Terjemahan disediakan oleh mesin penerjemah. Jika konten terjemahan yang diberikan bertentangan dengan versi bahasa Inggris aslinya, utamakan versi bahasa Inggris.
# Menangani permintaan alat penggunaan komputer dari agen dalam percakapan
Saat agen Anda meminta alat, respons terhadap operasi InvokeAgent API Anda menyertakan `returnControl` payload yang menyertakan alat yang akan digunakan dan tindakan alat di InvocationInputs. Untuk informasi selengkapnya tentang kontrol pengembalian ke pengembang agen, lihat[Kembalikan kontrol ke pengembang agen dengan mengirimkan informasi yang diperoleh sebagai tanggapan InvokeAgent](agents-returncontrol.md).
**Topics**
+ [Contoh kontrol pengembalian](#agent-computer-use-tool-request-format)
+ [Contoh kode untuk mengurai permintaan alat](#agent-computer-use-implementation-example)
## Contoh kontrol pengembalian
Berikut ini adalah contoh `returnControl` payload dengan permintaan untuk menggunakan `ANTHROPIC.Computer` alat dengan `screenshot` tindakan.
```
{
"returnControl": {
"invocationId": "invocationIdExample",
"invocationInputs": [{
"functionInvocationInput": {
"actionGroup": "my_computer",
"actionInvocationType": "RESULT",
"agentId": "agentIdExample",
"function": "computer",
"parameters": [{
"name": "action",
"type": "string",
"value": "screenshot"
}]
}
}]
}
}
```
## Contoh kode untuk mengurai permintaan alat
Kode berikut menunjukkan cara mengekstrak pilihan alat penggunaan komputer dalam InvokeAgent respons, memetakannya ke implementasi alat tiruan untuk alat yang berbeda, dan kemudian mengirim hasil penggunaan alat dalam permintaan berikutnya InvokeAgent .
+ `manage_computer_interaction`Fungsi ini menjalankan loop di mana ia memanggil operasi InvocationAgent API dan mem-parsing respons sampai tidak ada tugas yang harus diselesaikan. Ketika mem-parsing respons, ia mengekstrak alat apa pun untuk digunakan dari `returnControl` muatan dan meneruskan fungsi. `handle_computer_action`
+ `handle_computer_action`Memetakan nama fungsi untuk mengolok-olok implementasi untuk empat tindakan. Misalnya implementasi alat, lihat [computer-use-demo](https://github.com/anthropics/anthropic-quickstarts/tree/main/computer-use-demo/computer_use_demo/) di repositori. Anthropic GitHub
Untuk informasi selengkapnya tentang alat penggunaan komputer, termasuk contoh implementasi dan deskripsi alat, lihat [Penggunaan komputer (beta)](https://docs.anthropic.com/en/docs/agents-and-tools/computer-use) dalam Anthropic dokumentasi.
```
import boto3
from botocore.exceptions import ClientError
import json
def handle_computer_action(action_params):
"""
Maps computer actions, like taking screenshots and moving the mouse to mock implementations and returns
the result.
Args:
action_params (dict): Dictionary containing the action parameters
Keys:
- action (str, required): The type of action to perform (for example 'screenshot' or 'mouse_move')
- coordinate (str, optional): JSON string containing [x,y] coordinates for mouse_move
Returns:
dict: Response containing the action result.
"""
action = action_params.get('action')
if action == 'screenshot':
# Mock screenshot response
with open("mock_screenshot.png", 'rb') as image_file:
image_bytes = image_file.read()
return {
"IMAGES": {
"images": [
{
"format": "png",
"source": {
"bytes": image_bytes
},
}
]
}
}
elif action == 'mouse_move':
# Mock mouse movement
coordinate = json.loads(action_params.get('coordinate', '[0, 0]'))
return {
"TEXT": {
"body": f"Mouse moved to coordinates {coordinate}"
}
}
elif action == 'left_click':
# Mock mouse left click
return {
"TEXT": {
"body": f"Mouse left clicked"
}
}
elif action == 'right_click':
# Mock mouse right click
return {
"TEXT": {
"body": f"Mouse right clicked"
}
}
### handle additional actions here
def manage_computer_interaction(bedrock_agent_runtime_client, agent_id, alias_id):
"""
Manages interaction between an Amazon Bedrock agent and computer use functions.
Args:
bedrock_agent_runtime_client: Boto3 client for Bedrock agent runtime
agent_id (str): The ID of the agent
alias_id (str): The Alias ID of the agent
The function:
- Initiates a session with initial prompt
- Makes agent requests with appropriate parameters
- Processes response chunks and return control events
- Handles computer actions via handle_computer_action()
- Continues interaction until task completion
"""
session_id = "session123"
initial_prompt = "Open a browser and go to a website"
computer_use_results = None
current_prompt = {{initial_prompt}}
while True:
# Make agent request with appropriate parameters
invoke_params = {
"agentId": agent_id,
"sessionId": session_id,
"inputText": current_prompt,
"agentAliasId": alias_id,
}
# Include session state if we have results from previous iteration
if computer_use_results:
invoke_params["sessionState"] = computer_use_results["sessionState"]
try:
response = bedrock_agent_runtime_client.invoke_agent(**invoke_params)
except ClientError as e:
print(f"Error: {e}")
has_return_control = False
# Process the response
for event in response.get('completion'):
if 'chunk' in event:
chunk_content = event['chunk'].get('bytes', b'').decode('utf-8')
if chunk_content:
print("\nAgent:", chunk_content)
if 'returnControl' in event:
has_return_control = True
invocationId = event["returnControl"]["invocationId"]
if "invocationInputs" in event["returnControl"]:
for invocationInput in event["returnControl"]["invocationInputs"]:
func_input = invocationInput["functionInvocationInput"]
# Extract action parameters
params = {p['name']: p['value'] for p in func_input['parameters']}
# Handle computer action and get result
action_result = handle_computer_action(params)
# Print action result for testing
print("\nExecuting function:", func_input['function'])
print("Parameters:", params)
# Prepare the session state for the next request
computer_use_results = {
"sessionState": {
"invocationId": invocationId,
"returnControlInvocationResults": [{
"functionResult": {
"actionGroup": func_input['actionGroup'],
"responseState": "REPROMPT",
"agentId": func_input['agentId'],
"function": func_input['function'],
"responseBody": action_result
}
}]
}
}
# If there's no return control event, the task is complete
if not has_return_control:
print("\nTask completed!")
break
# Use empty string as prompt for subsequent iterations
current_prompt = ""
def main():
bedrock_agent_runtime_client = boto3.client(service_name="bedrock-agent-runtime",
region_name="{{REGION}}"
)
agent_id = "{{AGENT_ID}}"
alias_id = "{{ALIAS_ID}}"
manage_computer_interaction(bedrock_agent_runtime_client, agent_id, alias_id)
if __name__ == "__main__":
main()
```
Output harus serupa dengan yang berikut ini:
```
Executing function: computer
Parameters: {'action': 'screenshot'}
Executing function: computer
Parameters: {'coordinate': '[467, 842]', 'action': 'mouse_move'}
Executing function: computer
Parameters: {'action': 'left_click'}
Agent: I've opened Firefox browser. Which website would you like to visit?
Task completed!
```