mirror of
https://github.com/aljazceru/Auto-GPT.git
synced 2025-12-17 05:54:26 +01:00
110 lines
3.7 KiB
Python
110 lines
3.7 KiB
Python
import json
|
|
import os
|
|
import time
|
|
from typing import Any, Dict, Optional
|
|
|
|
from agbenchmark.__main__ import TEMP_FOLDER_ABS_PATH, UPDATES_JSON_PATH
|
|
from agbenchmark.agent_interface import get_list_of_file_paths
|
|
from agbenchmark.agent_protocol_client import (
|
|
AgentApi,
|
|
ApiClient,
|
|
Configuration,
|
|
TaskRequestBody,
|
|
)
|
|
from agbenchmark.agent_protocol_client.models.step import Step
|
|
from agbenchmark.utils.data_types import ChallengeData
|
|
|
|
|
|
async def run_api_agent(
|
|
task: ChallengeData, config: Dict[str, Any], artifacts_location: str, timeout: int
|
|
) -> None:
|
|
host_value = None
|
|
|
|
configuration = Configuration(host=config["AgentBenchmarkConfig"].host + "/ap/v1")
|
|
async with ApiClient(configuration) as api_client:
|
|
api_instance = AgentApi(api_client)
|
|
task_request_body = TaskRequestBody(input=task.task)
|
|
|
|
start_time = time.time()
|
|
response = await api_instance.create_agent_task(
|
|
task_request_body=task_request_body
|
|
)
|
|
task_id = response.task_id
|
|
|
|
await upload_artifacts(
|
|
api_instance, artifacts_location, task_id, "artifacts_in"
|
|
)
|
|
|
|
i = 1
|
|
steps_remaining = True
|
|
while steps_remaining:
|
|
# Read the existing JSON data from the file
|
|
|
|
step = await api_instance.execute_agent_task_step(task_id=task_id)
|
|
await append_updates_file(step)
|
|
|
|
print(f"[{task.name}] - step {step.name} ({i}. request)")
|
|
i += 1
|
|
|
|
if time.time() - start_time > timeout:
|
|
raise TimeoutError("Time limit exceeded")
|
|
if not step or step.is_last:
|
|
steps_remaining = False
|
|
# if we're calling a mock agent, we "cheat" and give the correct artifacts to pass the tests
|
|
if os.getenv("IS_MOCK"):
|
|
await upload_artifacts(
|
|
api_instance, artifacts_location, task_id, "artifacts_out"
|
|
)
|
|
|
|
await copy_agent_artifacts_into_temp_folder(api_instance, task_id)
|
|
|
|
|
|
async def copy_agent_artifacts_into_temp_folder(api_instance, task_id):
|
|
artifacts = await api_instance.list_agent_task_artifacts(task_id=task_id)
|
|
for artifact in artifacts.artifacts:
|
|
# current absolute path of the directory of the file
|
|
directory_location = TEMP_FOLDER_ABS_PATH
|
|
if artifact.relative_path:
|
|
directory_location = directory_location / artifact.relative_path
|
|
|
|
with open(directory_location / artifact.file_name, "wb") as f:
|
|
content = await api_instance.download_agent_task_artifact(
|
|
task_id=task_id, artifact_id=artifact.artifact_id
|
|
)
|
|
|
|
f.write(content)
|
|
|
|
|
|
async def append_updates_file(step: Step):
|
|
with open(UPDATES_JSON_PATH, "r") as file:
|
|
existing_data = json.load(file)
|
|
# Append the new update to the existing array
|
|
new_update = create_update_json(step)
|
|
|
|
existing_data.append(new_update)
|
|
# Write the updated array back to the file
|
|
with open(UPDATES_JSON_PATH, "w") as file:
|
|
file.write(json.dumps(existing_data, indent=2))
|
|
|
|
|
|
async def upload_artifacts(
|
|
api_instance: ApiClient, artifacts_location: str, task_id: str, type: str
|
|
) -> None:
|
|
for file_path in get_list_of_file_paths(artifacts_location, type):
|
|
relative_path: Optional[str] = "/".join(
|
|
file_path.split(f"{type}/", 1)[-1].split("/")[:-1]
|
|
)
|
|
if not relative_path:
|
|
relative_path = None
|
|
|
|
await api_instance.upload_agent_task_artifacts(
|
|
task_id=task_id, file=file_path, relative_path=relative_path
|
|
)
|
|
|
|
|
|
def create_update_json(step: Step):
|
|
now = int(time.time())
|
|
content = {"content": step.to_dict(), "timestamp": now}
|
|
|
|
return content
|