> ## Documentation Index
> Fetch the complete documentation index at: https://langchain.idochub.dev/llms.txt
> Use this file to discover all available pages before exploring further.

# LocalAI

<Info>
  **`langchain-localai` is a 3rd party integration package for LocalAI. It provides a simple way to use LocalAI services in LangChain.**

  The source code is available on [Github](https://github.com/mkhludnev/langchain-localai)
</Info>

Let's load the LocalAI Embedding class. In order to use the LocalAI Embedding class, you need to have the LocalAI service hosted somewhere and configure the embedding models. See the documentation at [localai.io/basics/getting\_started/index.html](https://localai.io/basics/getting_started/index.html) and [localai.io/features/embeddings/index.html](https://localai.io/features/embeddings/index.html).

```python theme={null}
%pip install -U langchain-localai
```

```python theme={null}
from langchain_localai import LocalAIEmbeddings
```

```python theme={null}
embeddings = LocalAIEmbeddings(
    openai_api_base="http://localhost:8080", model="embedding-model-name"
)
```

```python theme={null}
text = "This is a test document."
```

```python theme={null}
query_result = embeddings.embed_query(text)
```

```python theme={null}
doc_result = embeddings.embed_documents([text])
```

Let's load the LocalAI Embedding class with first generation models (e.g. text-search-ada-doc-001/text-search-ada-query-001). Note: These are not recommended models - see [here](https://platform.openai.com/docs/guides/embeddings/what-are-embeddings)

```python theme={null}
from langchain_community.embeddings import LocalAIEmbeddings
```

```python theme={null}
embeddings = LocalAIEmbeddings(
    openai_api_base="http://localhost:8080", model="embedding-model-name"
)
```

```python theme={null}
text = "This is a test document."
```

```python theme={null}
query_result = embeddings.embed_query(text)
```

```python theme={null}
doc_result = embeddings.embed_documents([text])
```

```python theme={null}
import os

# if you are behind an explicit proxy, you can use the OPENAI_PROXY environment variable to pass through
os.environ["OPENAI_PROXY"] = "http://proxy.yourcompany.com:8080"
```