docs: ollama model and embeddings examples (#7672)

* ollama-model-component

* ollama-embeddings-example

* screenshot-and-model-name
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@ -3,6 +3,8 @@ title: Embeddings
slug: /components-embedding-models
---
import Icon from "@site/src/components/icon";
# Embeddings models in Langflow
Embeddings models convert text into numerical vectors. These embeddings capture semantic meaning of the input text, and allow LLMs to understand context.
@ -343,10 +345,25 @@ This component generates embeddings using [NVIDIA models](https://docs.nvidia.co
|------|------|-------------|
| embeddings | Embeddings | NVIDIAEmbeddings instance for generating embeddings |
## Ollama Embeddings
## Ollama embeddings
This component generates embeddings using [Ollama models](https://ollama.com/).
For a list of Ollama embeddings models, see the [Ollama documentation](https://ollama.com/search?c=embedding).
To use this component in a flow, connect Langflow to your locally running Ollama server and select an embeddings model.
1. In the Ollama component, in the **Ollama Base URL** field, enter the address for your locally running Ollama server.
This value is set as the `OLLAMA_HOST` environment variable in Ollama. The default base URL is `http://127.0.0.1:11434`.
2. To refresh the server's list of models, click <Icon name="RefreshCw" aria-label="Refresh"/>.
3. In the **Ollama Model** field, select an embeddings model. This example uses `all-minilm:latest`.
4. Connect the **Ollama** embeddings component to a flow.
For example, this flow connects a local Ollama server running a `all-minilm:latest` embeddings model to a [Chroma DB](/components-vector-stores#chroma) vector store to generate embeddings for split text.
![Ollama embeddings connected to Chroma DB](/img/component-ollama-embeddings-chromadb.png)
For more information, see the [Ollama documentation](https://ollama.com/).
### Inputs
| Name | Type | Description |

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@ -458,7 +458,18 @@ For more information, see [NVIDIA AI documentation](https://developer.nvidia.com
This component generates text using Ollama's language models.
For more information, see [Ollama documentation](https://ollama.com/).
To use this component in a flow, connect Langflow to your locally running Ollama server and select a model.
1. In the Ollama component, in the **Base URL** field, enter the address for your locally running Ollama server.
This value is set as the `OLLAMA_HOST` environment variable in Ollama.
The default base URL is `http://127.0.0.1:11434`.
2. To refresh the server's list of models, click <Icon name="RefreshCw" aria-label="Refresh"/>.
3. In the **Model Name** field, select a model. This example uses `llama3.2:latest`.
4. Connect the **Ollama** model component to a flow. For example, this flow connects a local Ollama server running a Llama 3.2 model as the custom model for an [Agent](/components-agents) component.
![Ollama model as Agent custom model](/img/component-ollama-model.png)
For more information, see the [Ollama documentation](https://ollama.com/).
### Inputs

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