Here is a short preview how to use the API that I also added to the README
To start the server run (from classic directory):
python api.py
and then you can call the API using either the following commands:
To create a task run:
curl --request POST \
--url http://localhost:8000/agent/tasks \
--header 'Content-Type: application/json' \
--data '{
"input": "Find the Answer to the Ultimate Question of Life, the Universe, and Everything."
}'
You will get a response like this:
{"input":"Find the Answer to the Ultimate Question of Life, the Universe, and Everything.","task_id":"d2c4e543-ae08-4a97-9ac5-5f9a4459cb19","artifacts":[]}
Then to execute one step of the task copy the task_id you got from the previous request and run:
curl --request POST \
--url http://localhost:8000/agent/tasks/<task-id>/steps
from agent_protocol_client import AgentApi, ApiClient, TaskRequestBody
...
prompt = "Find the Answer to the Ultimate Question of Life, the Universe, and Everything."
async with ApiClient() as api_client:
# Create an instance of the API class
api_instance = AgentApi(api_client)
task_request_body = TaskRequestBody(input=prompt)
task = await api_instance.create_agent_task(
task_request_body=task_request_body
)
task_id = task.task_id
response = await api_instance.execute_agent_task_step(task_id=task_id)
...
API mode
This PR adds an API to the babyagi by using the e2b agent protocol SDK that implements the Agent Communication Protocol.
Here is a short preview how to use the API that I also added to the README
To start the server run (from
classic
directory):and then you can call the API using either the following commands:
To create a task run:
You will get a response like this:
Then to execute one step of the task copy the
task_id
you got from the previous request and run:or you can use Python client library: