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Assistants API (Preview) runs reference

  • Artikkeli

Note

  • File search can ingest up to 10,000 files per assistant - 500 times more than before. It is fast, supports parallel queries through multi-threaded searches, and features enhanced reranking and query rewriting.
    • Vector store is a new object in the API. Once a file is added to a vector store, it's automatically parsed, chunked, and embedded, made ready to be searched. Vector stores can be used across assistants and threads, simplifying file management and billing.
  • We've added support for the tool_choice parameter which can be used to force the use of a specific tool (like file search, code interpreter, or a function) in a particular run.

This article provides reference documentation for Python and REST for the new Assistants API (Preview). More in-depth step-by-step guidance is provided in the getting started guide.

Create run

POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs?api-version=2024-08-01-preview

Create a run.

Path parameter

Parameter Type Required Description
thread_id string Required The ID of the thread to create a message for.

Request body

Name Type Required Description
assistant_id string Required The ID of the assistant to use to execute this run.
model string or null Optional The model deployment name to be used to execute this run. If a value is provided here, it will override the model deployment name associated with the assistant. If not, the model deployment name associated with the assistant will be used.
instructions string or null Optional Overrides the instructions of the assistant. This is useful for modifying the behavior on a per-run basis.
additional_instructions string Optional Appends additional instructions at the end of the instructions for the run. This is useful for modifying the behavior on a per-run basis without overriding other instructions.
additional_messages array Optional Adds additional messages to the thread before creating the run.
tools array or null Optional Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.
metadata map Optional Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.
temperature number Optional What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. Default is 1.
top_p number Optional An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both. Default is 1.
stream boolean optional If true, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a data: [DONE] message.
max_prompt_tokens integer optional The maximum number of completion tokens that might be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete.
max_completion_tokens integer optional The maximum number of completion tokens that might be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete.
truncation_strategy truncationObject optional Controls for how a thread will be truncated prior to the run. Use this to control the initial context window of the run.
tool_choice string or object optional Controls which (if any) tool is called by the model. A none value means the model won't call any tools and instead generates a message. auto is the default value and means the model can pick between generating a message or calling a tool. Specifying a particular tool like {"type": "file_search"} or {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
response_format string or object optional Specifies the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.
Setting to { "type": "json_object" } enables JSON mode, which guarantees the message the model generates is valid JSON.
Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model might generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content might be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

Returns

A run object.

Example create run request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run = client.beta.threads.runs.create(
  thread_id="thread_abc123",
  assistant_id="asst_abc123"
)
print(run)

Create thread and run

POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/runs?api-version=2024-08-01-preview

Create a thread and run it in a single request.

Request Body

Name Type Required Description
assistant_id string Required The ID of the assistant to use to execute this run.
thread object Optional
model string or null Optional The ID of the Model deployment name to be used to execute this run. If a value is provided here, it will override the model deployment name associated with the assistant. If not, the model deployment name associated with the assistant will be used.
instructions string or null Optional Override the default system message of the assistant. This is useful for modifying the behavior on a per-run basis.
tools array or null Optional Override the tools the assistant can use for this run. This is useful for modifying the behavior on a per-run basis.
metadata map Optional Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.
temperature number Optional What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. Default is 1.
top_p number Optional An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both. Default is 1.
stream boolean optional If true, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a data: [DONE] message.
max_prompt_tokens integer optional The maximum number of completion tokens that might be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete.
max_completion_tokens integer optional The maximum number of completion tokens that might be used over the course of the run. The run will make a best effort to use only the number of completion tokens specified, across multiple turns of the run. If the run exceeds the number of completion tokens specified, the run will end with status incomplete.
truncation_strategy truncationObject optional Controls for how a thread will be truncated prior to the run. Use this to control the initial context window of the run.
tool_choice string or object optional Controls which (if any) tool is called by the model. A none value means the model won't call any tools and instead generates a message. auto is the default value and means the model can pick between generating a message or calling a tool. Specifying a particular tool like {"type": "file_search"} or {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
response_format string or object optional Specifies the format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.
Setting to { "type": "json_object" } enables JSON mode, which guarantees the message the model generates is valid JSON.
Important: when using JSON mode, you must also instruct the model to produce JSON yourself via a system or user message. Without this, the model might generate an unending stream of whitespace until the generation reaches the token limit, resulting in a long-running and seemingly "stuck" request. Also note that the message content might be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.

Returns

A run object.

