Run and Run Step API
Last updated
Last updated
Runs are processes that execute the assistant’s logic within a thread, allowing it to process messages, generate responses, and call external tools if needed. Runs go through different statuses, such as queued
, in_progress
, and completed
, and trigger events based on their progress, including tool calls and message updates.
This page provides API schemas for the following methods:
After each schema, you'll find a short example demonstrating how to correctly call the described method in code using the OpenAI SDK.
Note that the method names in the API schema and the SDK often differ. Accordingly, when calling these methods via the REST API, you should use the names from the API schema, while for calls through the OpenAI SDK, use the names from the examples.
from openai import OpenAI
client = OpenAI()
run = client.beta.threads.runs.create(
thread_id="thread_abc123",
assistant_id="asst_abc123"
)
print(run)
from openai import OpenAI
client = OpenAI()
run = client.beta.threads.create_and_run(
assistant_id="asst_abc123",
thread={
"messages": [
{"role": "user", "content": "Explain deep learning to a 5 year old."}
]
}
)
print(run)
from openai import OpenAI
client = OpenAI()
runs = client.beta.threads.runs.list(
"thread_abc123"
)
print(runs)
from openai import OpenAI
client = OpenAI()
run = client.beta.threads.runs.retrieve(
thread_id="thread_abc123",
run_id="run_abc123"
)
print(run)
from openai import OpenAI
client = OpenAI()
run = client.beta.threads.runs.update(
thread_id="thread_abc123",
run_id="run_abc123",
metadata={"user_id": "user_abc123"},
)
print(run)
from openai import OpenAI
client = OpenAI()
run = client.beta.threads.runs.submit_tool_outputs(
thread_id="thread_123",
run_id="run_123",
tool_outputs=[
{
"tool_call_id": "call_001",
"output": "70 degrees and sunny."
}
]
)
print(run)
from openai import OpenAI
client = OpenAI()
run = client.beta.threads.runs.cancel(
thread_id="thread_abc123",
run_id="run_abc123"
)
print(run)
from openai import OpenAI
client = OpenAI()
run_steps = client.beta.threads.runs.steps.list(
thread_id="thread_abc123",
run_id="run_abc123"
)
print(run_steps)
from openai import OpenAI
client = OpenAI()
run_step = client.beta.threads.runs.steps.retrieve(
thread_id="thread_abc123",
run_id="run_abc123",
step_id="step_abc123"
)
print(run_step)
https://api.apilaplas.com/threads/{threadId}/runs
https://api.apilaplas.com/threads/runs
https://api.apilaplas.com/threads/{threadId}/runs
https://api.apilaplas.com/threads/{threadId}/runs/{runId}
https://api.apilaplas.com/threads/{threadId}/runs/{runId}
https://api.apilaplas.com/threads/{threadId}/runs/{runId}/submit_tool_outputs
https://api.apilaplas.com/threads/{threadId}/runs/{runId}/cancel
https://api.apilaplas.com/threads/{threadId}/runs/{runId}/steps
https://api.apilaplas.com/threads/{threadId}/runs/{runId}/steps/{stepId}