Assistants
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class Assistant: …Represents an assistant that can call the model and use tools.
Represents an assistant that can call the model and use tools.
The identifier, which can be referenced in API endpoints.
The Unix timestamp (in seconds) for when the assistant was created.
The description of the assistant. The maximum length is 512 characters.
The system instructions that the assistant uses. The maximum length is 256,000 characters.
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, and querying for objects via API or the dashboard.
Keys are strings with a maximum length of 64 characters. Values are strings with a maximum length of 512 characters.
ID of the model to use. You can use the List models API to see all of your available models, or see our Model overview for descriptions of them.
The name of the assistant. The maximum length is 256 characters.
The object type, which is always assistant.
A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types code_interpreter, file_search, or function.
A list of tool enabled on the assistant. There can be a maximum of 128 tools per assistant. Tools can be of types code_interpreter, file_search, or function.
class CodeInterpreterTool: …
The type of tool being defined: code_interpreter
class FileSearchTool: …
The type of tool being defined: file_search
file_search: Optional[FileSearch]Overrides for the file search tool.
Overrides for the file search tool.
The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.
Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.
ranking_options: Optional[FileSearchRankingOptions]The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.
See the file search tool documentation for more information.
The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.
See the file search tool documentation for more information.
The score threshold for the file search. All values must be a floating point number between 0 and 1.
ranker: Optional[Literal["auto", "default_2024_08_21"]]The ranker to use for the file search. If not specified will use the auto ranker.
The ranker to use for the file search. If not specified will use the auto ranker.
class FunctionTool: …
The type of tool being defined: function
Specifies the format that the model must output. Compatible with GPT-4o, GPT-4 Turbo, and all GPT-3.5 Turbo models since gpt-3.5-turbo-1106.
Setting to { "type": "json_schema", "json_schema": {...} } enables Structured Outputs which ensures the model will match your supplied JSON schema. Learn more in the Structured Outputs guide.
Setting to { "type": "json_object" } enables JSON mode, which ensures 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 may 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 may be partially cut off if finish_reason="length", which indicates the generation exceeded max_tokens or the conversation exceeded the max context length.
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.
tool_resources: Optional[ToolResources]A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.
A set of resources that are used by the assistant's tools. The resources are specific to the type of tool. For example, the code_interpreter tool requires a list of file IDs, while the file_search tool requires a list of vector store IDs.
code_interpreter: Optional[ToolResourcesCodeInterpreter]
A list of file IDs made available to the `code_interpreter`` tool. There can be a maximum of 20 files associated with the tool.
file_search: Optional[ToolResourcesFileSearch]
The ID of the vector store attached to this assistant. There can be a maximum of 1 vector store attached to the assistant.
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.
class AssistantDeleted: …
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", ...}
We emit events whenever a new object is created, transitions to a new state, or is being
streamed in parts (deltas). For example, we emit thread.run.created 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.
We may add additional events over time, so we recommend handling unknown events gracefully
in your code. See the Assistants API quickstart to learn how to
integrate the Assistants API with streaming.
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", ...}We emit events whenever a new object is created, transitions to a new state, or is being
streamed in parts (deltas). For example, we emit thread.run.created 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.
We may add additional events over time, so we recommend handling unknown events gracefully in your code. See the Assistants API quickstart to learn how to integrate the Assistants API with streaming.
class ThreadRunStepDelta: …Occurs when parts of a run step are being streamed.
Occurs when parts of a run step are being streamed.
Represents a run step delta i.e. any changed fields on a run step during streaming.
class ThreadMessageDelta: …Occurs when parts of a Message are being streamed.
Occurs when parts of a Message are being streamed.
Represents a message delta i.e. any changed fields on a message during streaming.
class ErrorEvent: …Occurs when an error occurs. This can happen due to an internal server error or a timeout.
Occurs when an error occurs. This can happen due to an internal server error or a timeout.
class CodeInterpreterTool: …
The type of tool being defined: code_interpreter
class FileSearchTool: …
The type of tool being defined: file_search
file_search: Optional[FileSearch]Overrides for the file search tool.
Overrides for the file search tool.
The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.
Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.
ranking_options: Optional[FileSearchRankingOptions]The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.
See the file search tool documentation for more information.
The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.
See the file search tool documentation for more information.
The score threshold for the file search. All values must be a floating point number between 0 and 1.
ranker: Optional[Literal["auto", "default_2024_08_21"]]The ranker to use for the file search. If not specified will use the auto ranker.
The ranker to use for the file search. If not specified will use the auto ranker.
class FunctionTool: …
The type of tool being defined: function
class CodeInterpreterTool: …
The type of tool being defined: code_interpreter
class FileSearchTool: …
The type of tool being defined: file_search
file_search: Optional[FileSearch]Overrides for the file search tool.
Overrides for the file search tool.
The maximum number of results the file search tool should output. The default is 20 for gpt-4* models and 5 for gpt-3.5-turbo. This number should be between 1 and 50 inclusive.
Note that the file search tool may output fewer than max_num_results results. See the file search tool documentation for more information.
ranking_options: Optional[FileSearchRankingOptions]The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.
See the file search tool documentation for more information.
The ranking options for the file search. If not specified, the file search tool will use the auto ranker and a score_threshold of 0.
See the file search tool documentation for more information.
The score threshold for the file search. All values must be a floating point number between 0 and 1.
ranker: Optional[Literal["auto", "default_2024_08_21"]]The ranker to use for the file search. If not specified will use the auto ranker.
The ranker to use for the file search. If not specified will use the auto ranker.
class FunctionTool: …
The type of tool being defined: function
Occurs when a new run is created.
Occurs when a new run is created.