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53 lines
1.3 KiB
Markdown
53 lines
1.3 KiB
Markdown
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---
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title: GPT4All
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weight: 1700
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aliases:
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- /documentation/examples/gpt4all-search/
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- /documentation/tutorials/gpt4all-search/
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- /documentation/integrations/gpt4all/
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---
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# Using GPT4All with Qdrant
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GPT4All offers a range of large language models that can be fine-tuned for various applications. GPT4All runs large language models (LLMs) privately on everyday desktops & laptops.
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No API calls or GPUs required - you can just download the application and get started. Use GPT4All in Python to program with LLMs implemented with the llama.cpp backend and Nomic's C backend.
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## Installation
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You can install the required package using the following pip command:
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```bash
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pip install gpt4all
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```
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Here is how you might connect to GPT4ALL using Qdrant:
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```python
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import qdrant_client
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from qdrant_client.models import Batch
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from gpt4all import GPT4All
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# Initialize GPT4All model
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model = GPT4All("gpt4all-lora-quantized")
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# Generate embeddings for a text
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text = "GPT4All enables open-source AI applications."
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embeddings = model.embed(text)
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# Initialize Qdrant client
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qdrant_client = qdrant_client.QdrantClient(host="localhost", port=6333)
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# Upsert the embedding into Qdrant
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qdrant_client.upsert(
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collection_name="OpenSourceAI",
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points=Batch(
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ids=[1],
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vectors=[embeddings],
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)
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)
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```
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