autogen_core.models#
- pydantic model AssistantMessage[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "AssistantMessage", "type": "object", "properties": { "content": { "anyOf": [ { "type": "string" }, { "items": { "$ref": "#/$defs/FunctionCall" }, "type": "array" } ], "title": "Content" }, "source": { "title": "Source", "type": "string" }, "type": { "const": "AssistantMessage", "default": "AssistantMessage", "title": "Type", "type": "string" } }, "$defs": { "FunctionCall": { "properties": { "id": { "title": "Id", "type": "string" }, "arguments": { "title": "Arguments", "type": "string" }, "name": { "title": "Name", "type": "string" } }, "required": [ "id", "arguments", "name" ], "title": "FunctionCall", "type": "object" } }, "required": [ "content", "source" ] } - Fields:
- content (str | List[autogen_core._types.FunctionCall])
- source (str)
- type (Literal['AssistantMessage'])
 
 - field content: str | List[FunctionCall] [Required]#
 
- class ChatCompletionClient[source]#
- Bases: - ComponentBase[- BaseModel],- ABC- abstract actual_usage() RequestUsage[source]#
 - abstract property capabilities: ModelCapabilities#
 - abstract count_tokens(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], *, tools: Sequence[Tool | ToolSchema] = []) int[source]#
 - abstract async create(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], *, tools: Sequence[Tool | ToolSchema] = [], json_output: bool | None = None, extra_create_args: Mapping[str, Any] = {}, cancellation_token: CancellationToken | None = None) CreateResult[source]#
 - abstract create_stream(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], *, tools: Sequence[Tool | ToolSchema] = [], json_output: bool | None = None, extra_create_args: Mapping[str, Any] = {}, cancellation_token: CancellationToken | None = None) AsyncGenerator[str | CreateResult, None][source]#
 - abstract remaining_tokens(messages: Sequence[Annotated[SystemMessage | UserMessage | AssistantMessage | FunctionExecutionResultMessage, FieldInfo(annotation=NoneType, required=True, discriminator='type')]], *, tools: Sequence[Tool | ToolSchema] = []) int[source]#
 - abstract total_usage() RequestUsage[source]#
 
- pydantic model ChatCompletionTokenLogprob[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "ChatCompletionTokenLogprob", "type": "object", "properties": { "token": { "title": "Token", "type": "string" }, "logprob": { "title": "Logprob", "type": "number" }, "top_logprobs": { "anyOf": [ { "items": { "$ref": "#/$defs/TopLogprob" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Top Logprobs" }, "bytes": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Bytes" } }, "$defs": { "TopLogprob": { "properties": { "logprob": { "title": "Logprob", "type": "number" }, "bytes": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Bytes" } }, "required": [ "logprob" ], "title": "TopLogprob", "type": "object" } }, "required": [ "token", "logprob" ] } - Fields:
- bytes (List[int] | None)
- logprob (float)
- token (str)
- top_logprobs (List[autogen_core.models._types.TopLogprob] | None)
 
 - field top_logprobs: List[TopLogprob] | None = None#
 
- pydantic model CreateResult[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "CreateResult", "type": "object", "properties": { "finish_reason": { "enum": [ "stop", "length", "function_calls", "content_filter", "unknown" ], "title": "Finish Reason", "type": "string" }, "content": { "anyOf": [ { "type": "string" }, { "items": { "$ref": "#/$defs/FunctionCall" }, "type": "array" } ], "title": "Content" }, "usage": { "$ref": "#/$defs/RequestUsage" }, "cached": { "title": "Cached", "type": "boolean" }, "logprobs": { "anyOf": [ { "items": { "$ref": "#/$defs/ChatCompletionTokenLogprob" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Logprobs" } }, "$defs": { "ChatCompletionTokenLogprob": { "properties": { "token": { "title": "Token", "type": "string" }, "logprob": { "title": "Logprob", "type": "number" }, "top_logprobs": { "anyOf": [ { "items": { "$ref": "#/$defs/TopLogprob" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Top Logprobs" }, "bytes": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Bytes" } }, "required": [ "token", "logprob" ], "title": "ChatCompletionTokenLogprob", "type": "object" }, "FunctionCall": { "properties": { "id": { "title": "Id", "type": "string" }, "arguments": { "title": "Arguments", "type": "string" }, "name": { "title": "Name", "type": "string" } }, "required": [ "id", "arguments", "name" ], "title": "FunctionCall", "type": "object" }, "RequestUsage": { "properties": { "prompt_tokens": { "title": "Prompt Tokens", "type": "integer" }, "completion_tokens": { "title": "Completion Tokens", "type": "integer" } }, "required": [ "prompt_tokens", "completion_tokens" ], "title": "RequestUsage", "type": "object" }, "TopLogprob": { "properties": { "logprob": { "title": "Logprob", "type": "number" }, "bytes": { "anyOf": [ { "items": { "type": "integer" }, "type": "array" }, { "type": "null" } ], "default": null, "title": "Bytes" } }, "required": [ "logprob" ], "title": "TopLogprob", "type": "object" } }, "required": [ "finish_reason", "content", "usage", "cached" ] } - Fields:
- cached (bool)
- content (str | List[autogen_core._types.FunctionCall])
- finish_reason (Literal['stop', 'length', 'function_calls', 'content_filter', 'unknown'])
- logprobs (List[autogen_core.models._types.ChatCompletionTokenLogprob] | None)
- usage (autogen_core.models._types.RequestUsage)
 
