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remove slop comments
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2 changed files with 0 additions and 37 deletions
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@ -20,23 +20,6 @@ T = TypeVar("T", bound=BaseModel)
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@dataclass
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class ChatLiteLLM(BaseChatModel):
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"""Chat model that routes to any provider via LiteLLM.
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Uses litellm's unified ``acompletion`` API to support all providers
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(OpenAI, Anthropic, Google, Ollama, OpenRouter, DeepSeek, etc.)
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through a single interface.
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The ``model`` parameter uses litellm's model format, e.g.::
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"gpt-4o"
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"anthropic/claude-sonnet-4-20250514"
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"openrouter/google/gemini-2.0-flash-001"
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"ollama/llama3"
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Structured output (``output_format``) is handled via litellm's
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``response_format`` parameter which translates across providers.
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"""
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model: str
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api_key: str | None = None
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api_base: str | None = None
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@ -128,16 +111,6 @@ class ChatLiteLLM(BaseChatModel):
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output_format: type[T] | None = None,
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**kwargs: Any, # noqa: ARG002
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) -> ChatInvokeCompletion[T] | ChatInvokeCompletion[str]:
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"""Invoke the model via litellm.
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Args:
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messages: List of browser-use chat messages.
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output_format: Optional Pydantic model class for structured output.
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**kwargs: Extra keyword args (``session_id`` etc.) — ignored.
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Returns:
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``ChatInvokeCompletion`` with either a string or parsed Pydantic model.
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"""
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import litellm
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litellm_messages = LiteLLMMessageSerializer.serialize(messages)
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@ -11,13 +11,10 @@ from browser_use.llm.messages import (
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class LiteLLMMessageSerializer:
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"""Serializer for converting browser-use message types to LiteLLM format."""
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@staticmethod
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def _serialize_user_content(
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content: str | list[ContentPartTextParam | ContentPartImageParam],
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) -> str | list[dict[str, Any]]:
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"""Convert user message content for LiteLLM compatibility."""
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if isinstance(content, str):
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return content
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@ -46,7 +43,6 @@ class LiteLLMMessageSerializer:
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def _serialize_system_content(
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content: str | list[ContentPartTextParam],
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) -> str | list[dict[str, Any]]:
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"""Convert system message content for LiteLLM compatibility."""
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if isinstance(content, str):
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return content
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@ -62,7 +58,6 @@ class LiteLLMMessageSerializer:
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def _serialize_assistant_content(
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content: str | list[Any] | None,
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) -> str | list[dict[str, Any]] | None:
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"""Convert assistant message content for LiteLLM compatibility."""
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if content is None:
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return None
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if isinstance(content, str):
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@ -88,11 +83,6 @@ class LiteLLMMessageSerializer:
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@staticmethod
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def serialize(messages: list[BaseMessage]) -> list[dict[str, Any]]:
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"""Convert browser-use messages to litellm-compatible dicts (OpenAI format).
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LiteLLM accepts OpenAI-format message dicts for all providers, handling
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provider-specific conversion (e.g. image blocks for Anthropic) internally.
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"""
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result: list[dict[str, Any]] = []
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for msg in messages:
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if isinstance(msg, UserMessage):
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