> ## Documentation Index
> Fetch the complete documentation index at: https://portkey-docs-add-third-party-integration-issues-fixes.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# DeepSeek

> Portkey provides a robust and secure gateway to facilitate the integration of various Large Language Models (LLMs) into your applications, including DeepSeek models. 

With Portkey, you can take advantage of features like fast AI gateway access, observability, prompt management, and more, all while ensuring the secure management of your LLM API keys through a [virtual key](/product/ai-gateway/virtual-keys) system.

<Note>
  Provider Slug: **deepseek**
</Note>

## Portkey SDK Integration with DeepSeek Models

Portkey provides a consistent API to interact with models from various providers. To integrate DeepSeek with Portkey:

### 1. Install the Portkey SDK

Add the Portkey SDK to your application to interact with DeepSeek AI's API through Portkey's gateway.

<Tabs>
  <Tab title="NodeJS">
    ```sh theme={null}
    npm install --save portkey-ai
    ```
  </Tab>

  <Tab title="Python">
    ```sh theme={null}
    pip install portkey-ai
    ```
  </Tab>
</Tabs>

### 2. Initialize Portkey with the Virtual Key

To use DeepSeek with Portkey, [get your API key from here](https://platform.deepseek.com/api_keys), then add it to Portkey to create the virtual key.

<Tabs>
  <Tab title="NodeJS SDK">
    ```javascript theme={null}
    import Portkey from 'portkey-ai'

    const portkey = new Portkey({
        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
        virtualKey: "VIRTUAL_KEY" // Your DeepSeek Virtual Key
    })
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={null}
    from portkey_ai import Portkey

    portkey = Portkey(
        api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
        virtual_key="VIRTUAL_KEY"   # Replace with your virtual key for DeepSeek
    )
    ```
  </Tab>
</Tabs>

### 3. Invoke Chat Completions with DeepSeek

Use the Portkey instance to send requests to DeepSeek. You can also override the virtual key directly in the API call if needed.

<Tabs>
  <Tab title="NodeJS SDK">
    ```javascript theme={null}
    const chatCompletion = await portkey.chat.completions.create({
        messages: [{ role: 'user', content: 'Say this is a test' }],
        model: 'deepseek-chat',
    });

    console.log(chatCompletion.choices);
    ```
  </Tab>

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

    print(completion)
    ```
  </Tab>
</Tabs>

### 4. Invoke Multi-round Conversation with DeepSeek

<Tabs>
  <Tab title="NodeJS SDK">
    ```javascript theme={null}
    const client = new Portkey({
        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
        virtualKey: "VIRTUAL_KEY" // Your DeepSeek Virtual Key
    })

    // Function to send chat messages and get a response
    async function sendChatMessages(messages) {
      try {
        const response = await axios.post(baseURL, {
          model: 'deepseek-chat',
          messages: messages
        }, { headers: headers });
        return response.data;
      } catch (error) {
        console.error('Error during the API request:', error.response ? error.response.data : error.message);
        return null;
      }
    }

    // Round 1
    (async () => {
      let messages = [{ role: 'user', content: "What's the highest mountain in the world?" }];

      let response = await sendChatMessages(messages);
      if (response) {
        messages.push(response.choices[0].message);
        console.log(`Messages Round 1: ${JSON.stringify(messages, null, 2)}`);
      }

      // Round 2
      messages.push({ role: 'user', content: 'What is the second?' });
      response = await sendChatMessages(messages);
      if (response) {
        messages.push(response.choices[0].message);
        console.log(`Messages Round 2: ${JSON.stringify(messages, null, 2)}`);
      }
    })();
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={null}
    client = Portkey(
        api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
        virtual_key="VIRTUAL_KEY"   # Replace with your virtual key for DeepSeek
    )

    # Round 1
    messages = [{"role": "user", "content": "What's the highest mountain in the world?"}]
    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=messages
    )

    messages.append(response.choices[0].message)
    print(f"Messages Round 1: {messages}")

    # Round 2
    messages.append({"role": "user", "content": "What is the second?"})
    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=messages
    )

    messages.append(response.choices[0].message)
    print(f"Messages Round 2: {messages}")
    ```
  </Tab>
</Tabs>

### 5. JSON Output with DeepSeek

<Tabs>
  <Tab title="NodeJS SDK">
    ```javascript theme={null}
    const client = new Portkey({
        apiKey: "PORTKEY_API_KEY", // defaults to process.env["PORTKEY_API_KEY"]
        virtualKey: "VIRTUAL_KEY" // Your DeepSeek Virtual Key
    })

    const systemPrompt = `
    The user will provide some exam text. Please parse the "question" and "answer" and output them in JSON format.

    EXAMPLE INPUT:
    Which is the highest mountain in the world? Mount Everest.

    EXAMPLE JSON OUTPUT:
    {
        "question": "Which is the highest mountain in the world?",
        "answer": "Mount Everest"
    }
    `;

    const userPrompt = "Which is the longest river in the world? The Nile River.";

    const messages = [
        { role: "system", content: systemPrompt },
        { role: "user", content: userPrompt }
    ];

    client.chat.completions.create({
        model: "deepseek-chat",
        messages: messages,
        responseFormat: {
            type: 'json_object'
        }
    }).then(response => {
        console.log(JSON.parse(response.choices[0].message.content));
    }).catch(error => {
        console.error('Error:', error);
    });
    ```
  </Tab>

  <Tab title="Python SDK">
    ```python theme={null}
    import json

    client = Portkey(
        api_key="PORTKEY_API_KEY",  # Replace with your Portkey API key
        virtual_key="VIRTUAL_KEY"   # Replace with your virtual key for DeepSeek
    )

    system_prompt = """
    The user will provide some exam text. Please parse the "question" and "answer" and output them in JSON format.

    EXAMPLE INPUT:
    Which is the highest mountain in the world? Mount Everest.

    EXAMPLE JSON OUTPUT:
    {
        "question": "Which is the highest mountain in the world?",
        "answer": "Mount Everest"
    }
    """

    user_prompt = "Which is the longest river in the world? The Nile River."

    messages = [{"role": "system", "content": system_prompt},
                {"role": "user", "content": user_prompt}]

    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=messages,
        response_format={
            'type': 'json_object'
        }
    )

    print(json.loads(response.choices[0].message.content))
    ```
  </Tab>
</Tabs>

## Managing DeepSeek Prompts

You can manage all prompts to DeepSeek in the [Prompt Library](/product/prompt-library). All the current models of DeepSeek are supported and you can easily start testing different prompts.

Once you're ready with your prompt, you can use the `portkey.prompts.completions.create` interface to use the prompt in your application.

### Supported Endpoints

1. `CHAT_COMPLETIONS`
2. `STREAM_CHAT_COMPLETIONS`

The complete list of features supported in the SDK is available on the link below.

<Card title="Portkey SDK Client" icon="code" href="/api-reference/portkey-sdk-client">
  Learn more about the Portkey SDK Client
</Card>

You'll find more information in the relevant sections:

1. [Add metadata to your requests](/product/observability/metadata)
2. [Add gateway configs to your DeepSeek requests](/product/ai-gateway/configs)
3. [Tracing DeepSeek requests](/product/observability/traces)
4. [Setup a fallback from OpenAI to DeepSeek APIs](/product/ai-gateway/fallbacks)