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chore: add missing docstrings · digitalocean/gradient-python@484e2a8 · GitHub

This repository was archived by the owner on Aug 17, 2026. It is now read-only.
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chore: add missing docstrings
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‎src/gradient/types/agent_create_response.py‎

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class AgentCreateResponse(BaseModel):
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"""Information about a newly created Agent"""
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agent: Optional["APIAgent"] = None
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"""An Agent"""
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‎src/gradient/types/agent_delete_response.py‎

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class AgentDeleteResponse(BaseModel):
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"""Info about a deleted agent"""
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agent: Optional["APIAgent"] = None
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"""An Agent"""
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‎src/gradient/types/agent_list_response.py‎

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class AgentChatbot(BaseModel):
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"""A Chatbot"""
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allowed_domains: Optional[List[str]] = None
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button_background_color: Optional[str] = None
@@ -41,11 +43,15 @@ class AgentChatbot(BaseModel):
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class AgentChatbotIdentifier(BaseModel):
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"""Agent Chatbot Identifier"""
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agent_chatbot_identifier: Optional[str] = None
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"""Agent chatbot identifier"""
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class AgentDeployment(BaseModel):
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"""Description of deployment"""
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created_at: Optional[datetime] = None
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"""Creation date / time"""
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class AgentTemplate(BaseModel):
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"""Represents an AgentTemplate entity"""
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created_at: Optional[datetime] = None
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"""The agent template's creation date"""
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class Agent(BaseModel):
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"""A GenAI Agent's configuration"""
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chatbot: Optional[AgentChatbot] = None
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"""A Chatbot"""
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class AgentListResponse(BaseModel):
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"""List of Agents"""
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agents: Optional[List[Agent]] = None
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"""Agents"""
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‎src/gradient/types/agent_retrieve_response.py‎

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class AgentRetrieveResponse(BaseModel):
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"""One Agent"""
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agent: Optional["APIAgent"] = None
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"""An Agent"""
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‎src/gradient/types/agent_retrieve_usage_response.py‎

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class LogInsightsUsageMeasurement(BaseModel):
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"""Usage Measurement Description"""
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tokens: Optional[int] = None
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usage_type: Optional[str] = None
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class LogInsightsUsage(BaseModel):
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"""Resource Usage Description"""
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measurements: Optional[List[LogInsightsUsageMeasurement]] = None
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resource_uuid: Optional[str] = None
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class UsageMeasurement(BaseModel):
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"""Usage Measurement Description"""
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tokens: Optional[int] = None
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usage_type: Optional[str] = None
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class Usage(BaseModel):
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"""Resource Usage Description"""
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measurements: Optional[List[UsageMeasurement]] = None
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resource_uuid: Optional[str] = None
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class AgentRetrieveUsageResponse(BaseModel):
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"""Agent usage"""
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log_insights_usage: Optional[LogInsightsUsage] = None
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"""Resource Usage Description"""
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‎src/gradient/types/agent_update_response.py‎

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class AgentUpdateResponse(BaseModel):
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"""Information about an updated agent"""
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agent: Optional["APIAgent"] = None
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"""An Agent"""
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‎src/gradient/types/agent_update_status_response.py‎

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class AgentUpdateStatusResponse(BaseModel):
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"""UpdateAgentDeploymentVisbilityOutput description"""
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agent: Optional["APIAgent"] = None
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"""An Agent"""
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‎src/gradient/types/agents/api_link_knowledge_base_output.py‎

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class APILinkKnowledgeBaseOutput(BaseModel):
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"""Information about a linked knowledge base"""
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agent: Optional["APIAgent"] = None
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"""An Agent"""
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‎src/gradient/types/agents/chat/completion_create_params.py‎

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class MessageChatCompletionRequestSystemMessageContentArrayOfContentPartUnionMember1(TypedDict, total=False):
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"""Content part with type and text"""
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text: Required[str]
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"""The text content"""
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class MessageChatCompletionRequestSystemMessage(TypedDict, total=False):
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"""
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System-provided instructions that the model should follow, regardless of
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messages sent by the user.
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"""
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content: Required[Union[str, SequenceNotStr[MessageChatCompletionRequestSystemMessageContentArrayOfContentPart]]]
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"""The contents of the system message."""
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class MessageChatCompletionRequestDeveloperMessageContentArrayOfContentPartUnionMember1(TypedDict, total=False):
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"""Content part with type and text"""
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text: Required[str]
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"""The text content"""
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class MessageChatCompletionRequestDeveloperMessage(TypedDict, total=False):
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"""
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Developer-provided instructions that the model should follow, regardless of
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messages sent by the user.
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"""
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content: Required[Union[str, SequenceNotStr[MessageChatCompletionRequestDeveloperMessageContentArrayOfContentPart]]]
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"""The contents of the developer message."""
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class MessageChatCompletionRequestUserMessageContentArrayOfContentPartUnionMember1(TypedDict, total=False):
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"""Content part with type and text"""
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"""The text content"""
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class MessageChatCompletionRequestUserMessage(TypedDict, total=False):
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"""
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Messages sent by an end user, containing prompts or additional context
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information.
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"""
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content: Required[Union[str, SequenceNotStr[MessageChatCompletionRequestUserMessageContentArrayOfContentPart]]]
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"""The contents of the user message."""
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class MessageChatCompletionRequestAssistantMessageContentArrayOfContentPartUnionMember1(TypedDict, total=False):
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"""Content part with type and text"""
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"""The text content"""
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class MessageChatCompletionRequestAssistantMessageToolCallFunction(TypedDict, total=False):
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"""The function that the model called."""
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arguments: Required[str]
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"""
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class MessageChatCompletionRequestAssistantMessage(TypedDict, total=False):
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"""Messages sent by the model in response to user messages."""
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role: Required[Literal["assistant"]]
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"""The role of the messages author, in this case `assistant`."""
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class StreamOptions(TypedDict, total=False):
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"""Options for streaming response. Only set this when you set `stream: true`."""
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include_usage: bool
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"""If set, an additional chunk will be streamed before the `data: [DONE]` message.
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class ToolChoiceChatCompletionNamedToolChoice(TypedDict, total=False):
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"""Specifies a tool the model should use.
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Use to force the model to call a specific function.
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"""
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function: Required[ToolChoiceChatCompletionNamedToolChoiceFunction]
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type: Required[Literal["function"]]

‎src/gradient/types/agents/chat/completion_create_response.py‎

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class ChoiceLogprobs(BaseModel):
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"""Log probability information for the choice."""
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content: Optional[List[ChatCompletionTokenLogprob]] = None
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class ChoiceMessageToolCallFunction(BaseModel):
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"""The function that the model called."""
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arguments: str
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"""
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class ChoiceMessage(BaseModel):
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"""A chat completion message generated by the model."""
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content: Optional[str] = None
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"""The contents of the message."""
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class CompletionCreateResponse(BaseModel):
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"""
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Represents a chat completion response returned by model, based on the provided input.
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"""
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id: str
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"""A unique identifier for the chat completion."""
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