> For clean Markdown of any page, append .md to the page URL.
> For a complete documentation index, see https://www.comet.com/docs/opik/integrations/deepseek/llms.txt.
> For AI client integration (Claude Code, Cursor, etc.), connect to the MCP server at https://www.comet.com/_mcp/server.

# Observability for DeepSeek with Opik

> Start here to integrate Opik into your DeepSeek-based genai application for end-to-end LLM observability, unit testing, and optimization.

Deepseek is an Open-Source LLM model that rivals o1 from OpenAI. You can learn more about DeepSeek on [Github](https://github.com/deepseek-ai/DeepSeek-R1) or
on [deepseek.com](https://www.deepseek.com/).

In this guide, we will showcase how to track DeepSeek calls using Opik. As DeepSeek is open-source, there are many way to run and call the model. We will focus on how to integrate Opik with the following hosting options:

1. DeepSeek API
2. Fireworks AI API
3. Together AI API

## Getting started

### Configuring your hosting provider

Before you can start tracking DeepSeek calls, you need to get the API key from your hosting provider.

#### DeepSeek API

In order to use the DeepSeek API, you will need to have an API key. You can register for an account on [DeepSeek.com](https://chat.deepseek.com/sign_up).
Once you have signed up, you can register for an API key.

#### Fireworks AI API

You can log into Fireworks AI on [fireworks.ai](https://fireworks.ai/). You can then access your API key on the [API keys](https://fireworks.ai/account/api-keys) page.

#### Together AI API

You can log into Together AI on [together.ai](https://together.ai/). You can then access your API key on the [API keys](https://api.together.ai/settings/api-keys) page.

### Configuring Opik

```bash
pip install --upgrade --quiet opik

opik configure
```

> **Tip**
>
> Opik is fully open-source and can be run locally or through the Opik Cloud platform. You can learn more about hosting
> Opik on your own infrastructure in the [self-hosting guide](/self-host/overview).

## Tracking DeepSeek calls

The easiest way to call DeepSeek with Opik is to use the OpenAI Python SDK and the `track_openai` decorator. This approach is compatible with the DeepSeek API, Fireworks AI API and Together AI API:

#### DeepSeek API

```python
from opik.integrations.openai import track_openai
from openai import OpenAI

# Create the OpenAI client that points to DeepSeek API
client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")

# Wrap your OpenAI client to track all calls to Opik
client = track_openai(client)

# Call the API
response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "Hello"},
    ],
    stream=False
)

print(response.choices[0].message.content)
```

#### Fireworks AI API

```python
from opik.integrations.openai import track_openai
from openai import OpenAI

# Create the OpenAI client that points to DeepSeek API
client = OpenAI(api_key="<Fireworks AI API Key>", base_url="https://api.fireworks.ai/inference/v1")

# Wrap your OpenAI client to track all calls to Opik
client = track_openai(client)

# Call the API
response = client.chat.completions.create(
    model="accounts/fireworks/models/deepseek-v3",
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "Hello"},
    ],
    stream=False
)

print(response.choices[0].message.content)
```

#### Together AI API

```python
from opik.integrations.openai import track_openai
from openai import OpenAI

# Create the OpenAI client that points to Together AI API
client = OpenAI(api_key="<Together AI API Key>", base_url="https://api.together.xyz/v1")

# Wrap your OpenAI client to track all calls to Opik
client = track_openai(client)

# Call the API
response = client.chat.completions.create(
    model="deepseek-ai/DeepSeek-R1",
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "Hello"},
    ],
    stream=False
)

print(response.choices[0].message.content)
```

> Debug, evaluate, and monitor your LLM applications, RAG systems, and agentic workflows with comprehensive tracing, automated evaluations, and production-ready dashboards.