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from __future__ import annotations
import os
from typing import Optional, List
from time import time
from ..image import extract_data_uri
from ..image.copy_images import get_media_dir
from ..client.helper import filter_markdown
from ..providers.response import Reasoning, ToolCalls, AudioResponse
from .helper import filter_none
try:
from pydantic import BaseModel, field_serializer
except ImportError:
class BaseModel():
@classmethod
def model_construct(cls, **data):
new = cls()
for key, value in data.items():
setattr(new, key, value)
return new
class field_serializer():
def __init__(self, field_name):
self.field_name = field_name
def __call__(self, *args, **kwargs):
return args[0]
class BaseModel(BaseModel):
@classmethod
def model_construct(cls, **data):
if hasattr(super(), "model_construct"):
return super().model_construct(**data)
return cls.construct(**data)
class TokenDetails(BaseModel):
cached_tokens: int
class UsageModel(BaseModel):
prompt_tokens: int
completion_tokens: int
total_tokens: int
prompt_tokens_details: TokenDetails
completion_tokens_details: TokenDetails
@classmethod
def model_construct(cls, prompt_tokens=0, completion_tokens=0, total_tokens=0, prompt_tokens_details=None, completion_tokens_details=None, **kwargs):
return super().model_construct(
prompt_tokens=prompt_tokens,
completion_tokens=completion_tokens,
total_tokens=total_tokens,
prompt_tokens_details=TokenDetails.model_construct(**prompt_tokens_details if prompt_tokens_details else {"cached_tokens": 0}),
completion_tokens_details=TokenDetails.model_construct(**completion_tokens_details if completion_tokens_details else {}),
**kwargs
)
class ToolFunctionModel(BaseModel):
name: str
arguments: str
class ToolCallModel(BaseModel):
id: str
type: str
function: ToolFunctionModel
@classmethod
def model_construct(cls, function=None, **kwargs):
return super().model_construct(
**kwargs,
function=ToolFunctionModel.model_construct(**function),
)
class ChatCompletionChunk(BaseModel):
id: str
object: str
created: int
model: str
provider: Optional[str]
choices: List[ChatCompletionDeltaChoice]
usage: UsageModel
conversation: dict
@classmethod
def model_construct(
cls,
content: str,
finish_reason: str,
completion_id: str = None,
created: int = None,
usage: UsageModel = None,
conversation: dict = None
):
return super().model_construct(
id=f"chatcmpl-{completion_id}" if completion_id else None,
object="chat.completion.chunk",
created=created,
model=None,
provider=None,
choices=[ChatCompletionDeltaChoice.model_construct(
ChatCompletionDelta.model_construct(content),
finish_reason
)],
**filter_none(usage=usage, conversation=conversation)
)
@field_serializer('conversation')
def serialize_conversation(self, conversation: dict):
if hasattr(conversation, "get_dict"):
return conversation.get_dict()
return conversation
class ResponseMessage(BaseModel):
type: str = "message"
role: str
content: list[ResponseMessageContent]
@classmethod
def model_construct(cls, content: str):
return super().model_construct(role="assistant", content=[ResponseMessageContent.model_construct(content)])
class ResponseMessageContent(BaseModel):
type: str
text: str
@classmethod
def model_construct(cls, text: str):
return super().model_construct(type="output_text", text=text)
@field_serializer('text')
def serialize_text(self, text: str):
return str(text)
class AudioResponseModel(BaseModel):
data: str
transcript: Optional[str] = None
@classmethod
def model_construct(cls, data: str, transcript: Optional[str] = None):
return super().model_construct(data=data, transcript=transcript)
class ChatCompletionMessage(BaseModel):
role: str
content: str
reasoning: Optional[str] = None
tool_calls: list[ToolCallModel] = None
audio: AudioResponseModel = None
@classmethod
def model_construct(cls, content: str):
return super().model_construct(role="assistant", content=[ResponseMessageContent.model_construct(content)])
@classmethod
def model_construct(cls, content: str, reasoning: list[Reasoning] = None, tool_calls: list = None):
if isinstance(content, AudioResponse) and content.data.startswith("data:"):
return super().model_construct(
role="assistant",
audio=AudioResponseModel.model_construct(
data=content.data.split(",")[-1],
transcript=content.transcript
),
content=content
)
if reasoning is not None and isinstance(reasoning, list):
reasoning = "".join([str(content) for content in reasoning])
return super().model_construct(role="assistant", content=content, **filter_none(tool_calls=tool_calls, reasoning=reasoning))