Example create thread and run request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run = client.beta.threads.create_and_run(
  assistant_id="asst_abc123",
  thread={
    "messages": [
      {"role": "user", "content": "Explain deep learning to a 5 year old."}
    ]
  }
)

List runs

GET https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs?api-version=2024-08-01-preview

Returns a list of runs belonging to a thread.

Path parameter

Parameter Type Required Description
thread_id string Required The ID of the thread that the run belongs to.

Query Parameters

Name Type Required Description
limit integer Optional - Defaults to 20 A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.
order string Optional - Defaults to desc Sort order by the created_at timestamp of the objects. asc for ascending order and desc for descending order.
after string Optional A cursor for use in pagination. after is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.
before string Optional A cursor for use in pagination. before is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.

Returns

A list of run objects.

Example list runs request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

runs = client.beta.threads.runs.list(
  "thread_abc123"
)
print(runs)

List run steps

GET https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs/{run_id}/steps?api-version=2024-08-01-preview

Returns a list of steps belonging to a run.

Path parameters

Parameter Type Required Description
thread_id string Required The ID of the thread that the run belongs to.
run_id string Required The ID of the run associated with the run steps to be queried.

Query parameters

Name Type Required Description
limit integer Optional - Defaults to 20 A limit on the number of objects to be returned. Limit can range between 1 and 100, and the default is 20.
order string Optional - Defaults to desc Sort order by the created_at timestamp of the objects. asc for ascending order and desc for descending order.
after string Optional A cursor for use in pagination. after is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include after=obj_foo in order to fetch the next page of the list.
before string Optional A cursor for use in pagination. before is an object ID that defines your place in the list. For instance, if you make a list request and receive 100 objects, ending with obj_foo, your subsequent call can include before=obj_foo in order to fetch the previous page of the list.

Returns

A list of run step objects.

Example list run steps request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run_steps = client.beta.threads.runs.steps.list(
    thread_id="thread_abc123",
    run_id="run_abc123"
)
print(run_steps)

Retrieve run

from openai import OpenAI
client = OpenAI()

run = client.beta.threads.runs.retrieve(
  thread_id="thread_abc123",
  run_id="run_abc123"
)

print(run)

Retrieves a run.

Path parameters

Parameter Type Required Description
thread_id string Required The ID of the thread that was run.
run_id string Required The ID of the run to retrieve.

Returns

The run object matching the specified run ID.

Example list run steps request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run = client.beta.threads.runs.retrieve(
  thread_id="thread_abc123",
  run_id="run_abc123"
)
print(run)

Retrieve run step

GET https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs/{run_id}/steps/{step_id}?api-version=2024-08-01-preview

Retrieves a run step.

Path Parameters

Parameter Type Required Description
thread_id string Required The ID of the thread to which the run and run step belongs.
run_id string Required The ID of the run to which the run step belongs.
step_id string Required The ID of the run step to retrieve.

Returns

The run step object matching the specified ID.

Example retrieve run steps request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run_step = client.beta.threads.runs.steps.retrieve(
    thread_id="thread_abc123",
    run_id="run_abc123",
    step_id="step_abc123"
)
print(run_step)

Modify run

POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs/{run_id}?api-version=2024-08-01-preview

Modifies a run.

Path Parameters

Parameter Type Required Description
thread_id string Required The ID of the thread that was run.
run_id string Required The ID of the run to modify.

Request body

Name Type Required Description
metadata map Optional Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.

Returns

The modified run object matching the specified ID.

Example modify run request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run = client.beta.threads.runs.update(
  thread_id="thread_abc123",
  run_id="run_abc123",
  metadata={"user_id": "user_abc123"},
)
print(run)

Submit tool outputs to run

POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs/{run_id}/submit_tool_outputs?api-version=2024-08-01-preview

When a run has the status: "requires_action" and required_action.type is submit_tool_outputs, this endpoint can be used to submit the outputs from the tool calls once they're all completed. All outputs must be submitted in a single request.

Path Parameters

Parameter Type Required Description
thread_id string Required The ID of the thread to which this run belongs.
run_id string Required The ID of the run that requires the tool output submission.

Request body

Name Type Required Description
tool_outputs array Required A list of tools for which the outputs are being submitted.
stream boolean Optional If true, returns a stream of events that happen during the Run as server-sent events, terminating when the Run enters a terminal state with a data: [DONE] message.

Returns

The modified run object matching the specified ID.

