> For the complete documentation index, see [llms.txt](https://docs.projectbit.ca/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.projectbit.ca/documentation/embeddings/ollama-embedder.md).

# Ollama Embedder

The `OllamaEmbedder` can be used to embed text data into vectors locally using Ollama.

The model used for generating embeddings needs to run locally.

### [​](https://docs.phidata.com/embedder/ollama#usage)Usage <a href="#usage" id="usage"></a>

cookbook/embedders/ollama\_embedder.py

```python
from bitca.agent import AgentKnowledge
from bitca.vectordb.pgvector import PgVector
from bitca.embedder.ollama import OllamaEmbedder

embeddings = OllamaEmbedder().get_embedding("The quick brown fox jumps over the lazy dog.")

# Print the embeddings and their dimensions
print(f"Embeddings: {embeddings[:5]}")
print(f"Dimensions: {len(embeddings)}")

# Example usage:
knowledge_base = AgentKnowledge(
    vector_db=PgVector(
        db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
        table_name="ollama_embeddings",
        embedder=OllamaEmbedder(),
    ),
    num_documents=2,
)
```

### [​](https://docs.phidata.com/embedder/ollama#params)Params <a href="#params" id="params"></a>

| Parameter       | Type                       | Default        | Description                                                               |
| --------------- | -------------------------- | -------------- | ------------------------------------------------------------------------- |
| `model`         | `str`                      | `"openhermes"` | The name of the model used for generating embeddings.                     |
| `dimensions`    | `int`                      | `4096`         | The dimensionality of the embeddings generated by the model.              |
| `host`          | `str`                      | -              | The host address for the API endpoint.                                    |
| `timeout`       | `Any`                      | -              | The timeout duration for API requests.                                    |
| `options`       | `Any`                      | -              | Additional options for configuring the API request.                       |
| `client_kwargs` | `Optional[Dict[str, Any]]` | -              | Additional keyword arguments for configuring the API client. Optional.    |
| `ollama_client` | `Optional[OllamaClient]`   | -              | An instance of the OllamaClient to use for making API requests. Optional. |


---

# Agent Instructions
This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com.

## Querying This Documentation
If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter, and the optional `goal` query parameter:

```
GET https://docs.projectbit.ca/documentation/embeddings/ollama-embedder.md?ask=<question>&goal=<endgoal>
```

`ask` is the immediate question: it should be specific, self-contained, and written in natural language.
`goal` is optional and describes the broader end goal you are ultimately trying to accomplish on behalf of the user. GitBook uses it to tailor the answer towards what is most useful for that goal.

The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.