mirror of
https://github.com/browser-use/browser-use.git
synced 2026-09-14 19:59:47 +08:00
38703d5ad7
- agent/views.py: Move RateLimitError import inside format_error() function to avoid loading openai SDK (~800ms) at module level - llm/messages.py: Replace openai.BaseModel with pydantic.BaseModel directly to remove unnecessary openai dependency - filesystem/file_system.py: Move reportlab imports inside sync_to_disk_sync() to avoid ~40ms startup cost when PDF generation is not used - utils.py: Convert OpenAIBadRequestError and GroqBadRequestError to lazy loaders to avoid loading SDKs at module level This improves import time for users who don't use OpenAI provider, especially when using Anthropic, Google, or other providers. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
239 lines
6.4 KiB
Python
239 lines
6.4 KiB
Python
"""
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This implementation is based on the OpenAI types, while removing all the parts that are not needed for Browser Use.
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"""
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# region - Content parts
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from typing import Literal, Union
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from pydantic import BaseModel
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def _truncate(text: str, max_length: int = 50) -> str:
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"""Truncate text to max_length characters, adding ellipsis if truncated."""
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if len(text) <= max_length:
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return text
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return text[: max_length - 3] + '...'
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def _format_image_url(url: str, max_length: int = 50) -> str:
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"""Format image URL for display, truncating if necessary."""
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if url.startswith('data:'):
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# Base64 image
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media_type = url.split(';')[0].split(':')[1] if ';' in url else 'image'
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return f'<base64 {media_type}>'
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else:
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# Regular URL
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return _truncate(url, max_length)
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class ContentPartTextParam(BaseModel):
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text: str
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type: Literal['text'] = 'text'
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def __str__(self) -> str:
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return f'Text: {_truncate(self.text)}'
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def __repr__(self) -> str:
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return f'ContentPartTextParam(text={_truncate(self.text)})'
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class ContentPartRefusalParam(BaseModel):
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refusal: str
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type: Literal['refusal'] = 'refusal'
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def __str__(self) -> str:
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return f'Refusal: {_truncate(self.refusal)}'
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def __repr__(self) -> str:
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return f'ContentPartRefusalParam(refusal={_truncate(repr(self.refusal), 50)})'
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SupportedImageMediaType = Literal['image/jpeg', 'image/png', 'image/gif', 'image/webp']
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class ImageURL(BaseModel):
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url: str
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"""Either a URL of the image or the base64 encoded image data."""
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detail: Literal['auto', 'low', 'high'] = 'auto'
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"""Specifies the detail level of the image.
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Learn more in the
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[Vision guide](https://platform.openai.com/docs/guides/vision#low-or-high-fidelity-image-understanding).
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"""
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# needed for Anthropic
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media_type: SupportedImageMediaType = 'image/png'
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def __str__(self) -> str:
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url_display = _format_image_url(self.url)
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return f'🖼️ Image[{self.media_type}, detail={self.detail}]: {url_display}'
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def __repr__(self) -> str:
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url_repr = _format_image_url(self.url, 30)
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return f'ImageURL(url={repr(url_repr)}, detail={repr(self.detail)}, media_type={repr(self.media_type)})'
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class ContentPartImageParam(BaseModel):
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image_url: ImageURL
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type: Literal['image_url'] = 'image_url'
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def __str__(self) -> str:
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return str(self.image_url)
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def __repr__(self) -> str:
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return f'ContentPartImageParam(image_url={repr(self.image_url)})'
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class Function(BaseModel):
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arguments: str
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"""
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The arguments to call the function with, as generated by the model in JSON
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format. Note that the model does not always generate valid JSON, and may
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hallucinate parameters not defined by your function schema. Validate the
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arguments in your code before calling your function.
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"""
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name: str
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"""The name of the function to call."""
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def __str__(self) -> str:
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args_preview = _truncate(self.arguments, 80)
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return f'{self.name}({args_preview})'
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def __repr__(self) -> str:
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args_repr = _truncate(repr(self.arguments), 50)
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return f'Function(name={repr(self.name)}, arguments={args_repr})'
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class ToolCall(BaseModel):
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id: str
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"""The ID of the tool call."""
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function: Function
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"""The function that the model called."""
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type: Literal['function'] = 'function'
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"""The type of the tool. Currently, only `function` is supported."""
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def __str__(self) -> str:
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return f'ToolCall[{self.id}]: {self.function}'
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def __repr__(self) -> str:
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return f'ToolCall(id={repr(self.id)}, function={repr(self.function)})'
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# endregion
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# region - Message types
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class _MessageBase(BaseModel):
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"""Base class for all message types"""
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role: Literal['user', 'system', 'assistant']
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cache: bool = False
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"""Whether to cache this message. This is only applicable when using Anthropic models.
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"""
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class UserMessage(_MessageBase):
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role: Literal['user'] = 'user'
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"""The role of the messages author, in this case `user`."""
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content: str | list[ContentPartTextParam | ContentPartImageParam]
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"""The contents of the user message."""
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name: str | None = None
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"""An optional name for the participant.
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Provides the model information to differentiate between participants of the same
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role.
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"""
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@property
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def text(self) -> str:
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"""
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Automatically parse the text inside content, whether it's a string or a list of content parts.
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"""
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if isinstance(self.content, str):
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return self.content
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elif isinstance(self.content, list):
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return '\n'.join([part.text for part in self.content if part.type == 'text'])
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else:
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return ''
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def __str__(self) -> str:
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return f'UserMessage(content={self.text})'
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def __repr__(self) -> str:
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return f'UserMessage(content={repr(self.text)})'
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class SystemMessage(_MessageBase):
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role: Literal['system'] = 'system'
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"""The role of the messages author, in this case `system`."""
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content: str | list[ContentPartTextParam]
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"""The contents of the system message."""
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name: str | None = None
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@property
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def text(self) -> str:
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"""
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Automatically parse the text inside content, whether it's a string or a list of content parts.
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"""
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if isinstance(self.content, str):
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return self.content
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elif isinstance(self.content, list):
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return '\n'.join([part.text for part in self.content if part.type == 'text'])
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else:
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return ''
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def __str__(self) -> str:
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return f'SystemMessage(content={self.text})'
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def __repr__(self) -> str:
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return f'SystemMessage(content={repr(self.text)})'
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class AssistantMessage(_MessageBase):
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role: Literal['assistant'] = 'assistant'
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"""The role of the messages author, in this case `assistant`."""
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content: str | list[ContentPartTextParam | ContentPartRefusalParam] | None
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"""The contents of the assistant message."""
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name: str | None = None
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refusal: str | None = None
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"""The refusal message by the assistant."""
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tool_calls: list[ToolCall] = []
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"""The tool calls generated by the model, such as function calls."""
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@property
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def text(self) -> str:
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"""
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Automatically parse the text inside content, whether it's a string or a list of content parts.
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"""
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if isinstance(self.content, str):
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return self.content
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elif isinstance(self.content, list):
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text = ''
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for part in self.content:
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if part.type == 'text':
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text += part.text
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elif part.type == 'refusal':
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text += f'[Refusal] {part.refusal}'
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return text
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else:
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return ''
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def __str__(self) -> str:
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return f'AssistantMessage(content={self.text})'
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def __repr__(self) -> str:
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return f'AssistantMessage(content={repr(self.text)})'
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BaseMessage = Union[UserMessage, SystemMessage, AssistantMessage]
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# endregion
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