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CoACT initialize (#292)

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Linxin Song
2025-07-30 19:35:20 -07:00
committed by GitHub
parent 862d704b8c
commit b968155757
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mm_agents/coact/autogen/oai/oai_models/__init__.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
from .chat_completion import ChatCompletionExtended as ChatCompletion
from .chat_completion import Choice
from .chat_completion_message import ChatCompletionMessage
from .chat_completion_message_tool_call import ChatCompletionMessageToolCall
from .completion_usage import CompletionUsage
__all__ = ["ChatCompletion", "ChatCompletionMessage", "ChatCompletionMessageToolCall", "Choice", "CompletionUsage"]

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mm_agents/coact/autogen/oai/oai_models/_models.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/main/src/openai/_models.py
import pydantic
import pydantic.generics
from pydantic import ConfigDict
from typing_extensions import ClassVar
__all__ = ["BaseModel"]
class BaseModel(pydantic.BaseModel):
model_config: ClassVar[ConfigDict] = ConfigDict(extra="allow")

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mm_agents/coact/autogen/oai/oai_models/chat_completion.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/3e69750d47df4f0759d4a28ddc68e4b38756d9ca/src/openai/types/chat/chat_completion.py
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from typing import Any, Callable, List, Optional
from typing_extensions import Literal
from ._models import BaseModel
from .chat_completion_message import ChatCompletionMessage
from .chat_completion_token_logprob import ChatCompletionTokenLogprob
from .completion_usage import CompletionUsage
__all__ = ["ChatCompletion", "Choice", "ChoiceLogprobs"]
class ChoiceLogprobs(BaseModel):
content: Optional[List[ChatCompletionTokenLogprob]] = None
"""A list of message content tokens with log probability information."""
refusal: Optional[List[ChatCompletionTokenLogprob]] = None
"""A list of message refusal tokens with log probability information."""
class Choice(BaseModel):
finish_reason: Literal["stop", "length", "tool_calls", "content_filter", "function_call"]
"""The reason the model stopped generating tokens.
This will be `stop` if the model hit a natural stop point or a provided stop
sequence, `length` if the maximum number of tokens specified in the request was
reached, `content_filter` if content was omitted due to a flag from our content
filters, `tool_calls` if the model called a tool, or `function_call`
(deprecated) if the model called a function.
"""
index: int
"""The index of the choice in the list of choices."""
logprobs: Optional[ChoiceLogprobs] = None
"""Log probability information for the choice."""
message: ChatCompletionMessage
"""A chat completion message generated by the model."""
class ChatCompletion(BaseModel):
id: str
"""A unique identifier for the chat completion."""
choices: List[Choice]
"""A list of chat completion choices.
Can be more than one if `n` is greater than 1.
"""
created: int
"""The Unix timestamp (in seconds) of when the chat completion was created."""
model: str
"""The model used for the chat completion."""
object: Literal["chat.completion"]
"""The object type, which is always `chat.completion`."""
service_tier: Optional[Literal["auto", "default", "flex", "scale"]] = None
"""The service tier used for processing the request."""
system_fingerprint: Optional[str] = None
"""This fingerprint represents the backend configuration that the model runs with.
Can be used in conjunction with the `seed` request parameter to understand when
backend changes have been made that might impact determinism.
"""
usage: Optional[CompletionUsage] = None
"""Usage statistics for the completion request."""
class ChatCompletionExtended(ChatCompletion):
message_retrieval_function: Optional[Callable[[Any, "ChatCompletion"], list[ChatCompletionMessage]]] = None
config_id: Optional[str] = None
pass_filter: Optional[Callable[..., bool]] = None
cost: Optional[float] = None

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mm_agents/coact/autogen/oai/oai_models/chat_completion_audio.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/3e69750d47df4f0759d4a28ddc68e4b38756d9ca/src/openai/types/chat/chat_completion_audio.py
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from ._models import BaseModel
__all__ = ["ChatCompletionAudio"]
class ChatCompletionAudio(BaseModel):
id: str
"""Unique identifier for this audio response."""
data: str
"""
Base64 encoded audio bytes generated by the model, in the format specified in
the request.
"""
expires_at: int
"""
The Unix timestamp (in seconds) for when this audio response will no longer be
accessible on the server for use in multi-turn conversations.
"""
transcript: str
"""Transcript of the audio generated by the model."""

