore(client=client, collection_name="documents")
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```
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The library [comes with a notebook](https://github.com/jerryjliu/llama_index/blob/main/docs/examples/vector_stores/QdrantIndexDemo.ipynb)
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that shows an end-to-end example of how to use Qdrant within LlamaIndex. |