Conversations

1
from scrapybara import Scrapybara
2
from scrapybara.anthropic import Anthropic
3
from scrapybara.prompts import UBUNTU_SYSTEM_PROMPT
4
from scrapybara.tools import BashTool, ComputerTool, EditTool
5
6
client = Scrapybara()
7
instance = client.start_ubuntu()
8
9
# Initial conversation
10
response = client.act(
11
    model=Anthropic(),
12
    tools=[
13
        BashTool(instance),
14
        ComputerTool(instance),
15
        EditTool(instance),
16
    ],
17
    on_step=lambda step: print(step.text),
18
    system=UBUNTU_SYSTEM_PROMPT,
19
    prompt="Create a file called hello.py that prints 'Hello, World!'",
20
)
21
22
print('--------------------------------')
23
24
# Continue the conversation with the previous messages
25
follow_up_response = client.act(
26
    model=Anthropic(),
27
    tools=[
28
        BashTool(instance),
29
        ComputerTool(instance),
30
        EditTool(instance),
31
    ],
32
    on_step=lambda step: print(step.text),
33
    system=UBUNTU_SYSTEM_PROMPT,
34
    messages=response.messages + [
35
        {
36
            "role": "user",
37
            "content": [
38
                {
39
                    "type": "text",
40
                    "text": "Now modify the file to accept a name as a command line argument and print 'Hello, {name}!'"
41
                }
42
            ]
43
        }
44
    ]
45
)
46
47
instance.stop()

1
from scrapybara import Scrapybara
2
from scrapybara.anthropic import Anthropic
3
from scrapybara.prompts import UBUNTU_SYSTEM_PROMPT
4
5
client = Scrapybara()
6
instance = client.start_ubuntu()
7
8
# Take a screenshot
9
screenshot = instance.screenshot().base_64_image
10
11
# Send the screenshot to the agent
12
messages = [
13
    {
14
        "role": "user",
15
        "content": [
16
            {
17
                "type": "text",
18
                "text": "What do you see in this screenshot? Describe the desktop environment."
19
            },
20
            {
21
                "type": "image",
22
                "image": 'data:image/png;base64,' + screenshot,
23
                "mime_type": "image/png"
24
            }
25
        ]
26
    }
27
]
28
29
response = client.act(
30
    model=Anthropic(),
31
    system=UBUNTU_SYSTEM_PROMPT,
32
    messages=messages,
33
)
34
35
print(response.text)
36
instance.stop()

1
from scrapybara import Scrapybara
2
from scrapybara.anthropic import Anthropic
3
from scrapybara.prompts import UBUNTU_SYSTEM_PROMPT
4
from scrapybara.tools import BashTool
5
6
client = Scrapybara()
7
instance = client.start_ubuntu()
8
9
response = client.act(
10
    model=Anthropic(),
11
    tools=[BashTool(instance)],
12
    system=UBUNTU_SYSTEM_PROMPT,
13
    prompt="Show me the current directory structure",
14
)
15
16
# Analyze the conversation steps
17
for message in response.messages:
18
    if message.role == "assistant":
19
        for part in message.content:
20
            if part.type == "tool-call":
21
                print(f"Tool called: {part.tool_name}")
22
                print(f"Arguments: {part.args}")
23
    elif message.role == "tool":
24
        for part in message.content:
25
            print(f"Tool result from {part.tool_name}: {part.result}")
26
27
instance.stop()

1
from scrapybara import Scrapybara
2
from scrapybara.anthropic import Anthropic
3
from scrapybara.prompts import UBUNTU_SYSTEM_PROMPT
4
from scrapybara.tools import BashTool, ComputerTool
5
6
client = Scrapybara()
7
instance = client.start_ubuntu()
8
9
response = client.act(
10
    model=Anthropic(name="claude-3-7-sonnet-20250219-thinking"),
11
    tools=[
12
        BashTool(instance),
13
        ComputerTool(instance),
14
    ],
15
    system=UBUNTU_SYSTEM_PROMPT,
16
    prompt="Open Firefox and navigate to scrapybara.com",
17
)
18
19
# Extract reasoning parts from assistant messages
20
for message in response.messages:
21
    if message.role == "assistant":
22
        for part in message.content:
23
            if part.type == "reasoning":
24
                print("Agent reasoning:")
25
                print(part.reasoning)
26
27
# Or access reasoning directly from steps
28
for step in response.steps:
29
    if step.reasoning_parts:
30
        print(f"Step reasoning: {step.reasoning_parts}")
31
32
instance.stop()

1
from scrapybara import Scrapybara
2
from scrapybara.anthropic import Anthropic
3
from scrapybara.prompts import UBUNTU_SYSTEM_PROMPT
4
from scrapybara.tools import BashTool, ComputerTool, EditTool
5
6
def agent_repl():
7
    client = Scrapybara()
8
    instance = client.start_ubuntu()
9
    tools = [BashTool(instance), ComputerTool(instance), EditTool(instance)]
10
    messages = []
11
    
12
    print("Scrapybara REPL started. Type 'exit' to quit")
13
    
14
    try:
15
        while True:
16
            # Get user input
17
            user_input = input("\n> ")
18
            
19
            # Exit command
20
            if user_input.lower() == 'exit':
21
                break
22
                
23
            # Regular text command
24
            messages.append({
25
                "role": "user",
26
                "content": [{"type": "text", "text": user_input}]
27
            })
28
            
29
            # Process with agent
30
            print("Processing...")
31
            response = client.act(
32
                model=Anthropic(),
33
                tools=tools,
34
                system=UBUNTU_SYSTEM_PROMPT,
35
                on_step=lambda step: print(step.text),
36
                messages=messages
37
            )
38
            
39
            # Update conversation history
40
            messages = response.messages
41
    finally:
42
        instance.stop()
43
        print("Session ended.")
44
45
if __name__ == "__main__":
46
    agent_repl()