Cohere's Command family of LLMs are available via the Chat endpoint. This endpoint enables you to build generative AI applications and facilitates a conversational interface for building chatbots.

This quickstart guide shows you how to perform text generation with the Chat endpoint.

::::::steps{titleSize="h2"}
:::::step{title="Setup"}
First, install the Cohere Python SDK with the following command.

```bash
pip install -U cohere
```

Next, import the library and create a client.

::::tabs
:::tab{title="Cohere Platform"}
```python PYTHON
import cohere

co = cohere.Client(
    "COHERE_API_KEY"
)  # Get your free API key here: https://dashboard.cohere.com/api-keys
```
:::

:::tab{title="Private Deployment"}
```python PYTHON
import cohere

co = cohere.Client(
    api_key="",  # Leave this blank
    base_url="<YOUR_DEPLOYMENT_URL>",
)
```
:::

:::tab{title="Bedrock"}
```python PYTHON
import cohere

co = cohere.BedrockClient(
    aws_region="AWS_REGION",
    aws_access_key="AWS_ACCESS_KEY_ID",
    aws_secret_key="AWS_SECRET_ACCESS_KEY",
    aws_session_token="AWS_SESSION_TOKEN",
)

# Get the model name: https://docs.aws.amazon.com/bedrock/latest/userguide/models-supported.html
```
:::

:::tab{title="SageMaker"}
```python PYTHON
import cohere

co = cohere.SagemakerClient(
    aws_region="AWS_REGION",
    aws_access_key="AWS_ACCESS_KEY_ID",
    aws_secret_key="AWS_SECRET_ACCESS_KEY",
    aws_session_token="AWS_SESSION_TOKEN",
)
```
:::

:::tab{title="Azure AI"}
```python PYTHON
import cohere

co = cohere.Client(
    api_key="AZURE_API_KEY",
    base_url="AZURE_ENDPOINT",  # example: "https://cohere-command-r-plus-08-2024-xyz.eastus.models.ai.azure.com/"
)
```
:::
::::
:::::

:::::step{title="Basic Text Generation"}
To perform a basic text generation, call the Chat endpoint by passing the `message` parameter containing the user message.

::::tabs
:::tab{title="Cohere Platform"}
```python PYTHON
response = co.chat(
    model="command-a-plus-05-2026",
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)

```
:::

:::tab{title="Private Deployment"}
```python PYTHON
response = co.chat(
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?"
)

print(response.text)
```
:::

:::tab{title="Bedrock"}
```python PYTHON
response = co.chat(
    model="YOUR_MODEL_NAME",
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)

```
:::

:::tab{title="SageMaker"}
```python PYTHON
response = co.chat(
    model="YOUR_ENDPOINT_NAME",
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)
```
:::

:::tab{title="Azure AI"}
```python PYTHON
response = co.chat(
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?"
)

print(response.text)

```
:::
::::

```mdx wordWrap
"Excited to be part of the Co1t team, I'm [Your Name], a [Your Role], passionate about [Your Area of Expertise] and looking forward to contributing to the company's success."
```
:::::

:::::step{title="State Management"}
To maintain the state of a conversation, such as for building chatbots, append a sequence of `user` and `chatbot` messages to the `chat_history` list. You can also include a `preamble` parameter, which will act as a system message to set the context of the conversation.

::::tabs
:::tab{title="Cohere Platform"}
```python PYTHON
response = co.chat(
    model="command-a-plus-05-2026",
    preamble="You respond in concise sentences.",
    chat_history=[
        {"role": "user", "message": "Hello"},
        {
            "role": "chatbot",
            "message": "Hi, how can I help you today?",
        },
    ],
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)

```
:::

:::tab{title="Private Deployment"}
```python PYTHON
response = co.chat(
    preamble="You respond in concise sentences.",
    chat_history=[
        {"role": "user", "message": "Hello"},
        {
            "role": "chatbot",
            "message": "Hi, how can I help you today?",
        },
    ],
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)
```
:::

:::tab{title="Bedrock"}
```python PYTHON
response = co.chat(
    model="YOUR_MODEL_NAME",
    preamble="You respond in concise sentences.",
    chat_history=[
        {"role": "user", "message": "Hello"},
        {
            "role": "chatbot",
            "message": "Hi, how can I help you today?",
        },
    ],
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)

```
:::

:::tab{title="SageMaker"}
```python PYTHON
response = co.chat(
    model="YOUR_ENDPOINT_NAME",
    preamble="You respond in concise sentences.",
    chat_history=[
        {"role": "user", "message": "Hello"},
        {
            "role": "chatbot",
            "message": "Hi, how can I help you today?",
        },
    ],
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)
```
:::

:::tab{title="Azure AI"}
```python PYTHON
response = co.chat(
    preamble="You respond in concise sentences.",
    chat_history=[
        {"role": "user", "message": "Hello"},
        {
            "role": "chatbot",
            "message": "Hi, how can I help you today?",
        },
    ],
    message="I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates?",
)

print(response.text)

```
:::
::::

```mdx wordWrap
"Excited to join the team at Co1t, looking forward to contributing my skills and collaborating with everyone!"
```
:::::

:::::step{title="Streaming"}
To stream the generated text, call the Chat endpoint using `chat_stream` instead of `chat`. This returns a generator that yields `chunk` objects, which you can access the generated text from.

::::tabs
:::tab{title="Cohere Platform"}
```python PYTHON
message = "I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates."

response = co.chat_stream(
    model="command-a-plus-05-2026", message=message
)

for chunk in response:
    if chunk.event_type == "text-generation":
        print(chunk.text, end="")

```
:::

:::tab{title="Private Deployment"}
```python PYTHON
message = "I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates."

response = co.chat_stream(message=message)

for chunk in response:
    if chunk.event_type == "text-generation":
        print(chunk.text, end="")
```
:::

:::tab{title="Bedrock"}
```python PYTHON
message = "I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates."

response = co.chat_stream(model="YOUR_MODEL_NAME", message=message)

for chunk in response:
    if chunk.event_type == "text-generation":
        print(chunk.text, end="")

```
:::

:::tab{title="SageMaker"}
```python PYTHON
message = "I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates."

response = co.chat_stream(model="YOUR_ENDPOINT_NAME", message=message)

for chunk in response:
    if chunk.event_type == "text-generation":
        print(chunk.text, end="")
```
:::

:::tab{title="Azure AI"}
```python PYTHON
message = "I'm joining a new startup called Co1t today. Could you help me write a one-sentence introduction message to my teammates."

response = co.chat_stream(message=message)

for chunk in response:
    if chunk.event_type == "text-generation":
        print(chunk.text, end="")

```
:::
::::

```mdx wordWrap
"Excited to be part of the Co1t team, I'm [Your Name], a [Your Role/Position], looking forward to contributing my skills and collaborating with this talented group to drive innovation and success."
```
:::::
::::::

## Further Resources

- [Chat endpoint API reference](/api)
- [Documentation on text generation](/guides/text-generation-introduction-to-text-generation-at-cohere)
- [LLM University module on text generation](https://cohere.com/llmu#text-generation)

## Related pages

- [Changelog](../changelog.md)
- [Cohere](../index.md)
- [Cohere API](./cohere-api-index.md)
- [Cohere Labs](./cohere-labs-index.md)
- [Cohere Platform](./cohere-platform-index.md)
- [Cookbooks](./cookbooks-index.md)
- [Deployment Options](./deployment-options-index.md)
- [Embeddings (Vectors, Search, Retrieval)](./embeddings-vectors-search-retrieval-index.md)
- [Get Started](./get-started-index.md)
- [Going to Production](./going-to-production-index.md)

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