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

# Ollama

Obiguard provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including your **locally hosted models through Ollama**.

<Note>
  Provider Slug. `ollama`
</Note>

## Obiguard SDK Integration with Ollama Models

Obiguard provides a consistent API to interact with models from various providers.

### 1. Expose your Ollama API

Expose your Ollama API by using a tunneling service like [ngrok](https://ngrok.com/) or any other way you prefer.

For using Ollama with ngrok, here's a [useful guide](https://github.com/ollama/ollama/blob/main/docs/faq.md#how-can-i-use-ollama-with-ngrok)

```sh theme={null}
ngrok http 11434 --host-header="localhost:11434"
```

### 2. Install the Obiguard SDK

Install the Obiguard SDK in your application to interact with your Ollama API through Obiguard.

<Tabs>
  <Tab title="Python SDK">
    ```sh theme={null}
    pip install obiguard
    ```
  </Tab>
</Tabs>

### 3. Initialize Obiguard with Ollama URL

Instantiate the Obiguard client by adding your Ollama publicly-exposed URL to the `customHost` property.

<Tabs>
  <Tab title="Python SDK">
    ```python theme={null}
    from obiguard import Obiguard

    client = Obiguard(
      obiguard_api_key="sk-obg***",  # Your Obiguard API key
      provider="ollama",
      custom_host="https://8cc4-2-234-255-255.ngrok-free.app" # Your Ollama ngrok URL
    )
    ```
  </Tab>
</Tabs>

<Note>
  For the Ollama integration, you only need to pass the base URL to `customHost` without the version identifier (such as
  `/v1`) - Obiguard takes care of the rest!
</Note>

### **4. Invoke Chat Completions with** Ollama

Use the Obiguard SDK to invoke chat completions from your Ollama model, just as you would with any other provider.

<Tabs>
  <Tab title="Python SDK">
    ```python theme={null}
    completion = client.chat.completions.create(
      messages= [{"role": 'user', "content": 'Say this is a test'}],
      model= 'llama3'
    )

    print(completion)
    ```
  </Tab>

  <Tab title="cURL">
    ```sh theme={null}
    curl --location 'https://gateway.obiguard.ai/v1/chat/completions' \
      --header 'Content-Type: application/json' \
      --header 'x-obiguard-custom-host: https://1eb6-103-180-45-255.ngrok-free.app' \
      --header 'x-obiguard-provider: ollama' \
      --header 'x-obiguard-api-key: $OBIGUARD_API_KEY' \
      --data '{
        "model": "tinyllama",
        "max_tokens": 200,
        "stream": false,
        "messages": [
          {
            "role": "system",
            "content": [
              {
                "type": "text",
                "text": "You are Batman"
              }
            ]
          },
          {
            "role": "user",
            "content": [
              {
                "type": "text",
                "text": "Who is the greatest detective"
              }
            ]
          },
          {
            "role": "assistant",
            "content": [
              {
                "type": "text",
                "text": "is it me?"
              }
            ]
          }
        ]
      }'
    ```
  </Tab>
</Tabs>

## [Using Virtual Keys](/virtual-keys)

Virtual Keys serve as Obiguard's unified authentication system for all LLM interactions, simplifying the use of multiple providers and
Obiguard features within your application.

For self-hosted LLMs, you can configure custom authentication requirements including authorization keys, bearer tokens, or any other headers needed to access your models.

1. Navigate to [Virtual Keys](/virtual-keys) in your Obiguard dashboard
2. Click **"Add Key"** and enable the **"Local/Privately hosted provider"** toggle
3. Configure your deployment:

* Select the matching provider API specification (typically `OpenAI`)
* Enter your model's base public URL in the `Custom Host` field
* Add required authentication headers and their values

4. Click **"Create"** to generate your virtual key

You can now use this virtual key in your requests:

<Tabs>
  <Tab title="Python SDK">
    ```python theme={null}
    client = Obiguard(
      obiguard_api_key="sk-obg***",  # Your Obiguard API key
      virtual_key="YOUR_SELF_HOSTED_LLM_VIRTUAL_KEY"
    )

    response = client.chat.completions.create(
      model="your-self-hosted-model-name",
      messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
      ]
    )

    print(response)
    ```
  </Tab>

  <Tab title="OpenAI SDK">
    ```py theme={null}
    from openai import OpenAI
    from obiguard import OBIGUARD_GATEWAY_URL, createHeaders

    client = OpenAI(
      api_key='OPENAI_API_KEY',
      base_url=OBIGUARD_GATEWAY_URL,
      default_headers=createHeaders(
        provider="openai",
        obiguard_api_key="vk-obg******",  # Your Obiguard virtual key
      )
    )

    completion = client.chat.completions.create(
      model="gpt-4o",
      messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"}
      ]
    )

    print(completion.choices[0].message)
    ```
  </Tab>

  <Tab title="cURL">
    ```sh theme={null}
    curl https://gateway.obiguard.ai/v1/chat/completions \
      -H "Content-Type: application/json" \
      -H "x-obiguard-api-key: $OBIGUARD_API_KEY" \
      -d '{
        "model": "gpt-4o",
        "messages": [
          {"role": "user", "content": "Hello!"}
        ]
    }'
    ```
  </Tab>
</Tabs>

## Ollama Tool Calling

Tool calling feature lets models trigger external tools based on conversation context.
You define available functions, the model chooses when to use them, and your application executes them and returns results.

Obiguard supports Ollama Tool Calling and makes it interoperable across multiple providers.

<Card title="Supported Ollama Models with Tool Calling" href="https://ollama.com/search?c=tools" />

<Tabs>
  <Tab title="Python SDK">
    ```python theme={null}
    tools = [{
      "type": "function",
      "function": {
        "name": "getWeather",
        "description": "Get the current weather",
        "parameters": {
          "type": "object",
          "properties": {
            "location": {"type": "string", "description": "City and state"},
            "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
          },
          "required": ["location"]
        }
      }
    }]


    response = client.chat.completions.create(
      model="llama-3.3-70b-versatile",
      messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What's the weather like in Delhi - respond in JSON"}
      ],
      tools=tools,
      tool_choice="auto"
    )

    print(response.choices[0].finish_reason)
    ```
  </Tab>

  <Tab title="cURL">
    ```sh theme={null}
    curl -X POST "https://gateway.obiguard.ai/v1/chat/completions" \
      -H "Content-Type: application/json" \
      -H "Authorization: Bearer $YOUR_OBIGUARD_VIRTUAL_KEY" \
      -d '{
        "model": "llama-3.3-70b-versatile",
        "messages": [
          {"role": "system", "content": "You are a helpful assistant."},
          {"role": "user", "content": "What'\''s the weather like in Delhi - respond in JSON"}
        ],
        "tools": [{
          "type": "function",
          "function": {
            "name": "getWeather",
            "description": "Get the current weather",
            "parameters": {
              "type": "object",
              "properties": {
                "location": {"type": "string", "description": "City and state"},
                "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
              },
              "required": ["location"]
            }
          }
        }],
        "tool_choice": "auto"
      }'
    ```
  </Tab>
</Tabs>

## Next Steps

Explore the complete list of features supported in the SDK:

<Card title="SDK" href="/api-reference/sdk/python" />