@field_serializer('content')
def serialize_content(self, content: str):
return str(content)
def save(self, filepath: str, allowed_types = None):
if hasattr(self.content, "data"):
os.rename(self.content.data.replace("/media", get_media_dir()), filepath)
return
if self.content.startswith("data:"):
with open(filepath, "wb") as f:
f.write(extract_data_uri(self.content))
return
content = filter_markdown(self.content, allowed_types, self.content if not allowed_types else None)
if content is not None:
with open(filepath, "w") as f:
f.write(content)
class ChatCompletionChoice(BaseModel):
index: int
message: ChatCompletionMessage
finish_reason: str
@classmethod
def model_construct(cls, message: ChatCompletionMessage, finish_reason: str):
return super().model_construct(index=0, message=message, finish_reason=finish_reason)
class ChatCompletion(BaseModel):
id: str
object: str
created: int
model: str
provider: Optional[str]
choices: list[ChatCompletionChoice]
usage: UsageModel
conversation: dict
@classmethod
def model_construct(
cls,
content: str,
finish_reason: str,
completion_id: str = None,
created: int = None,
tool_calls: list[ToolCallModel] = None,
usage: UsageModel = None,
conversation: dict = None,
reasoning: list[Reasoning] = None
):
return super().model_construct(
id=f"chatcmpl-{completion_id}" if completion_id else None,
object="chat.completion",
created=created,
model=None,
provider=None,
choices=[ChatCompletionChoice.model_construct(
ChatCompletionMessage.model_construct(content, reasoning, tool_calls),
finish_reason,
)],
**filter_none(usage=usage, conversation=conversation)
)
@field_serializer('conversation')
def serialize_conversation(self, conversation: dict):
if hasattr(conversation, "get_dict"):
return conversation.get_dict()
return conversation
class ClientResponse(BaseModel):
id: str
object: str
created_at: int
model: str
provider: Optional[str]
output: list[ResponseMessage]
usage: UsageModel
conversation: dict
@classmethod
def model_construct(
cls,
content: str,
response_id: str = None,
created_at: int = None,
usage: UsageModel = None,
conversation: dict = None
) -> ClientResponse:
return super().model_construct(
id=f"resp-{response_id}" if response_id else None,
object="response",
created_at=created_at,
model=None,
provider=None,
output=[
ResponseMessage.model_construct(content),
],
**filter_none(usage=usage, conversation=conversation)
)
@field_serializer('conversation')
def serialize_conversation(self, conversation: dict):
if hasattr(conversation, "get_dict"):
return conversation.get_dict()
return conversation
class ChatCompletionDelta(BaseModel):
role: str
content: Optional[str]
reasoning: Optional[str] = None
tool_calls: list[ToolCallModel] = None
@classmethod
def model_construct(cls, content: Optional[str]):
if isinstance(content, Reasoning):
return super().model_construct(role="assistant", content=None, reasoning=str(content))
elif isinstance(content, ToolCalls) and content.get_list():
return super().model_construct(role="assistant", content=None, tool_calls=[
ToolCallModel.model_construct(**tool_call) for tool_call in content.get_list()
])
return super().model_construct(role="assistant", content=content)
@field_serializer('content')
def serialize_content(self, content: Optional[str]):
if content is None:
return ""
if isinstance(content, (Reasoning, ToolCalls)):
return None
return str(content)
class ChatCompletionDeltaChoice(BaseModel):
index: int
delta: ChatCompletionDelta
finish_reason: Optional[str]
@classmethod
def model_construct(cls, delta: ChatCompletionDelta, finish_reason: Optional[str]):
return super().model_construct(index=0, delta=delta, finish_reason=finish_reason)
class Image(BaseModel):
url: Optional[str]
b64_json: Optional[str]
revised_prompt: Optional[str]
@classmethod
def model_construct(cls, url: str = None, b64_json: str = None, revised_prompt: str = None):
return super().model_construct(**filter_none(
url=url,
b64_json=b64_json,
revised_prompt=revised_prompt
))
def save(self, path: str):
if self.url is not None and self.url.startswith("/media/"):
os.rename(self.url.replace("/media", get_media_dir()), path)
class ImagesResponse(BaseModel):
data: List[Image]
model: str
provider: str
created: int
@classmethod
def model_construct(cls, data: List[Image], created: int = None, model: str = None, provider: str = None):
if created is None:
created = int(time())
return super().model_construct(
data=data,
model=model,
provider=provider,
created=created
)
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