Example submit tool outputs to run request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run = client.beta.threads.runs.submit_tool_outputs(
  thread_id="thread_abc123",
  run_id="run_abc123",
  tool_outputs=[
    {
      "tool_call_id": "call_abc123",
      "output": "28C"
    }
  ]
)
print(run)

Cancel a run

POST https://YOUR_RESOURCE_NAME.openai.azure.com/openai/threads/{thread_id}/runs/{run_id}/cancel?api-version=2024-08-01-preview

Cancels a run that is in_progress.

Path Parameters

Parameter Type Required Description
thread_id string Required The ID of the thread to which this run belongs.
run_id string Required The ID of the run to cancel.

Returns

The modified run object matching the specified ID.

Example submit tool outputs to run request

from openai import AzureOpenAI
    
client = AzureOpenAI(
    api_key=os.getenv("AZURE_OPENAI_API_KEY"),  
    api_version="2024-08-01-preview",
    azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT")
    )

run = client.beta.threads.runs.cancel(
  thread_id="thread_abc123",
  run_id="run_abc123"
)
print(run)

Run object

Represents an execution run on a thread.

Name Type Description
id string The identifier, which can be referenced in API endpoints.
object string The object type, which is always thread.run.
created_at integer The Unix timestamp (in seconds) for when the run was created.
thread_id string The ID of the thread that was executed on as a part of this run.
assistant_id string The ID of the assistant used for execution of this run.
status string The status of the run, which can be either queued, in_progress, requires_action, cancelling, cancelled, failed, completed, or expired.
required_action object or null Details on the action required to continue the run. Will be null if no action is required.
last_error object or null The last error associated with this run. Will be null if there are no errors.
expires_at integer The Unix timestamp (in seconds) for when the run will expire.
started_at integer or null The Unix timestamp (in seconds) for when the run was started.
cancelled_at integer or null The Unix timestamp (in seconds) for when the run was canceled.
failed_at integer or null The Unix timestamp (in seconds) for when the run failed.
completed_at integer or null The Unix timestamp (in seconds) for when the run was completed.
model string The model deployment name that the assistant used for this run.
instructions string The instructions that the assistant used for this run.
tools array The list of tools that the assistant used for this run.
file_ids array The list of File IDs the assistant used for this run.
metadata map Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.
tool_choice string or object Controls which (if any) tool is called by the model. none means the model won't call any tools and instead generates a message. auto is the default value and means the model can pick between generating a message or calling a tool. Specifying a particular tool like {"type": "file_search"} or {"type": "function", "function": {"name": "my_function"}} forces the model to call that tool.
max_prompt_tokens integer or null The maximum number of prompt tokens specified to have been used over the course of the run.
max_completion_tokens integer or null The maximum number of completion tokens specified to have been used over the course of the run.
usage object or null Usage statistics related to the run. This value will be null if the run is not in a terminal state (for example in_progress, queued).
truncation_strategy object Controls for how a thread will be truncated prior to the run.
response_format string The format that the model must output. Compatible with GPT-4 Turbo and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.
tool_choice string Controls which (if any) tool is called by the model. none means the model won't call any tools and instead generates a message. auto is the default value and means the model can pick between generating a message or calling a tool.

Run step object

Represent a step in execution of a run.

Name Type Description
id string The identifier of the run step, which can be referenced in API endpoints.
object string The object type, which is always thread.run.step.
created_at integer The Unix timestamp (in seconds) for when the run step was created.
assistant_id string The ID of the assistant associated with the run step.
thread_id string The ID of the thread that was run.
run_id string The ID of the run that this run step is a part of.
type string The type of run step, which can be either message_creation or tool_calls.
status string The status of the run step, which can be either in_progress, cancelled, failed, completed, or expired.
step_details object The details of the run step.
last_error object or null The last error associated with this run step. Will be null if there are no errors.
expired_at integer or null The Unix timestamp (in seconds) for when the run step expired. A step is considered expired if the parent run is expired.
cancelled_at integer or null The Unix timestamp (in seconds) for when the run step was canceled.
failed_at integer or null The Unix timestamp (in seconds) for when the run step failed.
completed_at integer or null The Unix timestamp (in seconds) for when the run step completed.
metadata map Set of 16 key-value pairs that can be attached to an object. This can be useful for storing additional information about the object in a structured format. Keys can be a maximum of 64 characters long and values can be a maximum of 512 characters long.

Stream a run result (preview)

Stream the result of executing a Run or resuming a Run after submitting tool outputs. You can stream events after:

To stream a result, pass "stream": true while creating a run. The response will be a Server-Sent events stream.