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mm_agents/coact/autogen/oai/oai_models/chat_completion_message.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/16a10604fbd0d82c1382b84b417a1d6a2d33a7f1/src/openai/types/chat/chat_completion_message.py
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from typing import List, Optional
from typing_extensions import Literal
from ._models import BaseModel
from .chat_completion_audio import ChatCompletionAudio
from .chat_completion_message_tool_call import ChatCompletionMessageToolCall
__all__ = ["Annotation", "AnnotationURLCitation", "ChatCompletionMessage", "FunctionCall"]
class AnnotationURLCitation(BaseModel):
end_index: int
"""The index of the last character of the URL citation in the message."""
start_index: int
"""The index of the first character of the URL citation in the message."""
title: str
"""The title of the web resource."""
url: str
"""The URL of the web resource."""
class Annotation(BaseModel):
type: Literal["url_citation"]
"""The type of the URL citation. Always `url_citation`."""
url_citation: AnnotationURLCitation
"""A URL citation when using web search."""
class FunctionCall(BaseModel):
arguments: str
"""
The arguments to call the function with, as generated by the model in JSON
format. Note that the model does not always generate valid JSON, and may
hallucinate parameters not defined by your function schema. Validate the
arguments in your code before calling your function.
"""
name: str
"""The name of the function to call."""
class ChatCompletionMessage(BaseModel):
content: Optional[str] = None
"""The contents of the message."""
refusal: Optional[str] = None
"""The refusal message generated by the model."""
role: Literal["assistant"]
"""The role of the author of this message."""
annotations: Optional[List[Annotation]] = None
"""
Annotations for the message, when applicable, as when using the
[web search tool](https://platform.openai.com/docs/guides/tools-web-search?api-mode=chat).
"""
audio: Optional[ChatCompletionAudio] = None
"""
If the audio output modality is requested, this object contains data about the
audio response from the model.
[Learn more](https://platform.openai.com/docs/guides/audio).
"""
function_call: Optional[FunctionCall] = None
"""Deprecated and replaced by `tool_calls`.
The name and arguments of a function that should be called, as generated by the
model.
"""
tool_calls: Optional[List[ChatCompletionMessageToolCall]] = None
"""The tool calls generated by the model, such as function calls."""

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mm_agents/coact/autogen/oai/oai_models/chat_completion_message_tool_call.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/3e69750d47df4f0759d4a28ddc68e4b38756d9ca/src/openai/types/chat/chat_completion_message_tool_call.py
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from typing_extensions import Literal
from ._models import BaseModel
__all__ = ["ChatCompletionMessageToolCall", "Function"]
class Function(BaseModel):
arguments: str
"""
The arguments to call the function with, as generated by the model in JSON
format. Note that the model does not always generate valid JSON, and may
hallucinate parameters not defined by your function schema. Validate the
arguments in your code before calling your function.
"""
name: str
"""The name of the function to call."""
class ChatCompletionMessageToolCall(BaseModel):
id: str
"""The ID of the tool call."""
function: Function
"""The function that the model called."""
type: Literal["function"]
"""The type of the tool. Currently, only `function` is supported."""

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mm_agents/coact/autogen/oai/oai_models/chat_completion_token_logprob.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/3e69750d47df4f0759d4a28ddc68e4b38756d9ca/src/openai/types/chat/chat_completion_token_logprob.py
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from typing import List, Optional
from ._models import BaseModel
__all__ = ["ChatCompletionTokenLogprob", "TopLogprob"]
class TopLogprob(BaseModel):
token: str
"""The token."""
bytes: Optional[List[int]] = None
"""A list of integers representing the UTF-8 bytes representation of the token.
Useful in instances where characters are represented by multiple tokens and
their byte representations must be combined to generate the correct text
representation. Can be `null` if there is no bytes representation for the token.
"""
logprob: float
"""The log probability of this token, if it is within the top 20 most likely
tokens.
Otherwise, the value `-9999.0` is used to signify that the token is very
unlikely.
"""
class ChatCompletionTokenLogprob(BaseModel):
token: str
"""The token."""
bytes: Optional[List[int]] = None
"""A list of integers representing the UTF-8 bytes representation of the token.
Useful in instances where characters are represented by multiple tokens and
their byte representations must be combined to generate the correct text
representation. Can be `null` if there is no bytes representation for the token.
"""
logprob: float
"""The log probability of this token, if it is within the top 20 most likely
tokens.
Otherwise, the value `-9999.0` is used to signify that the token is very
unlikely.
"""
top_logprobs: List[TopLogprob]
"""List of the most likely tokens and their log probability, at this token
position.
In rare cases, there may be fewer than the number of requested `top_logprobs`
returned.
"""

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mm_agents/coact/autogen/oai/oai_models/completion_usage.py Normal file
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# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
#
# SPDX-License-Identifier: Apache-2.0
# Taken over from https://github.com/openai/openai-python/blob/3e69750d47df4f0759d4a28ddc68e4b38756d9ca/src/openai/types/completion_usage.py
# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
from typing import Optional
from ._models import BaseModel
__all__ = ["CompletionTokensDetails", "CompletionUsage", "PromptTokensDetails"]
class CompletionTokensDetails(BaseModel):
accepted_prediction_tokens: Optional[int] = None
"""
When using Predicted Outputs, the number of tokens in the prediction that
appeared in the completion.
"""
audio_tokens: Optional[int] = None
"""Audio input tokens generated by the model."""
reasoning_tokens: Optional[int] = None
"""Tokens generated by the model for reasoning."""
rejected_prediction_tokens: Optional[int] = None
"""
When using Predicted Outputs, the number of tokens in the prediction that did
not appear in the completion. However, like reasoning tokens, these tokens are
still counted in the total completion tokens for purposes of billing, output,
and context window limits.
"""
class PromptTokensDetails(BaseModel):
audio_tokens: Optional[int] = None
"""Audio input tokens present in the prompt."""
cached_tokens: Optional[int] = None
"""Cached tokens present in the prompt."""
class CompletionUsage(BaseModel):
completion_tokens: int
"""Number of tokens in the generated completion."""
prompt_tokens: int
"""Number of tokens in the prompt."""
total_tokens: int
"""Total number of tokens used in the request (prompt + completion)."""
completion_tokens_details: Optional[CompletionTokensDetails] = None
"""Breakdown of tokens used in a completion."""
prompt_tokens_details: Optional[PromptTokensDetails] = None
"""Breakdown of tokens used in the prompt."""