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

# ChatNetmind

This will help you get started with Netmind [chat models](https://www.netmind.ai/). For detailed documentation of all ChatNetmind features and configurations head to the [API reference](https://github.com/protagolabs/langchain-netmind).

* See [www.netmind.ai/](https://www.netmind.ai/) for an example.

## Overview

### Integration details

| Class                                                      | Package                                                          | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/) |                                              Downloads                                             |                                             Version                                             |
| :--------------------------------------------------------- | :--------------------------------------------------------------- | :---: | :----------: | :------------------------------------------------------------: | :------------------------------------------------------------------------------------------------: | :---------------------------------------------------------------------------------------------: |
| [ChatNetmind](https://python.langchain.com/api_reference/) | [langchain-netmind](https://python.langchain.com/api_reference/) |   ✅   |       ❌      |                                ❌                               | ![PyPI - Downloads](https://img.shields.io/pypi/dm/langchain-netmind?style=flat-square\&label=%20) | ![PyPI - Version](https://img.shields.io/pypi/v/langchain-netmind?style=flat-square\&label=%20) |

### Model features

| [Tool calling](../../how_to/tool_calling.ipynb) | [Structured output](../../how_to/structured_output.ipynb) | JSON mode | [Image input](../../how_to/multimodal_inputs.ipynb) | Audio input | Video input | [Token-level streaming](../../how_to/chat_streaming.ipynb) | Native async | [Token usage](../../how_to/chat_token_usage_tracking.ipynb) | [Logprobs](../../how_to/logprobs.ipynb) |
| :---------------------------------------------: | :-------------------------------------------------------: | :-------: | :-------------------------------------------------: | :---------: | :---------: | :--------------------------------------------------------: | :----------: | :---------------------------------------------------------: | :-------------------------------------: |
|                        ✅                        |                             ✅                             |     ✅     |                          ❌                          |      ❌      |      ❌      |                              ✅                             |       ✅      |                              ✅                              |                    ✅                    |

## Setup

To access Netmind models you'll need to create a/an Netmind account, get an API key, and install the `langchain-netmind` integration package.

### Credentials

Head to [www.netmind.ai/](https://www.netmind.ai/) to sign up to Netmind and generate an API key. Once you've done this set the NETMIND\_API\_KEY environment variable:

```python theme={null}
import getpass
import os

if not os.getenv("NETMIND_API_KEY"):
    os.environ["NETMIND_API_KEY"] = getpass.getpass("Enter your Netmind API key: ")
```

If you want to get automated tracing of your model calls you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:

```python theme={null}
# os.environ["LANGCHAIN_TRACING_V2"] = "true"
# os.environ["LANGCHAIN_API_KEY"] = getpass.getpass("Enter your LangSmith API key: ")
```

### Installation

The LangChain Netmind integration lives in the `langchain-netmind` package:

```python theme={null}
%pip install -qU langchain-netmind
```

```output theme={null}
[notice] A new release of pip is available: 24.0 -> 25.0.1
[notice] To update, run: pip install -U pip
Note: you may need to restart the kernel to use updated packages.
```

## Instantiation

Now we can instantiate our model object and generate chat completions:

```python theme={null}
from langchain_netmind import ChatNetmind

llm = ChatNetmind(
    model="deepseek-ai/DeepSeek-V3",
    temperature=0,
    max_tokens=None,
    timeout=None,
    max_retries=2,
    # other params...
)
```

## Invocation

```python theme={null}
messages = [
    (
        "system",
        "You are a helpful assistant that translates English to French. Translate the user sentence.",
    ),
    ("human", "I love programming."),
]
ai_msg = llm.invoke(messages)
ai_msg
```

```output theme={null}
AIMessage(content="J'adore programmer.", additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 13, 'prompt_tokens': 31, 'total_tokens': 44, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'deepseek-ai/DeepSeek-V3', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-ca6c2010-844d-4bf6-baac-6e248491b000-0', usage_metadata={'input_tokens': 31, 'output_tokens': 13, 'total_tokens': 44, 'input_token_details': {}, 'output_token_details': {}})
```

```python theme={null}
print(ai_msg.content)
```

```output theme={null}
J'adore programmer.
```

## Chaining

We can [chain](/oss/python/how-to/sequence/) our model with a prompt template like so:

```python theme={null}
from langchain_core.prompts import ChatPromptTemplate

prompt = ChatPromptTemplate(
    [
        (
            "system",
            "You are a helpful assistant that translates {input_language} to {output_language}.",
        ),
        ("human", "{input}"),
    ]
)

chain = prompt | llm
chain.invoke(
    {
        "input_language": "English",
        "output_language": "German",
        "input": "I love programming.",
    }
)
```

```output theme={null}
AIMessage(content='Ich liebe es zu programmieren.', additional_kwargs={'refusal': None}, response_metadata={'token_usage': {'completion_tokens': 14, 'prompt_tokens': 26, 'total_tokens': 40, 'completion_tokens_details': None, 'prompt_tokens_details': None}, 'model_name': 'deepseek-ai/DeepSeek-V3', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-d63adcc6-53ba-4caa-9a79-78d640b39274-0', usage_metadata={'input_tokens': 26, 'output_tokens': 14, 'total_tokens': 40, 'input_token_details': {}, 'output_token_details': {}})
```

## API reference

For detailed documentation of all ChatNetmind features and configurations head to the API reference:

* [API reference](https://python.langchain.com/api_reference/)
* [langchain-netmind](https://github.com/protagolabs/langchain-netmind)
* [pypi](https://pypi.org/project/langchain-netmind/)

```python theme={null}
```