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---
title: Arguments
---
<Card
title="New: Streaming responses in Python"
icon="arrow-up-right"
href="/usage/python/streaming-response"
>
Learn how to build Open Interpreter into your application.
</Card>
#### `messages`
This property holds a list of `messages` between the user and the interpreter.
You can use it to restore a conversation:
```python
interpreter.chat("Hi! Can you print hello world?")
print(interpreter.messages)
# This would output:
[
{
"role": "user",
"message": "Hi! Can you print hello world?"
},
{
"role": "assistant",
"message": "Sure!"
}
{
"role": "assistant",
"language": "python",
"code": "print('Hello, World!')",
"output": "Hello, World!"
}
]
```
You can use this to restore `interpreter` to a previous conversation.
```python
interpreter.messages = messages # A list that resembles the one above
```
---
#### `offline`
<Info>This replaced `interpreter.local` in the New Computer Update (`0.2.0`).</Info>
This boolean flag determines whether to enable or disable some offline features like [open procedures](https://open-procedures.replit.app/).
```python
interpreter.offline = True # Check for updates, use procedures
interpreter.offline = False # Don't check for updates, don't use procedures
```
Use this in conjunction with the `model` parameter to set your language model.
---
#### `auto_run`
Setting this flag to `True` allows Open Interpreter to automatically run the generated code without user confirmation.
```python
interpreter.auto_run = True # Don't require user confirmation
interpreter.auto_run = False # Require user confirmation (default)
```
---
#### `verbose`
Use this boolean flag to toggle verbose mode on or off. Verbose mode will print information at every step to help diagnose problems.
```python
interpreter.verbose = True # Turns on verbose mode
interpreter.verbose = False # Turns off verbose mode
```
---
#### `max_output`
This property sets the maximum number of tokens for the output response.
```python
interpreter.max_output = 2000
```
---
#### `conversation_history`
A boolean flag to indicate if the conversation history should be stored or not.
```python
interpreter.conversation_history = True # To store history
interpreter.conversation_history = False # To not store history
```
---
#### `conversation_filename`
This property sets the filename where the conversation history will be stored.
```python
interpreter.conversation_filename = "my_conversation.json"
```
---
#### `conversation_history_path`
You can set the path where the conversation history will be stored.
```python
import os
interpreter.conversation_history_path = os.path.join("my_folder", "conversations")
```
---
#### `model`
Specifies the language model to be used.
```python
interpreter.llm.model = "gpt-3.5-turbo"
```
---
#### `temperature`
Sets the randomness level of the model's output.
```python
interpreter.llm.temperature = 0.7
```
---
#### `system_message`
This stores the model's system message as a string. Explore or modify it:
```python
interpreter.system_message += "\nRun all shell commands with -y."
```
---
#### `context_window`
This manually sets the context window size in tokens.
We try to guess the right context window size for you model, but you can override it with this parameter.
```python
interpreter.llm.context_window = 16000
```
---
#### `max_tokens`
Sets the maximum number of tokens the model can generate in a single response.
```python
interpreter.llm.max_tokens = 100
```
---
#### `api_base`
If you are using a custom API, you can specify its base URL here.
```python
interpreter.llm.api_base = "https://api.example.com"
```
---
#### `api_key`
Set your API key for authentication.
```python
interpreter.llm.api_key = "your_api_key_here"
```
---
#### `max_budget`
This property sets the maximum budget limit for the session in USD.
```python
interpreter.max_budget = 0.01 # 1 cent
```
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