Streaming example

from typing_extensions import override
from openai import AssistantEventHandler
 
# First, we create a EventHandler class to define
# how we want to handle the events in the response stream.
 
class EventHandler(AssistantEventHandler):    
  @override
  def on_text_created(self, text) -> None:
    print(f"\nassistant > ", end="", flush=True)
      
  @override
  def on_text_delta(self, delta, snapshot):
    print(delta.value, end="", flush=True)
      
  def on_tool_call_created(self, tool_call):
    print(f"\nassistant > {tool_call.type}\n", flush=True)
  
  def on_tool_call_delta(self, delta, snapshot):
    if delta.type == 'code_interpreter':
      if delta.code_interpreter.input:
        print(delta.code_interpreter.input, end="", flush=True)
      if delta.code_interpreter.outputs:
        print(f"\n\noutput >", flush=True)
        for output in delta.code_interpreter.outputs:
          if output.type == "logs":
            print(f"\n{output.logs}", flush=True)
 
# Then, we use the `create_and_stream` SDK helper 
# with the `EventHandler` class to create the Run 
# and stream the response.
 
with client.beta.threads.runs.stream(
  thread_id=thread.id,
  assistant_id=assistant.id,
  instructions="Please address the user as Jane Doe. The user has a premium account.",
  event_handler=EventHandler(),
) as stream:
  stream.until_done()

Truncation object

Controls for how a thread will be truncated prior to the run. Use this to control the initial context window of the run.

Name Type Description Required
type string The truncation strategy to use for the thread. The default is auto. If set to last_messages, the thread will be truncated to the n most recent messages in the thread. When set to auto, messages in the middle of the thread will be dropped to fit the context length of the model, max_prompt_tokens. Yes
last_messages integer The number of most recent messages from the thread when constructing the context for the run. No

Message delta object

Represents a message delta. For example any changed fields on a message during streaming.

Name Type Description
id string The identifier of the message, which can be referenced in API endpoints.
object string The object type, which is always thread.message.delta.
delta object The delta containing the fields that have changed on the Message.

Run step delta object

Represents a run step delta. For example any changed fields on a run step during streaming.

Name Type Description
id string The identifier of the run step, which can be referenced in API endpoints.
object string The object type, which is always thread.run.step.delta.
delta object The delta containing the fields that have changed on the run step.

Assistant stream events

Represents an event emitted when streaming a Run. Each event in a server-sent events stream has an event and data property:

event: thread.created
data: {"id": "thread_123", "object": "thread", ...}

Events are emitted whenever a new object is created, transitions to a new state, or is being streamed in parts (deltas). For example, thread.run.created is emitted when a new run is created, thread.run.completed when a run completes, and so on. When an Assistant chooses to create a message during a run, we emit a thread.message.created event, a thread.message.in_progress event, many thread.message.delta events, and finally a thread.message.completed event.

Name Type Description
thread.created data is a thread. Occurs when a new thread is created.
thread.run.created data is a run. Occurs when a new run is created.
thread.run.queued data is a run. Occurs when a run moves to a queued status.
thread.run.in_progress data is a run. Occurs when a run moves to an in_progress status.
thread.run.requires_action data is a run. Occurs when a run moves to a requires_action status.
thread.run.completed data is a run. Occurs when a run is completed.
thread.run.failed data is a run. Occurs when a run fails.
thread.run.cancelling data is a run. Occurs when a run moves to a cancelling status.
thread.run.cancelled data is a run. Occurs when a run is canceled.
thread.run.expired data is a run. Occurs when a run expires.
thread.run.step.created data is a run step. Occurs when a run step is created.
thread.run.step.in_progress data is a run step. Occurs when a run step moves to an in_progress state.
thread.run.step.delta data is a run step delta. Occurs when parts of a run step are being streamed.
thread.run.step.completed data is a run step. Occurs when a run step is completed.
thread.run.step.failed data is a run step. Occurs when a run step fails.
thread.run.step.cancelled data is a run step. Occurs when a run step is canceled.
thread.run.step.expired data is a run step. Occurs when a run step expires.
thread.message.created data is a message. Occurs when a message is created.
thread.message.in_progress data is a message. Occurs when a message moves to an in_progress state.
thread.message.delta data is a message delta. Occurs when parts of a Message are being streamed.
thread.message.completed data is a message. Occurs when a message is completed.
thread.message.incomplete data is a message. Occurs when a message ends before it is completed.
error data is an error. Occurs when an error occurs. This can happen due to an internal server error or a timeout.
done data is [DONE] Occurs when a stream ends.