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

# Say

> Add a message to a thread and get an agent's response

The `say` function adds a user message to a thread and gets an agent's response. It transforms `str → str`, making it easy to:

* Store messages in a thread ("My name is Alice" → thread.messages += \[user\_msg, agent\_msg])
* Get contextual responses ("What's my name?" → "Your name is Alice")
* Guide agent behavior ("You are a chef..." → "Let me suggest a recipe...")

For complex conversations, consider creating a custom task. The `say` function is a convenient wrapper around Marvin's task system - see [Tasks](/concepts/tasks) for more details.

## Usage

Add a message and get a response:

```python theme={null}
import marvin

# Create a thread to store the conversation
thread = marvin.Thread()

# Add a message and get a response
response = marvin.say(
    "My name is Alice",
    thread=thread  # Messages are stored in the thread
)
print(response)

# The agent can now reference previous messages
response = marvin.say(
    "What's my name?",
    thread=thread
)
print(response)
```

```python theme={null}
"Hello Alice! Nice to meet you."
"Your name is Alice."
```

## Parameters

* `message`: The message to add to the thread
* `instructions`: Optional guidance for the agent's responses
* `agent`: Optional custom agent to use
* `thread`: Optional thread to store conversation history
* `context`: Optional additional context

## Async Support

The function is also available in an async version:

```python theme={null}
import marvin
import asyncio

async def main():
    thread = marvin.Thread()
    response = await marvin.say_async(
        "What's the weather like?",
        thread=thread
    )
    print(response)

asyncio.run(main())
```

## Examples

### With Instructions

Guide the agent's responses:

```python theme={null}
import marvin

thread = marvin.Thread()
response = marvin.say(
    "What should I cook for dinner?",
    instructions="Respond as a professional chef",
    thread=thread
)
print(response)
```

```python theme={null}
"I'd recommend a pan-seared salmon with lemon butter sauce. Start by patting the salmon dry and seasoning with salt and pepper..."
```

### With Custom Agent

Use a specialized agent:

```python theme={null}
import marvin

thread = marvin.Thread()
tech_agent = marvin.Agent(
    name="TechSupport",
    instructions="You are a helpful tech support agent"
)

response = marvin.say(
    "My computer won't start",
    agent=tech_agent,
    thread=thread
)
print(response)
```

```python theme={null}
"Let's troubleshoot this step by step. First, check if your computer is properly plugged in and the power button lights up..."
```

### With Memory

Remember previous interactions:

```python theme={null}
import marvin

thread = marvin.Thread()
agent = marvin.Agent(
    memories=[
        marvin.Memory(
            key="user_preferences",
            instructions="Remember user preferences"
        )
    ]
)

# Store preference in memory
response = marvin.say(
    "I prefer vegetarian food",
    agent=agent,
    thread=thread
)
print(response)

# Agent can access both memory and thread history
response = marvin.say(
    "What should I cook?",
    agent=agent,
    thread=thread
)
print(response)
```

```python theme={null}
"I'll remember your preference for vegetarian food."
"Given your vegetarian preference, I'd suggest a delicious mushroom risotto..."
```