 - field content: str | List[FunctionCall] [Required]#
 - field finish_reason: Literal['stop', 'length', 'function_calls', 'content_filter', 'unknown'] [Required]#
 - field logprobs: List[ChatCompletionTokenLogprob] | None = None#
 - field usage: RequestUsage [Required]#
 
- pydantic model FunctionExecutionResult[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "FunctionExecutionResult", "type": "object", "properties": { "content": { "title": "Content", "type": "string" }, "call_id": { "title": "Call Id", "type": "string" } }, "required": [ "content", "call_id" ] } - Fields:
- call_id (str)
- content (str)
 
 
- pydantic model FunctionExecutionResultMessage[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "FunctionExecutionResultMessage", "type": "object", "properties": { "content": { "items": { "$ref": "#/$defs/FunctionExecutionResult" }, "title": "Content", "type": "array" }, "type": { "const": "FunctionExecutionResultMessage", "default": "FunctionExecutionResultMessage", "title": "Type", "type": "string" } }, "$defs": { "FunctionExecutionResult": { "properties": { "content": { "title": "Content", "type": "string" }, "call_id": { "title": "Call Id", "type": "string" } }, "required": [ "content", "call_id" ], "title": "FunctionExecutionResult", "type": "object" } }, "required": [ "content" ] } - Fields:
- content (List[autogen_core.models._types.FunctionExecutionResult])
- type (Literal['FunctionExecutionResultMessage'])
 
 - field content: List[FunctionExecutionResult] [Required]#
 
- class ModelFamily(*args: Any, **kwargs: Any)[source]#
- Bases: - object- A model family is a group of models that share similar characteristics from a capabilities perspective. This is different to discrete supported features such as vision, function calling, and JSON output. - This namespace class holds constants for the model families that AutoGen understands. Other families definitely exist and can be represented by a string, however, AutoGen will treat them as unknown. - GPT_35 = 'gpt-35'#
 - GPT_4 = 'gpt-4'#
 - GPT_4O = 'gpt-4o'#
 - O1 = 'o1'#
 - UNKNOWN = 'unknown'#
 
- class ModelInfo[source]#
- Bases: - TypedDict- family: Required[Literal['gpt-4o', 'o1', 'gpt-4', 'gpt-35', 'unknown'] | str]#
- Model family should be one of the constants from - ModelFamilyor a string representing an unknown model family.
 
- pydantic model SystemMessage[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "SystemMessage", "type": "object", "properties": { "content": { "title": "Content", "type": "string" }, "type": { "const": "SystemMessage", "default": "SystemMessage", "title": "Type", "type": "string" } }, "required": [ "content" ] } - Fields:
- content (str)
- type (Literal['SystemMessage'])
 
 
- pydantic model UserMessage[source]#
- Bases: - BaseModel- Show JSON schema- { "title": "UserMessage", "type": "object", "properties": { "content": { "anyOf": [ { "type": "string" }, { "items": { "anyOf": [ { "type": "string" }, {} ] }, "type": "array" } ], "title": "Content" }, "source": { "title": "Source", "type": "string" }, "type": { "const": "UserMessage", "default": "UserMessage", "title": "Type", "type": "string" } }, "required": [ "content", "source" ] } - Fields:
- content (str | List[str | autogen_core._image.Image])
- source (str)
- type (Literal['UserMessage'])